Reconstruction of 60 Years of Chikungunya Epidemiology in the Philippines Demonstrates Episodic and Focal Transmission

Global age-stratified seroprevalence of enterovirus D68: a systematic literature review

Enterovirus D68 (EV-D68), first isolated in 1962, emerged in 2014, causing outbreaks of severe respiratory infections and acute flaccid myelitis. In this systematic review, we have compiled all available literature on age-stratified seroprevalence estimates of EV-D68. Ten studies from six countries were retained, all conducted using microneutralisation assays, despite wide variations in protocols and challenge viruses. The age profiles of seroprevalence were similar across time and regions; seroprevalence increased quickly with age, reaching roughly 100% by the age of 20 years and with no sign of decline throughout adulthood. This suggests continuous or frequent exposure of the populations to the virus, or possible cross-reactivity with other viruses. Studies with two or more cross-sectional surveys reported consistently higher seroprevalence at later timepoints, suggesting a global increase in transmission over time. This systematic review concludes that standardising serological protocols, understanding the contribution of cross-reactivity with other pathogens to the high reported seroprevalence, and quantifying individual exposure to EV-D68 over time are the main research priorities for the future.

Geographical migration and fitness dynamics of Streptococcus pneumoniae

Streptococcus pneumoniae is a leading cause of pneumonia and meningitis worldwide. Many different serotypes co-circulate endemically in any one location1,2. The extent and mechanisms of spread and vaccine-driven changes in fitness and antimicrobial resistance remain largely unquantified. Here using geolocated genome sequences from South Africa (n = 6,910, collected from 2000 to 2014), we developed models to reconstruct spread, pairing detailed human mobility data and genomic data. Separately, we estimated the population-level changes in fitness of strains that are included (vaccine type (VT)) and not included (non-vaccine type (NVT)) in pneumococcal conjugate vaccines, first implemented in South Africa in 2009. Differences in strain fitness between those that are and are not resistant to penicillin were also evaluated. We found that pneumococci only become homogenously mixed across South Africa after 50 years of transmission, with the slow spread driven by the focal nature of human mobility. Furthermore, in the years following vaccine implementation, the relative fitness of NVT compared with VT strains increased (relative risk of 1.68; 95% confidence interval of 1.59-1.77), with an increasing proportion of these NVT strains becoming resistant to penicillin. Our findings point to highly entrenched, slow transmission and indicate that initial vaccine-linked decreases in antimicrobial resistance may be transient.

Model-based estimates of chikungunya epidemiological parameters and outbreak risk from varied data types

Assessing the factors responsible for differences in outbreak severity for the same pathogen is a challenging task, since outbreak data are often incomplete and may vary in type across outbreaks (e.g., daily case counts, serology, cases per household). We propose that outbreaks described with varied data types can be directly compared by using those data to estimate a common set of epidemiological parameters. To demonstrate this for chikungunya virus (CHIKV), we developed a realistic model of CHIKV transmission, along with a Bayesian inference method that accommodates any type of outbreak data that can be simulated. The inference method makes use of the fact that all data types arise from the same transmission process, which is simulated by the model. We applied these tools to data from three real-world outbreaks of CHIKV in Italy, Cambodia, and Bangladesh to estimate nine model parameters. We found that these populations differed in several parameters, including pre-existing immunity and house-to-house differences in mosquito activity. These differences resulted in posterior predictions of local CHIKV transmission risk that varied nearly fourfold: 16% in Italy, 28% in Cambodia, and 62% in Bangladesh. Our inference method and model can be applied to improve understanding of the epidemiology of CHIKV and other pathogens for which outbreaks are described with varied data types.

Epidemiological and genomic investigation of chikungunya virus in Rio de Janeiro state, Brazil, between 2015 and 2018

Since 2014, Brazil has experienced an unprecedented epidemic caused by chikungunya virus (CHIKV), with several waves of East-Central-South-African (ECSA) lineage transmission reported across the country. In 2018, Rio de Janeiro state, the third most populous state in Brazil, reported 41% of all chikungunya cases in the country. Here we use evolutionary and epidemiological analysis to estimate the timescale of CHIKV-ECSA-American lineage and its epidemiological patterns in Rio de Janeiro. We show that the CHIKV-ECSA outbreak in Rio de Janeiro derived from two distinct clades introduced from the Northeast region in mid-2015 (clade RJ1, n = 63/67 genomes from Rio de Janeiro) and mid-2017 (clade RJ2, n = 4/67). We detected evidence for positive selection in non-structural proteins linked with viral replication in the RJ1 clade (clade-defining: nsP4-A481D) and the RJ2 clade (nsP1-D531G). Finally, we estimate the CHIKV-ECSA's basic reproduction number (R0) to be between 1.2 to 1.6 and show that its instantaneous reproduction number (Rt) displays a strong seasonal pattern with peaks in transmission coinciding with periods of high Aedes aegypti transmission potential. Our results highlight the need for continued genomic and epidemiological surveillance of CHIKV in Brazil, particularly during periods of high ecological suitability, and show that selective pressures underline the emergence and evolution of the large urban CHIKV-ECSA outbreak in Rio de Janeiro.

serosim: An R package for simulating serological data arising from vaccination, epidemiological and antibody kinetics processes

serosim is an open-source R package designed to aid inference from serological studies, by simulating data arising from user-specified vaccine and antibody kinetics processes using a random effects model. Serological data are used to assess population immunity by directly measuring individuals' antibody titers. They uncover locations and/or populations which are susceptible and provide evidence of past infection or vaccination to help inform public health measures and surveillance. Both serological data and new analytical techniques used to interpret them are increasingly widespread. This creates a need for tools to simulate serological studies and the processes underlying observed titer values, as this will enable researchers to identify best practices for serological study design, and provide a standardized framework to evaluate the performance of different inference methods. serosim allows users to specify and adjust model inputs representing underlying processes responsible for generating the observed titer values like time-varying patterns of infection and vaccination, population demography, immunity and antibody kinetics, and serological sampling design in order to best represent the population and disease system(s) of interest. This package will be useful for planning sampling design of future serological studies, understanding determinants of observed serological data, and validating the accuracy and power of new statistical methods.

Dewi Y, Syafruddin D, Idris I, B.B. Bernadus J, Telew A, S. Purwanto D, D. Rosita Y, Antonjaya U, S.A. Myint K. Seroprevalence of Chikungunya in an Asymptomatic Adult Population in North and South Sulawesi, Indonesia

Chikungunya (CHIK) is an emerging and reemerging infectious disease of public health importance in Indonesia. Information on the asymptomatic and true burden of CHIK virus (CHIKV) infections is limited. We assayed 1,092 healthy population samples, collected in North and South Sulawesi between 2019 and 2020, for antibodies against CHIKV. Blood samples were screened by IgM and IgG ELISAs and quantitative real-time reverse transcription polymerase chain reaction (qRT-PCR) assay. CHIKV IgG seroprevalence in North and South Sulawesi was 53.2% and 53.9%, respectively. The overall prevalence of anti-CHIKV IgM antibody was 12.9%. Molecular testing of blood donors revealed 0.66% (2/300) were positive for CHIKV qRT-PCR. Our study provides new insights into the CHIKV endemicity situation in the eastern part of Indonesia and warrants the need for further systematic surveillance considering there is no treatment or vaccine for CHIK infection.

Geographic migration and vaccine-induced fitness changes of Streptococcus pneumoniae

Streptococcus pneumoniae is a leading cause of pneumonia and meningitis worldwide. Many different serotypes co-circulate endemically in any one location. The extent and mechanisms of spread, and vaccine-driven changes in fitness and antimicrobial resistance (AMR), remain largely unquantified. Using geolocated genome sequences from South Africa (N=6910, 2000-2014) we developed models to reconstruct spread, pairing detailed human mobility data and genomic data. Separately we estimated the population level changes in fitness of strains that are (vaccine type, VT) and are not (non-vaccine type, NVT) included in the vaccine, first implemented in 2009, as well as differences in strain fitness between those that are and are not resistant to penicillin. We estimated that pneumococci only become homogenously mixed across South Africa after about 50 years of transmission, with the slow spread driven by the focal nature of human mobility. Further, in the years following vaccine implementation the relative fitness of NVT compared to VT strains increased (RR: 1.29 [95% CI 1.20-1.37]) - with an increasing proportion of these NVT strains becoming penicillin resistant. Our findings point to highly entrenched, slow transmission and indicate that initial vaccine-linked decreases in AMR may be transient.

Expected endpoints from future chikungunya vaccine trial sites informed by serological data and modeling

In recent decades, there has been an increased interest in developing a vaccine for chikungunya. However, due to its unpredictable transmission, planning for a chikungunya vaccine trial is challenging. To inform decision making on the selection of sites for a vaccine efficacy trial, we developed a new framework for projecting the expected number of endpoint events at a given site. In this framework, we first accounted for population immunity using serological data collated from a systematic review and used it to estimate parameters related to the timing and size of past outbreaks, as predicted by an SIR transmission model. Then, we used that model to project the infection attack rate of a hypothetical future outbreak, in the event that one were to occur at the time of a future trial. This informed projections of how many endpoint events could be expected if a trial were to take place at that site. Our results suggest that some sites may have sufficient transmission potential and susceptibility to support future vaccine trials, in the event that an outbreak were to occur at those sites. In general, we conclude that sites that have experienced outbreaks within the past 10 years may be poorer targets for chikungunya vaccine efficacy trials in the near future. Our framework also generates projections of the numbers of endpoint events by age, which could inform study participant recruitment efforts.

The origin and continuing adaptive evolution of chikungunya virus

Chikungunya virus (CHIKV) is the responsible agent of chikungunya fever, a debilitating arthritic disease in humans. CHIKV is endemic in Africa and Asia, although transmission cycles are considerably different on these continents. Before 2004, CHIKV had received little attention, since it was only known to cause localised outbreaks in a limited region with no fatalities. However, the recent global reemergence of CHIKV has caused serious global health problems and shown its potential to become a significant viral threat in the future. Unexpectedly, the reemergence is more rapid and is geographically more extensive, especially due to increased intensity of global travel systems or failure to contain mosquito populations. Another important factor is the successful adaptation of CHIKV to a new vector, the Aedes albopictus mosquito. Ae. albopictus survives in both temperate and tropical climates, thus facilitating CHIKV expansion to non-endemic regions. The continuous spread and transmission of CHIKV pose challenges for the development of effective vaccines and specific antiviral therapies. In this review, we discuss the biology and origin of CHIKV in Africa as well as its subsequent expansion to other parts of the world. We also review the transmission cycle of CHIKV and its continuing adaptation to its mosquito vectors and vertebrate hosts. More-complete understanding of the continuous evolution of CHIKV may help in predicting the emergence of CHIKV strains with possibly greater transmission efficiency in the future.

Reconstructing long-term dengue virus immunity in French Polynesia

BACKGROUND

Understanding the underlying risk of infection by dengue virus from surveillance systems is complicated due to the complex nature of the disease. In particular, the probability of becoming severely sick is driven by serotype-specific infection histories as well as age; however, this has rarely been quantified. Island communities that have periodic outbreaks dominated by single serotypes provide an opportunity to disentangle the competing role of serotype, age and changes in surveillance systems in characterising disease risk.

METHODOLOGY

We develop mathematical models to analyse 35 years of dengue surveillance (1979-2014) and seroprevalence studies from French Polynesia. We estimate the annual force of infection, serotype-specific reporting probabilities and changes in surveillance capabilities using the annual age and serotype-specific distribution of dengue.

PRINCIPAL FINDINGS

Eight dengue epidemics occurred between 1979 and 2014, with reporting probabilities for DENV-1 primary infections increasing from 3% to 5%. The reporting probability for DENV-1 secondary infections was 3.6 times that for primary infections. We also observed heterogeneity in reporting probabilities by serotype, with DENV-3 having the highest probability of being detected. Reporting probabilities declined with age after 14 y.o. Between 1979 and 2014, the proportion never infected declined from 70% to 23% while the proportion infected at least twice increased from 4.5% to 45%. By 2014, almost half of the population had acquired heterotypic immunity. The probability of an epidemic increased sharply with the estimated fraction of susceptibles among children.

CONCLUSION/SIGNIFICANCE

By analysing 35 years of dengue data in French Polynesia, we characterised key factors affecting the dissemination profile and reporting of dengue cases in an epidemiological context simplified by mono-serotypic circulation. Our analysis provides key estimates that can inform the study of dengue in more complex settings where the co-circulation of multiple serotypes can greatly complicate inference.

Building an integrated serosurveillance platform to inform public health interventions: Insights from an experts' meeting on serum biomarkers

The use of biomarkers to measure immune responses in serum is crucial for understanding population-level exposure and susceptibility to human pathogens. Advances in sample collection, multiplex testing, and computational modeling are transforming serosurveillance into a powerful tool for public health program design and response to infectious threats. In July 2018, 70 scientists from 16 countries met to perform a landscape analysis of approaches that support an integrated serosurveillance platform, including the consideration of issues for successful implementation. Here, we summarize the group's insights and proposed roadmap for implementation, including objectives, technical requirements, ethical issues, logistical considerations, and monitoring and evaluation.

Predictable Chikungunya Infection Dynamics in Brazil

Chikungunya virus (CHIKV) was first imported into the Caribbean in 2013 and subsequently spread across the Americas. It has infected millions in the region and Brazil has become the hub of ongoing transmission. Using Seasonal Autoregressive Integrated Moving Average (SARIMA) models trained and validated on Brazilian data from the Ministry of Health’s notifiable diseases information system, we tested the hypothesis that transmission in Brazil had transitioned from sporadic and explosive to become more predictable. Consistency weighted, population standardized kernel density estimates were used to identify municipalities with the most consistent inter-annual transmission rates. Spatial clustering was assessed per calendar month for 2017−2021 inclusive using Moran’s I. SARIMA models were validated on 2020−2021 data and forecasted 106,162 (95%CI 27,303−200,917) serologically confirmed cases and 339,907 (95%CI 35,780−1035,449) total notifications for 2022−2023 inclusive, with >90% of cases in the Northeast and Southeast regions. Comparing forecasts for the first five months of 2022 to the most up-to-date ECDC report (published 2 June 2022) showed remarkable accuracy: the models predicted 92,739 (95%CI 20,685−195,191) case notifications during which the ECDC reported 92,349 case notifications. Hotspots of consistent transmission were identified in the states of Para and Tocantins (North region); Rio Grande do Norte, Paraiba and Pernambuco (Northeast region); and Rio de Janeiro and eastern Minas Gerais (Southeast region). Significant spatial clustering peaked during late summer/early autumn. This analysis highlights how CHIKV transmission in Brazil has transitioned, making it more predictable and thus enabling improved control targeting and site selection for trialing interventions.

Seroepidemiological Reconstruction of Long-term Chikungunya Virus Circulation in Burkina Faso and Gabon

Chikungunya virus (CHIKV) is a major public health concern worldwide. However, infection levels are rarely known, especially in Africa. We recruited individuals from Ouagadougou, Burkina Faso and Lambaréné, Gabon (age range, 1-55 years), tested their blood for CHIKV antibodies, and used serocatalytic models to reconstruct epidemiological histories. In Ouagadougou, 291 of 999 (29.1%) individuals were seropositive, ranging from 2% among those aged <10 years to 66% in those aged 40-55 years. We estimated there were 7 outbreaks since the 1970s but none since 2001, resulting in 600 000 infections in the city, none of which were reported. However, we could not definitively conclude whether infections were due to CHIKV or o'nyong-nyong, another alphavirus. In Lambaréné, 117 of 427 (27%) participants were seropositive. Our model identified a single outbreak sometime since 2007, consistent with the only reported CHIKV outbreak in the country. These findings suggest sporadic outbreaks in these settings and that the burden remains undetected or incorrectly attributed.

Household clustering supports a novel chemoprophylaxis trial design for a mosquito-borne viral disease

Infections because of chikungunya and other mosquito-borne viruses, such as dengue and Zika, represent an area of significant unmet medical need. There are currently no approved medicines for prophylaxis or treatment of these diseases, and the development and implementation of vaccines against these viruses have proved problematic. Although antiviral molecules with treatment and prophylactic potential against the chikungunya virus have been identified, no successful field trials have been reported. Chemoprophylaxis may be attractive for unvaccinated at-risk populations; however, performing a successful chemoprophylaxis trial during a chikungunya outbreak will require a clearly identifiable at-risk population. We propose the application of a household transmission model as used in testing drugs against respiratory viruses. Current evidence on household clustering of chikungunya and other Aedes mosquito-borne viral infections is supportive. We suggest that this model may improve prophylaxis trial feasibility and focus research and future treatment on a population likely to benefit.

Individual, household and community drivers of dengue virus infection risk in Kamphaeng Phet province, Thailand

Dengue virus (DENV) often circulates endemically. In such settings with high levels of transmission, it remains unclear whether there are risk factors that alter individual infection risk. We tested blood taken from individuals living in multigenerational households in Kamphaeng Phet province, Thailand for DENV antibodies (N = 2364, mean age 31y). Seropositivity ranged from 45.4% among those 1-5y to 99.5% for those >30y. Using spatially explicit catalytic models, we estimated 11.8% of the susceptible population gets infected annually. We found 37.5% of the variance in seropositivity was explained by unmeasured household-level effects with only 4.2% explained by spatial differences between households. The serostatus of individuals from the same household remained significantly correlated even when separated by up to 15 years in age. These findings show that despite highly endemic transmission, persistent differences in infection risk exist across households, the reasons for which remain unclear.

A protocol for a longitudinal, observational cohort study of infection and exposure to zoonotic and vector-borne diseases across a land-use gradient in Sabah, Malaysian Borneo: a socio-ecological systems approach

Introduction. Landscape changes disrupt environmental, social and biological systems, altering pathogen spillover and transmission risks. This study aims to quantify the impact of specific land management practices on spillover and transmission rates of zoonotic and vector-borne diseases within Malaysian Borneo. This protocol describes a cohort study with integrated ecological sampling to assess how deforestation and agricultural practices impact pathogen flow from wildlife and vector populations to human infection and detection by health facilities. This will focus on malaria, dengue and emerging arboviruses (Chikungunya and Zika), vector-borne diseases with varying contributions of simian reservoirs within this setting. Methods. A prospective longitudinal observational cohort study will be established in communities residing or working within the vicinity of the Stability of Altered Forest Ecosystems (SAFE) Project, a landscape gradient within Malaysian Borneo encompassing different plantation and forest types. The primary outcome of this study will be transmission intensity of selected zoonotic and vector-borne diseases, as quantified by changes in pathogen-specific antibody levels. Exposure will be measured using paired population-based serological surveys conducted at the beginning and end of the two-year cohort study. Secondary outcomes will include the distribution and infection rates of Aedes and Anopheles mosquito vectors, human risk behaviours and clinical cases reported to health facilities. Longitudinal data on human behaviour, contact with wildlife and GPS tracking of mobility patterns will be collected throughout the study period. This will be integrated with entomological surveillance to monitor densities and pathogen infection rates of Aedes and Anopheles mosquitoes relative to land cover. Within surrounding health clinics, continuous health facility surveillance will be used to monitor reported infections and febrile illnesses. Models will be developed to assess spillover and transmission rates relative to specific land management practices and evaluate abilities of surveillance systems to capture these risks.

Estimating the annual dengue force of infection from the age of reporting primary infections across urban centres in endemic countries

BACKGROUND

Stratifying dengue risk within endemic countries is crucial for allocating limited control interventions. Current methods of monitoring dengue transmission intensity rely on potentially inaccurate incidence estimates. We investigated whether incidence or alternate metrics obtained from standard, or laboratory, surveillance operations represent accurate surrogate indicators of the burden of dengue and can be used to monitor the force of infection (FOI) across urban centres.

METHODS

Among those who reported and resided in 13 cities across the Philippines, we collected epidemiological data from all dengue case reports between 2014 and 2017 (N 80,043) and additional laboratory data from a cross-section of sampled case reports (N 11,906) between 2014 and 2018. At the city level, we estimated the aggregated annual FOI from age-accumulated IgG among the non-dengue reporting population using catalytic modelling. We compared city-aggregated FOI estimates to aggregated incidence and the mean age of clinically and laboratory diagnosed dengue cases using Pearson's Correlation coefficient and generated predicted FOI estimates using regression modelling.

RESULTS

We observed spatial heterogeneity in the dengue average annual FOI across sampled cities, ranging from 0.054 [0.036-0.081] to 0.249 [0.223-0.279]. Compared to FOI estimates, the mean age of primary dengue infections had the strongest association (ρ -0.848, p value<0.001) followed by the mean age of those reporting with warning signs (ρ -0.642, p value 0.018). Using regression modelling, we estimated the predicted annual dengue FOI across urban centres from the age of those reporting with primary infections and revealed prominent spatio-temporal heterogeneity in transmission intensity.

CONCLUSIONS

We show the mean age of those reporting with their first dengue infection or those reporting with warning signs of dengue represent superior indicators of the dengue FOI compared to crude incidence across urban centres. Our work provides a framework for national dengue surveillance to routinely monitor transmission and target control interventions to populations most in need.

Ecology, evolution, and epidemiology of zoonotic and vector-borne infectious diseases in French Guiana: Transdisciplinarity does matter to tackle new emerging threats

French Guiana is a European ultraperipheric region located on the northern Atlantic coast of South America. It constitutes an important forested region for biological conservation in the Neotropics. Although very sparsely populated, with its inhabitants mainly concentrated on the Atlantic coastal strip and along the two main rivers, it is marked by the presence and development of old and new epidemic disease outbreaks, both research and health priorities. In this review paper, we synthetize 15 years of multidisciplinary and integrative research at the interface between wildlife, ecosystem modification, human activities and sociodemographic development, and human health. This study reveals a complex epidemiological landscape marked by important transitional changes, facilitated by increased interconnections between wildlife, land-use change and human occupation and activity, human and trade transportation, demography with substantial immigration, and identified vector and parasite pharmacological resistance. Among other French Guianese characteristics, we demonstrate herein the existence of more complex multi-host disease life cycles than previously described for several disease systems in Central and South America, which clearly indicates that today the greater promiscuity between wildlife and humans due to demographic and economic pressures may offer novel settings for microbes and their hosts to circulate and spread. French Guiana is a microcosm that crystallizes all the current global environmental, demographic and socioeconomic change conditions, which may favor the development of ancient and future infectious diseases.

Developments in statistical inference when assessing spatiotemporal disease clustering with the tau statistic

The tau statistic τ uses geolocation and, usually, symptom onset time to assess global spatiotemporal clustering from epidemiological data. We test different methods that could bias the clustering range estimate based on the statistic or affect its apparent precision, by comparison with a baseline analysis of an open access measles dataset. From re-analysing this data we find evidence against no clustering and no inhibition, p -value ∈ [ 0 , 0 ⋅ 022 ] (global envelope test). We develop a tau-specific modification of the Loh & Stein spatial bootstrap sampling method, which gives bootstrap tau estimates with 24% lower sampling error and a 110% higher estimated clustering endpoint than previously published (61⋅0 m vs. 29 m) and an equivalent increase in the clustering area of elevated disease odds by 342%. These differences could have important consequences for control efforts. Correct practice of graphical hypothesis testing of no clustering and clustering range estimation of the tau statistic are illustrated in the online Graphical abstract. We advocate proper implementation of this useful statistic, ultimately to reduce inaccuracies in control policy decisions made during disease clustering analysis.

Endemic and Epidemic Human Alphavirus Infections in Eastern Panama: An Analysis of Population-Based Cross-Sectional Surveys

Madariaga virus (MADV) has recently been associated with severe human disease in Panama, where the closely related Venezuelan equine encephalitis virus (VEEV) also circulates. In June 2017, a fatal MADV infection was confirmed in a community of Darien Province. We conducted a cross-sectional outbreak investigation with human and mosquito collections in July 2017, where sera were tested for alphavirus antibodies and viral RNA. In addition, by applying a catalytic, force-of-infection (FOI) statistical model to two serosurveys from Darien Province in 2012 and 2017, we investigated whether endemic or epidemic alphavirus transmission occurred historically. In 2017, MADV and VEEV IgM seroprevalences were 1.6% and 4.4%, respectively; IgG antibody prevalences were MADV: 13.2%, VEEV: 16.8%, Una virus (UNAV): 16.0%, and Mayaro virus: 1.1%. Active viral circulation was not detected. Evidence of MADV and UNAV infection was found near households, raising questions about its vectors and enzootic transmission cycles. Insomnia was associated with MADV and VEEV infections, depression symptoms were associated with MADV, and dizziness with VEEV and UNAV. Force-of-infection analyses suggest endemic alphavirus transmission historically, with recent increased human exposure to MADV and VEEV in Aruza and Mercadeo, respectively. The lack of additional neurological cases suggests that severe MADV and VEEV infections occur only rarely. Our results indicate that over the past five decades, alphavirus infections have occurred at low levels in eastern Panama, but that MADV and VEEV infections have recently increased-potentially during the past decade. Endemic infections and outbreaks of MADV and VEEV appear to differ spatially in some locations of eastern Panama.

A serological framework to investigate acute primary and post-primary dengue cases reporting across the Philippines

BACKGROUND

In dengue-endemic countries, targeting limited control interventions to populations at risk of severe disease could enable increased efficiency. Individuals who have had their first (primary) dengue infection are at risk of developing more severe secondary disease, thus could be targeted for disease prevention. Currently, there is no reliable algorithm for determining primary and post-primary (infection with more than one flavivirus) status from a single serum sample. In this study, we developed and validated an immune status algorithm using single acute serum samples from reporting patients and investigated dengue immuno-epidemiological patterns across the Philippines.

METHODS

During 2015/2016, a cross-sectional sample of 10,137 dengue case reports provided serum for molecular (anti-DENV PCR) and serological (anti-DENV IgM/G capture ELISA) assay. Using mixture modelling, we re-assessed IgM/G seroprevalence and estimated functional, disease day-specific, IgG:IgM ratios that categorised the reporting population as negative, historical, primary and post-primary for dengue. We validated our algorithm against WHO gold standard criteria and investigated cross-reactivity with Zika by assaying a random subset for anti-ZIKV IgM and IgG. Lastly, using our algorithm, we explored immuno-epidemiological patterns of dengue across the Philippines.

RESULTS

Our modelled IgM and IgG seroprevalence thresholds were lower than kit-provided thresholds. Individuals anti-DENV PCR+ or IgM+ were classified as active dengue infections (83.1%, 6998/8425). IgG- and IgG+ active dengue infections on disease days 1 and 2 were categorised as primary and post-primary, respectively, while those on disease days 3 to 5 with IgG:IgM ratios below and above 0.45 were classified as primary and post-primary, respectively. A significant proportion of post-primary dengue infections had elevated anti-ZIKV IgG inferring previous Zika exposure. Our algorithm achieved 90.5% serological agreement with WHO standard practice. Post-primary dengue infections were more likely to be older and present with severe symptoms. Finally, we identified a spatio-temporal cluster of primary dengue case reporting in northern Luzon during 2016.

CONCLUSIONS

Our dengue immune status algorithm can equip surveillance operations with the means to target dengue control efforts. The algorithm accurately identified primary dengue infections who are at risk of future severe disease.

Spatial modes for transmission of chikungunya virus during a large chikungunya outbreak in Italy: a modeling analysis

BACKGROUND

The spatial spread of many mosquito-borne diseases occurs by focal spread at the scale of a few hundred meters and over longer distances due to human mobility. The relative contributions of different spatial scales for transmission of chikungunya virus require definition to improve outbreak vector control recommendations.

METHODS

We analyzed data from a large chikungunya outbreak mediated by the mosquito Aedes albopictus in the Lazio region, Italy, consisting of 414 reported human cases between June and November 2017. Using dates of symptom onset, geographic coordinates of residence, and information from epidemiological questionnaires, we reconstructed transmission chains related to that outbreak.

RESULTS

Focal spread (within 1 km) accounted for 54.9% of all cases, 15.8% were transmitted at a local scale (1-15 km) and the remaining 29.3% were exported from the main areas of chikungunya circulation in Lazio to longer distances such as Rome and other geographical areas. Seventy percent of focal infections (corresponding to 38% of the total 414 cases) were transmitted within a distance of 200 m (the buffer distance adopted by the national guidelines for insecticide spraying). Two main epidemic clusters were identified, with a radius expanding at a rate of 300-600 m per month. The majority of exported cases resulted in either sporadic or no further transmission in the region.

CONCLUSIONS

Evidence suggest that human mobility contributes to seeding a relevant number of secondary cases and new foci of transmission over several kilometers. Reactive vector control based on current guidelines might allow a significant number of secondary clusters in untreated areas, especially if the outbreak is not detected early. Existing policies and guidelines for control during outbreaks should recommend the prioritization of preventive measures in neighboring territories with known mobility flows to the main areas of transmission.

A SIR-Poisson Model for COVID-19: Evolution and Transmission Inference in the Maghreb Central Regions

2019-nCoV is a virulent virus belonging to the coronavirus family that caused the new pneumonia (COVID-19) which has spread internationally very rapidly and has become pandemic. In this research paper, we set forward a statistical model called SIR-Poisson that predicts the evolution and the global spread of infectious diseases. The proposed SIR-Poisson model is able to predict the range of the infected cases in a future period. More precisely, it is used to infer the transmission of the COVID-19 in the three Maghreb Central countries (Tunisia, Algeria, and Morocco). Using the SIR-Poisson model and based on daily reported disease data, since its emergence until end April 2020, we attempted to predict the future disease period over 60 days. The estimated average number of contacts by an infected individual with others was around 2 for Tunisia and 3 for Algeria and Morocco. Relying on inferred scenarios, although the pandemic situation would tend to decline, it has not ended. From this perspective, the risk of COVID-19 spreading still exists after the deconfinement act. It is necessary, therefore, to carry on the containment until the estimated infected number achieves 0.

Seroepidemiologic Study Designs for Determining SARS-COV-2 Transmission and Immunity

Serologic studies are crucial for clarifying dynamics of the coronavirus disease pandemic. Past work on serologic studies (e.g., during influenza pandemics) has made relevant contributions, but specific conditions of the current situation require adaptation. Although detection of antibodies to measure exposure, immunity, or both seems straightforward conceptually, numerous challenges exist in terms of sample collection, what the presence of antibodies actually means, and appropriate analysis and interpretation to account for test accuracy and sampling biases. Successful deployment of serologic studies depends on type and performance of serologic tests, population studied, use of adequate study designs, and appropriate analysis and interpretation of data. We highlight key questions that serologic studies can help answer at different times, review strengths and limitations of different assay types and study designs, and discuss methods for rapid sharing and analysis of serologic data to determine global transmission of severe acute respiratory syndrome coronavirus 2.

Comparing insights from clinic-based versus community-based outbreak investigations: a case study of chikungunya in Bangladesh

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A healthcare facility-based investigation of an outbreak would have been limited.

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Clinic-based case identification in this chikungunya outbreak would only have identified a quarter of all cases.

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Community-based household investigation involving only case households revealed that cases were more likely to be female and had lower educational attainment.

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Community-based investigation involving all households additionally identified clothing that exposed both limbs and traveling outside the district as risk factors.

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Outbreak investigations that identify cases in community and enroll controls from across the community should be used for better understanding of the risk factors as well as community transmission estimates.

Background

Outbreak investigations typically focus their efforts on identifying cases that present at healthcare facilities. However, these cases rarely represent all cases in the wider community. In this context, community-based investigations may provide additional insight into key risk factors for infection, however, the benefits of these more laborious data collection strategies remains unclear.

Methods

We used different subsets of the data from a comprehensive outbreak investigation to compare the inferences we make in alternative investigation strategies.

Results

The outbreak investigation team interviewed 1,933 individuals from 460 homes. 364 (18%) of individuals had symptoms consistent with chikungunya. A theoretical clinic-based study would have identified 26% of the cases. Adding in community-based cases provided an overall estimate of the attack rate in the community. Comparison with controls from the same household revealed that those with at least secondary education had a reduced risk. Finally, enrolling residents from households across the community allowed us to characterize spatial heterogeneity of risk and identify the type of clothing usually worn and travel history as risk factors. This also revealed that household-level use of mosquito control was not associated with infection.

Conclusions

These findings highlight that while clinic-based studies may be easier to conduct, they only provide limited insight into the burden and risk factors for disease. Enrolling people who escaped from infection, both in the household and in the community allows a step change in our understanding of the spread of a pathogen and maximizes opportunities for control.

An open source tool to infer epidemiological and immunological dynamics from serological data: serosolver

We present a flexible, open source R package designed to obtain biological and epidemiological insights from serological datasets. Characterising past exposures for multi-strain pathogens poses a specific statistical challenge: observed antibody responses measured in serological assays depend on multiple unobserved prior infections that produce cross-reactive antibody responses. We provide a general modelling framework to jointly infer infection histories and describe immune responses generated by these infections using antibody titres against current and historical strains. We do this by linking latent infection dynamics with a mechanistic model of antibody kinetics that generates expected antibody titres over time. Our aim is to provide a flexible package to identify infection histories that can be applied to a range of pathogens. We present two case studies to illustrate how our model can infer key immunological parameters, such as antibody titre boosting, waning and cross-reaction, as well as latent epidemiological processes such as attack rates and age-stratified infection risk.

Pre-existing chikungunya virus neutralizing antibodies correlate with risk of symptomatic infection and subclinical seroconversion in a Philippine cohort

BACKGROUND

A longitudinal cohort study performed in Cebu City, Philippines found that the presence of pre-existing chikungunya virus (CHIKV) neutralizing antibodies (NAb) was associated with a decreased risk of symptomatic CHIKV infection. However, the relationship between pre-existing NAb and the risk of subclinical seroconversion has not been well described.

METHODS

Data were analyzed from a longitudinal cohort aged 6 months to 83 years who underwent active fever surveillance in Cebu City, Philippines from 2012 to 2014. Participants with a history of fever underwent acute and 3-week convalescent visits with blood collection, and annual visits at baseline, 12 months, and 24 months. Symptomatic CHIKV infections were detected by PCR of acute illness sera. Subclinical seroconversion was defined as a ≥8-fold rise in 80% plaque reduction neutralization test (PRNT80) titer between annual visits without intervening symptomatic infection.

RESULTS

Among 854 participants who completed the 12-month visit (year 1) and 765 who completed the 24-month visit (year 2), 25 symptomatic CHIKV infections and 104 subclinical seroconversions occurred among 615 individuals with no detectable pre-year NAb in year 1 and 444 in year 2, while no symptomatic infections and one subclinical seroconversion occurred in those with a pre-year PRNT80 titer ≥1:10. Pre-year PRNT80 titer ≥1:10 was associated with zero relative risk of symptomatic CHIKV infection and 0.018 risk of subclinical seroconversion.

CONCLUSIONS

The presence of detectable pre-existing CHIKV NAb correlated with a decreased risk of both symptomatic CHIKV infection and subclinical seroconversion. These findings support the potential use of CHIKV NAb titer as a surrogate endpoint of protection from infection for vaccine development.

Persistence and gender differences in protection against severe fever with thrombocytopaenia syndrome virus with natural infection: a 4-year follow-up and mathematical prediction study

Severe fever with thrombocytopaenia syndrome (SFTS) is an emerging infectious disease discovered in 2010 and has a case fatality as high as 30%. We intended to study the immune protection conferred by SFTS with natural infection. We collected and analysed 4-year follow-up data to study the characteristics of neutralising antibodies against SFTS virus (SFTSV). The 50% plaque reduction neutralisation test was used for the detection of neutralising antibodies against SFTSV. Geometric mean titres (GMTs) and proportions of patients with a protective titre were analysed, and the persistence of protection was predicted. The titre of antibodies declined yearly in the 4-year study period. Approximately 3 months after infection, the GMT was 143 (95% confidence interval (CI): 89–231), and 100% of patients had a protective titre. In the fourth year, the GMT declined to 53 (95% CI: 37–76), and 95% of patients had a protective titre. The titre was higher in females than in males. On average, the protection offered by neutralising antibodies against SFTSV could last as long as 9 years. The durations of protection were different for different initial titres. The characteristics of neutralising antibodies can be used as a reference for the vaccination doses and schedules of forthcoming vaccines.

Influence of herd immunity in the cyclical nature of arboviruses

We review and contrast the evidence for an effect of amplifying host herd immunity on circulation and human exposure to arboviruses. Herd immunity of short-lived West Nile virus avian amplifying hosts appears to play a limited role in levels of enzootic circulation and spillover infections of humans, which are not amplifiers. In contrast, herd immunity of nonhuman primate hosts for enzootic Zika, dengue, and chikungunya viruses is much stronger and appears to regulate to a large extent the periodicity of sylvatic amplification in Africa. Following the recent Zika and chikungunya pandemics, human herd immunity in the Americas quickly rose to ∼50% in many regions, although seroprevalence remains patchy. Modeling from decades of chikungunya circulation in Asia suggests that this level of herd immunity will suppress for many years major chikungunya and Zika epidemics in the Americas, followed by smaller outbreaks as herd immunity cycles with a periodicity of up to several decades.

Correlation of the basic reproduction number (R0) and eco-environmental variables in Colombian municipalities with chikungunya outbreaks during 2014-2016

Chikungunya virus (CHIKV) emerged in Colombia in 2014 into a population presumed fully susceptible. This resulted in a quick and intense spread across Colombia, resulting in an epidemic that affected an estimated 450,000 people. The reported Colombian cases accounted for over 49% of all the cases reported to the PAHO. Eco-environmental factors are known to be associated with the spread of arboviruses such as CHIKV, and likely contribute to the differences in transmission profiles that were observed across several municipalities. To determine the association of eco-environmental factors and CHIKV, the basic reproduction number (R₀) in 85 municipalities, which accounted for 65.6% of reported CHIKV cases in Colombia, was estimated. Estimates of R₀ ranged from 1 to 9, where over 76% of municipalities had R₀ values between 1 and 2. When we looked at the distribution of R₀, the cumulative proportions were 20% with R₀>2, 14% with R₀>3, and 9% with R₀>4. Next, we determined that there were different patterns of correlation between environmental and/or ecological variables and R₀ when we considered different R₀ lower-thresholds. Broadly, we found that temperature-related variables are significantly and positively correlated to R₀ regardless of the lower threshold, while other variables like duration of outbreak and size of the urban area are inversely related to R₀. Specifically, we conclude that high values of temperature-related variables where R₀ > 1 will result in a fast growth of cases in a shorter time period (with faster cessation of outbreak transmission) but will result overall in a fewer total cases compared to outbreak areas (R₀ > 1, but classified as lower). Thus, in the absence of vector control, a less explosive outbreak may be more advantageous for the virus in terms of transmission.

Chikungunya virus emerged in Colombia in 2014 into a presumed fully susceptible population and rapidly spread in the country. Numerous municipalities were differently affected by this virus across the country. The main purpose of this work was understanding why those differences were produced and, in turn, what are the variables addressing such differences. For this purpose, we estimated for 85 municipalities the basic reproduction number (R₀), a crucial parameter to understand epidemics that is expressed as the number of secondary cases produced by a primary case. Such parameter was correlated with numerous variables resulting evident a crucial role of temperature in the increase of R₀. Interestingly, other variables like size of the urban area and cases showed to be negatively correlated with R₀. Results shows that high temperatures produce high R₀, but those municipalities that showed high R₀ showed an explosive epidemic with faster increase of cases that ceased equally fast, so the duration of epidemic is short producing small amount of cases. In this way, more cases are expected with municipalities with lower values of R₀, which is suitably explained by the tortoise-hare model, where the less explosive outbreak results to be more advantageous for the virus.

Dengue serosurvey after a 2-month long outbreak in Nîmes, France, 2015: was there more than met the eye?

Clusters of dengue cases have recently become more frequent in areas of southern France colonised by the vector mosquito Aedes albopictus. In July 2015, a 2-month outbreak of dengue virus serotype 1 (DENV-1) was reported in Nîmes. Aim: We conducted a serosurvey in the affected area at the end of the vector activity period to determine the true extent of dengue transmission. Methods: We collected capillary blood from consenting household members, and information on their medical and travel histories, and exposure to mosquito bites. Recent infections were identified using IgM and IgG anti-DENV ELISA, followed, when positive, by plaque reduction neutralisation tests on serum against DENV 1–4 and West Nile virus. The prevalence estimator was calibrated on reference demographic data. We quantified the spatial clustering of dengue cases within the affected community and inferred the transmission tree. Results: The study participation rate was 39% (564/1,431). Three of 564 participants tested positive for DENV-1 infection (after marginal calibration, 0.41%; 95% confidence interval: 0.00–0.84). The spatial analysis showed that cases were clustered at the household level. Most participants perceived the presence of mosquitos as abundant (83%) and reported frequent mosquito bites (57%). We incidentally identified six past West Nile virus infections (0.9%; 95% CI: 0.2–1.6). Conclusion: This serosurvey confirms the potential for arboviral diseases to cause outbreaks − albeit limited for now − in France and Europe.

Differences in Prevalence of Symptomatic Zika Virus Infection, by Age and Sex-Puerto Rico, 2016

Background

During the outbreak of Zika virus (ZIKV) disease in Puerto Rico in 2016, nonpregnant women aged 20-39 years were disproportionately identified with ZIKV disease. We used household-based cluster investigations to determine whether this disparity was associated with age- or sex-dependent differences in the rate of ZIKV infection or reported symptoms.

Methods

Participation was offered to residents of households within a 100-m radius of the residences of a convenience sample of 19 laboratory-confirmed ZIKV disease cases. Participants answered a questionnaire and provided specimens for diagnostic testing by reverse transcription-polymerase chain reaction (RT-PCR) and enzyme-linked immunosorbent assay (ELISA).

Results

Among 367 study participants, 114 (31.1%) were laboratory positive for ZIKV infection, of whom 30% reported a recent illness (defined as self-reported rash or arthralgia) attributable to ZIKV infection. Age and sex were not associated with ZIKV infection. Female sex (adjusted prevalence ratio [aPR], 2.28; 95% confidence interval [CI], 1.40, 3.67), age <40 years (aPR, 2.39; 95% CI, 1.55, 3.70), and asthma (aPR, 1.63; 95% CI, 1.12, 2.37) were independently associated with symptomatic infection.

Conclusions

Although neither female sex nor age were associated with an increased prevalence of ZIKV infection, both were associated with symptomatic infection. Further investigation to identify a potential mechanism of age- and sex-dependent differences in reporting symptomatic ZIKV infection is warranted.

Opportunities for improved surveillance and control of dengue from age-specific case data

One of the challenges faced by global disease surveillance efforts is the lack of comparability across systems. Reporting commonly focuses on overall incidence, despite differences in surveillance quality between and within countries. For most immunizing infections, the age distribution of incident cases provides a more robust picture of trends in transmission. We present a framework to estimate transmission intensity for dengue virus from age-specific incidence data, and apply it to 359 administrative units in Thailand, Colombia, Brazil and Mexico. Our estimates correlate well with those derived from seroprevalence data (the gold standard), capture the expected spatial heterogeneity in risk, and correlate with known environmental drivers of transmission. We show how this approach could be used to guide the implementation of control strategies such as vaccination. Since age-specific counts are routinely collected by masany surveillance systems, they represent a unique opportunity to further our understanding of disease burden and risk for many diseases.

Quantifying bluetongue vertical transmission in French cattle from surveillance data

Bluetongue is a vector-borne disease of ruminants with economic consequences for the livestock industry. Bluetongue virus serotype 8 (BTV-8) caused a massive outbreak in Europe in 2006/2009 and re-emerged in France in 2015. Given the unprecedented epidemiological features of this serotype in cattle, the importance of secondary routes of transmission was reconsidered and transplacental transmission of BTV-8 was demonstrated in naturally and experimentally infected cattle. Here we used surveillance data from the on-going outbreak to quantify BTV-8 vertical transmission in French cattle. We used RT-PCR pre-export tests collected from June to December 2016 on the French territory and developed a catalytic model to disentangle vertical and vector-borne transmission. A series of in silico experiments validated the ability of our framework to quantify vertical transmission provided sufficient prevalence levels. By applying our model to an area selected accordingly, we estimated a probability of vertical transmission of 56% (55.8%, 95% credible interval 41.7–70.6) in unvaccinated heifers infected late in gestation. The influence of this high probability of vertical transmission on BTV-8 spread and persistence should be further investigated.

Nationally-representative serostudy of dengue in Bangladesh allows generalizable disease burden estimates

Serostudies are needed to answer generalizable questions on disease risk. However, recruitment is usually biased by age or location. We present a nationally-representative study for dengue from 70 communities in Bangladesh. We collected data on risk factors, trapped mosquitoes and tested serum for IgG. Out of 5866 individuals, 24% had evidence of historic infection, ranging from 3% in the north to >80% in Dhaka. Being male (aOR:1.8, [95%CI:1.5–2.0]) and recent travel (aOR:1.3, [1.1–1.8]) were linked to seropositivity. We estimate that 40 million [34.3–47.2] people have been infected nationally, with 2.4 million ([1.3–4.5]) annual infections. Had we visited only 20 communities, seropositivity estimates would have ranged from 13% to 37%, highlighting the lack of representativeness generated by small numbers of communities. Our findings have implications for both the design of serosurveys and tackling dengue in Bangladesh.

Dengue is a mosquito-borne virus that infects millions of people each year. Often the countries most affected by the virus, such as Bangladesh, do not have the resources needed to tackle the disease. For resources sent to these countries to have the greatest impact, it is important to know which areas are most affected, and which subsets of the population are most at risk. A way to gather this information is to test for dengue virus antibodies a protein produced by the immune system in response to the infection in the blood of individuals. However, previous efforts to use these tests to understand dengue risk in communities have generally only been done in single locations, typically a major city, and the findings of these tests are unlikely to be applicable to the wider population.

Now, Salje et al. have visited 70 different communities from all around Bangladesh and used these tests on blood samples collected from over 5,000 individuals from a range of age-groups. From these measurements it was estimated that an average 2.4 million people are infected with dengue each year in Bangladesh, with major cities, such as Dhaka, experiencing more concentrated levels. The exposure to dengue outside major cities was much lower, and men, who tend to travel more, were found to be at greater risk of infection.

Salje et al. also showed that using a small number of communities to estimate national levels of infection led to misleading results. This highlights the danger of using information collected from a limited number of places to represent the effects of a disease on the wider population.

Public health agencies in Bangladesh will be able to use this information to tackle dengue more effectively, focusing on the areas and the populations most affected by the disease. In addition, the design and analytical approaches used in this study could be applied to other countries, and to different diseases.

Genomic, epidemiological and digital surveillance of Chikungunya virus in the Brazilian Amazon

BACKGROUND

Since its first detection in the Caribbean in late 2013, chikungunya virus (CHIKV) has affected 51 countries in the Americas. The CHIKV epidemic in the Americas was caused by the CHIKV-Asian genotype. In August 2014, local transmission of the CHIKV-Asian genotype was detected in the Brazilian Amazon region. However, a distinct lineage, the CHIKV-East-Central-South-America (ECSA)-genotype, was detected nearly simultaneously in Feira de Santana, Bahia state, northeast Brazil. The genomic diversity and the dynamics of CHIKV in the Brazilian Amazon region remains poorly understood despite its importance to better understand the epidemiological spread and public health impact of CHIKV in the country.

METHODOLOGY/PRINCIPAL FINDINGS

We report a large CHIKV outbreak (5,928 notified cases between August 2014 and August 2018) in Boa vista municipality, capital city of Roraima's state, located in the Brazilian Amazon region. We generated 20 novel CHIKV-ECSA genomes from the Brazilian Amazon region using MinION portable genome sequencing. Phylogenetic analyses revealed that despite an early introduction of the Asian genotype in 2015 in Roraima, the large CHIKV outbreak in 2017 in Boa Vista was caused by an ECSA-lineage most likely introduced from northeastern Brazil. Epidemiological analyses suggest a basic reproductive number of R0 of 1.66, which translates in an estimated 39 (95% CI: 36 to 45) % of Roraima's population infected with CHIKV-ECSA. Finally, we find a strong association between Google search activity and the local laboratory-confirmed CHIKV cases in Roraima.

CONCLUSIONS/SIGNIFICANCE

This study highlights the potential of combining traditional surveillance with portable genome sequencing technologies and digital epidemiology to inform public health surveillance in the Amazon region. Our data reveal a large CHIKV-ECSA outbreak in Boa Vista, limited potential for future CHIKV outbreaks, and indicate a replacement of the Asian genotype by the ECSA genotype in the Amazon region.

Long-term circulation of Zika virus in Thailand: an observational study

BACKGROUND

Little is known about the historical and current risk of Zika virus infection in southeast Asia, where the mosquito vector is widespread and other arboviruses circulate endemically. Centralised Zika virus surveillance began in Thailand in January, 2016. We assessed the long-term circulation of Zika virus in Thailand.

METHODS

In this observational study, we analysed data from individuals with suspected Zika virus infection who presented at hospitals throughout the country and had biological samples (serum, plasma, or urine) tested for confirmation with PCR at the National Institute of Health laboratories in Bangkok. We analysed the spatial and age distribution of cases, and constructed time-resolved phylogenetic trees using genomes from Thailand and elsewhere to estimate when Zika virus was first introduced.

FINDINGS

Of the 3089 samples from 1717 symptomatic individuals tested between January, 2016, and December, 2017, 368 were confirmed to have Zika virus infection. Cases of Zika virus infection were reported throughout the year, and from 29 of the 76 Thai provinces. Individuals had 2·8 times (95% CI 2·3-3·6) the odds of testing positive for Zika virus infection if they came from the same district and were sick within the same year of a person with a confirmed infection relative to the odds of testing positive anywhere, consistent with focal transmission. The probability of cases being younger than 10 years was 0·99 times (0·72-1·30) the probability of being that age in the underlying population. This probability rose to 1·62 (1·33-1·92) among those aged 21-30 years and fell to 0·53 (0·40-0·66) for those older than 50 years. This age distribution is consistent with that observed in the Zika virus epidemic in Colombia. Phylogenetic reconstructions suggest persistent circulation within Thailand since at least 2002.

INTERPRETATION

Our evidence shows that Zika virus has circulated at a low but sustained level for at least 16 years, suggesting that Zika virus can adapt to persistent endemic transmission. Health systems need to adapt to cope with regular occurrences of the severe complications associated with infection.

FUNDING

European Research Council, National Science Foundation, and National Institutes of Health.

How Modelling Can Enhance the Analysis of Imperfect Epidemic Data

Mathematical models play an increasingly important role in our understanding of the transmission and control of infectious diseases. Here, we present concrete examples illustrating how mathematical models, paired with rigorous statistical methods, are used to parse data of different levels of detail and breadth and estimate key epidemiological parameters (e.g., transmission and its determinants, severity, impact of interventions, drivers of epidemic dynamics) even when these parameters are not directly measurable, when data are limited, and when the epidemic process is only partially observed. Finally, we assess the hurdles to be taken to increase availability and applicability of these approaches in an effort to ultimately enhance their public health impact.

Many data can be used to estimate the transmission potential of a pathogen, including descriptions of the transmission chains, human cluster sizes, sources of infection, and epidemic curves.

An important agenda in public health is understanding the impact of control methods. However, the dynamic nature of epidemics makes this task challenging. Models can disentangle the natural course of outbreaks from the effect of external factors.

In the absence of reliable surveillance data, models can reconstruct epidemic history by combining age-specific seroprevalence data with an understanding of the natural history of infection.

Mechanisms of immunity are hard to observe at an individual level, yet they affect population-level dynamics. Models can tease out such signatures.

Morbidity and mortality can be difficult to estimate when many infections are unobserved and severe infections are reported more often. Models can be used to correct for under-reporting and selection bias.

Local and regional dynamics of chikungunya virus transmission in Colombia: the role of mismatched spatial heterogeneity

BACKGROUND

Mathematical models of transmission dynamics are routinely fitted to epidemiological time series, which must inevitably be aggregated at some spatial scale. Weekly case reports of chikungunya have been made available nationally for numerous countries in the Western Hemisphere since late 2013, and numerous models have made use of this data set for forecasting and inferential purposes. Motivated by an abundance of literature suggesting that the transmission of this mosquito-borne pathogen is localized at scales much finer than nationally, we fitted models at three different spatial scales to weekly case reports from Colombia to explore limitations of analyses of nationally aggregated time series data.

METHODS

We adapted the recently developed Disease Transmission Kernel (DTK)-Dengue model for modeling chikungunya virus (CHIKV) transmission, given the numerous similarities of these viruses vectored by a common mosquito vector. We fitted versions of this model specified at different spatial scales to weekly case reports aggregated at different spatial scales: (1) single-patch national model fitted to national data; (2) single-patch departmental models fitted to departmental data; and (3) multi-patch departmental models fitted to departmental data, where the multiple patches refer to municipalities within a department. We compared the consistency of simulations from fitted models with empirical data.

RESULTS

We found that model consistency with epidemic dynamics improved with increasing spatial granularity of the model. Specifically, the sum of single-patch departmental model fits better captured national-level temporal patterns than did a single-patch national model. Likewise, multi-patch departmental model fits better captured department-level temporal patterns than did single-patch departmental model fits. Furthermore, inferences about municipal-level incidence based on multi-patch departmental models fitted to department-level data were positively correlated with municipal-level data that were withheld from model fitting.

CONCLUSIONS

Our model performed better when posed at finer spatial scales, due to better matching between human populations with locally relevant risk. Confronting spatially aggregated models with spatially aggregated data imposes a serious structural constraint on model behavior by averaging over epidemiologically meaningful spatial variation in drivers of transmission, impairing the ability of models to reproduce empirical patterns.

Using serological studies to reconstruct the history of bluetongue epidemic in French cattle under successive vaccination campaigns

Bluetongue virus is a vector-borne pathogen affecting ruminants that has caused major epidemics in France. Reconstructing the history of bluetongue in French cattle under control strategies such as vaccination has been hampered by the high level of sub-clinical infection, incomplete case data and poor understanding of vaccine uptake over time and space. To tackle these challenges, we used three age-structured serological surveys carried out in cattle (N = 22,342) from ten administrative subdivisions called departments. We fitted catalytic models within a Bayesian MCMC framework to reconstruct the force of seroconversion from infection or vaccination, and the population-level susceptibility per semester between 2007 and 2016. In the departments of the study area, we estimated that 36% of cattle had been infected prior to vaccine rollout that became compulsory from July 2008. The last outbreak case was notified in December 2009, at which time 83% of the animals were seropositive, under the cumulative effect of vaccination and infection. The probability of seroconversion per semester dropped below 10% after 2010 when vaccination became optional. Vaccine uptake was smaller during the 2012 campaign than during the one in 2011, with strong regional contrasts. Eighty four percent of cattle were susceptible when bluetongue re-emerged in 2015. Thus, serological surveys can be used to estimate vaccine uptake and the magnitude of infection, the relative effect of which can sometimes be inferred using prior knowledge on reported incidence and vaccination dates.

Evidence of previous but not current transmission of chikungunya virus in southern and central Vietnam: Results from a systematic review and a seroprevalence study in four locations

BACKGROUND

Arbovirus infections are a serious concern in tropical countries due to their high levels of transmission and morbidity. With the outbreaks of chikungunya (CHIKV) in surrounding regions in recent years and the fact that the environment in Vietnam is suitable for the vectors of CHIKV, the possibility of transmission of CHIKV in Vietnam is of great interest. However, information about CHIKV activity in Vietnam remains limited.

METHODOLOGY

In order to address this question, we performed a systematic review of CHIKV in Vietnam and a CHIKV seroprevalence survey. The seroprevalence survey tested for CHIKV IgG in population serum samples from individuals of all ages in 2015 from four locations in Vietnam.

PRINCIPAL FINDINGS

The four locations were An Giang province (n = 137), Ho Chi Minh City (n = 136), Dak Lak province (n = 137), and Hue City (n = 136). The findings give us evidence of some CHIKV activity: 73/546 of overall samples were seropositive (13.4%). The age-adjusted seroprevalences were 12.30% (6.58-18.02), 13.42% (7.16-19.68), 7.97% (3.56-12.38), and 3.72% (1.75-5.69) in An Giang province, Ho Chi Minh City, Dak Lak province, and Hue City respectively. However, the age-stratified seroprevalence suggests that the last transmission ended around 30 years ago, consistent with results from the systematic review. We see no evidence for on-going transmission in three of the locations, though with some evidence of recent exposure in Dak Lak, most likely due to transmission in neighbouring countries. Before the 1980s, when transmission was occurring, we estimate on average 2-4% of the population were infected each year in HCMC and An Giang and Hue (though transmision ended earlier in Hue). We estimate lower transmission in Dak Lak, with around 1% of the population infected each year.

CONCLUSION

In conclusion, we find evidence of past CHIKV transmission in central and southern Vietnam, but no evidence of recent sustained transmission. When transmission of CHIKV did occur, it appeared to be widespread and affect a geographically diverse population. The estimated susceptibility of the population to chikungunya is continually increasing, therefore the possibility of future CHIKV transmission in Vietnam remains.

The potential impact of case-area targeted interventions in response to cholera outbreaks: A modeling study

BACKGROUND

Cholera prevention and control interventions targeted to neighbors of cholera cases (case-area targeted interventions [CATIs]), including improved water, sanitation, and hygiene, oral cholera vaccine (OCV), and prophylactic antibiotics, may be able to efficiently avert cholera cases and deaths while saving scarce resources during epidemics. Efforts to quickly target interventions to neighbors of cases have been made in recent outbreaks, but little empirical evidence related to the effectiveness, efficiency, or ideal design of this approach exists. Here, we aim to provide practical guidance on how CATIs might be used by exploring key determinants of intervention impact, including the mix of interventions, "ring" size, and timing, in simulated cholera epidemics fit to data from an urban cholera epidemic in Africa.

METHODS AND FINDINGS

We developed a micro-simulation model and calibrated it to both the epidemic curve and the small-scale spatiotemporal clustering pattern of case households from a large 2011 cholera outbreak in N'Djamena, Chad (4,352 reported cases over 232 days), and explored the potential impact of CATIs in simulated epidemics. CATIs were implemented with realistic logistical delays after cases presented for care using different combinations of prophylactic antibiotics, OCV, and/or point-of-use water treatment (POUWT) starting at different points during the epidemics and targeting rings of various radii around incident case households. Our findings suggest that CATIs shorten the duration of epidemics and are more resource-efficient than mass campaigns. OCV was predicted to be the most effective single intervention, followed by POUWT and antibiotics. CATIs with OCV started early in an epidemic focusing on a 100-m radius around case households were estimated to shorten epidemics by 68% (IQR 62% to 72%), with an 81% (IQR 69% to 87%) reduction in cases compared to uncontrolled epidemics. These same targeted interventions with OCV led to a 44-fold (IQR 27 to 78) reduction in the number of people needed to target to avert a single case of cholera, compared to mass campaigns in high-cholera-risk neighborhoods. The optimal radius to target around incident case households differed by intervention type, with antibiotics having an optimal radius of 30 m to 45 m compared to 70 m to 100 m for OCV and POUWT. Adding POUWT or antibiotics to OCV provided only marginal impact and efficiency improvements. Starting CATIs early in an epidemic with OCV and POUWT targeting those within 100 m of an incident case household reduced epidemic durations by 70% (IQR 65% to 75%) and the number of cases by 82% (IQR 71% to 88%) compared to uncontrolled epidemics. CATIs used late in epidemics, even after the peak, were estimated to avert relatively few cases but substantially reduced the number of epidemic days (e.g., by 28% [IQR 15% to 45%] for OCV in a 100-m radius). While this study is based on a rigorous, data-driven approach, the relatively high uncertainty about the ways in which POUWT and antibiotic interventions reduce cholera risk, as well as the heterogeneity in outbreak dynamics from place to place, limits the precision and generalizability of our quantitative estimates.

CONCLUSIONS

In this study, we found that CATIs using OCV, antibiotics, and water treatment interventions at an appropriate radius around cases could be an effective and efficient way to fight cholera epidemics. They can provide a complementary and efficient approach to mass intervention campaigns and may prove particularly useful during the initial phase of an outbreak, when there are few cases and few available resources, or in order to shorten the often protracted tails of cholera epidemics.

Seroprevalence of antibodies against chikungunya virus in Singapore resident adult population

Objectives

We determined the seroprevalence of chikungunya virus (CHIKV) infection in the adult resident population in Singapore following local outbreaks of chikungunya fever (CHIKF) in 2008–2009.

Methods

Our cross-sectional study involved residual sera from 3,293 adults aged 18–79 years who had participated in the National Health Survey in 2010. Sera were tested for IgG antibodies against CHIKV and dengue virus (DENV) and neutralizing antibodies against CHIKV.

Results

The prevalence of CHIKV-neutralizing antibodies among Singapore residents aged 18–79 years was 1.9% (95% confidence interval: 1.4%– 2.3%). The CHIKV seroprevalence was highest in the elderly aged 70–79 years at 11.5%, followed by those aged 30–39 years at 3.1%. Men had significantly higher CHIKV seroprevalence than women (2.5% versus 1.3%, p = 0.01). Among the three main ethnic groups, Indians had the highest seroprevalence (3.5%) compared to Chinese (1.6%) and Malays (0.7%) (p = 0.02 and p = 0.01, respectively). Multivariable logistic regression identified adults aged 30–39 years and 70–79 years, men, those of Indian ethnicity and ethnic minority groups, and residence on ground floor of public and private housing apartments as factors that were significantly associated with a higher likelihood of exposure to CHIKV. The overall prevalence of anti-DENV IgG antibodies was 56.8% (95% CI: 55.1%– 58.5%), while 1.5% (95% CI: 1.1%– 2.0%) of adults possessed both neutralizing antibodies against CHIKV and IgG antibodies against DENV.

Conclusions

Singapore remains highly susceptible to CHIKV infection. There is a need to maintain a high degree of vigilance through disease surveillance and vector control. Findings from such serological study, when conducted on a regular periodic basis, could supplement surveillance to provide insights on CHIKV circulation in at-risk population.

The prevalence of neutralizing antibodies against chikungunya virus (CHIKV) was low at 1.9% among resident adults in Singapore after local outbreaks in 2008–2009. Adults aged 30–39 years and 70–79 years, men, those of Indian ethnicity and ethnic minority groups, and residence on ground floor of public and private housing apartments were significantly associated with a higher likelihood of exposure to CHIKV.

Development and evaluation of one-step multiplex real-time RT-PCR assay for simultaneous detection of Zika virus and Chikungunya virus

Zika virus (ZIKV) and chikungunya virus (CHIKV) are important human pathogens and mosquito-borne arboviruses, which have resembling history, common vectors, circulating regions, and indistinguishable clinical symptoms. Wide geographical range that is suitable for ZIKV and CHIKV transmission underlines the concern about the impact of epidemic and endemic infections on burden of public health. In the present study, a highly sensitive and specific one-step multiplex real-time RT-PCR assay was developed and evaluated for simultaneous detection and quantification of ZIKV and CHIKV. The single reaction assay employs two pairs of primers and two TaqMan probes that differentiate ZIKV and CHIKV infections. The entire viral genomic RNA in vitro transcribed from full-length infectious clones were used to generate the standard curves for absolute quantification in subsequent tests. The detection limit of the one-step multiplex assay was 1 and 0.5 PFU for infectious ZIKV and CHIKV, respectively. The assessment of specificity indicated this assay is highly specific to targeted viruses showing no amplification of a variety of other flaviviruses. Our assay was able to detect geographically separated and phylogenetically diverse strains of ZIKV and CHIKV. On the applicability of monitoring viral multiplication in cells and testing clinical samples, the one-step multiplex assay provided efficient and accurate determination. The one-step multiplex real-time RT-PCR assay offers a valuable tool for detection of ZIKV and CHIKV and potentially contributes to general surveillance and clinical treatment.

The Bridges and Blockades to Evolutionary Convergence on the Road to Predicting Chikungunya Virus Evolution

Chikungunya virus, first isolated in the 1950s, has since reemerged to cause several epidemics and millions of infections throughout the world. What was once blurred and confused with dengue virus in both diagnosis and name has since become one of the best-characterized arboviral diseases. In this review, we cover the history of this virus, its evolution into distinct genotypes and lineages, and, most notably, the convergent evolution observed in recent years. We highlight research that reveals to what extent convergent evolution, and its inherent predictability, may occur and what genetic or environmental factors may hinder it.

Assessing the population at risk of Zika virus in Asia - is the emergency really over?

On November 18, 2016, the WHO ended its designation of the Zika virus (ZIKV) epidemic as a Public Health Emergency of International Concern (PHEIC). At the same time, ZIKV transmission continues in Asia, with the number of Asian countries reporting Zika cases increasing over the last 2 years. Applying a method that combines epidemiological theory with data on epidemic size and drivers of transmission, we characterised the population at risk of ZIKV infection from Aedes aegypti mosquitoes in 15 countries in Asia. Projections made under the assumption of no pre-existing immunity suggest that up to 785 (range: 730-992) million people in Asia would be at risk of ZIKV infection under that scenario. Assuming that 20% of ZIKV infections are symptomatic, this implies an upper limit of 146-198 million for the population at risk of a clinical episode of Zika. Due to limited information about pre-existing immunity to ZIKV in the region, we were unable to make specific numerical projections under a more realistic assumption about pre-existing immunity. Even so, combining numerical projections under an assumption of no pre-existing immunity together with theoretical insights about the extent to which pre-existing immunity may lower epidemic size, our results suggest that the population at risk of ZIKV infection in Asia could be even larger than in the Americas. As a result, we conclude that the WHO's removal of the PHEIC designation should not be interpreted as an indication that the threat posed by ZIKV has subsided.

Host outdoor exposure variability affects the transmission and spread of Zika virus: Insights for epidemic control

BACKGROUND

Zika virus transmission dynamics in urban environments follow a complex spatiotemporal pattern that appears unpredictable and barely related to high mosquito density areas. In this context, human activity patterns likely have a major role in Zika transmission dynamics. This paper examines the effect of host variability in the amount of time spent outdoors on Zika epidemiology in an urban environment.

METHODOLOGY/PRINCIPAL FINDINGS

First, we performed a survey on time spent outdoors by residents of Miami-Dade County, Florida. Second, we analyzed both the survey and previously published national data on outdoors time in the U.S. to provide estimates of the distribution of the time spent outdoors. Third, we performed a computational modeling evaluation of Zika transmission dynamics, based on the time spent outdoors by each person. Our analysis reveals a strong heterogeneity of the host population in terms of time spent outdoors-data are well captured by skewed gamma distributions. Our model-based evaluation shows that in a heterogeneous population, Zika would cause a lower number of infections than in a more homogenous host population (up to 4-fold differences), but, at the same time, the epidemic would spread much faster. We estimated that in highly heterogeneous host populations the timing of the implementation of vector control measures is the major factor for limiting the number of Zika infections.

CONCLUSIONS/SIGNIFICANCE

Our findings highlight the need of considering host variability in exposure time for managing mosquito-borne infections and call for the revision of the triggers for vector control strategies, which should integrate mosquito density data and human outdoor activity patterns in specific areas.

Epidemiological and ecological determinants of Zika virus transmission in an urban setting

The Zika virus has emerged as a global public health concern. Its rapid geographic expansion is attributed to the success of Aedes mosquito vectors, but local epidemiological drivers are still poorly understood. Feira de Santana played a pivotal role in the Chikungunya epidemic in Brazil and was one of the first urban centres to report Zika infections. Using a climate-driven transmission model and notified Zika case data, we show that a low observation rate and high vectorial capacity translated into a significant attack rate during the 2015 outbreak, with a subsequent decline in 2016 and fade-out in 2017 due to herd-immunity. We find a potential Zika-related, low risk for microcephaly per pregnancy, but with significant public health impact given high attack rates. The balance between the loss of herd-immunity and viral re-importation will dictate future transmission potential of Zika in this urban setting.

Mosquitoes can transmit viruses that cause Zika, dengue and several other tropical diseases that affect humans. Zika virus usually causes mild symptoms, but it is thought that infection during pregnancy can lead to brain abnormalities, including microcephaly, where babies are born with an abnormally small head. Recent studies have shed light on how the Zika virus spread from Africa to reach South America, the Caribbean and North America. However, much less is known about the ecological factors that contribute to the spread of the virus within towns, cities and other local areas.

In 2015, Brazil was struck by an outbreak of the Zika virus that led to an international public health emergency. Lourenço et al. used a mathematical model to explore the local conditions within Feira de Santana (a major urban center in Brazil) that contributed to the outbreak. The model took into account numerous factors, including temperature, humidity, rainfall and the mosquito life-cycle, which made it possible to reconstruct the history of the virus over the past three years and to make projections for the next decades.

It revealed that most of the infections occured during 2015, with approximately 65% of the population infected. The incidences of new infections declined in 2016, as increasing numbers of local people had already been exposed to the virus and became immune. Temperature and humidity appeared to have played a critical role in sustaining the mosquito population carrying the Zika virus.

Further analysis suggests that the risk of Zika virus causing microcephaly is very low – only 0.3–0.5% of the pregnant women in Feira de Santana who were infected with Zika gave birth to a baby with the condition. What therefore makes Zika a public health concern is the combination of a low risk with very high infection rates, which can affect a large number of pregnancies.

This study will help researchers and policy makers to predict how the Zika virus will behave in the coming years. It also highlights the limitations and successes of the current system of surveillance. Moreover, it will help to identify critical time periods in the year when mosquito control strategies should be implemented to limit the spread of this virus. In future, this could help shape new local strategies to control Zika virus, dengue and other diseases carried by mosquitoes.