T. Déirdre Hollingsworth

Pandemic Potential of a Strain of Influenza A (H1N1): Early Findings

Swine Flu Benchmark The World Health Organization (WHO) announced on 29 April 2009, a level-5 pandemic alert for a strain of H1N1 influenza originating in pigs in Mexico and transmitting from human to human in several countries. Fraser et al. (p. 1557, published online 11 May; see the cover) amassed a team of experts in Mexico and WHO to make an initial assessment of the outbreak with a view to guiding future policy. The outbreak appears to have originated in mid-February in the village of La Gloria, Veracruz, where over half the population suffered acute respiratory illness, affecting more than 61% of children under 15 years old in the community. The basic reproduction number (the number of people infected per patient) is in the range of 1.5—similar or less than that of the pandemics of 1918, 1957, and 1968. There remain significant uncertainties about the severity of this outbreak, which makes it difficult to compare the economic and societal costs of intervention with lives saved and the risks of generating antiviral resistance. An international collaborative effort has analyzed the initial dynamics of the swine flu outbreak. A novel influenza A (H1N1) virus has spread rapidly across the globe. Judging its pandemic potential is difficult with limited data, but nevertheless essential to inform appropriate health responses. By analyzing the outbreak in Mexico, early data on international spread, and viral genetic diversity, we make an early assessment of transmissibility and severity. Our estimates suggest that 23,000 (range 6000 to 32,000) individuals had been infected in Mexico by late April, giving an estimated case fatality ratio (CFR) of 0.4% (range: 0.3 to 1.8%) based on confirmed and suspected deaths reported to that time. In a community outbreak in the small community of La Gloria, Veracruz, no deaths were attributed to infection, giving an upper 95% bound on CFR of 0.6%. Thus, although substantial uncertainty remains, clinical severity appears less than that seen in the 1918 influenza pandemic but comparable with that seen in the 1957 pandemic. Clinical attack rates in children in La Gloria were twice that in adults (<15 years of age: 61%; ≥15 years: 29%). Three different epidemiological analyses gave basic reproduction number (R0) estimates in the range of 1.4 to 1.6, whereas a genetic analysis gave a central estimate of 1.2. This range of values is consistent with 14 to 73 generations of human-to-human transmission having occurred in Mexico to late April. Transmissibility is therefore substantially higher than that of seasonal flu, and comparable with lower estimates of R0 obtained from previous influenza pandemics.

HIV-1 Transmission, by Stage of Infection

BACKGROUND The epidemiological impact of public health interventions targeted at reducing transmission of human immunodeficiency virus type 1 (HIV-1) during early or late-stage infection depends on the contribution of these disease stages to transmission within a particular epidemic. METHODS Transmission hazards and durations of periods of high infectivity during primary, asymptomatic, and late-stage infection were estimated for HIV-1-serodiscordant heterosexual couples in Rakai, Uganda, by use of a robust probabilistic framework. RESULTS Primary infection and late-stage infection were estimated to be 26 and 7 times, respectively, more infectious than asymptomatic infection. High infectiousness during primary infection was estimated to last for approximately 3 months after seroconversion, whereas high infectiousness during late-stage infection was estimated to be concentrated between 19 months and 10 months before death. CONCLUSIONS Primary and late-stage HIV-1 infection are more infectious than previously estimated, but for shorter periods. In a homogeneous population, the asymptomatic stage of infection will typically contribute more to the net transmission of HIV-1 over the lifetime of an infected individual, because of its longer duration. The dependence of the relative contribution of infectious stages on patterns of sexual behavior and the phase of epidemics is discussed.

Variation in HIV-1 set-point viral load: Epidemiological analysis and an evolutionary hypothesis

The natural course of HIV-1 infection is characterized by a high degree of heterogeneity in viral load, not just within patients over time, but also between patients, especially during the asymptomatic stage of infection. Asymptomatic, or set-point, viral load has been shown to correlate with both decreased time to AIDS and increased infectiousness. The aim of this study is to characterize the epidemiological impact of heterogeneity in set-point viral load. By analyzing two cohorts of untreated patients, we quantify the relationships between both viral load and infectiousness and the duration of the asymptomatic infectious period. We find that, because both the duration of infection and infectiousness determine the opportunities for the virus to be transmitted, this suggests a trade-off between these contributions to the overall transmission potential. Some public health implications of variation in set-point viral load are discussed. We observe that set-point viral loads are clustered around those that maximize the transmission potential, and this leads us to hypothesize that HIV-1 could have evolved to optimize its transmissibility, a form of adaptation to the human host population. We discuss how this evolutionary hypothesis can be tested, review the evidence available to date, and highlight directions for future research.

A resurgent HIV-1 epidemic among men who have sex with men in the era of potent antiretroviral therapy

Objective:Reducing viral load, highly active antiretroviral therapy has the potential to limit onwards transmission of HIV-1 and thus help contain epidemic spread. However, increases in risk behaviour and resurgent epidemics have been widely reported post-highly active antiretroviral therapy. The aim of this study was to quantify the impact that highly active antiretroviral therapy had on the epidemic. Design:We focus on the HIV-1 epidemic among men who have sex with men in the Netherlands, which has been well documented over the past 20 years within several long-standing national surveillance programs. Methods:We used a mathematical model including highly active antiretroviral therapy use and estimated the changes in risk behaviour and diagnosis rate needed to explain annual data on HIV and AIDS diagnoses. Results:We show that the reproduction number R(t), a measure of the state of the epidemic, declined early on from initial values above two and was maintained below one from 1985 to 2000. Since 1996, when highly active antiretroviral therapy became widely used, the risk behaviour rate has increased 66%, resulting in an increase of R(t) to 1.04 in the latest period 2000–2004 (95% confidence interval 0.98–1.09) near or just above the threshold for a self-sustaining epidemic. Hypothetical scenario analysis shows that the epidemiological benefits of highly active antiretroviral therapy and earlier diagnosis on incidence have been entirely offset by increases in the risk behaviour rate. Conclusion:We provide the first detailed quantitative analysis of the HIV epidemic in a well defined population and find a resurgent epidemic in the era of highly active antiretroviral therapy, most likely predominantly caused by increasing sexual risk behaviour.

Modeling infectious disease dynamics in the complex landscape of global health

Mathematical modeling of infectious diseases The spread of infectious diseases can be unpredictable. With the emergence of antibiotic resistance and worrying new viruses, and with ambitious plans for global eradication of polio and the elimination of malaria, the stakes have never been higher. Anticipation and measurement of the multiple factors involved in infectious disease can be greatly assisted by mathematical methods. In particular, modeling techniques can help to compensate for imperfect knowledge, gathered from large populations and under difficult prevailing circumstances. Heesterbeek et al. review the development of mathematical models used in epidemiology and how these can be harnessed to develop successful control strategies and inform public health policy. Science, this issue 10.1126/science.aaa4339 BACKGROUND Despite many notable successes in prevention and control, infectious diseases remain an enormous threat to human and animal health. The ecological and evolutionary dynamics of pathogens play out on a wide range of interconnected temporal, organizational, and spatial scales that span hours to months, cells to ecosystems, and local to global spread. Some pathogens are directly transmitted between individuals of a single species, whereas others circulate among multiple hosts, need arthropod vectors, or persist in environmental reservoirs. Many factors, including increasing antimicrobial resistance, human connectivity, population growth, urbanization, environmental and land-use change, as well as changing human behavior, present global challenges for prevention and control. Faced with this complexity, mathematical models offer valuable tools for understanding epidemiological patterns and for developing and evaluating evidence for decision-making in global health. ADVANCES During the past 50 years, the study of infectious disease dynamics has matured into a rich interdisciplinary field at the intersection of mathematics, epidemiology, ecology, evolutionary biology, immunology, sociology, and public health. The practical challenges range from establishing appropriate data collection to managing increasingly large volumes of information. The theoretical challenges require fundamental study of many-layered, nonlinear systems in which infections evolve and spread and where key events can be governed by unpredictable pathogen biology or human behavior. In this Review, we start with an examination of real-time outbreak response using the West African Ebola epidemic as an example. Here, the challenges range from underreporting of cases and deaths, and missing information on the impact of control measures to understanding human responses. The possibility of future zoonoses tests our ability to detect anomalous outbreaks and to estimate human-to-human transmissibility against a backdrop of ongoing zoonotic spillover while also assessing the risk of more dangerous strains evolving. Increased understanding of the dynamics of infections in food webs and ecosystems where host and nonhost species interact is key. Simultaneous multispecies infections are increasingly recognized as a notable public health burden, yet our understanding of how different species of pathogens interact within hosts is rudimentary. Pathogen genomics has become an essential tool for drawing inferences about evolution and transmission and, here but also in general, heterogeneity is the major challenge. Methods that depart from simplistic assumptions about random mixing are yielding new insights into the dynamics of transmission and control. There is rapid growth in estimation of model parameters from mismatched or incomplete data, and in contrasting model output with real-world observations. New data streams on social connectivity and behavior are being used, and combining data collected from very different sources and scales presents important challenges. All these mathematical endeavors have the potential to feed into public health policy and, indeed, an increasingly wide range of models is being used to support infectious disease control, elimination, and eradication efforts. OUTLOOK Mathematical modeling has the potential to probe the apparently intractable complexity of infectious disease dynamics. Coupled to continuous dialogue between decision-makers and the multidisciplinary infectious disease community, and by drawing on new data streams, mathematical models can lay bare mechanisms of transmission and indicate new approaches to prevention and control that help to shape national and international public health policy. Modeling for public health. Policy questions define the model’s purpose. Initial model design is based on current scientific understanding and the available relevant data. Model validation and fit to disease data may require further adaptation; sensitivity and uncertainty analysis can point to requirements for collection of additional specific data. Cycles of model testing and analysis thus lead to policy advice and improved scientific understanding. Despite some notable successes in the control of infectious diseases, transmissible pathogens still pose an enormous threat to human and animal health. The ecological and evolutionary dynamics of infections play out on a wide range of interconnected temporal, organizational, and spatial scales, which span hours to months, cells to ecosystems, and local to global spread. Moreover, some pathogens are directly transmitted between individuals of a single species, whereas others circulate among multiple hosts, need arthropod vectors, or can survive in environmental reservoirs. Many factors, including increasing antimicrobial resistance, increased human connectivity and changeable human behavior, elevate prevention and control from matters of national policy to international challenge. In the face of this complexity, mathematical models offer valuable tools for synthesizing information to understand epidemiological patterns, and for developing quantitative evidence for decision-making in global health.

Will travel restrictions control the international spread of pandemic influenza

A key question in contingency planning for a possible influenza pandemic is the value of restricting international travel to and from affected countries or regions, or imposing entry or exit screening of passengers at airports1. The potential for infectious diseases to spread rapidly through an increasingly well-connected, steadily growing world population2, 3, 4, 5 was brought into sharp focus during the 2003 epidemic of severe acute respiratory syndrome (SARS).

Virulence and Pathogenesis of HIV-1 Infection: An Evolutionary Perspective

Background Why some individuals develop AIDS rapidly whereas others remain healthy without treatment for many years remains a central question of HIV research. Of the quantities that predict how quickly an untreated infection progresses, the most widely used is set-point viral load. This measure varies by orders of magnitude between infected individuals and is predictive of infectiousness and time to onset of AIDS. Host factors, predominantly linked to the immune system, are known to influence the set point, but much variation remains unexplained. A transmission chain with heritable virulence. Individuals infected with HIV show differences in clinical progression. Untreated infections are characterized by viral loads (the viral particle density in the blood) that are relatively stable for years, but they can differ by orders of magnitude between individuals. Host factors clearly influence viral load, but viral loads have also recently been found to correlate among individuals in transmission pairs and chains. This indicates a moderate to strong influence of viral genotype on the viral load. Strikingly, this influence persists for years and across transmission events, despite intense within-host viral evolution. A transmission chain with heritable virulence. Individuals infected with HIV show differences in clinical progression. Untreated infections are characterized by viral loads (the viral particle density in the blood) that are relatively stable for years, but they can differ by orders of magnitude between individuals. Host factors clearly influence viral load, but viral loads have also recently been found to correlate among individuals in transmission pairs and chains. This indicates a moderate to strong influence of viral genotype on the viral load. Strikingly, this influence persists for years and across transmission events, despite intense within-host viral evolution. Advances We review recent evidence showing that HIV genotype influences the set-point viral load far more than anticipated. Our summary of published estimates suggests that 33% (95% confidence interval, 20 to 46%) of the variation is attributable to the virus. Because set-point viral load is heritable (partially controlled by virus genotype) and is linked to transmissibility, it is likely to have evolved to maintain transmission fitness and may continue to evolve in response to diverse selection pressures. These findings are unexpected and paradoxical because rapid and error-prone viral replication should favor within-host adaptation and rapidly scramble signals of viral genotype as infection progresses, rather than leaving a lasting footprint that is preserved throughout an infection and from one infection to the next in transmission chains. Outlook We propose that resolving the paradox of heritability of set-point viral load will provide new insights into the mechanisms of HIV pathogenesis. To this end, we provide three parsimonious, testable, and nonexclusive explanatory mechanisms. The first states that HIV evolution in virulence genes is more functionally constrained than previously thought. The second proposes that virulence of HIV is mediated through the virus’s capacity to systemically activate target cells in which it can efficiently replicate. The capacity to activate would not be expected to evolve rapidly because it does not provide a specific selective advantage to virus strains that activate more cells; rather, it is an advantage shared by all viruses. The third mechanism implicates the preferential transmission of viruses that are stored in nonreplicating cells or during early infection, and the disproportionate influence on long-term pathogenesis of these early viruses. In addition to these insights into mechanisms of pathogenesis, we believe that this research highlights a major gap in our knowledge of HIV. The identification of the genetic determinants of HIV virulence, which appear to vary between closely related strains of the virus, should be a major priority. Thus, whole-genome association studies that are focused on the virus genome should be pursued and expanded, as well as more functional and mechanistic studies, which could be guided by hypotheses such as those presented here. HIV Virulence A major focus of research on HIV is on host responses to infection—understandably, because the virus targets the immune system and because of the interest in vaccine development. In reviewing what little research has been done on viral virulence determinants, Fraser et al. (10.1126/science.1243727) present evolutionary explanations for some of the poorly understood phenomena that mark HIV infection, including long-term survivorship, latency, rapid within-host evolution, and inheritability of between-host virulence. Why some individuals develop AIDS rapidly whereas others remain healthy without treatment for many years remains a central question of HIV research. An evolutionary perspective reveals an apparent conflict between two levels of selection on the virus. On the one hand, there is rapid evolution of the virus in the host, and on the other, new observations indicate the existence of virus factors that affect the virulence of infection whose influence persists over years in infected individuals and across transmission events. Here, we review recent evidence that shows that viral genetic factors play a larger role in modulating disease severity than anticipated. We propose conceptual models that reconcile adaptive evolution at both levels of selection. Evolutionary analysis provides new insight into HIV pathogenesis.

The potential contribution of mass treatment to the control of Plasmodium falciparum malaria.

Mass treatment as a means to reducing P. falciparum malaria transmission was used during the first global malaria eradication campaign and is increasingly being considered for current control programmes. We used a previously developed mathematical transmission model to explore both the short and long-term impact of possible mass treatment strategies in different scenarios of endemic transmission. Mass treatment is predicted to provide a longer-term benefit in areas with lower malaria transmission, with reduced transmission levels for at least 2 years after mass treatment is ended in a scenario where the baseline slide-prevalence is 5%, compared to less than one year in a scenario with baseline slide-prevalence at 50%. However, repeated annual mass treatment at 80% coverage could achieve around 25% reduction in infectious bites in moderate-to-high transmission settings if sustained. Using vector control could reduce transmission to levels at which mass treatment has a longer-term impact. In a limited number of settings (which have isolated transmission in small populations of 1000–10,000 with low-to-medium levels of baseline transmission) we find that five closely spaced rounds of mass treatment combined with vector control could make at least temporary elimination a feasible goal. We also estimate the effects of using gametocytocidal treatments such as primaquine and of restricting treatment to parasite-positive individuals. In conclusion, mass treatment needs to be repeated or combined with other interventions for long-term impact in many endemic settings. The benefits of mass treatment need to be carefully weighed against the risks of increasing drug selection pressure.

The coverage and frequency of mass drug administration required to eliminate persistent transmission of soil-transmitted helminths

A combination of methods, including mathematical model construction, demographic plus epidemiological data analysis and parameter estimation, are used to examine whether mass drug administration (MDA) alone can eliminate the transmission of soil-transmitted helminths (STHs). Numerical analyses suggest that in all but low transmission settings (as defined by the magnitude of the basic reproductive number, R0), the treatment of pre-school-aged children (pre-SAC) and school-aged children (SAC) is unlikely to drive transmission to a level where the parasites cannot persist. High levels of coverage (defined as the fraction of an age group effectively treated) are required in pre-SAC, SAC and adults, if MDA is to drive the parasite below the breakpoint under which transmission is eliminated. Long-term solutions to controlling helminth infections lie in concomitantly improving the quality of the water supply, sanitation and hygiene (WASH). MDA, however, is a very cost-effective tool in long-term control given that most drugs are donated free by the pharmaceutical industry for poor regions of the world. WASH interventions, by lowering the basic reproductive number, can facilitate the ability of MDA to interrupt transmission.

How Effective Is School-Based Deworming for the Community-Wide Control of Soil-Transmitted Helminths?

Background The London Declaration on neglected tropical diseases was based in part on a new World Health Organization roadmap to “sustain, expand and extend drug access programmes to ensure the necessary supply of drugs and other interventions to help control by 2020”. Large drug donations from the pharmaceutical industry form the backbone to this aim, especially for soil-transmitted helminths (STHs) raising the question of how best to use these resources. Deworming for STHs is often targeted at school children because they are at greatest risk of morbidity and because it is remarkably cost-effective. However, the impact of school-based deworming on transmission in the wider community remains unclear. Methods We first estimate the proportion of parasites targeted by school-based deworming using demography, school enrolment, and data from a small number of example settings where age-specific intensity of infection (either worms or eggs) has been measured for all ages. We also use transmission models to investigate the potential impact of this coverage on transmission for different mixing scenarios. Principal Findings In the example settings <30% of the population are 5 to <15 years old. Combining this demography with the infection age-intensity profile we estimate that in one setting school children output as little as 15% of hookworm eggs, whereas in another setting they harbour up to 50% of Ascaris lumbricoides worms (the highest proportion of parasites for our examples). In addition, it is estimated that from 40–70% of these children are enrolled at school. Conclusions These estimates suggest that, whilst school-based programmes have many important benefits, the proportion of infective stages targeted by school-based deworming may be limited, particularly where hookworm predominates. We discuss the consequences for transmission for a range of scenarios, including when infective stages deposited by children are more likely to contribute to transmission than those from adults.