Por Aluizio Marino², Danielle Klintowitz³, Gisele Brito², Raquel Rolnik¹, Paula Santoro¹, Pedro Mendonça²
Foto: Roberto Moreyra (Agência O Globo)
Desde o início da pandemia no Brasil muito tem se debatido acerca dos impactos nos diferentes territórios e segmentos sociais. Algo fundamental tanto para encontrar os melhores meios de prevenir a difusão da doença como de proteger aqueles que estão mais vulneráveis. Entretanto, a forma como as informações e os dados têm sido divulgados não auxilia na análise dos impactos territoriais e da difusão espacial da pandemia, dificultando também o seu devido enfrentamento.
Em artigo anterior, apresentamos o resultado de pesquisa em outra escala, a da rua. Para tanto, mapeamos as hospitalizações e óbitos pós internação por Covid-19 a partir do CEP – informação fornecida nas fichas dos pacientes hospitalizados com Síndrome Respiratória Aguda e Grave (SRAG) incluindo Covid-19 e disponibilizadas pelo DATASUS até aquele momento (18 de maio de 2020). Esse procedimento permitiu olhar mais detalhadamente para a distribuição territorial da pandemia, e assim evidenciar a complexidade de questões que explicam a sua difusão espacial, não apenas a precariedade habitacional e a presença de favelas.
A partir desta constatação passamos a investigar outros possíveis elementos explicativos, entre eles, a mobilidade urbana durante o período da pandemia, especificamente compreendendo o fluxo de circulação das pessoas na cidade e como isso influencia na difusão espacial da Covid-19. Com base nos dados disponibilizados pela SPTrans sobre dados de GPS dos ônibus, e a partir do roteamento de viagens selecionadas da Pesquisa Origem Destino de 2017, buscamos identificar de onde saíram e para onde foram as pessoas que circularam de transporte coletivo no dia 5 de junho, dia em que, segundo a SPTrans, cerca de 3 milhões de viagens foram realizadas usando os ônibus municipais. Ao mesmo tempo, fizemos uma leitura territorial sobre a origem das viagens durante o período de pandemia. Para esta análise identificou-se na Pesquisa Origem Destino (2017) as pessoas que usam transporte público como modo principal para chegar ao seu destino, motivadas pela ida ao local de trabalho. Consideramos apenas as viagens realizadas por pessoas sem ensino superior e em cargos não executivos. Esse perfil foi selecionado considerando que pessoas com ensino superior, em cargos executivos e profissionais liberais tenham aderido ao teletrabalho e que viagens com outras motivações, como educação e compras, pararam de ocorrer. Esses dados de mobilidade foram correlacionados com os dados de hospitalizações por SRAG não identificada, e Covid-19, até o dia 18 de maio, última data para qual o dado do CEP no DATASUS estava disponibilizado pelo Ministério da Saúde.
Desta forma produzimos um mapa que ilustra a distribuição dos lugares de origem das viagens diárias, a partir de uma distribuição que considera número de viagens nas zonas origem-destino e distribuição populacional dentro dessas zonas. O resultado mostra uma forte associação entre os locais que mais concentraram as origens das viagens com as manchas de concentração do local de residência de pessoas hospitalizadas com Covid-19 e Síndrome Respiratória Grave (SRAG) sem identificação, possivelmente casos de Covid-19, mas que não foram testados ou não tiveram resultado confirmado.
Mapa: Pedro Mendonça/ LabCidade
Com base neste estudo, pode-se dizer que, em síntese, quem está sendo mais atingido pela Covid-19 são as pessoas que tiveram que sair para trabalhar. Embora tenhamos mapeado os locais que concentram os maiores números de origens ou destinos dos fluxos de circulação por transporte coletivo, não é possível ainda afirmar se o contágio ocorreu no percurso do transporte, no local de trabalho ou no local de moradia, o que vai exigir análises futuras, que serão realizadas no âmbito desta pesquisa. Mas o que está evidente é que quem saiu para trabalhar e realizou percursos longos de transporte coletivo é que quem foi mais impactado pelos óbitos ocorridos. Enquanto esse fator mostrou associação forte com os casos de hospitalizações por SRAG não identificada e Covid-19, a densidade demográfica — frequentemente associada a áreas favelizadas e bairros populares — apresentou associação fraca.
Ainda que preliminares, esses dados apontam para a incoerência e inconsequência da abertura planejada pelas prefeituras e governo do estado. A reabertura de comércios e restaurantes implica em aumentar significativamente o número de áreas de origens com mais densidades de viagens e maior circulação de pessoas no transporte público. Se o maior número de óbitos está nos territórios que tiveram mais pessoas saindo para trabalhar durante o período de isolamento, temos que pensar tanto em políticas que as protejam em seus percursos como ampliar o direito ao isolamento paras as pessoas que não estão envolvidas com serviços essenciais mais precisam trabalhar para garantir seu sustento, o que reforça a importância de políticas de garantia de renda e segurança alimentar, subsídios de aluguel e outras despesas, e ações articuladas a coletivos e organizações locais para a proteção dos que mais estão ameaçados durante a pandemia.
Embora esses dados sejam públicos, nos parece que estão sendo ignorados para a definição de estratégias de enfrentamento a pandemia. É urgente repensar a forma como a política de mobilidade na cidade tem sido pensada, já que foram cometidos equívocos tal como o mega rodízio para veículos individuais, que durou apenas alguns dias e provocou uma superlotação nos transportes públicos ampliando os riscos das pessoas que precisavam sair para trabalhar. Ainda não foram implementadas medidas que garantam condições seguras para que as pessoas dos serviços essenciais pudessem fazer as viagens necessárias para exercer seus trabalhos sem ampliar a difusão da infecção do coronavírus. Bem como não existe uma leitura sobre a mobilidade metropolitana — inclusive não existem dados abertos sobre isso — ignorando as dinâmicas pendulares de pessoas que moram e trabalham em municípios diferentes da região metropolitana.
¹ Coordenadoras do LabCidade e professoras da Faculdade de Arquitetura e Urbanismo (FAU) da USP ² Pesquisadores do LabCidade ³ Pesquisadora do Instituto Pólis
Contrary to hopes for a tidy conclusion to the COVID-19 pandemic, history shows that outbreaks of infectious disease often have much murkier outcomes—including simply being forgotten about, or dismissed as someone else’s problem.
Recent history tells us a lot about how epidemics unfold, how outbreaks spread, and how they are controlled. We also know a good deal about beginnings—those first cases of pneumonia in Guangdong marking the SARS outbreak of 2002–3, the earliest instances of influenza in Veracruz leading to the H1N1 influenza pandemic of 2009–10, the outbreak of hemorrhagic fever in Guinea sparking the Ebola pandemic of 2014–16. But these stories of rising action and a dramatic denouement only get us so far in coming to terms with the global crisis of COVID-19. The coronavirus pandemic has blown past many efforts at containment, snapped the reins of case detection and surveillance across the world, and saturated all inhabited continents. To understand possible endings for this epidemic, we must look elsewhere than the neat pattern of beginning and end—and reconsider what we mean by the talk of “ending” epidemics to begin with.
The social lives of epidemics show them to be not just natural phenomena but also narrative ones: deeply shaped by the stories we tell about their beginnings, their middles, their ends.
Historians have long been fascinated by epidemics in part because, even where they differ in details, they exhibit a typical pattern of social choreography recognizable across vast reaches of time and space. Even though the biological agents of the sixth-century Plague of Justinian, the fourteenth-century Black Death, and the early twentieth-century Manchurian Plague were almost certainly not identical, the epidemics themselves share common features that link historical actors to present experience. “As a social phenomenon,” the historian Charles Rosenberg has argued, “an epidemic has a dramaturgic form. Epidemics start at a moment in time, proceed on a stage limited in space and duration, following a plot line of increasing and revelatory tension, move to a crisis of individual and collective character, then drift towards closure.” And yet not all diseases fit so neatly into this typological structure. Rosenberg wrote these words in 1992, nearly a decade into the North American HIV/AIDS epidemic. His words rang true about the origins of that disease—thanks in part to the relentless, overzealous pursuit of its “Patient Zero”—but not so much about its end, which was, as for COVID-19, nowhere in sight.
In the case of the new coronavirus, we have now seen an initial fixation on origins give way to the question of endings. In March The Atlantic offered four possible “timelines for life returning to normal,” all of which depended the biological basis of a sufficient amount of the population developing immunity (perhaps 60 to 80 percent) to curb further spread. This confident assertion derived from models of infectious outbreaks formalized by epidemiologists such as W. H. Frost a century earlier. If the world can be defined into those susceptible (S), infected (I) and resistant (R) to a disease, and a pathogen has a reproductive number R0 (pronounced R-naught) describing how many susceptible people can be infected by a single infected person, the end of the epidemic begins when the proportion of susceptible people drops below the reciprocal, 1/R0. When that happens, one person would infect, on average, less than one other person with the disease.
These formulas reassure us, perhaps deceptively. They conjure up a set of natural laws that give order to the cadence of calamities. The curves produced by models, which in better times belonged to the arcana of epidemiologists, are now common figures in the lives of billions of people learning to live with contractions of civil society promoted in the name of “bending,” “flattening,” or “squashing” them. At the same time, as David Jones and Stefan Helmreich recently wrote in these pages, the smooth lines of these curves are far removed from jagged realities of the day-to-day experience of an epidemic—including the sharp spikes in those “reopening” states where modelers had predicted continued decline.
In other words, epidemics are not merely biological phenomena. They are inevitably framed and shaped by our social responses to them, from beginning to end (whatever that may mean in any particular case). The questions now being asked of scientists, clinicians, mayors, governors, prime ministers, and presidents around the world is not merely “When will the biological phenomenon of this epidemic resolve?” but rather “When, if ever, will the disruption to our social life caused in the name of coronavirus come to an end?” As peak incidence nears, and in many places appears to have passed, elected officials and think tanks from opposite ends of the political spectrum provide “roadmaps” and “frameworks” for how an epidemic that has shut down economic, civic, and social life in a manner not seen globally in at least a century might eventually recede and allow resumption of a “new normal.”
To understand possible endings for this epidemic, we must look elsewhere than the neat pattern of beginning and end—and reconsider what we mean by the talk of “ending” epidemics to begin with.
These two faces of an epidemic, the biological and the social, are closely intertwined, but they are not the same. The biological epidemic can shut down daily life by sickening and killing people, but the social epidemic also shuts down daily life by overturning basic premises of sociality, economics, governance, discourse, interaction—and killing people in the process as well. There is a risk, as we know from both the Spanish influenza of 1918–19 and the more recent swine flu of 2008–9, of relaxing social responses before the biological threat has passed. But there is also a risk in misjudging a biological threat based on faulty models or bad data and in disrupting social life in such a way that the restrictions can never properly be taken back. We have seen in the case of coronavirus the two faces of the epidemic escalating on local, national, and global levels in tandem, but the biological epidemic and the social epidemic don’t necessarily recede on the same timeline.
For these sorts of reasons we must step back and reflect in detail on what we mean by ending in the first place. The history of epidemic endings has taken many forms, and only a handful of them have resulted in the elimination of a disease.
History reminds us that the interconnections between the timing of the biological and social epidemics are far from obvious. In some cases, like the yellow fever epidemics of the eighteenth century and the cholera epidemics of the nineteenth century, the dramatic symptomatology of the disease itself can make its timing easy to track. Like a bag of popcorn popping in the microwave, the tempo of visible case-events begins slowly, escalates to a frenetic peak, and then recedes, leaving a diminishing frequency of new cases that eventually are spaced far enough apart to be contained and then eliminated. In other examples, however, like the polio epidemics of the twentieth century, the disease process itself is hidden, often mild in presentation, threatens to come back, and ends not on a single day but over different timescales and in different ways for different people.
Campaigns against infectious diseases are often discussed in military terms, and one result of that metaphor is to suggest that epidemics too must have a singular endpoint. We approach the infection peak as if it were a decisive battle like Waterloo, or a diplomatic arrangement like the Armistice at Compiègne in November 1918. Yet the chronology of a single, decisive ending is not always true even for military history, of course. Just as the clear ending of a military war does not necessarily bring a close to the experience of war in everyday life, so too the resolution of the biological epidemic does not immediately undo the effects of the social epidemic. The social and economic effects of the 1918–1919 pandemic, for example, were felt long after the end of the third and putatively final wave of the virus. While the immediate economic effect on many local businesses caused by shutdowns appears to have resolved in a matter of months, the broader economic effects of the epidemic on labor-wage relations were still visible in economic surveys in 1920, again in 1921, and in several areas as far as 1930.
The history of epidemic endings has taken many forms, and only a handful of them have resulted in the elimination of a disease.
And yet, like World War One with which its history was so closely intertwined, the influenza pandemic of 1918–19 appeared at first to have a singular ending. In individual cities the epidemic often produced dramatic spikes and falls in equally rapid tempo. In Philadelphia, as John Barry notes in The Great Influenza (2004), after an explosive and deadly rise in October 1919 that peaked at 4,597 deaths in a single week, cases suddenly dropped so precipitously that the public gathering ban could be lifted before the month was over, with almost no new cases in following weeks. A phenomenon whose destructive potential was limited by material laws, “the virus burned through available fuel, then it quickly faded away.”
As Barry reminds us, however, scholars have since learned to differentiate at least three different sequences of epidemics within the broader pandemic. The first wave blazed through military installations in the spring of 1918, the second wave caused the devastating mortality spikes in the summer and fall of 1918, and the third wave began in December 1918 and lingered long through the summer of 1919. Some cities, like San Francisco, passed through the first and second waves relatively unscathed only to be devastated by the third wave. Nor was it clear to those still alive in 1919 that the pandemic was over after the third wave receded. Even as late as 1922, a bad flu season in Washington State merited a response from public health officials to enforce absolute quarantine as they had during 1918–19. It is difficult, looking back, to say exactly when this prototypical pandemic of the twentieth century was really over.
Who can tell when a pandemic has ended? Today, strictly speaking, only the World Health Organization (WHO). The Emergency Committee of the WHO is responsible for the global governance of health and international coordination of epidemic response. After the SARS coronavirus pandemic of 2002–3, this body was granted sole power to declare the beginnings and endings of Public Health Emergencies of International Concern (PHEIC). While SARS morbidity and mortality—roughly 8,000 cases and 800 deaths in 26 countries—has been dwarfed by the sheer scale of COVID-19, the pandemic’s effect on national and global economies prompted revisions to the International Health Regulations in 2005, a body of international law that had remained unchanged since 1969. This revision broadened the scope of coordinated global response from a handful of diseases to any public health event that the WHO deemed to be of international concern and shifted from a reactive response framework to a pro-active one based on real-time surveillance and detection and containment at the source rather than merely action at international borders.
This social infrastructure has important consequences, not all of them necessarily positive. Any time the WHO declares a public health event of international concern—and frequently when it chooses not to declare one—the event becomes a matter of front-page news. Since the 2005 revision, the group has been criticized both for declaring a PHEIC too hastily (as in the case of H1N1) or too late (in the case of Ebola). The WHO’s decision to declare the end of a PHEIC, by contrast, is rarely subject to the same public scrutiny. When an outbreak is no longer classified as an “extraordinary event” and no longer is seen to pose a risk at international spread, the PHEIC is considered not to be justified, leading to a withdrawal of international coordination. Once countries can grapple with the disease within their own borders, under their own national frameworks, the PHEIC is quietly de-escalated.
At their worst, epidemic endings are a form of collective amnesia, transmuting the disease that remains into merely someone else’s problem.
As the response to the 2014–16 Ebola outbreak in West Africa demonstrates, however, the act of declaring the end of a pandemic can be just as powerful as the act of declaring its beginning—in part because emergency situations can continue even after a return to “normal” has been declared. When WHO Director General Margaret Chan announced in March 2016 that the Ebola outbreak was no longer a public health event of international concern, international donors withdrew funds and care to the West African countries devastated by the outbreak, even as these struggling health systems continued to be stretched beyond their means by the needs of Ebola survivors. NGOs and virologists expressed concern that efforts to fund Ebola vaccine development would likewise fade without a sense of global urgency pushing research forward.
Part of the reason that the role of the WHO in proclaiming and terminating the state of pandemic is subject to so much scrutiny is that it can be. The WHO is the only global health body that is accountable to all governments of the world; its parliamentary World Health Assembly contains health ministers from every nation. Its authority rests not so much on its battered budget as its access to epidemic intelligence and pool of select individuals, technical experts with vast experience in epidemic response. But even though internationally sourced scientific and public health authority is key to its role in pandemic crises, WHO guidance is ultimately carried out in very different ways and on very different time scales in different countries, provinces, states, counties, and cities. One state might begin to ease up restrictions to movement and industry just as another implements more and more stringent measures. If each country’s experience of “lockdown” has already been heterogeneous, the reconnection between them after the PHEIC is ended will likely show even more variance.
So many of our hopes for the termination of the present PHEIC now lie in the promise of a COVID-19 vaccine. Yet a closer look at one of the central vaccine success stories of the twentieth century shows that technological solutions rarely offer resolution to pandemics on their own. Contrary to our expectations, vaccines are not universal technologies. They are always deployed locally, with variable resources and commitments to scientific expertise. International variations in research, development, and dissemination of effective vaccines are especially relevant in the global fight against epidemic polio.
The development of the polio vaccine is relatively well known, usually told as a story of an American tragedy and triumph. Yet while polio epidemics that swept the globe in the postwar decades did not respect national borders or the Iron Curtain, the Cold War provided context for both collaboration and antagonism. Only a few years after the licensing of Jonas Salk’s inactivated vaccine in the United States, his technique became widely used across the world, although its efficacy outside of the United States was questioned. The second, live oral vaccine developed by Albert Sabin, however, involved extensive collaboration in with Eastern European and Soviet colleagues. As the success of the Soviet polio vaccine trials marked a rare landmark of Cold War cooperation, Basil O’Connor, president of the March of Dimes movement, speaking at the Fifth International Poliomyelitis Conference in 1960, proclaimed that “in search for the truth that frees man from disease, there is no cold war.”
Two faces of an epidemic, the biological and the social, are closely intertwined, but they are not the same.
Yet the differential uptake of this vaccine retraced the divisions of Cold War geography. The Soviet Union, Hungary, and Czechoslovakia were the first countries in the world to begin nationwide immunization with the Sabin vaccine, soon followed by Cuba, the first country in the Western Hemisphere to eliminate the disease. By the time the Sabin vaccine was licensed in the United States in 1963, much of Eastern Europe had done away with epidemics and was largely polio-free. The successful ending of this epidemic within the communist world was immediately held up as proof of the superiority of their political system.
Western experts who trusted the Soviet vaccine trials, including the Yale virologist and WHO envoy Dorothy Horstmann, nonetheless emphasized that their results were possible because of the military-like organization of the Soviet health care system. Yet these enduring concerns that authoritarianism itself was the key tool for ending epidemics—a concern reflected in current debates over China’s heavy-handed interventions in Wuhan this year—can also be overstated. The Cold War East was united not only by authoritarianism and heavy hierarchies in state organization and society, but also by a powerful shared belief in the integration of paternal state, biomedical research, and socialized medicine. Epidemic management in these countries combined an emphasis on prevention, easily mobilized health workers, top-down organization of vaccinations, and a rhetoric of solidarity, all resting on a health care system that aimed at access to all citizens.
Still, authoritarianism as a catalyst for controlling epidemics can be singled out and pursued with long-lasting consequences. Epidemics can be harbingers of significant political changes that go well beyond their ending, significantly reshaping a new “normal” after the threat passes. Many Hungarians, for example, have watched with alarm the complete sidelining of parliament and the introduction of government by decree at the end of March this year. The end of any epidemic crisis, and thus the end of the need for the significantly increased power of Viktor Orbán, would be determined by Orbán himself. Likewise, many other states, urging the mobilization of new technologies as a solution to end epidemics, are opening the door to heightened state surveillance of their citizens. The apps and trackers now being designed to follow the movement and exposure of people in order to enable the end of epidemic lockdowns can collect data and establish mechanisms that reach well beyond the original intent. The digital afterlives of these practices raise new and unprecedented questions about when and how epidemics end.
Like infectious agents on an agar plate, epidemics colonize our social lives and force us to learn to live with them, in some way or another, for the foreseeable future.
Although we want to believe that a single technological breakthrough will end the present crisis, the application of any global health technology is always locally determined. After its dramatic successes in managing polio epidemics in the late 1950s and early 1960s, the oral poliovirus vaccine became the tool of choice for the Global Polio Eradication Initiative in the late 1980s, as it promised an end to “summer fears” globally. But since vaccines are in part technologies of trust, ending polio outbreaks depends on maintaining confidence in national and international structures through which vaccines are delivered. Wherever that often fragile trust is fractured or undermined, vaccination rates can drop to a critical level, giving way to vaccine-derived polio, which thrives in partially vaccinated populations.
In Kano, Nigeria, for example, a ban on polio vaccination between 2000 and 2004 resulted in a new national polio epidemic that soon spread to neighboring countries. As late as December 2019 polio outbreaks were still reported in fifteen African countries, including Angola and the Democratic Republic of the Congo. Nor is it clear that polio can fully be regarded as an epidemic at this point: while polio epidemics are now a thing of the past for Hungary—and the rest of Europe, the Americas, Australia, and East Asia as well—the disease is still endemic to parts of Africa and South Asia. A disease once universally epidemic is now locally endemic: this, too, is another way that epidemics end.
Indeed, many epidemics have only “ended” through widespread acceptance of a newly endemic state. Consider the global threat of HIV/AIDS. From a strictly biological perspective, the AIDS epidemic has never ended; the virus continues to spread devastation through the world, infecting 1.7 million people and claiming an estimated 770,000 lives in the year 2018 alone. But HIV is not generally described these days with the same urgency and fear that accompanied the newly defined AIDS epidemic in the early 1980s. Like coronavirus today, AIDS at that time was a rapidly spreading and unknown emerging threat, splayed across newspaper headlines and magazine covers, claiming the lives of celebrities and ordinary citizens alike. Nearly forty years later it has largely become a chronic disease endemic, at least in the Global North. Like diabetes, which claimed an estimated 4.9 million lives in 2019, HIV/AIDS became a manageable condition—if one had access to the right medications.
Those who are no longer directly threatened by the impact of the disease have a hard time continuing to attend to the urgency of an epidemic that has been rolling on for nearly four decades. Even in the first decade of the AIDS epidemic, activists in the United States fought tooth and nail to make their suffering visible in the face of both the Reagan administration’s dogged refusal to talk publicly about the AIDS crisis and the indifference of the press after the initial sensation of the newly discovered virus had become common knowledge. In this respect, the social epidemic does not necessarily end when biological transmission has ended, or even peaked, but rather when, in the attention of the general public and in the judgment of certain media and political elites who shape that attention, the disease ceases to be newsworthy.
Though we like to think of science as universal and objective, crossing borders and transcending differences, it is in fact deeply contingent upon local practices.
Polio, for its part, has not been newsworthy for a while, even as thousands around the world still live with polio with ever-decreasing access to care and support. Soon after the immediate threat of outbreaks passed, so did support for those whose lives were still bound up with the disease. For others, it became simply a background fact of life—something that happens elsewhere. The polio problem was “solved,” specialized hospitals were closed, fundraising organizations found new causes, and poster children found themselves in an increasingly challenging world. Few medical professionals are trained today in the treatment of the disease. As intimate knowledge of polio and its treatment withered away with time, people living with polio became embodied repositories of lost knowledge.
History tells us public attention is much more easily drawn to new diseases as they emerge rather than sustained over the long haul. Well before AIDS shocked the world into recognizing the devastating potential of novel epidemic diseases, a series of earlier outbreaks had already signaled the presence of emerging infectious agents. When hundreds of members of the American Legion fell ill after their annual meeting in Philadelphia in 1976, the efforts of epidemiologists from the Centers for Disease Control to explain the spread of this mysterious disease and its newly discovered bacterial agent, Legionella, occupied front-page headlines. In the years since, however, as the 1976 incident faded from memory, Legionella infections have become everyday objects of medical care, even though incidence in the U.S. has grown ninefold since 2000, tracing a line of exponential growth that looks a lot like COVID-19’s on a longer time scale. Yet few among us pause in our daily lives to consider whether we are living through the slowly ascending limb of a Legionella epidemic.
Nor do most people living in the United States stop to consider the ravages of tuberculosis as a pandemic, even though an estimated 10 million new cases of tuberculosis were reported around the globe in 2018, and an estimated 1.5 million people died from the disease. The disease seems to only receive attention in relation to newer scourges: in the late twentieth century TB coinfection became a leading cause of death in emerging HIV/AIDS pandemic, while in the past few months TB coinfection has been invoked as a rising cause of mortality in COVID-19 pandemic. Amidst these stories it is easy to miss that on its own, tuberculosis has been and continues to be the leading cause of death worldwide from a single infectious agent. And even though tuberculosis is not an active concern of middle-class Americans, it is still not a thing of the past even in this country. More than 9,000 cases of tuberculosis were reported in the United States in 2018—overwhelmingly affecting racial and ethnic minority populations—but they rarely made the news.
There will be no simple return to the way things were: whatever normal we build will be a new one—whether many of us realize it or not.
While tuberculosis is the target of concerted international disease control efforts, and occasionally eradication efforts, the time course of this affliction has been spread out so long—and so clearly demarcated in space as a problem of “other places”—that it is no longer part of the epidemic imagination of the Global North. And yet history tells a very different story. DNA lineage studies of tuberculosis now show that the spread of tuberculosis in sub-Saharan Africa and Latin America was initiated by European contact and conquest from the fifteenth century through the nineteenth. In the early decades of the twentieth century, tuberculosis epidemics accelerated throughout sub-Saharan Africa, South Asia, and Southeast Asia due to the rapid urbanization and industrialization of European colonies. Although the wave of decolonizations that swept these regions between the 1940s and the 1980s established autonomy and sovereignty for newly post-colonial nations, this movement did not send tuberculosis back to Europe.
These features of the social lives of epidemics—how they live on even when they seem, to some, to have disappeared—show them to be not just natural phenomena but also narrative ones: deeply shaped by the stories we tell about their beginnings, their middles, their ends. At their best, epidemic endings are a form of relief for the mainstream “we” that can pick up the pieces and reconstitute a normal life. At their worst, epidemic endings are a form of collective amnesia, transmuting the disease that remains into merely someone else’s problem.
What are we to conclude from these complex interactions between the social and the biological faces of epidemics, past and present? Like infectious agents on an agar plate, epidemics colonize our social lives and force us to learn to live with them, in some way or another, for the foreseeable future. Just as the postcolonial period continued to be shaped by structures established under colonial rule, so too are our post-pandemic futures indelibly shaped by what we do now. There will be no simple return to the way things were: whatever normal we build will be a new one—whether many of us realize it or not. Like the world of scientific facts after the end of a critical experiment, the world that we find after an the end of an epidemic crisis—whatever we take that to be—looks in many ways like the world that came before, but with new social truths established. How exactly these norms come into being depends a great deal on particular circumstances: current interactions among people, the instruments of social policy as well as medical and public health intervention with which we apply our efforts, and the underlying response of the material which we applied that apparatus against (in this case, the coronavirus strain SARS-CoV-2). While we cannot know now how the present epidemic will end, we can be confident that it in its wake it will leave different conceptions of normal in realms biological and social, national and international, economic and political.
Though we like to think of science as universal and objective, crossing borders and transcending differences, it is in fact deeply contingent upon local practices—including norms that are easily thrown over in an emergency, and established conventions that do not always hold up in situations of urgency. Today we see civic leaders jumping the gun in speaking of access to treatments, antibody screens, and vaccines well in advance of any scientific evidence, while relatively straightforward attempts to estimate the true number of people affected by the disease spark firestorms over the credibility of medical knowledge. Arduous work is often required to achieve scientific consensus, and when the stakes are high—especially when huge numbers of lives are at risk—heterogeneous data give way to highly variable interpretations. As data moves too quickly in some domains and too slowly in others, and sped-up time pressures are placed on all investigations the projected curve of the epidemic is transformed into an elaborate guessing game, in which different states rely on different kinds of scientific claims to sketch out wildly different timetables for ending social restrictions.
The falling action of an epidemic is perhaps best thought of as asymptotic: never disappearing, but rather fading to the point where signal is lost in the noise of the new normal—and even allowed to be forgotten.
These varied endings of the epidemic across local and national settings will only be valid insofar as they are acknowledged as such by others—especially if any reopening of trade and travel is to be achieved. In this sense, the process of establishing a new normal in global commerce will continue to be bound up in practices of international consensus. What the new normal in global health governance will look like, however, is more uncertain than ever. Long accustomed to the role of international scapegoat, the WHO Secretariat seems doomed to be accused either of working beyond its mandate or not acting fast enough. Moreover, it can easily become a target of scapegoating, as the secessionist posturing of Donald Trump demonstrates. Yet the U.S. president’s recent withdrawal from this international body is neither unprecedented nor unsurmountable. Although Trump’s voting base might not wish to be grouped together with the only other global power to secede from the WHO, after the Soviet Union’s 1949 departure from the group it ultimately brought all Eastern Bloc back to task of international health leadership in 1956. Much as the return of the Soviets to the WHO resulted in the global eradication of smallpox—the only human disease so far to have been intentionally eradicated—it is possible that some future return of the United States to the project of global health governance might also result in a more hopeful post-pandemic future.
As the historians at the University of Oslo have recently noted, in epidemic periods “the present moves faster, the past seems further removed, and the future seems completely unpredictable.” How, then, are we to know when epidemics end? How does the act of looking back aid us in determining a way forward? Historians make poor futurologists, but we spend a lot of time thinking about time. And epidemics produce their own kinds of time, in both biological and social domains, disrupting our individual senses of passing days as well as conventions for collective behavior. They carry within them their own tempos and rhythms: the slow initial growth, the explosive upward limb of the outbreak, the slowing of transmission that marks the peak, plateau, and the downward limb. This falling action is perhaps best thought of as asymptotic: rarely disappearing, but rather fading to the point where signal is lost in the noise of the new normal—and even allowed to be forgotten.
Have you heard the axiom “In war, truth is the first casualty?”
As healthcare providers around the world wage war against the COVID-19 pandemic, national governments have taken to brawling with researchers, the media and each other over the veracity of the data used to monitor and track the disease’s march across the globe.
Allegations of deliberate data tampering carry profound public health implications. If a country knowingly misleads the World Health Organization (WHO) about the emergence of an epidemic or conceals the severity of an outbreak within its borders, precious time is lost. Time that could be spent mobilising resources around the globe to contain the spread of the disease. Time to prepare health systems for a coming tsunami of infections. Time to save more lives.
No one country has claimed that their science or data is perfect: French and US authorities confirmed they had their first coronavirus cases weeks earlier than previously thought.
Still, coronavirus – and the data used to benchmark it – has become grist for the political mill. But if we tune out the voices of politicians and pundits, and listen to those of good governance experts, data scientists and epidemiological specialists, what does the most basic but consequential data – the number of confirmed cases per country – tell us about how various governments around the globe are crunching coronavirus numbers and spinning corona-narratives?
What the good governance advocates say
Similar to how meteorologists track storms, data scientists use models to express how epidemics progress, and to predict where the next hurricane of new infections will batter health systems.
This data is fed by researchers into computer modelling programmes that national authorities and the WHO use to advise countries and aid organisations on where to send medical professionals and equipment, and when to take actions such as issuing lockdown orders.
The WHO also harnesses this data to produce a daily report that news organisations use to provide context around policy decisions related to the pandemic. But, unlike a hurricane, which cannot be hidden, epidemic data can be fudged and manipulated.
“The WHO infection numbers are based on reporting from its member states. The WHO cannot verify these numbers,” said Michael Meyer-Resende, Democracy Reporting International’s executive director.
To date, more than 8 million people have been diagnosed as confirmed cases of COVID-19. Of that number, more than 443,000 have died from the virus, according to Johns Hopkins University.
Those numbers are commonly quoted, but what is often not explained is that they both ultimately hinge on two factors: how many people are being tested, and the accuracy of the tests being administered. These numbers we “fetishise”, said Meyer-Resende, “depend on testing, on honesty of governments and on size of the population”.
“Many authoritarian governments are not transparent with their data generally, and one should not expect that they are transparent in this case,” he said. To test Meyer-Resende’s theory that less government transparency equals less transparent COVID-19 case data, Al Jazeera used Transparency International’s Corruption Perceptions Index and the Economist Intelligence Unit’s Democracy Index as lenses through which to view the number of reported cases of the coronavirus.
The examination revealed striking differences in the number of confirmed COVID-19 cases that those nations deemed transparent and democratic reported compared to the numbers reported by nations perceived to be corrupt and authoritarian.
Denmark, with a population of roughly six million, is ranked in the top 10 of the most transparent and democratic countries. The country reported on May 1 that it had 9,158 confirmed cases of COVID-19, a ratio of 1,581 confirmed cases per million. That was more than triple the world average for that day – 412 cases per million people – according to available data.
Meanwhile, Turkmenistan, a regular in the basement of governance and corruption indexes, maintains that not one of its roughly six million citizens has been infected with COVID-19, even though it borders and has extensive trade with Iran, a regional epicentre of the pandemic.
Also on May 1, Myanmar, with a population of more than 56 million, reported just 151 confirmed cases of infection, a rate of 2.8 infections per million. That is despite the fact that every day, roughly 10,000 workers cross the border into China, where the pandemic first began.
On February 4, Myanmar suspended its air links with Chinese cities, including Wuhan, where COVID-19 is said to have originated last December (however, a recent study reported that the virus may have hit the city as early as August 2019).
“That just seems abnormal, out of the ordinary. Right?” said Roberto Kukutschka, Transparency International’s research coordinator, in reference to the numbers of reported cases.
“In these countries where you have high levels of corruption, there are high levels of discretion as well,” he told Al Jazeera. “It’s counter-intuitive that these countries are reporting so few cases, when all countries that are more open about these things are reporting way more. It’s very strange.”
While Myanmar has started taking steps to address the pandemic, critics say a month of preparation was lost to jingoistic denial. Ten days before the first two cases were confirmed, government spokesman Zaw Htay claimed the country was protected by its lifestyle and diet, and because cash is used instead of credit cards to make purchases.
Turkmenistan’s authorities have reportedly removed almost all mentions of the coronavirus from official publications, including a read-out of a March 27 phone call between Uzbek President Shavkat Mirziyoyev and Turkmen President Gurbanguly Berdimuhamedov.
It is unclear if Turkmenistan even has a testing regime.
Russia, on the other hand, touts the number of tests it claims to have performed, but not how many people have been tested – and that is a key distinction because the same person can be tested more than once. Transparency International places Russia in the bottom third of its corruption index.
On May 1, Russia, with a population just above 145 million, reported that it had confirmed 106,498 cases of COVID-19 after conducting an astounding 3.72 million “laboratory tests”. Just 2.9 percent of the tests produced a positive result.
Remember, Denmark’s population is six million, or half that of Moscow’s. Denmark had reportedly tested 206,576 people by May 1 and had 9,158 confirmed coronavirus cases, a rate of 4.4 percent. Finland, another democracy at the top of the transparency index, has a population of 5.5 million and a positive test result rate of 4.7 percent.
This discrepancy spurred the editors of PCR News, a Moscow-based Russian-language molecular diagnostics journal, to take a closer look at the Russian test. They reported that in order to achieve a positive COVID-19 result, the sample tested must contain a much higher volume of the virus, or viral load, as compared to the amount required for a positive influenza test result.
In terms of sensitivity or ability to detect COVID-19, the authors wrote: “Is it high or low? By modern standards – low.”
They later added, “The test will not reveal the onset of the disease, or it will be decided too early that the recovering patient no longer releases viruses and cannot infect anyone. And he walks along the street, and he is contagious.”
Ostensibly, if that person then dies, COVID-19 will not be certified as the cause of death.
Good governance experts see a dynamic at play.
Countries who test less will be shown as less of a problem. Countries that test badly will seem as if they don’t have a problem. Numbers are very powerful.
Michael Meyer-Resende, Democracy Reporting International
“In many of these countries, the legitimacy of the state depends on not going into crisis,” said Kukutschka, adding that he counts countries with world-class health systems among them.
“Countries who test less will be shown as less of a problem. Countries that test badly will seem as if they don’t have a problem,” said Meyer-Resende. “Numbers are very powerful. They seem objective.”
Meyer-Resende highlighted the case of China. “The Chinese government said for a while that it had zero new cases. That’s a very powerful statement. It says it all with a single digit: ‘We have solved the problem’. Except, it hadn’t. It had changed the way of counting cases.”
China – where the pandemic originated – recently escaped a joint US-Australian-led effort at the World Health Assembly to investigate whether Beijing had for weeks concealed a deadly epidemic from the WHO.
China alerted the WHO about the epidemic on December 31, 2019. Researchers at the University of Hong Kong estimated that the actual number of COVID-19 cases in China, where the coronavirus first appeared, could have been four times greater in the beginning of this year than what Chinese authorities had been reporting to the WHO.
“We estimated that by Feb 20, 2020, there would have been 232,000 confirmed cases in China as opposed to the 55,508 confirmed cases reported,” said the researchers’ report published by the Lancet.
The University of Hong Kong researchers attribute the discrepancy to ever-changing case definitions, the official guidance that tells doctors which symptoms – and therefore patients – can be diagnosed and recorded as COVID-19. China’s National Health Commission issued no less than seven versions of these guidelines between January 15 and March 3.
All of which adds to the confusion.
“Essentially, we are moving in a thick fog, and the numbers we have are no more than a small flashlight,” said Meyer-Resende.
What the epidemiological expert thinks
Dr Ghassan Aziz monitors epidemics in the Middle East. He is the Health Surveillance Program manager at the Doctors Without Borders (MSF) Middle East Unit. He spoke to Al Jazeera in his own capacity and not on behalf of the NGO.
“I think Iran, they’re not reporting everything,” he told Al Jazeera. “It’s fair to assume that [some countries] are underreporting because they are under-diagnosing. They report what they detect.”
“Maybe [it’s] on purpose, and maybe because of the sanctions and the lack of testing capacities,” said Aziz.
Once China shared the novel coronavirus genome on January 24, many governments began in earnest to test their populations. Others have placed limits on who can be tested.
In Brazil, due to a sustained lack of available tests, patients using the public health network in April were tested only if they were hospitalised with severe symptoms. On April 1, Brazil reported that 201 people had died from the virus. That number was challenged by doctors and relatives of the dead. A month later, after one minister of health was fired and another resigned after a week on the job, the testing protocols had not changed.
On May 1, Brazil reported that COVID-19 was the cause of death for 5,901 people. On June 5, Brazil’s health ministry took down the website that reported cumulative coronavirus numbers – only to be ordered by the country’s Supreme Court to reinstate the information.
Right-wing President Jair Bolsonaro has repeatedly played down the severity of the coronavirus pandemic, calling it “a little flu”. Brazilian Supreme Court Justice Gilmar Mendes accused the government of attempting to manipulate statistics, calling it “a manoeuvre of totalitarian regimes”.
Brazil currently has the dubious distinction of having the second-highest number of COVID-19 deaths in the world, behind the US. By June 15, the COVID-19 death toll in the country had surpassed 43,300 people.
Dr Aziz contends that even with testing, many countries customarily employ a “denial policy”. He said in his native country, Iraq, health authorities routinely obfuscate health emergencies by changing the names of outbreaks such as cholera to “endemic diarrhoea”, or Crimean-Congo hemorrhagic fever to “epidemic fever”.
“In Iraq, they give this idea to the people that ‘We did our best. We controlled it,'” Dr Aziz said. “When someone dies, ‘Oh. It’s not COVID-19. He was sick. He was old. This is God’s will. It was Allah.’ This is what I find so annoying.”
What the data scientist says
Sarah Callaghan, a data scientist and the editor-in-chief of Patterns, a data-science medical journal, told Al Jazeera the numbers of confirmed cases countries report reflect “the unique testing and environmental challenges that each country is facing”.
But, she cautioned: “Some countries have the resources and infrastructure to carry out widespread testing, others simply don’t. Some countries might have the money and the ability to test, but other local issues come into play, like politics.”
According to Callaghan, even in the best of times under the best circumstances, collecting data on an infectious disease is both difficult and expensive. But despite the difficulties presented by some countries’ data, she remains confident that the data and modelling that is available will indeed contribute much to understanding how COVID-19 spreads, how the virus reacts to different environmental conditions, and discovering the questions that need answers.
Her advice is: “When looking at the numbers, think about them. Ask yourself if you trust the source. Ask yourself if the source is trying to push a political or economic agenda.”
“There’s a lot about this situation that we don’t know, and a lot more misinformation that’s being spread, accidentally or deliberately.”
Many mass immunization efforts worldwide were halted this spring to prevent spread of the virus at crowded inoculation sites. The consequences have been alarming.
As poor countries around the world struggle to beat back the coronavirus, they are unintentionally contributing to fresh explosions of illness and death from other diseases — ones that are readily prevented by vaccines.
This spring, after the World Health Organization and UNICEF warned that the pandemic could spread swiftly when children gathered for shots, many countries suspended their inoculation programs. Even in countries that tried to keep them going, cargo flights with vaccine supplies were halted by the pandemic and health workers diverted to fight it.
Now, diphtheria is appearing in Pakistan, Bangladesh and Nepal.
Cholera is in South Sudan, Cameroon, Mozambique, Yemen and Bangladesh.
A mutated strain of poliovirus has been reported in more than 30 countries.
And measles is flaring around the globe, including in Bangladesh, Brazil, Cambodia, Central African Republic, Iraq, Kazakhstan, Nepal, Nigeria and Uzbekistan.
Of 29 countries that have currently suspended measles campaigns because of the pandemic, 18 are reporting outbreaks. An additional 13 countries are considering postponement. According to the Measles and Rubella Initiative, 178 million people are at risk of missing measles shots in 2020.
The risk now is “an epidemic in a few months’ time that will kill more children than Covid,” said Chibuzo Okonta, the president of Doctors Without Borders in West and Central Africa.
As the pandemic lingers, the W.H.O. and other international public health groups are now urging countries to carefully resume vaccination while contending with the coronavirus.
“Immunization is one of the most powerful and fundamental disease prevention tools in the history of public health,” said Dr. Tedros Adhanom Ghebreyesus, director general of the W.H.O., in a statement. “Disruption to immunization programs from the Covid-19 pandemic threatens to unwind decades of progress against vaccine-preventable diseases like measles.”
But the obstacles to restarting are considerable. Vaccine supplies are still hard to come by. Health care workers are increasingly working full time on Covid-19, the infection caused by the coronavirus. And a new wave of vaccine hesitancy is keeping parents from clinics.
Many countries have yet to be hit with the full force of the pandemic itself, which will further weaken their capabilities to handle outbreaks of other diseases.
“We will have countries trying to recover from Covid and then facing measles. It would stretch their health systems further and have serious economic and humanitarian consequences,” said Dr. Robin Nandy, chief of immunization for UNICEF, which supplies vaccines to 100 countries, reaching 45 percent of children under 5.
The breakdown of vaccine delivery also has stark implications for protecting against the coronavirus itself.
But as services collapse under the pandemic, “they are the same ones that will be needed to send out a Covid vaccine,” warned Dr. Katherine O’Brien, the W.H.O.’s director of immunization, vaccines and biologicals, during a recent webinar on immunization challenges.
Battling Measles in Congo
Three health care workers with coolers full of vaccines and a support team of town criers and note-takers recently stepped into a motorized wooden canoe to set off down the wide Tshopo River in the Democratic Republic of Congo.
Although measles was breaking out in all of the country’s 26 provinces, the pandemic had shut down many inoculation programs weeks earlier.
The crew in the canoe needed to strike a balance between preventing the transmission of a new virus that is just starting to hit Africa hard and stopping an old, known killer. But when the long, narrow canoe pulled in at riverside communities, the crew’s biggest challenge turned out not to be the mechanics of vaccinating children while observing the pandemic’s new safety strictures. Instead, the crew found themselves working hard just to persuade villagers to allow their children to be immunized at all.
Many parents were convinced that the team was lying about the vaccine — that it was not for measles but, secretly, an experimental coronavirus vaccine, for which they would be unwitting guinea pigs.
In April, French-speaking Africa had been outraged by a French television interview in which two researchers said coronavirus vaccines should be tested in Africa — a remark that reignited memories of a long history of such abuses. And in Congo, the virologist in charge of the coronavirus response said that the country had indeed agreed to take part in clinical vaccine trials this summer. Later, he clarified that any vaccine would not be tested in Congo until it had been tested elsewhere. But pernicious rumors had already spread.
The team cajoled parents as best they could. Although vaccinators throughout Tshopo ultimately immunized 16,000 children, 2,000 others eluded them.
This had been the year that Congo, the second-largest country in Africa, was to launch a national immunization program. The urgency could not have been greater. The measles epidemic in the country, which started in 2018, has run on and on: Since this January alone, there have been more than 60,000 cases and 800 deaths. Now, Ebola has again flared, in addition to tuberculosis and cholera, which regularly strike the country.
Vaccines exist for all these diseases, although they are not always available. In late 2018, the country began an immunization initiative in nine provinces. It was a feat of coordination and initiative, and in 2019, the first full year, the percentage of fully immunized children jumped from 42 to 62 percent in Kinshasa, the capital.
This spring, as the program was being readied for its nationwide rollout, the coronavirus struck. Mass vaccination campaigns, which often mean summoning hundreds of children to sit close together in schoolyards and markets, seemed guaranteed to spread coronavirus. Even routine immunization, which typically occurs in clinics, became untenable in many areas.
The country’s health authorities decided to allow vaccinations to continue in areas with measles but no coronavirus cases. But the pandemic froze international flights that would bring medical supplies, and several provinces began running out of vaccines for polio, measles and tuberculosis.
When immunization supplies finally arrived in Kinshasa, they could not be moved around the country. Domestic flights had been suspended. Ground transport was not viable because of shoddy roads. Eventually, a United Nations peacekeeping mission ferried supplies on its planes.
Still, health workers, who had no masks, gloves or sanitizing gel, worried about getting infected; many stopped working. Others were diverted to be trained for Covid.
The cumulative impact has been particularly dire for polio eradication — around 85,000 Congolese children have not received that vaccine.
But the disease that public health officials are most concerned about erupting is measles.
More contagious than Covid
Measles virus spreads easily by aerosol — tiny particles or droplets suspended in the air — and is far more contagious than the coronavirus, according to experts at the Centers for Disease Control and Prevention.
“If people walk into a room where a person with measles had been two hours ago and no one has been immunized, 100 percent of those people will get infected,” said Dr. Yvonne Maldonado, a pediatric infectious disease expert at Stanford University.
In poorer countries, the measles mortality rate for children under 5 ranges between 3 and 6 percent; conditions like malnutrition or an overcrowded refugee camp can increase the fatality rate. Children may succumb to complications such as pneumonia, encephalitis and severe diarrhea.
In 2018, the most recent year for which data worldwide has been compiled, there were nearly 10 million estimated cases of measles and 142,300 related deaths. And global immunization programs were more robust then.
Before the coronavirus pandemic in Ethiopia, 91 percent of children in the capital, Addis Ababa, received their first measles vaccination during routine visits, while 29 percent in rural regions got them. (To prevent an outbreak of a highly infectious disease like measles, the optimum coverage is 95 percent or higher, with two doses of vaccine.) When the pandemic struck, the country suspended its April measles campaign. But the government continues to report many new cases.
“Outbreak pathogens don’t recognize borders,” said Dr. O’Brien of the W.H.O. “Especially measles: Measles anywhere is measles everywhere.”
Once people start traveling again, the risk of infection will surge. “It keeps me up at night,” said Dr. Stephen L. Cochi, a senior adviser at the global immunization division at the C.D.C. “These vaccine-preventable diseases are just one plane ride away.”
After the W.H.O. and its vaccine partners released the results of a survey last month showing that 80 million babies under a year old were at risk of missing routine immunizations, some countries, including Ethiopia, the Central African Republic and Nepal, began trying to restart their programs.
Uganda is now supplying health workers with motorbikes. In Brazil, some pharmacies are offering drive-by immunization services. In the Indian state of Bihar, a 50-year-old health care worker learned to ride a bicycle in three days so she could take vaccines to far-flung families. UNICEF chartered a flight to deliver vaccines to seven African countries.
Dr. Cochi of the C.D.C., which provides technical and program support to more than 40 countries, said that whether such campaigns can be conducted during the pandemic is an open question. “It will be fraught with limitations. We’re talking low-income countries where social distancing is not a reality, not possible,” he said, citing Brazilian favelas and migrant caravans.
He hopes that polio campaigns will resume swiftly, fearing that the pandemic could set back a global, decades-long effort to eradicate the disease.
Dr. Cochi is particularly worried about Pakistan and Afghanistan, where 61 cases of wild poliovirus Type 1 have been reported this year, and about Chad, Ghana, Ethiopia and Pakistan, where cases of Type 2 poliovirus, mutated from the oral vaccine,have appeared.
Thabani Maphosa, a managing director at Gavi, which partners with 73 countries to purchase vaccines, said that at least a half dozen of those countries say they cannot afford their usual share of vaccine costs because of the economic toll of the pandemic.
If the pandemic cleared within three months, Mr. Maphosa said, he believed the international community could catch up with immunizations over the next year and a half.
“But our scenarios are not telling us that will happen,” he added.
Jan Hoffman reported from New York, and Ruth Maclean from Dakar, Senegal.
What’s the risk of catching coronavirus from a surface? Touching contaminated objects and then infecting ourselves with the germs is not typically how the virus spreads. But it can happen. A number of studies of flu, rhinovirus, coronavirus and other microbes have shown that respiratory illnesses, including the new coronavirus, can spread by touching contaminated surfaces, particularly in places like day care centers, offices and hospitals. But a long chain of events has to happen for the disease to spread that way. The best way to protect yourself from coronavirus — whether it’s surface transmission or close human contact — is still social distancing, washing your hands, not touching your face and wearing masks.
Does asymptomatic transmission of Covid-19 happen? So far, the evidence seems to show it does. A widely cited paper published in April suggests that people are most infectious about two days before the onset of coronavirus symptoms and estimated that 44 percent of new infections were a result of transmission from people who were not yet showing symptoms. Recently, a top expert at the World Health Organization stated that transmission of the coronavirus by people who did not have symptoms was “very rare,” but she later walked back that statement.
How does blood type influence coronavirus? A study by European scientists is the first to document a strong statistical link between genetic variations and Covid-19, the illness caused by the coronavirus. Having Type A blood was linked to a 50 percent increase in the likelihood that a patient would need to get oxygen or to go on a ventilator, according to the new study.
How many people have lost their jobs due to coronavirus in the U.S.? The unemployment rate fell to 13.3 percent in May, the Labor Department said on June 5, an unexpected improvement in the nation’s job market as hiring rebounded faster than economists expected. Economists had forecast the unemployment rate to increase to as much as 20 percent, after it hit 14.7 percent in April, which was the highest since the government began keeping official statistics after World War II. But the unemployment rate dipped instead, with employers adding 2.5 million jobs, after more than 20 million jobs were lost in April.
Will protests set off a second viral wave of coronavirus? Mass protests against police brutality that have brought thousands of people onto the streets in cities across America are raising the specter of new coronavirus outbreaks, prompting political leaders, physicians and public health experts to warn that the crowds could cause a surge in cases. While many political leaders affirmed the right of protesters to express themselves, they urged the demonstrators to wear face masks and maintain social distancing, both to protect themselves and to prevent further community spread of the virus. Some infectious disease experts were reassured by the fact that the protests were held outdoors, saying the open air settings could mitigate the risk of transmission.
How do we start exercising again without hurting ourselves after months of lockdown? Exercise researchers and physicians have some blunt advice for those of us aiming to return to regular exercise now: Start slowly and then rev up your workouts, also slowly. American adults tended to be about 12 percent less active after the stay-at-home mandates began in March than they were in January. But there are steps you can take to ease your way back into regular exercise safely. First, “start at no more than 50 percent of the exercise you were doing before Covid,” says Dr. Monica Rho, the chief of musculoskeletal medicine at the Shirley Ryan AbilityLab in Chicago. Thread in some preparatory squats, too, she advises. “When you haven’t been exercising, you lose muscle mass.” Expect some muscle twinges after these preliminary, post-lockdown sessions, especially a day or two later. But sudden or increasing pain during exercise is a clarion call to stop and return home.
My state is reopening. Is it safe to go out?States are reopening bit by bit. This means that more public spaces are available for use and more and more businesses are being allowed to open again. The federal government is largely leaving the decision up to states, and some state leaders are leaving the decision up to local authorities. Even if you aren’t being told to stay at home, it’s still a good idea to limit trips outside and your interaction with other people.
What are the symptoms of coronavirus? Common symptoms include fever, a dry cough, fatigue and difficulty breathing or shortness of breath. Some of these symptoms overlap with those of the flu, making detection difficult, but runny noses and stuffy sinuses are less common. The C.D.C. has also added chills, muscle pain, sore throat, headache and a new loss of the sense of taste or smell as symptoms to look out for. Most people fall ill five to seven days after exposure, but symptoms may appear in as few as two days or as many as 14 days.
How can I protect myself while flying? If air travel is unavoidable, there are some steps you can take to protect yourself. Most important: Wash your hands often, and stop touching your face. If possible, choose a window seat. A study from Emory University found that during flu season, the safest place to sit on a plane is by a window, as people sitting in window seats had less contact with potentially sick people. Disinfect hard surfaces. When you get to your seat and your hands are clean, use disinfecting wipes to clean the hard surfaces at your seat like the head and arm rest, the seatbelt buckle, the remote, screen, seat back pocket and the tray table. If the seat is hard and nonporous or leather or pleather, you can wipe that down, too. (Using wipes on upholstered seats could lead to a wet seat and spreading of germs rather than killing them.)
Should I wear a mask? The C.D.C. has recommended that all Americans wear cloth masks if they go out in public. This is a shift in federal guidance reflecting new concerns that the coronavirus is being spread by infected people who have no symptoms. Until now, the C.D.C., like the W.H.O., has advised that ordinary people don’t need to wear masks unless they are sick and coughing. Part of the reason was to preserve medical-grade masks for health care workers who desperately need them at a time when they are in continuously short supply. Masks don’t replace hand washing and social distancing.
What should I do if I feel sick?If you’ve been exposed to the coronavirus or think you have, and have a fever or symptoms like a cough or difficulty breathing, call a doctor. They should give you advice on whether you should be tested, how to get tested, and how to seek medical treatment without potentially infecting or exposing others.
Summary: Researchers describe a single function that accurately describes all existing available data on active COVID-19 cases and deaths — and predicts forthcoming peaks.
As of late May, COVID-19 has killed more than 325,000 people around the world. Even though the worst seems to be over for countries like China and South Korea, public health experts warn that cases and fatalities will continue to surge in many parts of the world. Understanding how the disease evolves can help these countries prepare for an expected uptick in cases.
This week in the journal Frontiers in Physics, researchers describe a single function that accurately describes all existing available data on active cases and deaths — and predicts forthcoming peaks. The tool uses q-statistics, a set of functions and probability distributions developed by Constantino Tsallis, a physicist and member of the Santa Fe Institute’s external faculty. Tsallis worked on the new model together with Ugur Tirnakli, a physicist at Ege University, in Turkey.
“The formula works in all the countries in which we have tested,” says Tsallis.
Neither physicist ever set out to model a global pandemic. But Tsallis says that when he saw the shape of published graphs representing China’s daily active cases, he recognized shapes he’d seen before — namely, in graphs he’d helped produce almost two decades ago to describe the behavior of the stock market.
“The shape was exactly the same,” he says. For the financial data, the function described probabilities of stock exchanges; for COVID-19, it described daily the number of active cases — and fatalities — as a function of time.
Modeling financial data and tracking a global pandemic may seem unrelated, but Tsallis says they have one important thing in common. “They’re both complex systems,” he says, “and in complex systems, this happens all the time.” Disparate systems from a variety of fields — biology, network theory, computer science, mathematics — often reveal patterns that follow the same basic shapes and evolution.
The financial graph appeared in a 2004 volume co-edited by Tsallis and the late Nobelist Murray Gell-Mann. Tsallis developed q-statitics, also known as “Tsallis statistics,” in the late 1980s as a generalization of Boltzmann-Gibbs statistics to complex systems.
In the new paper, Tsallis and Tirnakli used data from China, where the active case rate is thought to have peaked, to set the main parameters for the formula. Then, they applied it to other countries including France, Brazil, and the United Kingdom, and found that it matched the evolution of the active cases and fatality rates over time.
The model, says Tsallis, could be used to create useful tools like an app that updates in real-time with new available data, and can adjust its predictions accordingly. In addition, he thinks that it could be fine-tuned to fit future outbreaks as well.
“The functional form seems to be universal,” he says, “Not just for this virus, but for the next one that might appear as well.”
Editor’s note: Some of our covid-19 coverage is free for readers of The Economist Today, our daily newsletter. For more stories and our pandemic tracker, see our coronavirus hub
AMERICA HAS passed a grim milestone: 100,000 deaths from a novel coronavirus that began to spread half a year and half a world away. Many Americans think their president has handled the epidemic disastrously, that their country has been hit uniquely hard and that there is a simple causal relationship between the two. The 100,000, which does not include excess deaths mistakenly attributed to other causes, is higher than any other country’s. It has routinely been compared with the 60,000 American casualties in the Vietnam war. A Trump Death Clock in Times Square purports to show how many lives the president’s ineptitude has cost: as we went to press it stood at 60,262. Yet this widespread conviction that America has failed because of Donald Trump is not supported by the numbers. Or, at least, not yet.
The official death rate in America is about the same as in the European Union—which also has excess deaths, but has less erratic leaders and universal health care. Overall, America has fared a bit worse than Switzerland and a bit better than the Netherlands, neither of which is a failed state. New York has been hit about as hard as Lombardy in northern Italy; California acted early and is currently similar to Germany; so far, rural states have, like central Europe, been spared the worst. This reflects two things, both of which will matter now that America is reopening before it has the virus fully under control.
The first is that covid-19, when it first hit, displayed an indifference to presidents and their plans. Around the world it has killed in large, dense and connected cities like New York, London and Paris, and where people are crammed together, including care homes, slaughterhouses and prisons. In some countries, including America, testing was snarled up in red tape.
Having seen what was happening in China, Mr Trump could have acted sooner—as Taiwan, Singapore and Vietnam did. He has failed to do things ordinarily expected of an American president in a crisis, such as giving clear government advice or co-ordinating a federal response. Instead, he has touted quack remedies and spent the days when America passed its sombre milestone spreading suspicion of the voting system and accusing a television host of committing a murder that never happened. All this is reprehensible and it may have been costly. Yet, tempting as it is to conclude that the president’s failures bear most of the blame for covid-19’s spread through America, the reality is more complicated (see Briefing).
That leads to the second feature of the country’s response to covid-19. The virus was always going to be hard on a population with high levels of poverty, obesity and diseases such as diabetes, especially among minorities (see Lexington). But, to a remarkable degree, other layers of government have adapted around the hole where the president should have been. The federal system has limited the damage, thanks to its decentralised decision-making. Lockdowns vary by state, city and county. California responded as soon as it saw cases. In the north-east governors largely ignored the White House and got on with coping with the disease, earning the Republican governors of Maryland and Massachusetts the president’s enmity, but high approval ratings. In Florida, though the governor was reluctant to impose a lockdown, county officials went ahead and did so anyway.
Contrary to demands for nationwide rules, this is a strength not a weakness, and will become more so as the pandemic runs its course. In the best-organised states, which have built up testing capacity, it helps ensure that flare-ups can be spotted quickly and rules adjusted accordingly. Because each region is different, that is more efficient than a nationwide approach.
One way democracies can deal with the virus is to draw on reserves of trust. People must behave in ways that protect fellow citizens whom they have never met, even if they themselves are feeling fine. Americans trust their local officials far more than the president or the federal government. And when it comes to public health those local officials have real power. Without this balancing feature, America might today look like Brazil, where a president with a similar love of hydroxychloroquine and distaste for face masks is wreaking havoc (see article).
If the public-health response in the United States so far matches Europe’s, its economic response to the virus may turn out better. True, the unemployment rate in America is 15%, double that in the EU. Yet in Europe most governments are protecting jobs that may no longer exist once lockdowns end rather than focusing help on the unemployed as America’s has. The EU is probably delaying a painful adjustment. Congress, not known for passing consequential legislation with big bipartisan majorities, agreed on a vastly bigger fiscal stimulus than in the financial crisis a decade ago. With a Democrat in the White House and a Republican-controlled Senate, America might not have mustered a response that was either so rapid or so large.
America still has a hard road ahead. Were daily fatalities to remain at today’s level, which is being celebrated as a sign that the pandemic is waning, another 100,000 people would die by the end of the year. To prevent that, America needs to work with the system it has, trusting local politicians to balance the risks of reopening against the cost of lockdowns.
In the next months the infrastructure built during the lockdown must prove itself. Because the virus has yet to decline in some states, it may flare up in new places, which will then need targeted lockdowns. The capacity to test, vital to spotting clusters of infection, has increased, but is still lacking in some places. Almost all the states lack the contact tracers needed to work out who needs testing and quarantining. When it considers how to withdraw fiscal support, Congress should remember this.
That America and Europe have fared similarly in the pandemic does not absolve Mr Trump. This is the first international crisis since 1945 in which America has not only spurned global leadership but, by cutting funds to the World Health Organisation, actively undermined a co-ordinated international response. That matters, as does Mr Trump’s inability to cleave to a consistent message or to speak to the country in words that do not enrage half of the population. Yet four years after Mr Trump was elected, the time to be surprised by his behaviour has long gone. Luckily, he has mattered less than most Americans think.■
This article appeared in the Leaders section of the print edition under the headline “The American way”
Em entrevista à Folha, Mokdad diz que a tendência de casos e mortes no país é de alta e que a situação pode ser ainda pior se governo e população não levarem a crise a sério e adotarem “lockdown” por duas semanas.
“As infeções e mortes vão crescer e, o mais assustador, haverá a sobrecarga total do sistema de saúde.” Caso cumpra o confinamento total por 14 dias, explica Mokdad, o Brasil conseguirá controlar a propagação do vírus e poderá fazer a reabertura das atividades econômicas de maneira estratégica –e até mais rapidamente.
Especialista em saúde pública, diz sofrer críticas por ter um modelo que varia bastante, mas, no caso da pandemia, prefere que suas projeções se ajustem com o tempo. “Se os brasileiros ficarem em casa por duas semanas, meus números vão baixar. E não porque fiz algo errado, mas porque os brasileiros fizeram algo certo.”
Qual a situação da pandemia no Brasil? Infelizmente o que vemos no Brasil é uma tendência de aumento de casos, que vai resultar no crescimento das mortes no país. Isso se dá por várias razões. Primeiro porque o país não entrou em “lockdown” cedo para impedir a propagação do vírus. O governo e a população brasileira não levaram isso a sério e não fizeram logo as coisas certas para impedir a transmissão do vírus.
Segundo, há muita disparidade no Brasil e a Covid-19 aumenta isso. Nesse caso, é preciso proteger não só os trabalhadores de saúde mas os trabalhadores de serviços essenciais, pessoas pobres que trabalham em funções que as obrigam a sair de casa. Elas não estão protegidas e estão morrendo. A terceira e mais importante preocupação é a sobrecarga do sistema de saúde. Se o país não agir, vai haver mais casos no inverno e não haverá tempo para se preparar. É perigoso e arriscado. Se você colocar tudo isso junto, o Brasil ainda vai enfrentar sérias dificuldades diante da Covid-19.
Em duas semanas, o IHME aumentou as projeções de morte no Brasil de 88 mil para mais de 125 mil até agosto. O que aconteceu? Adicionamos mais estados [de 11 para 19] na nossa projeção, isso é uma coisa. Mas estamos vendo no Brasil mais surtos e casos do que esperávamos. O país está testando mais e encontrando mais casos, mas, mesmo quando ajustamos para os testes, há uma tendência de alta.
No Brasil há também um erro de suposição quando falamos de circulação. Os dados [de mobilidade da população] são baseados no Facebook e no Google, ou seja, em smartphones, ou seja, em pessoas mais ricas. Percebemos que a circulação não parou nas favelas, por exemplo, em lugares onde pessoas mais pobres precisam sair para trabalhar. Se as pessoas se recusarem a levar isso a sério, infelizmente vamos ver mais casos e mortes.
Quais medidas precisam ser tomadas? Fechar escolas e universidades, impedir grandes aglomerações e encontros de pessoas, fechar os estabelecimentos não essenciais, igrejas, templos e locais religiosos. Nos locais essenciais, como mercados e farmácias, é preciso estabelecer regras, limitando o número de pessoas dentro, garantindo que elas se mantenham distantes umas das outras.
A última e mais importante coisa é pedir para quem precisa sair de casa—e sabemos que há quem precise— usar máscara e manter distância de 2 metros de outras pessoas. Para o sistema de saúde, é aumentar a capacidade de tratamento, de detectar cedo a chegada de um surto, fazendo rastreamento e o isolamento de casos, o que é um desafio para o Brasil, onde muitas vezes dez pessoas vivem em uma mesma casa.
Se o Brasil não cumprir essas medidas, qual é o pior cenário para o país? As infeções e mortes vão crescer e, a parte mais assustadora, haverá a sobrecarga total do sistema de saúde. Isso vai causar mais prejuízo à economia do que se fizer o isolamento por duas semanas. Se a população ficar em casa e levar isso a sério por duas semanas, registraremos diminuição da propagação do vírus e poderemos reabrir em fases. É preciso garantir que a retomada econômica seja feita de maneira estratégica, por setores.
É possível evitar o pico de 1.500 mortes diárias em julho e as 125 mil mortes até agosto se o país parar agora? Sim. O Brasil está em uma situação muito difícil e pode ser assim por muito tempo, mas ainda há esperança. Se o governo e a população pararem por duas semanas, podemos parar a circulação do vírus e reabrir o comércio. Se você olhar para estados americanos, como Nova York, depois que há o “lockdown”, as mortes e os casos diminuem. O “lockdown” salvou muitas vidas nos EUA. Fizemos as projeções para o Brasil de 125 mil mortes até 4 de agosto, mas não significa que vai acontecer, podemos parar isso. É preciso que cada brasileiro faça sua parte.
O presidente Jair Bolsonaro é contra medidas de distanciamento social, compara a Covid-19 com uma gripezinha e defende um medicamento com eficácia não comprovada contra a doença. Como essa postura pode impactar a situação do Brasil? Aqui nos EUA temos também uma situação política nesse sentido, infelizmente. Não sou político, vejo os números e dou conselhos a partir do que concluo deles. Pelos dados, o Brasil precisa de uma ação coordenada, caso contrário, vamos ter muitas perdas.
Mas precisamos ter uma coisa clara: Covid-19 não é uma gripe, causa mais mortalidade que gripe, a gripe não causa AVC e nem ataca os pulmões da maneira que a Covid-19 ataca. Contra Covid-19 não há medicamento e ponto final. Não tem vacina. Não é possível comparar Covid-19 e gripe. Fazer isso é passar mensagem errada. Dizer para a população que é possível sair e ver quem pega a doença é inaceitável, é falha de liderança.
Como ganhar a confiança dos governos e da população com projeções que variam tanto e com tanta gente trabalhando com dados sobre o tema? Há muita gente fazendo projeção mas, pela primeira vez na história da ciência, todos concordamos. Os números podem ser diferentes, mas a mensagem mais importante é a mesma: isso é um vírus letal e temos que levá-lo a sério. Meus números mudam porque as pessoas mudam. Se os brasileiros ficarem em casa por duas semanas, meus números vão baixar. E não porque fiz algo errado, mas porque os brasileiros fizeram algo certo. Aprendemos que o modelo muda se novos dados aparecem.
O sr. já foi acusado de ser alarmista ou de produzir notícias falsas quando seus números mudam? Acusado é demais, mas tem gente que fala que meus números são mais altos ou mais baixos do que deveriam ser, e isso eu nem resposto, porque não é um debate científico, é um debate político. No debate científico está todo mundo a bordo com a mesma mensagem.
Como é trabalhar tendo isso em vista, com números tão sensíveis e poderosos? A gente não dorme muito por esses dias, é muito trabalho. É muito difícil dizer que 125 mil pessoas vão morrer no Brasil até agosto. Isso não é um número, são famílias, amigos, é muito duro.
Vou contar uma história longa. Calma, leiam até o fim. Confiem em mim. Era uma vez uma doença. Ela surgiu em um país muito, muito distante. De repente, começou a se alastrar como faísca sobre pólvora. Pessoas começaram a morrer, em números enormes, aos montes. Os jornais começaram a noticiar sobre a doença antes que ela chegasse ao nosso país. Informavam a população, mas as pessoas não acreditavam. Diziam que era algo distante, que era apenas uma gripe comum, que era tudo um grande exagero.
Algumas pessoas que chegavam de viagem da Europa caiam doentes. Algumas morreram. Mas eram velhas. Tinham doenças. Não havia motivo para pânico.
As pessoas liam os jornais e ficavam indignadas com o exagero da imprensa. Diziam que era uma jogada politica para derrubar o governo, para espalhar o comunismo pelo mundo.
Na tentativa de conter a doença, que a essa altura já se alastrara por várias nações, países começaram a indicar o uso de máscaras, recomendaram que as pessoas ficassem afastadas, em quarentena, em cidades do mundo todo.
– Quarentena? Como assim? O que será da nossa economia?? – gritavam pessoas indignadas.
Faziam piquetes, manifestações, carregavam cartazes dizendo que se recusavam a usar máscara. E, quando eram obrigadas, usavam placas informando que não concordavam com o uso dela.
Escolas foram fechadas, portas de negócios foram baixadas. Apenas farmácias e mercados poderiam permanecer abertos para abastecer a população.
Teatros e cinemas foram lacrados. Todos os campeonatos de futebol e outros esportes foram cancelados.
O Rio de Janeiro tornou-se um cenário de tragédia. Hospitais lotados, sem vias de saída, pessoas morrendo em casa. Por toda parte, a falta de caixões e pessoas precisando ser enterradas em valas comuns. Em um único dia, chegam a ser registradas mais de 1.000 mortes.
No Congresso, propôs-se que a formatura dos estudantes fosse antecipada, para que fossem logo para o mercado de trabalho.
Cientistas procuravam loucamente a cura ou o tratamento para aquela doença, até que algum jornal anunciou que um medicamento incrível, até então usado para a malária, parecia ser eficiente.
As pessoas ficaram em polvorosa. Todos queriam o medicamento. Alguns médicos passaram a anunciar o milagre dessa substância em veículos de comunicação, as pessoas se acumulavam na porta das farmácias e consultórios para recebê-la.
Não havia recomendação científica para o tal remédio, mas as pessoas não se importavam. Estavam desesperadas, qualquer coisa serviria.
Milhares de doentes foram medicados, mas a doença não parecia melhorar com o remédio.
Os veículos de comunicação então chegaram a uma conclusão que parecia óbvia: o remédio não funcionava porque estava sendo administrado tarde demais.
O ideal seria prescrevê-lo o quanto antes, até mesmo preventivamente, como garantia, para evitar a contaminação antes que ela acontecesse.
Alguns outros médicos tentaram alertar a população quanto ao risco do medicamento, mas foi em vão.
Estes médicos foram taxados de conspiracionistas, agredidos, xingados, tomados por comunistas, acusados de estarem contra o interesse da população.
As pessoas passaram a se auto administrar o medicamento para malária, como iriam esperar de braços cruzados?
Foi aí que a historia se complicou. Havia pessoas que não podiam tomar o tal remédio, pois eram portadoras de condições clinicas adversas que eram contra indicação ao uso dele. Algumas desmaiavam na rua. Correram lendas urbanas de pessoas que chegaram a ser tomadas por mortas e enterradas vivas, em decorrência de paradas cardíacas e arritmias causadas pelo remédio, cuja dose era propagada sem qualquer critério pela própria imprensa.
As pessoas, ao longo do tempo, ao verem que o medicamento não surtia o efeito prometido, passaram a recorrer a soluções populares e caseiras cujos boatos se disseminaram.
Aguardente, associada a limão e mel, seria um tratamento possível. Bares chegaram a ter filas de pessoas em busca de uma dose. O alcoolismo disparou. O preço da fruta atingiu valores jamais vistos e sumiu das prateleiras.
Correu o boato de que hospitais estavam administrando chás envenenados à meia noite, para pacientes terminais, para liberar leitos.
Por quase dois anos, o governo falhou em conseguir implementar um Ministério da Saúde eficiente. As opiniões se dividiam, discutiam o impacto do isolamento sobre o comércio
Da mesma forma que um famoso escritor chegou a descrever: “Cada médico tinha uma tentativa de explicação diferente; nós não sabíamos no quê e em quem acreditar. Esperávamos por uma explicação que ninguém tinha para dar, como até hoje esperamos para saber o que foi aquela sassânida infernal.”
Enquanto isso, a doença avançava. Em meio a promessas vãs, avançou e avançou. A única coisa que se provou eficaz para contê-la foram as regiões com alta adesão ao isolamento social e ao uso de máscaras.
Não, não se trata do coronavirus nem da cloroquina.
Trata-se da gripe espanhola e do sal de quinino, medicamento que na época era usado para malária.
O uso indiscriminado do sal de quinino foi promovido pela imprensa na época, a partir de 1918, e levou também inúmeras pessoas à morte. A imprensa em massa passou a prescrever os sais de quinino inicialmente como tratamento, e posteriormente como prevenção à gripe espanhola.
Nunca surtiu efeito.
A gripe espanhola terminou por matar 30 milhões de pessoas, sem que até hoje, 102 anos depois, tenha sido encontrada a cura.
Na época, muitas pessoas acreditavam que ela era uma mentira, um exagero e uma conspiração para alastrar a revolução comunista de 1917 pelo mundo.
A única medida que, retrospectivamente, conteve razoavelmente a doença em algumas regiões, foi o isolamento social.
A economia sobreviveu.
Quem não recorre aos livros de história para lê-la está fadado a repeti-la.
Notas: 1. A gripe espanhola matou o presidente da República brasileiro, recém reeleito, o Conselheiro Rodrigues Alves, em 1918, logo antes de sua posse.
2. O “medicamento caseiro” inventado para o tratamento da gripe espanhola, à base de aguardente, mel e limão, entrou para a cultura brasileira e hoje atende pelo nome de “caipirinha”.
3. O “chá da meia noite” foi um boato que difamou a Santa Casa do Rio de Janeiro em 1918. Foi apelidada na época de “Casa do Diabo”. Após o final da epidemia, o Chá da Meia Noite foi tema do primeiro bloco de carnaval do Rio, em 1919.
Summary: At the beginning of a new wave of an epidemic, extreme care should be used when extrapolating data to determine whether lockdowns are necessary, experts say.
As the infectious virus causing the COVID-19 disease began its devastating spread around the globe, an international team of scientists was alarmed by the lack of uniform approaches by various countries’ epidemiologists to respond to it.
Germany, for example, didn’t institute a full lockdown, unlike France and the U.K., and the decision in the U.S. by New York to go into a lockdown came only after the pandemic had reached an advanced stage. Data modeling to predict the numbers of likely infections varied widely by region, from very large to very small numbers, and revealed a high degree of uncertainty.
Davide Faranda, a scientist at the French National Centre for Scientific Research (CNRS), and colleagues in the U.K., Mexico, Denmark, and Japan decided to explore the origins of these uncertainties. This work is deeply personal to Faranda, whose grandfather died of COVID-19; Faranda has dedicated the work to him.
In the journal Chaos, from AIP Publishing, the group describes why modeling and extrapolating the evolution of COVID-19 outbreaks in near real time is an enormous scientific challenge that requires a deep understanding of the nonlinearities underlying the dynamics of epidemics.
“Our physical model is based on assuming that the total population can be divided into four groups: those who are susceptible to catching the virus, those who have contracted the virus but don’t show any symptoms, those who are infected and, finally, those who recovered or died from the virus,” Faranda said.
To determine how people move from one group to another, it’s necessary to know the infection rate, incubation time and recovery time. Actual infection data can be used to extrapolate the behavior of the epidemic with statistical models.
“Because of the uncertainties in both the parameters involved in the models — infection rate, incubation period and recovery time — and the incompleteness of infections data within different countries, extrapolations could lead to an incredibly large range of uncertain results,” Faranda said. “For example, just assuming an underestimation of the last data in the infection counts of 20% can lead to a change in total infections estimations from few thousands to few millions of individuals.”
The group has also shown that this uncertainty is due to a lack of data quality and also to the intrinsic nature of the dynamics, because it is ultrasensitive to the parameters — especially during the initial growing phase. This means that everyone should be very careful extrapolating key quantities to decide whether to implement lockdown measures when a new wave of the virus begins.
“The total final infection counts as well as the duration of the epidemic are sensitive to the data you put in,” he said.
The team’s model handles uncertainty in a natural way, so they plan to show how modeling of the post-confinement phase can be sensitive to the measures taken.
“Preliminary results show that implementing lockdown measures when infections are in a full exponential growth phase poses serious limitations for their success,” said Faranda.
Davide Faranda, Isaac Pérez Castillo, Oliver Hulme, Aglaé Jezequel, Jeroen S. W. Lamb, Yuzuru Sato, Erica L. Thompson. Asymptotic estimates of SARS-CoV-2 infection counts and their sensitivity to stochastic perturbation. Chaos: An Interdisciplinary Journal of Nonlinear Science, 2020; 30 (5): 051107 DOI: 10.1063/5.0008834
Covid-19 isn’t going away soon. Two recent studies mapped out the possible shapes of its trajectory.
By Siobhan Roberts – May 8, 2020
By now we know — contrary to false predictions — that the novel coronavirus will be with us for a rather long time.
“Exactly how long remains to be seen,” said Marc Lipsitch, an infectious disease epidemiologist at Harvard’s T.H. Chan School of Public Health. “It’s going to be a matter of managing it over months to a couple of years. It’s not a matter of getting past the peak, as some people seem to believe.”
A single round of social distancing — closing schools and workplaces, limiting the sizes of gatherings, lockdowns of varying intensities and durations — will not be sufficient in the long term.
In the interest of managing our expectations and governing ourselves accordingly, it might be helpful, for our pandemic state of mind, to envision this predicament — existentially, at least — as a soliton wave: a wave that just keeps rolling and rolling, carrying on under its own power for a great distance.
The Scottish engineer and naval architect John Scott Russell first spotted a soliton in 1834 as it traveled along the Union Canal. He followed on horseback and, as he wrote in his “Report on Waves,” overtook it rolling along at about eight miles an hour, at thirty feet long and a foot or so in height. “Its height gradually diminished, and after a chase of one or two miles I lost it in the windings of the channel.”
The pandemic wave, similarly, will be with us for the foreseeable future before it diminishes. But, depending on one’s geographic location and the policies in place, it will exhibit variegated dimensions and dynamics traveling through time and space.
“There is an analogy between weather forecasting and disease modeling,” Dr. Lipsitch said. Both, he noted, are simple mathematical descriptions of how a system works: drawing upon physics and chemistry in the case of meteorology; and on behavior, virology and epidemiology in the case of infectious-disease modeling. Of course, he said, “we can’t change the weather.” But we can change the course of the pandemic — with our behavior, by balancing and coordinating psychological, sociological, economic and political factors.
Dr. Lipsitch is a co-author of two recent analyses — one from the Center for Infectious Disease Research and Policy at the University of Minnesota, the other from the Chan School published in Science — that describe a variety of shapes the pandemic wave might take in the coming months.
The Minnesota study describes three possibilities:
Scenario No. 1 depicts an initial wave of cases — the current one — followed by a consistently bumpy ride of “peaks and valleys” that will gradually diminish over a year or two.
Scenario No. 2 supposes that the current wave will be followed by a larger “fall peak,” or perhaps a winter peak, with subsequent smaller waves thereafter, similar to what transpired during the 1918-1919 flu pandemic.
Scenario No. 3 shows an intense spring peak followed by a “slow burn” with less-pronounced ups and downs.
The authors conclude that whichever reality materializes (assuming ongoing mitigation measures, as we await a vaccine), “we must be prepared for at least another 18 to 24 months of significant Covid-19 activity, with hot spots popping up periodically in diverse geographic areas.”
In the Science paper, the Harvard team — infectious-disease epidemiologist Yonatan Grad, his postdoctoral fellow Stephen Kissler, Dr. Lipsitch, his doctoral student Christine Tedijanto and their colleague Edward Goldstein — took a closer look at various scenarios by simulating the transmission dynamics using the latest Covid-19 data and data from related viruses.
The authors conveyed the results in a series of graphs — composed by Dr. Kissler and Ms. Tedijanto — that project a similarly wavy future characterized by peaks and valleys.
One figure from the paper, reinterpreted below, depicts possible scenarios (the details would differ geographically) and shows the red trajectory of Covid-19 infections in response to “intermittent social distancing” regimes represented by the blue bands.
Social distancing is turned “on” when the number of Covid-19 cases reaches a certain prevalence in the population — for instance, 35 cases per 10,000, although the thresholds would be set locally, monitored with widespread testing. It is turned “off” when cases drop to a lower threshold, perhaps 5 cases per 10,000. Because critical cases that require hospitalization lag behind the general prevalence, this strategy aims to prevent the health care system from being overwhelmed.
The green graph represents the corresponding, if very gradual, increase in population immunity.
“The ‘herd immunity threshold’ in the model is 55 percent of the population, or the level of immunity that would be needed for the disease to stop spreading in the population without other measures,” Dr. Kissler said.
Another iteration shows the effects of seasonality — a slower spread of the virus during warmer months. Theoretically, seasonal effects allow for larger intervals between periods of social distancing.
This year, however, the seasonal effects will likely be minimal, since a large proportion of the population will still be susceptible to the virus come summer. And there are other unknowns, since the underlying mechanisms of seasonality — such as temperature, humidity and school schedules — have been studied for some respiratory infections, like influenza, but not for coronaviruses. So, alas, we cannot depend on seasonality alone to stave off another outbreak over the coming summer months.
Yet another scenario takes into account not only seasonality but also a doubling of the critical-care capacity in hospitals. This, in turn, allows for social distancing to kick in at a higher threshold — say, at a prevalence of 70 cases per 10,000 — and for even longer breaks between social distancing periods:
What is clear overall is that a one-time social distancing effort will not be sufficient to control the epidemic in the long term, and that it will take a long time to reach herd immunity.
“This is because when we are successful in doing social distancing — so that we don’t overwhelm the health care system — fewer people get the infection, which is exactly the goal,” said Ms. Tedijanto. “But if infection leads to immunity, successful social distancing also means that more people remain susceptible to the disease. As a result, once we lift the social distancing measures, the virus will quite possibly spread again as easily as it did before the lockdowns.”
So, lacking a vaccine, our pandemic state of mind may persist well into 2021 or 2022 — which surprised even the experts.
“We anticipated a prolonged period of social distancing would be necessary, but didn’t initially realize that it could be this long,” Dr. Kissler said.
The initiative has collected over 140,000 biological samples from animals and found over 1,000 new viruses, including a new strain of Ebola. Predict also trained about 5,000 people in 30 African and Asian countries, and has built or strengthened 60 medical research laboratories, mostly in poor countries.
Dennis Carroll, the former director of USAID’s emerging threats division who helped design Predict, oversaw it for a decade and retired when it was shut down. The surveillance project is closing because of “the ascension of risk-averse bureaucrats,” he said.
Because USAID’s chief mission is economic aid, he added, some federal officials felt uncomfortable funding cutting-edge science like tracking exotic pathogens.
Congress, along with the administrations of George W. Bush and Barack Obama, were “enormously supportive,” said Dr. Carroll, who is now a fellow at Texas A&M’s Bush School of Government and Public Service.
“But things got complicated in the last two years, and by January, Predict was essentially collapsed into hibernation.”
The end of the program “is definitely a loss,” said Peter Daszak, president of the EcoHealth Alliance, a nonprofit global health organization that received funding from the program. “Predict was an approach to heading off pandemics, instead of sitting there waiting for them to emerge and then mobilizing. That’s expensive.”
“The United States spent $5 billion fighting Ebola in West Africa,” he added. “This costs far less.”
It has long been known, of course, that AIDS originated in chimpanzees and probably was first contracted by bushmeat hunters. Ebola circulates in bats and apes, while SARS was found in captive civet cats in China.
These discoveries led to new ways of preventing spillovers of infections into human populations: closing markets where wildlife is butchered for food,; putting bamboo skirts on sap-collection jars to keep bats out; or penning pigs and camels in places where they cannot eat fruit that bats have gnawed.
Predict teams have investigated mysterious disease outbreaks in many countries, including a die-off of 3,000 wild birds in a Mongolian lake. One team proved that endangered otters in a Cambodian zoo were killed by their feed — raw chickens infected with bird flu.
A Predict laboratory helped identify bat-borne viruses that a boys’ soccer team might have been exposed to while trapped for weeks in a cave in Thailand.
Allowing Predict to end “is really unfortunate, and the opposite of what we’d like to see happening,” said Dr. Gro Harlem Brundtland, the former prime minister of Norway and former World Health Organization director-general.
Even though USAID is “incredibly proud and happy over the work Predict has done,” the program is closing because it reached the end of a 10-year funding cycle, said Irene Koek, acting assistant administrator of the agency’s global health bureau.
“We typically do programs in five-year cycles, and it had two,” she said. Some similar research will be part of future budget requests, “but it’s still in the design-and-procurement cycle, so exactly what will continue is a bit of a black box.”
In mid-October, the agency said it would spend $85 million over the next five years helping universities in Africa and Asia teach the “one-health” approach that Predict used. (“One health” describes the nexus between animal, human and environmental medicine).
But it will not involve the daring fieldwork that Predict specialized in.
Some Predict projects will be taken over by other government agencies, such as the Pentagon’s Defense Threat Reduction Agency or the National Institutes of Health. But those agencies have different missions, such as basic research or troop protection. They do not share USAID’s goal of training poor countries to do the work themselves.
As an agency that gives money to countries, USAID often has a friendlier, more cooperative relationship with governments in poor nations than, for example, Pentagon-led efforts might.
“I’ve always been impressed with the way they were able to work with ministries of health,” said Dr. James M. Hughes, a former chief of infectious diseases at the Centers for Disease Control and Prevention who was on Predict’s advisory board. “They have a high level of trust, and they help countries comply with the International Health Regulations.”
(Those regulations, in force since 2007, require countries to report all major disease outbreaks to the World Health Organization and allow the W.H.O. to declare health emergencies.)
USAID still supports some health-related programs like the President’s Malaria Initiative and the President’s Emergency Plan for AIDS Relief. But Dr. Carroll described those as “cookbook portfolios.”
How to fight those diseases is well-known, he explained, so the agency just comes up with a budget for drugs, diagnostic kits, insecticides, mosquito nets, condoms or other long-established interventions.
Predict more often placed medical detectives in the field, training local doctors, veterinarians, wildlife rangers and others to collect samples from wild and domestic animals.
It can be highly specialized work. Getting blood samples from pigs or wild rodents is fairly routine, but catching birds, bats or monkeys alive is not. Gorillas are harder. (Scientists usually content themselves with just collecting gorilla feces.)
Predict also experimented with novel ways to catch and release animals unharmed, to transport samples without refrigeration and to use DNA testing that can scan for whole viral families instead of just known viruses, said Dr. Christine Kreuder Johnson, associate director of the One Health Institute at the University of California, Davis.
Predict sponsored epidemiological modeling to predict where outbreaks are likely to erupt. It also sought ways to curb practices, such as hunting for bushmeat or breeding racing camels, that encourage eruptions.
The Zaire strain was found in a bat that roosts in caves and mines, said Dr. Jonathan Epstein, an EcoHealth Alliance veterinarian, while the Bombali type was in a species that roosts in houses.
Distinctions like that are important for telling people — especially people who eat bats — which species are dangerous.
“We generated an illustrated book on how to keep bats out of houses by putting screens on windows or mesh below the roof thatch,” he said. “That’s the kind of thing Predict paid for.”
Predict served as a proof of concept for a much more ambitious idea that Dr. Carroll proposed several years ago: the Global Virome Project, which envisioned trying to compile a genetic atlas of all the viruses circulating in all animals. By some estimates, there are more than 800,000 such viruses waiting to be discovered.
“Predict needed to go on for 20 years, not 10,” Dr. Epstein said. “We were getting to the point of having a trained work force that could gather animal samples and labs that could test for unknown viruses, not just known ones.”
“Once it stops, it’s going to be hard to maintain that level of proficiency.”
Physicists update predator-prey model for more clues on how bacteria evade attack from killer cells
April 29, 2016
Studying the way that solitary hunters such as tigers, bears or sea turtles chase down their prey turns out to be very useful in understanding the interaction between individual white blood cells and colonies of bacteria. Researchers have created a numerical model that explores this behavior in more detail.
Studying the way that solitary hunters such as tigers, bears or sea turtles chase down their prey turns out to be very useful in understanding the interaction between individual white blood cells and colonies of bacteria. Reporting their results in the Journal of Physics A: Mathematical and Theoretical, researchers in Europe have created a numerical model that explores this behaviour in more detail.
Using mathematical expressions, the group can examine the dynamics of a single predator hunting a herd of prey. The routine splits the hunter’s motion into a diffusive part and a ballistic part, which represent the search for prey and then the direct chase that follows.
“We would expect this to be a fairly good approximation for many animals,” explained Ralf Metzler, who led the work and is based at the University of Potsdam in Germany.
To further improve its analysis, the group, which includes scientists from the National Institute of Chemistry in Slovenia, and Sorbonne University in France, has incorporated volume effects into the latest version of its model. The addition means that prey can now inadvertently get in each other’s way and endanger their survival by blocking potential escape routes.
Thanks to this update, the team can study not just animal behaviour, but also gain greater insight into the way that killer cells such as macrophages (large white blood cells patrolling the body) attack colonies of bacteria.
One of the key parameters determining the life expectancy of the prey is the so-called ‘sighting range’ — the distance at which the prey is able to spot the predator. Examining this in more detail, the researchers found that the hunter profits more from the poor eyesight of the prey than from the strength of its own vision.
Long tradition with a new dimension
The analysis of predator-prey systems has a long tradition in statistical physics and today offers many opportunities for cooperative research, particularly in fields such as biology, biochemistry and movement ecology.
“With the ever more detailed experimental study of systems ranging from molecular processes in living biological cells to the motion patterns of animal herds and humans, the need for cross-fertilisation between the life sciences and the quantitative mathematical approaches of the physical sciences has reached a new dimension,” Metzler comments.
To help support this cross-fertilisation, he heads up a new section of the Journal of Physics A: Mathematical and Theoretical that is dedicated to biological modelling and examines the use of numerical techniques to study problems in the interdisciplinary field connecting biology, biochemistry and physics.
Maria Schwarzl, Aljaz Godec, Gleb Oshanin, Ralf Metzler. A single predator charging a herd of prey: effects of self volume and predator–prey decision-making. Journal of Physics A: Mathematical and Theoretical, 2016; 49 (22): 225601 DOI: 10.1088/1751-8113/49/22/225601
Summary: By treating incarceration as an infectious disease, researchers show that small differences in prison sentences can lead to large differences in incarceration rates. The incarceration rate has nearly quadrupled since the U.S. declared a war on drugs, researchers say. Along with that, racial disparities abound. Incarceration rates for black Americans are more than six times higher than those for white Americans, according to the U.S. Bureau of Justice Statistics.
The incarceration rate has nearly quadrupled since the U.S. declared a war on drugs, researchers say. Along with that, racial disparities abound. Incarceration rates for black Americans are more than six times higher than those for white Americans, according to the U.S. Bureau of Justice Statistics.
To explain these growing racial disparities, researchers at Virginia Tech are using the same modeling techniques used for infectious disease outbreaks to take on the mass incarceration problem.
By treating incarceration as an infectious disease, the scientists demonstrated that small but significant differences in prison sentences can lead to large differences in incarceration rates. The research was published in June in the Journal of the Royal Society Interface.
Incarceration can be “transmitted” to others, the researchers say. For instance, incarceration can increase family members’ emotional and economic stress or expose family and friends to a network of criminals, and these factors can lead to criminal activity.
Alternatively, “official bias” leads police and the courts to pay more attention to the incarcerated person’s family and friends, thereby increasing the probability they will be caught, prosecuted and processed by the criminal justice system, researchers said.
“Regardless of the specific mechanisms involved,” said Kristian Lum, a former statistician at the Virginia Bioinformatics Institute now working for DataPad, “the incarceration of one family member increases the likelihood of other family members and friends being incarcerated.”
Building on this insight, incarceration is treated like a disease in the model and the incarcerated are infectious to their social contacts — their family members and friends most likely affected by their incarceration.
“Criminologists have long recognized that social networks play an important role in criminal behavior, the control of criminal behavior, and the re-entry of prisoners into society,” said James Hawdon, a professor of sociology in the College of Liberal Arts and Human Sciences. “We therefore thought we should test if networks also played a role in the incarceration epidemic. Our model suggests they do.”
Synthesizing publically available data from a variety of sources, the researchers generated a realistic, multi-generational synthetic population with contact networks, sentence lengths, and transmission probabilities.
The researchers’ model is comparable to real-world incarceration rates, reproducing many facets of incarceration in the United States.
Both the model and actual statistics show large discrepancies in incarceration rates between black and white Americans and, subsequently, the likelihood of becoming a repeat offender is high.
Comparisons such as these can be used to validate the assumption that incarceration is infectious.
“Research clearly shows that this epidemic has had devastating effects on individuals, families, and entire communities,” Lum said. “Since our model captures the emergent properties of the incarceration epidemic, we can use it to test policy options designed to reverse it.”
Harsher sentencing may actually result in higher levels of criminality. Examining the role of social influence is an important step in reducing the growing incarceration epidemic.
K. Lum, S. Swarup, S. Eubank, J. Hawdon. The contagious nature of imprisonment: an agent-based model to explain racial disparities in incarceration rates. Journal of The Royal Society Interface, 2014; 11 (98): 20140409 DOI: 10.1098/rsif.2014.0409
Artigo de Luís Maurício Trambaioli para o Jornal da Ciência
Está sendo amplamente divulgado na mídia um recente estudo em que os pesquisadores de Harvard, a partir de questionário de perguntas feito em 1991 a enfermeiras, inferiu que mulheres teriam 22 % de risco relativo aumentado de câncer de mama quando consumindo uma porção a mais de carne vermelha que mulheres que consomem menos.
Entretanto, risco relativo não é risco absoluto, o qual pode ser calculado pelos dados originais. A chance de desenvolver a doença seria vista em 1 em cada 100.000 mulheres, e não em 22 em cada 100 mulheres como tem sido noticiado pela falsa impressão que o ‘risco relativo’ nos dá. Mais, esta incidência é exatamente em grupos de mulheres que mais fumam.
É importante cuidado na forma que se divulga as notícias de estudos epidemiológicos e feitos por apenas um grupo. Melhor seria obter um parecer de especialistas na área e ainda preferencialmente resultados advindos de mais estudos obtidos por outros pesquisadores, evitando assim bias e viés na ciência. Sob risco de acontecer acusações levianas como ocorrido na década de 80 que levou a demonizar a gordura saturada há exatos 30 anos sem evidências científicas que suportassem tal idéia, o que direcionou a humanidade ao desespero de consumo de alimentos sem gordura e compensando com a ingestão de mais “carboidratos complexos” (amido) e baixos em micronutrientes. E o resultado foi a epidemia de diabetes e obesidade (chamado no exterior de diabesity), doenças cardiovasculares, câncer, dentre outras.
E agora, o que cortar do bacon: a gordura ou a carne ?
Luís Maurício Trambaioli é professor associado da Faculdade de Farmácia da UFRJ e pesquisador associado do INMETRO
Dec. 6, 2013 — The majority of all violent crime in Sweden is committed by a small number of people. They are almost all male (92%) who early in life develops violent criminality, substance abuse problems, often diagnosed with personality disorders and commit large number non-violent crimes. These are the findings of researchers at Sahlgrenska Academy who have examined 2.5 million people in Swedish criminal and population registers.
In this study, the Gothenburg researchers matched all convictions for violent crime in Sweden between 1973 and 2004 with nation-wide population register for those born between 1958 to 1980 (2.5 million).
Of the 2.5 million individuals included in the study, 4 percent were convicted of at least one violent crime, 93,642 individuals in total. Of these convicted at least once, 26 percent were re-convicted three or more times, thus resulting in 1 percent of the population (23,342 individuals) accounting for 63 percent of all violent crime convictions during the study period.
“Our results show that 4 percent of those who have three or more violent crime convictions have psychotic disorders, such as schizophrenia and bipolar disorder. Psychotic disorders are twice as common among repeat offenders as in the general population, but despite this fact they constitute a very small proportion of the repeat offenders,” says Örjan Falk, researcher at Sahlgrenska Academy.
One finding the Gothenburg researchers present is that “acts of insanity” that receive a great deal of mass media coverage, committed by someone with a severe psychiatric disorder, are not responsible for the majority of violent crimes.
According to the researchers, the study’s results are important to crime prevention efforts.
“This helps us identify which individuals and groups in need of special attention and extra resources for intervention. A discussion on the efficacy of punishment (prison sentences) for this group is needed as well, and we would like to initiate a debate on what kind of criminological and medical action that could be meaningful to invest in,” says Örjan Falk.
Studies like this one are often used as arguments for more stringent sentences and US principles like “three strikes and you’re out.” What are your views on this?
“Just locking those who commit three or more violent crimes away for life is of course a compelling idea from a societal protective point of view, but could result in some undesirable consequences such as an escalation of serious violence in connection with police intervention and stronger motives for perpetrators of repeat violence to threaten and attack witnesses to avoid life sentences. It is also a fact that a large number of violent crimes are committed inside the penal system.”
“And from a moral standpoint it would mean that we give up on these, in many ways, broken individuals who most likely would be helped by intensive psychiatric treatments or other kind of interventions. There are also other plausible alternatives to prison for those who persistently relapse into violent crime, such as highly intensive monitoring, electronic monitoring and of course the continuing development of specially targeted treatment programs. This would initially entail a higher cost to society, but over a longer period of time would reduce the total number of violent crimes and thereby reduce a large part of the suffering and costs that result from violent crimes,” says Örjan Falk.
“I first and foremost advocate a greater focus on children and adolescents who exhibit signs of developing violent behavior and who are at the risk of later becoming repeat offenders of violent crime.”
Örjan Falk, Märta Wallinius, Sebastian Lundström, Thomas Frisell, Henrik Anckarsäter, Nóra Kerekes. The 1 % of the population accountable for 63 % of all violent crime convictions. Social Psychiatry and Psychiatric Epidemiology, 2013; DOI: 10.1007/s00127-013-0783-y
Apr. 15, 2013 — Mathematical estimates of treatment outcomes can cut costs and provide faster delivery of preventative measures.
South Africa is home to the largest HIV epidemic in the world with a total of 5.6 million people living with HIV. Large-scale clinical trials evaluating combination methods of prevention and treatment are often prohibitively expensive and take years to complete. In the absence of such trials, mathematical models can help assess the effectiveness of different HIV intervention combinations, as demonstrated in a new study by Elisa Long and Robert Stavert from Yale University in the US. Their findings appear in the Journal of General Internal Medicine, published by Springer.
Currently 60 percent of individuals in need of treatment for HIV in South Africa do not receive it. The allocation of scant resources to fight the HIV epidemic means each strategy must be measured in terms of cost versus benefit. A number of new clinical trials have presented evidence supporting a range of biomedical interventions that reduce transmission of HIV. These include voluntary male circumcision — now recommended by the World Health Organization and Joint United Nations Programme on HIV/AIDS as a preventive strategy — as well as vaginal microbicides and oral pre-exposure prophylaxis, all of which confer only partial protection against HIV. Long and Stavert show that a combination portfolio of multiple interventions could not only prevent up to two-thirds of future HIV infections, but is also cost-effective in a resource-limited setting such as South Africa.
The authors developed a mathematical model accounting for disease progression, mortality, morbidity and the heterosexual transmission of HIV to help forecast future trends in the disease. Using data specific for South Africa, the authors estimated the health benefits and cost-effectiveness of a “combination approach” using all three of the above methods in tandem with current levels of antiretroviral therapy, screening and counseling.
For each intervention, they calculated the HIV incidence and prevalence over 10 years. At present rates of screening and treatment, the researchers predict that HIV prevalence will decline from 19 percent to 14 percent of the population in the next 10 years. However, they calculate that their combination approach including male circumcision, vaginal microbicides and oral pre-exposure prophylaxis could further reduce HIV prevalence to 10 percent over that time scale — preventing 1.5 million HIV infection over 10 years — even if screening and antiretroviral therapy are kept at current levels. Increasing antiretroviral therapy use and HIV screening frequency in addition could avert more than 2 million HIV infections over 10 years, or 60 percent of the projected total.
The researchers also determined a hierarchy of effectiveness versus cost for these intervention strategies. Where budgets are limited, they suggest money should be allocated first to increasing male circumcision, then to more frequent HIV screening, use of vaginal microbicides and increasing antiretroviral therapy. Additionally, they calculate that omitting pre-exposure prophylaxis from their combination strategy could offer 90 percent of the benefits of treatment for less than 25 percent of the costs.
The authors conclude: “In the absence of multi-intervention randomized clinical or observational trials, a mathematical HIV epidemic model provides useful insights about the aggregate benefit of implementing a portfolio of biomedical, diagnostic and treatment programs. Allocating limited available resources for HIV control in South Africa is a key priority, and our study indicates that a multi-intervention HIV portfolio could avert nearly two-thirds of projected new HIV infections, and is a cost-effective use of resources.”
Long, E.F. and Stavert, R.R. Portfolios of biomedical HIV interventions in South Africa: a cost-effectiveness analysis. Journal of General Internal Medicine, 2013 DOI:10.1007/s11606-013-2417-1
ScienceDaily (Aug. 10, 2012) — A team of EPFL scientists has developed an algorithm that can identify the source of an epidemic or information circulating within a network, a method that could also be used to help with criminal investigations.
Investigators are well aware of how difficult it is to trace an unlawful act to its source. The job was arguably easier with old, Mafia-style criminal organizations, as their hierarchical structures more or less resembled predictable family trees.
In the Internet age, however, the networks used by organized criminals have changed. Innumerable nodes and connections escalate the complexity of these networks, making it ever more difficult to root out the guilty party. EPFL researcher Pedro Pinto of the Audiovisual Communications Laboratory and his colleagues have developed an algorithm that could become a valuable ally for investigators, criminal or otherwise, as long as a network is involved. The team’s research was published August 10, 2012, in the journal Physical Review Letters.
Finding the source of a Facebook rumor
“Using our method, we can find the source of all kinds of things circulating in a network just by ‘listening’ to a limited number of members of that network,” explains Pinto. Suppose you come across a rumor about yourself that has spread on Facebook and been sent to 500 people — your friends, or even friends of your friends. How do you find the person who started the rumor? “By looking at the messages received by just 15-20 of your friends, and taking into account the time factor, our algorithm can trace the path of that information back and find the source,” Pinto adds. This method can also be used to identify the origin of a spam message or a computer virus using only a limited number of sensors within the network.
Trace the propagation of an epidemic
Out in the real world, the algorithm can be employed to find the primary source of an infectious disease, such as cholera. “We tested our method with data on an epidemic in South Africa provided by EPFL professor Andrea Rinaldo’s Ecohydrology Laboratory,” says Pinto. “By modeling water networks, river networks, and human transport networks, we were able to find the spot where the first cases of infection appeared by monitoring only a small fraction of the villages.”
The method would also be useful in responding to terrorist attacks, such as the 1995 sarin gas attack in the Tokyo subway, in which poisonous gas released in the city’s subterranean tunnels killed 13 people and injured nearly 1,000 more. “Using this algorithm, it wouldn’t be necessary to equip every station with detectors. A sample would be sufficient to rapidly identify the origin of the attack, and action could be taken before it spreads too far,” says Pinto.
Identifying the brains behind a terrorist attack
Computer simulations of the telephone conversations that could have occurred during the terrorist attacks on September 11, 2001, were used to test Pinto’s system. “By reconstructing the message exchange inside the 9/11 terrorist network extracted from publicly released news, our system spit out the names of three potential suspects — one of whom was found to be the mastermind of the attacks, according to the official enquiry.”
The validity of this method thus has been proven a posteriori. But according to Pinto, it could also be used preventatively — for example, to understand an outbreak before it gets out of control. “By carefully selecting points in the network to test, we could more rapidly detect the spread of an epidemic,” he points out. It could also be a valuable tool for advertisers who use viral marketing strategies by leveraging the Internet and social networks to reach customers. For example, this algorithm would allow them to identify the specific Internet blogs that are the most influential for their target audience and to understand how in these articles spread throughout the online community.