Henrik Salje

Association between Zika virus and microcephaly in French Polynesia, 2013–15: a retrospective study

BACKGROUND The emergence of Zika virus in the Americas has coincided with increased reports of babies born with microcephaly. On Feb 1, 2016, WHO declared the suspected link between Zika virus and microcephaly to be a Public Health Emergency of International Concern. This association, however, has not been precisely quantified. METHODS We retrospectively analysed data from a Zika virus outbreak in French Polynesia, which was the largest documented outbreak before that in the Americas. We used serological and surveillance data to estimate the probability of infection with Zika virus for each week of the epidemic and searched medical records to identify all cases of microcephaly from September, 2013, to July, 2015. Simple models were used to assess periods of risk in pregnancy when Zika virus might increase the risk of microcephaly and estimate the associated risk. FINDINGS The Zika virus outbreak began in October, 2013, and ended in April, 2014, and 66% (95% CI 62-70) of the general population were infected. Of the eight microcephaly cases identified during the 23-month study period, seven (88%) occurred in the 4-month period March 1 to July 10, 2014. The timing of these cases was best explained by a period of risk in the first trimester of pregnancy. In this model, the baseline prevalence of microcephaly was two cases (95% CI 0-8) per 10,000 neonates, and the risk of microcephaly associated with Zika virus infection was 95 cases (34-191) per 10,000 women infected in the first trimester. We could not rule out an increased risk of microcephaly from infection in other trimesters, but models that excluded the first trimester were not supported by the data. INTERPRETATION Our findings provide a quantitative estimate of the risk of microcephaly in fetuses and neonates whose mothers are infected with Zika virus. FUNDING Labex-IBEID, NIH-MIDAS, AXA Research fund, EU-PREDEMICS.

Assessing the global threat from Zika virus

Global spread of Zika virus Zika virus was identified in Uganda in 1947; since then, it has enveloped the tropics, causing disease of varying severity. Lessler et al. review the historical literature to remind us that Zikas neurotropism was observed in mice even before clinical case reports in Nigeria in 1953. What determines the clinical manifestations; how local conditions, vectors, genetics, and wild hosts affect transmission and geographical spread; what the best control strategy is; and how to develop effective drugs, vaccines, and diagnostics are all critical questions that are begging for data. Science, this issue p. 663 Assessing the global threat from Zika virus. BACKGROUND First discovered in 1947, Zika virus (ZIKV) received little attention until a surge in microcephaly cases was reported after a 2015 outbreak in Brazil. The size of the outbreak and the severity of associated birth defects prompted the World Health Organization (WHO) to declare a Public Health Emergency of International Concern on 1 February 2016. In response, there has been an explosion in research and planning as the global health community has turned its attention to understanding and controlling ZIKV. Still, much of the information needed to evaluate the global health threat from ZIKV is lacking. The global threat posed by any emerging pathogen depends on its epidemiology, its clinical features, and our ability to implement effective control measures. Whether introductions of ZIKV result in epidemics depends on local ecology, population immunity, regional demographics, and, to no small degree, random chance. The same factors determine whether the virus will establish itself as an endemic disease. The burden of ZIKV spread on human health is mediated by its natural history and pathogenesis, particularly during pregnancy, and our ability to control the virus’s spread. In this Review, we examine the empirical evidence for a global threat from ZIKV through the lens of these processes, examining historic and current evidence, as well as parallel processes in closely related viruses. ADVANCES Because ZIKV was not recognized as an important disease in humans until recently, it was little studied before the recent crisis. Nevertheless, the limited data from the decades following its discovery provide important clues into ZIKV’s epidemiology and suggest that some populations were at risk for the virus for years in the mid-20th century, although this risk may predominantly have been the result of spillover infections from a sylvatic reservoir. Recent outbreaks on Yap Island (2007) and in French Polynesia (2014) provide the only previous observations of large epidemics and are the basis for the little that we do know about ZIKV’s acute symptoms (e.g., rash, fever, conjunctivitis, and arthralgia), the risk of birth defects, such as microcephaly (estimated to be 1 per 100 in French Polynesia), and the incidence of severe neurological outcomes (e.g., Guillain-Barré is estimated to occur in approximately 2 out of every 10,000 cases). The observation of an association between ZIKV and a surge in microcephaly cases in Brazil and the subsequent declaration of a Public Health Emergency of International Concern by the WHO have rapidly accelerated research into the virus. Small, but very important, studies have begun to identify the substantial risk the virus can pose throughout a pregnancy, and careful surveillance has established that ZIKV can be transmitted sexually. Numerous modeling studies have helped to estimate the potential range of ZIKV and measured its reproductive number R0 (estimates range from 1.4 to 6.6), a key measure of transmissibility in a number of settings. Still, it remains unclear whether the recent epidemic in the Americas is the result of fundamental changes in the virus or merely a chance event. OUTLOOK ZIKV research is progressing rapidly, and over the coming months and years our understanding of the virus will undoubtedly deepen considerably. Key questions about the virus’s range, its ability to persist, and its clinical severity will be answered as the current epidemic in the Americas runs its course. Moving forward, it is important that information on ZIKV be placed within the context of its effect on human health and that we remain cognizant of the structure of postinvasion epidemic dynamics as we respond to this emerging threat. The effect of ZIKV is a function of the local transmission regime and viral pathogenesis. (A) Many countries cannot maintain ongoing vector-mediated ZIKV transmission and are only at risk from importation by travelers and limited onward transmission (e.g., through sex). (B) If conditions are appropriate, importations can lead to postinvasion epidemics with high incidence across age ranges, after which the virus may go locally extinct or remain endemic

Revealing the microscale spatial signature of dengue transmission and immunity in an urban population

It is well-known that the distribution of immunity in a population dictates the future incidence of infectious disease, but this process is generally understood at individual or macroscales. For example, herd immunity to multiple pathogens has been observed at national and city levels. However, the effects of population immunity have not previously been shown at scales smaller than the city (e.g., neighborhoods). In particular, no study has shown long-term effects of population immunity at scales consistent with the spatial scale of person-to-person transmission. Here, we use the location of dengue patients’ homes in Bangkok with the serotype of the infecting pathogen to investigate the spatiotemporal distribution of disease risk at small spatial scales over a 5-y period. We find evidence for localized transmission at distances of under 1 km. We also observe patterns of spatiotemporal dependence consistent with the expected impacts of homotypic immunity, heterotypic immunity, and immune enhancement of disease at these distances. Our observations indicate that immunological memory of dengue serotypes occurs at the neighborhood level in this large urban setting. These methods have broad applications to studying the spatiotemporal structure of disease risk where pathogen serotype or genetic information is known.

High rate of subclinical chikungunya virus infection and association of neutralizing antibody with protection in a prospective cohort in the Philippines

Background Chikungunya virus (CHIKV) is a globally re-emerging arbovirus for which previous studies have indicated the majority of infections result in symptomatic febrile illness. We sought to characterize the proportion of subclinical and symptomatic CHIKV infections in a prospective cohort study in a country with known CHIKV circulation. Methods/Findings A prospective longitudinal cohort of subjects ≥6 months old underwent community-based active surveillance for acute febrile illness in Cebu City, Philippines from 2012-13. Subjects with fever history were clinically evaluated at acute, 2, 5, and 8 day visits, and at a 3-week convalescent visit. Blood was collected at the acute and 3-week convalescent visits. Symptomatic CHIKV infections were identified by positive CHIKV PCR in acute blood samples and/or CHIKV IgM/IgG ELISA seroconversion in paired acute/convalescent samples. Enrollment and 12-month blood samples underwent plaque reduction neutralization test (PRNT) using CHIKV attenuated strain 181/clone25. Subclinical CHIKV infections were identified by ≥8-fold rise from a baseline enrollment PRNT titer <10 without symptomatic infection detected during the intervening surveillance period. Selected CHIKV PCR-positive samples underwent viral isolation and envelope protein-1 gene sequencing. Of 853 subjects who completed all study procedures at 12 months, 19 symptomatic infections (2.19 per 100 person-years) and 87 subclinical infections (10.03 per 100 person-years) occurred. The ratio of subclinical-to-symptomatic infections was 4.6:1 varying with age from 2:1 in 6 month-5 year olds to 12:1 in those >50 years old. Baseline CHIKV PRNT titer ≥10 was associated with 100% (95%CI: 46.1, 100.0) protection from symptomatic CHIKV infection. Phylogenetic analysis demonstrated Asian genotype closely related to strains from Asia and the Caribbean. Conclusions Subclinical infections accounted for a majority of total CHIKV infections. A positive baseline CHIKV PRNT titer was associated with protection from symptomatic CHIKV infection. These findings have implications for assessing disease burden, understanding virus transmission, and supporting vaccine development.

Spread of yellow fever virus outbreak in Angola and the Democratic Republic of the Congo 2015–16: a modelling study

Summary Background Since late 2015, an epidemic of yellow fever has caused more than 7334 suspected cases in Angola and the Democratic Republic of the Congo, including 393 deaths. We sought to understand the spatial spread of this outbreak to optimise the use of the limited available vaccine stock. Methods We jointly analysed datasets describing the epidemic of yellow fever, vector suitability, human demography, and mobility in central Africa to understand and predict the spread of yellow fever virus. We used a standard logistic model to infer the district-specific yellow fever virus infection risk during the course of the epidemic in the region. Findings The early spread of yellow fever virus was characterised by fast exponential growth (doubling time of 5–7 days) and fast spatial expansion (49 districts reported cases after only 3 months) from Luanda, the capital of Angola. Early invasion was positively correlated with high population density (Pearsons r 0·52, 95% CI 0·34–0·66). The further away locations were from Luanda, the later the date of invasion (Pearsons r 0·60, 95% CI 0·52–0·66). In a Cox model, we noted that districts with higher population densities also had higher risks of sustained transmission (the hazard ratio for cases ceasing was 0·74, 95% CI 0·13–0·92 per log-unit increase in the population size of a district). A model that captured human mobility and vector suitability successfully discriminated districts with high risk of invasion from others with a lower risk (area under the curve 0·94, 95% CI 0·92–0·97). If at the start of the epidemic, sufficient vaccines had been available to target 50 out of 313 districts in the area, our model would have correctly identified 27 (84%) of the 32 districts that were eventually affected. Interpretation Our findings show the contributions of ecological and demographic factors to the ongoing spread of the yellow fever outbreak and provide estimates of the areas that could be prioritised for vaccination, although other constraints such as vaccine supply and delivery need to be accounted for before such insights can be translated into policy. Funding Wellcome Trust.

Use of Viremia to Evaluate the Baseline Case Fatality Ratio of Ebola Virus Disease and Inform Treatment Studies: A Retrospective Cohort Study

Background The case fatality ratio (CFR) of Ebola virus disease (EVD) can vary over time and space for reasons that are not fully understood. This makes it difficult to define the baseline CFRs needed to evaluate treatments in the absence of randomized controls. Here, we investigate whether viremia in EVD patients may be used to evaluate baseline EVD CFRs. Methods and Findings We analyzed the laboratory and epidemiological records of patients with EVD confirmed by reverse transcription PCR hospitalized in the Conakry area, Guinea, between 1 March 2014 and 28 February 2015. We used viremia and other variables to model the CFR. Data for 699 EVD patients were analyzed. In the week following symptom onset, mean viremia remained stable, and the CFR increased with viremia, V, from 21% (95% CI 16%–27%) for low viremia (V < 104.4 copies/ml) to 53% (95% CI 44%–61%) for intermediate viremia (104.4 ≤ V < 105.2 copies/ml) and 81% (95% CI 75%–87%) for high viremia (V ≥ 105.2 copies/ml). Compared to adults (15–44 y old [y.o.]), the CFR was larger in young children (0–4 y.o.) (odds ratio [OR]: 2.44; 95% CI 1.02–5.86) and older adults (≥45 y.o.) (OR: 2.84; 95% CI 1.81–4.46) but lower in children (5–14 y.o.) (OR: 0.46; 95% CI 0.24–0.86). An order of magnitude increase in mean viremia in cases after July 2014 compared to those before coincided with a 14% increase in the CFR. Our findings come from a large hospital-based study in Conakry and may not be generalizable to settings with different case profiles, such as with individuals who never sought care. Conclusions Viremia in EVD patients was a strong predictor of death that partly explained variations in CFR in the study population. This study provides baseline CFRs by viremia group, which allow appropriate adjustment when estimating efficacy in treatment studies. In randomized controlled trials, stratifying analysis on viremia groups could reduce sample size requirements by 25%. We hypothesize that monitoring the viremia of hospitalized patients may inform the ability of surveillance systems to detect EVD patients from the different severity strata.

Reconstruction of 60 years of chikungunya epidemiology in the Philippines demonstrates episodic and focal transmission

Proper understanding of the long-term epidemiology of chikungunya has been hampered by poor surveillance. Outbreak years are unpredictable and cases often misdiagnosed. Here we analyzed age-specific data from 2 serological studies (from 1973 and 2012) in Cebu, Philippines, to reconstruct both the annual probability of infection and population-level immunity over a 60-year period (1952–2012). We also explored whether seroconversions during 2012–2013 were spatially clustered. Our models identified 4 discrete outbreaks separated by an average delay of 17 years. On average, 23% (95% confidence interval [CI], 16%–37%) of the susceptible population was infected per outbreak, with >50% of the entire population remaining susceptible at any point. Participants who seroconverted during 2012–2013 were clustered at distances of <230 m, suggesting focal transmission. Large-scale outbreaks of chikungunya did not result in sustained multiyear transmission. Nevertheless, we estimate that >350 000 infections were missed by surveillance systems. Serological studies could supplement surveillance to provide important insights on pathogen circulation.

Seasonal concentrations and determinants of indoor particulate matter in a low-income community in Dhaka, Bangladesh

Indoor exposure to particulate matter (PM) increases the risk of acute lower respiratory tract infections, which are the leading cause of death in young children in Bangladesh. Few studies, however, have measured childrens exposures to indoor PM over time. The World Health Organization recommends that daily indoor concentrations of PM less than 2.5μm in diameter (PM(2.5)) not exceed 25μg/m(3). This study aimed to describe the seasonal variation and determinants of concentrations of indoor PM(2.5) in a low-income community in urban Dhaka, Bangladesh. PM(2.5) was measured in homes monthly during May 2009 to April 2010. We calculated the time-weighted average, 90th percentile PM(2.5) concentrations and the daily hours PM(2.5) exceeded 100μg/m(3). Linear regression models were used to estimate the associations between fuel use, ventilation, indoor smoking, and season to each metric describing indoor PM(2.5) concentrations. Time-weighted average PM(2.5) concentrations were 190μg/m(3) (95% CI 170-210). Sixteen percent of 258 households primarily used biomass fuels for cooking and PM(2.5) concentrations in these homes had average concentrations 75μg/m(3) (95% CI 56-124) greater than other homes. PM(2.5) concentrations were also associated with burning both biomass and kerosene, indoor smoking, and ventilation, and were more than twice as high during winter than during other seasons. Young children in this community are exposed to indoor PM(2.5) concentrations 7 times greater than those recommended by World Health Organization guidelines. Interventions to reduce biomass burning could result in a daily reduction of 75μg/m(3) (40%) in time-weighted average PM(2.5) concentrations.

How social structures, space, and behaviors shape the spread of infectious diseases using chikungunya as a case study

Significance Although the determinants of infectious disease transmission have been extensively investigated in small social structures such as households or schools, the impact of the wider environment (e.g., neighborhood) on transmission has received less attention. Here we use an outbreak of chikungunya as a case study where detailed epidemiological data were collected and combine it with statistical approaches to characterize the multiple factors that influence the risk of infectious disease transmission and may depend on characteristics of the individual (e.g., age, sex), of his or her close relatives (e.g., household members), or of the wider neighborhood. Our findings highlight the role that integrating statistical approaches with in-depth information on the at-risk population can have on understanding pathogen spread. Whether an individual becomes infected in an infectious disease outbreak depends on many interconnected risk factors, which may relate to characteristics of the individual (e.g., age, sex), his or her close relatives (e.g., household members), or the wider community. Studies monitoring individuals in households or schools have helped elucidate the determinants of transmission in small social structures due to advances in statistical modeling; but such an approach has so far largely failed to consider individuals in the wider context they live in. Here, we used an outbreak of chikungunya in a rural community in Bangladesh as a case study to obtain a more comprehensive characterization of risk factors in disease spread. We developed Bayesian data augmentation approaches to account for uncertainty in the source of infection, recall uncertainty, and unobserved infection dates. We found that the probability of chikungunya transmission was 12% [95% credible interval (CI): 8–17%] between household members but dropped to 0.3% for those living 50 m away (95% CI: 0.2–0.5%). Overall, the mean transmission distance was 95 m (95% CI: 77–113 m). Females were 1.5 times more likely to become infected than males (95% CI: 1.2–1.8), which was virtually identical to the relative risk of being at home estimated from an independent human movement study in the country. Reported daily use of antimosquito coils had no detectable impact on transmission. This study shows how the complex interplay between the characteristics of an individual and his or her close and wider environment contributes to the shaping of infectious disease epidemics.

Dengue diversity across spatial and temporal scales: Local structure and the effect of host population size

Regions of high human population density drive highly localized transmission chains of dengue virus, which then can disperse regionally. Estimating transmission chains for dengue Dengue virus (DENV) causes a large number of asymptomatic infections, so surveillance captures only a fraction of cases. Salje et al. developed a method for identifying the number of transmission chains of DENV from sequence data and serology. They found that sequential transmission of DENV typically occurs between households in the same neighborhood. Within high-density urban localities, such as Bangkok, there are surprisingly few transmission chains. This results in epidemic spikes within a regional background of endemicity. Large urban settings may thus act as a source of diverse viruses that can be transported elsewhere. Science, this issue p. 1302 A fundamental mystery for dengue and other infectious pathogens is how observed patterns of cases relate to actual chains of individual transmission events. These pathways are intimately tied to the mechanisms by which strains interact and compete across spatial scales. Phylogeographic methods have been used to characterize pathogen dispersal at global and regional scales but have yielded few insights into the local spatiotemporal structure of endemic transmission. Using geolocated genotype (800 cases) and serotype (17,291 cases) data, we show that in Bangkok, Thailand, 60% of dengue cases living <200 meters apart come from the same transmission chain, as opposed to 3% of cases separated by 1 to 5 kilometers. At distances <200 meters from a case (encompassing an average of 1300 people in Bangkok), the effective number of chains is 1.7. This number rises by a factor of 7 for each 10-fold increase in the population of the “enclosed” region. This trend is observed regardless of whether population density or area increases, though increases in density over 7000 people per square kilometer do not lead to additional chains. Within Thailand these chains quickly mix, and by the next dengue season viral lineages are no longer highly spatially structured within the country. In contrast, viral flow to neighboring countries is limited. These findings are consistent with local, density-dependent transmission and implicate densely populated communities as key sources of viral diversity, with home location the focal point of transmission. These findings have important implications for targeted vector control and active surveillance.