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

Reconciling heterogeneous dengue virus infection risk estimates from different study designs

Uncovering rates at which susceptible individuals become infected with a pathogen, i.e. the force of infection (FOI), is essential for assessing transmission risk and reconstructing distribution of immunity in a population. For dengue, reconstructing exposure and susceptibility statuses from the measured FOI is of particular significance as prior exposure is a strong risk factor for severe disease. FOI can be measured via many study designs. Longitudinal serology are considered gold standard measurements, as they directly track the transition of seronegative individuals to seropositive due to incident infections (seroincidence). Cross-sectional serology can provide estimates of FOI by contrasting seroprevalence across ages. Age of reported cases can also be used to infer FOI. Agreement of these measurements, however, have not been assessed. Using 26 years of data from cohort studies and hospital-attended cases from Kamphaeng Phet province, Thailand, we found FOI estimates from the three sources to be highly inconsistent. Annual FOI estimates from seroincidence was 2.46 to 4.33-times higher than case-derived FOI. Correlation between seroprevalence-derived and case-derived FOI was moderate (correlation coefficient=0.46) and no systematic bias. Through extensive simulations and theoretical analysis, we show that incongruences between methods can result from failing to account for dengue antibody kinetics, assay noise, and heterogeneity in FOI across ages. Extending standard inference models to include these processes reconciled the FOI and susceptibility estimates. Our results highlight the importance of comparing inferences across multiple data types to uncover additional insights not attainable through a single data type/analysis.

Age-specific case data reveal varying dengue transmission intensity in US states and territories

Dengue viruses (DENV) are endemic in the US territories of Puerto Rico, American Samoa, and the US Virgin Islands, with focal outbreaks also reported in the states of Florida and Hawaii. However, little is known about the intensity of dengue virus transmission over time and how dengue viruses have shaped the level of immunity in these populations, despite the importance of understanding how and why levels of immunity against dengue may change over time. These changes need to be considered when responding to future outbreaks and enacting dengue management strategies, such as guiding vaccine deployment. We used catalytic models fitted to case surveillance data stratified by age from the ArboNET national arboviral surveillance system to reconstruct the history of recent dengue virus transmission in Puerto Rico, American Samoa, US Virgin Islands, Florida, Hawaii, and Guam. We estimated average annual transmission intensity (i.e., force of infection) of DENV between 2010 and 2019 and the level of seroprevalence by age group in each population. We compared models and found that assuming all reported cases are secondary infections generally fit the surveillance data better than assuming all cases are primary infections. Using the secondary case model, we found that force of infection was highly heterogeneous between jurisdictions and over time within jurisdictions, ranging from 0.00008 (95% CrI: 0.00002-0.0004) in Florida to 0.08 (95% CrI: 0.044-0.14) in American Samoa during the 2010-2019 period. For early 2020, we estimated that seropositivity in 10 year-olds ranged from 0.09% (0.02%-0.54%) in Florida to 56.3% (43.7%-69.3%) in American Samoa. In the absence of serological data, age-specific case notification data collected through routine surveillance combined with mathematical modeling are powerful tools to monitor arbovirus circulation, estimate the level of population immunity, and design dengue management strategies.

Age-time-specific transmission of hand-foot-and-mouth disease enterovirus serotypes in Vietnam: A catalytic model with maternal immunity

Hand, foot and mouth disease (HFMD) is highly prevalent in the Asia Pacific region, particularly in Vietnam. To develop effective interventions and efficient vaccination programs, we inferred the age-time-specific transmission patterns of HFMD serotypes enterovirus A71 (EV-A71), coxsackievirus A6 (CV-A6), coxsackievirus A10 (CV-A10), coxsackievirus A16 (CV-A16) in Ho Chi Minh City, Vietnam from a case data collected during 2013-2018 and a serological survey data collected in 2015 and 2017. We proposed a catalytic model framework with good adaptability to incorporate maternal immunity using various mathematical functions. Our results indicate the high-level transmission of CV-A6 and CV-A10 which is not obvious in the case data, due to the variation of disease severity across serotypes. Our results provide statistical evidence supporting the strong association between severe illness and CV-A6 and EV-A71 infections. The HFMD dynamic pattern presents a cyclical pattern with large outbreaks followed by a decline in subsequent years. Additionally, we identify the age group with highest risk of infection as 1-2 years and emphasise the risk of future outbreaks as over 50% of children aged 6-7 years were estimated to be susceptible to CV-A16 and EV-A71. Our study highlights the importance of multivalent vaccines and active surveillance for different serotypes, supports early vaccination prior to 1 year old, and points out the potential utility for vaccinating children older than 5 years old in Vietnam.

Dengue

Dengue, caused by four closely related viruses, is a growing global public health concern, with outbreaks capable of overwhelming health-care systems and disrupting economies. Dengue is endemic in more than 100 countries across tropical and subtropical regions worldwide, and the expanding range of the mosquito vector, affected in part by climate change, increases risk in new areas such as Spain, Portugal, and the southern USA, while emerging evidence points to silent epidemics in Africa. Substantial advances in our understanding of the virus, immune responses, and disease progression have been made within the past decade. Novel interventions have emerged, including partially effective vaccines and innovative mosquito control strategies, although a reliable immune correlate of protection remains a challenge for the assessment of vaccines. These developments mark the beginning of a new era in dengue prevention and control, offering promise in addressing this pressing global health issue.

Increasing transmission of dengue virus across ecologically diverse regions of Ecuador and associated risk factors

The distribution and intensity of viral diseases transmitted by Aedes aegypti mosquitoes, including dengue, have rapidly increased over the last century. Here, we study dengue virus (DENV) transmission across the ecologically and demographically distinct regions or Ecuador. We analyzed province-level age-stratified dengue incidence data from 2000-2019 using catalytic models to estimate the force of infection of DENV over eight decades. We found that provinces established endemic DENV transmission at different time periods. Coastal provinces with the largest and most connected cities had the earliest and highest increase in DENV transmission, starting around 1980 and continuing to the present. In contrast, remote and rural areas with reduced access, like the northern coast and the Amazon regions, experienced a rise in DENV transmission and endemicity only in the last 10 to 20 years. The newly introduced chikungunya and Zika viruses have age-specific distributions of hospital-seeking cases consistent with recent emergence across all provinces. To evaluate factors associated with geographic differences in DENV transmission potential, we modeled DENV vector risk using 11,693 Aedes aegypti presence points to the resolution of 1 hectare. In total, 56% of the population of Ecuador, including in provinces identified as having increasing DENV transmission in our models, live in areas with high risk of Aedes aegypti, with population size, trash collection, elevation, and access to water as important determinants. Our investigation serves as a case study of the changes driving the expansion of DENV and other arboviruses globally and suggest that control efforts should be expanded to semi-urban and rural areas and to historically isolated regions to counteract increasing dengue outbreaks.

Global health concern on the rising dengue and chikungunya cases in the American regions: Countermeasures and preparedness

Background and Aim

Severe morbidity and mortality due to seasonal infectious diseases are common global public health issues. Vector-borne viral illnesses like dengue and chikungunya overload the healthcare systems leading to critical financial burden to manage them. There is no effective drug or vaccine currently available to control these two diseases.

Methods

The review was formulated by incorporating relevant reports on chikungunya and dengue in the Americas regions through a comprehensive search of literature that were available on dedicated scientific publication portals such as PubMed, ScienceDirect, and Web of Science.

Results

The strategies of public health administrations to control largely the mosquito vectors during tropical monsoon seem to be effective. Yet, it seems practically impossible to completely eliminate them. The mosquito vector disseminates the virus via transovarian route thereby internalising the virus through generations, a reason behind reappearing and recurring outbreaks. The numerous factors associated with industrialisation, urbanisation, population density, and easy transboundary movements appear to have contributed to the spread of vectors from an endemic region to elsewhere.

Conclusion

The article made a state-of-affair comprehensive analysis of the rising dengue and chikungunya cases in the tropics, particularly the tropical Americas, as a human health concern, the countermeasures undertaken and the overall preparedness. The viral transmission is a hard situation to tackle as the vector survives in diverse temperature and ecology, is resistant to insecticides, and the unavailability of drugs. Better vector-control measures and improved understanding of the reemerging arboviral infections could offer an extended reaction time to counter outbreaks, and minimise associated morbidity/mortality.

A simulation-based method to inform serosurvey design for estimating the force of infection using existing blood samples

The extent to which dengue virus has been circulating globally and especially in Africa is largely unknown. Testing available blood samples from previous cross-sectional serological surveys offers a convenient strategy to investigate past dengue infections, as such serosurveys provide the ideal data to reconstruct the age-dependent immunity profile of the population and to estimate the average per-capita annual risk of infection: the force of infection (FOI), which is a fundamental measure of transmission intensity. In this study, we present a novel methodological approach to inform the size and age distribution of blood samples to test when samples are acquired from previous surveys. The method was used to inform SERODEN, a dengue seroprevalence survey which is currently being conducted in Ghana among other countries utilizing samples previously collected for a SARS-CoV-2 serosurvey. The method described in this paper can be employed to determine sample sizes and testing strategies for different diseases and transmission settings.

Convergent trends and spatiotemporal patterns of Aedes-borne arboviruses in Mexico and Central America

BACKGROUND

Aedes-borne arboviruses cause both seasonal epidemics and emerging outbreaks with a significant impact on global health. These viruses share mosquito vector species, often infecting the same host population within overlapping geographic regions. Thus, comparative analyses of the virus evolutionary and epidemiological dynamics across spatial and temporal scales could reveal convergent trends.

METHODOLOGY/PRINCIPAL FINDINGS

Focusing on Mexico as a case study, we generated novel chikungunya and dengue (CHIKV, DENV-1 and DENV-2) virus genomes from an epidemiological surveillance-derived historical sample collection, and analysed them together with longitudinally-collected genome and epidemiological data from the Americas. Aedes-borne arboviruses endemically circulating within the country were found to be introduced multiple times from lineages predominantly sampled from the Caribbean and Central America. For CHIKV, at least thirteen introductions were inferred over a year, with six of these leading to persistent transmission chains. For both DENV-1 and DENV-2, at least seven introductions were inferred over a decade.

CONCLUSIONS/SIGNIFICANCE

Our results suggest that CHIKV, DENV-1 and DENV-2 in Mexico share evolutionary and epidemiological trajectories. The southwest region of the country was determined to be the most likely location for viral introductions from abroad, with a subsequent spread into the Pacific coast towards the north of Mexico. Virus diffusion patterns observed across the country are likely driven by multiple factors, including mobility linked to human migration from Central towards North America. Considering Mexico's geographic positioning displaying a high human mobility across borders, our results prompt the need to better understand the role of anthropogenic factors in the transmission dynamics of Aedes-borne arboviruses, particularly linked to land-based human migration.

Previous Dengue Infection among Children in Puerto Rico and Implications for Dengue Vaccine Implementation

Limited dengue virus (DENV) seroprevalence estimates are available for Puerto Rico, which are needed to inform the potential use and cost-effectiveness of DENV vaccines. The Communities Organized to Prevent Arboviruses (COPA) is a cohort study initiated in 2018 in Ponce, Puerto Rico, to assess arboviral disease risk and provide a platform to evaluate interventions. We recruited participants from households in 38 study clusters, who were interviewed and provided a serum specimen. Specimens from 713 children aged 1 to 16 years during the first year of COPA were tested for the four DENV serotypes and ZIKV using a focus reduction neutralization assay. We assessed the seroprevalence of DENV and ZIKV by age and developed a catalytic model from seroprevalence and dengue surveillance data to estimate the force of infection for DENV during 2003-2018. Overall, 37% (n = 267) were seropositive for DENV; seroprevalence was 9% (11/128) among children aged 1 to 8 years and 44% (256/585) among children aged 9 to 16 years, exceeding the threshold over which DENV vaccination is deemed cost-effective. A total of 33% were seropositive for ZIKV, including 15% among children aged 0 to 8 years and 37% among children aged 9 to 16 years. The highest force of infection occurred in 2007, 2010, and 2012-2013, with low levels of transmission from 2016 to 2018. A higher proportion of children had evidence of multitypic DENV infection than expected, suggesting high heterogeneity in DENV risk in this setting.

Increasing transmission of dengue virus across ecologically diverse regions of Ecuador and associated risk factors

The distribution and intensity of viral diseases transmitted by Aedes aegypti mosquitoes, including dengue, have rapidly increased over the last century. Ecuador is an interesting country to study drivers of dengue virus (DENV) transmission given it has multiple ecologically and demographically distinct regions. Here, we analyze province-level age-stratified dengue prevalence data from 2000-2019 using catalytic models to estimate the force of infection of DENV over eight decades and across provinces in Ecuador. We found that provinces established endemic DENV transmission at different time periods. Coastal provinces with the largest and most connected cities had the earliest and highest increase in DENV transmission, starting around 1980 and continuing to the present. In contrast, remote and rural areas with reduced access, like the northern coast and the Amazon regions, experienced a rise in DENV transmission and endemicity only in the last 10 to 20 years. The newly introduced chikungunya and Zika viruses have distinct age-specific prevalence distributions consistent with recent emergence across all provinces. We evaluated factors to the resolution of 1 hectare associated with geographic differences in vector suitability and arbovirus disease in the last 10 years by modeling 11,693 A aegypti presence points and 73,550 arbovirus cases. In total, 56% of the population of Ecuador lives in areas with high risk of Aedes aegypti. Most suitable provinces had hotspots for arbovirus disease risk, with population size, elevation, sewage connection, trash collection, and access to water as important determinants. Our investigation serves as a case study of the changes driving the expansion of DENV and other arboviruses globally and suggest that control efforts should be expanded to semi-urban and rural areas and to historically isolated regions to counteract increasing dengue outbreaks.

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.

Estimating dengue transmission intensity from serological data: A comparative analysis using mixture and catalytic models

Background

Dengue virus (DENV) infection is a global health concern of increasing magnitude. To target intervention strategies, accurate estimates of the force of infection (FOI) are necessary. Catalytic models have been widely used to estimate DENV FOI and rely on a binary classification of serostatus as seropositive or seronegative, according to pre-defined antibody thresholds. Previous work has demonstrated the use of thresholds can cause serostatus misclassification and biased estimates. In contrast, mixture models do not rely on thresholds and use the full distribution of antibody titres. To date, there has been limited application of mixture models to estimate DENV FOI.

Methods

We compare the application of mixture models and time-constant and time-varying catalytic models to simulated data and to serological data collected in Vietnam from 2004 to 2009 (N ≥ 2178) and Indonesia in 2014 (N = 3194).

Results

The simulation study showed larger mean FOI estimate bias from the time-constant and time-varying catalytic models (-0.007 (95% Confidence Interval (CI): -0.069, 0.029) and -0.006 (95% CI -0.095, 0.043)) than from the mixture model (0.001 (95% CI -0.036, 0.065)). Coverage of the true FOI was > 95% for estimates from both the time-varying catalytic and mixture model, however the latter had reduced uncertainty. When applied to real data from Vietnam, the mixture model frequently produced higher FOI and seroprevalence estimates than the catalytic models.

Conclusions

Our results suggest mixture models represent valid, potentially less biased, alternatives to catalytic models, which could be particularly useful when estimating FOI from data with largely overlapping antibody titre distributions.

Characterising the transmission intensity of dengue virus is essential to inform the implementation of interventions, such as vector control and vaccination, and to better understand the environmental drivers of transmission locally and globally. It is therefore important to understand how methodological differences and model choice may influence the accuracy of estimates of transmission intensity. Using a simulation study, we assessed the performance of catalytic and mixture models to reconstruct the force of infection (FOI) from simulated antibody titre data. Furthermore, we estimated the FOI of dengue virus from antibody titre data collected in Vietnam and Indonesia. The models produced consistent estimates of FOI when they were applied to data with clear separation between the distributions of seronegative and seropositive antibody titres. We observed greater bias in FOI estimates obtained from catalytic models than from mixture models when they were applied to data with high overlap in the bimodal distribution of antibody titres. Our results indicate that mixture models could be preferential to estimate dengue virus FOI when the antibody titre distributions of the seronegative and seropositive components largely overlap.

Knowledge gaps in the epidemiology of severe dengue impede vaccine evaluation

The most severe consequences of dengue virus infection include shock, haemorrhage, and major organ failure; however, the frequency of these manifestations varies, and the relative contribution of pre-existing anti-dengue virus antibodies, virus characteristics, and host factors (including age and comorbidities) are not well understood. Reliable characterisation of the epidemiology of severe dengue first depends on the use of consistent definitions of disease severity. As vaccine trials have shown, severe dengue is a crucial interventional endpoint, yet the infrequency of its occurrence necessitates the inclusion of thousands of study participants to appropriately compare its frequency among participants who have and have not been vaccinated. Hospital admission is frequently used as a proxy for severe dengue; however, lack of specificity and variability in clinical practices limit the reliability of this approach. Although previous infection with a dengue virus is the best characterised risk factor for developing severe dengue, the influence of the timing between dengue virus infections and the sequence of dengue virus infections on disease severity is only beginning to be elucidated. To improve our understanding of the diverse factors that shape the clinical spectrum of disease resulting from dengue virus infection, prospective, community-based and clinic-based immunological, virological, genetic, and clinical studies across a range of ages and geographical regions are needed.

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.

Serological Evidence of Widespread Zika Transmission across the Philippines

Zika virus (ZIKV) exposure across flavivirus-endemic countries, including the Philippines, remains largely unknown despite sporadic case reporting and environmental suitability for transmission. Using laboratory surveillance data from 2016, 997 serum samples were randomly selected from suspected dengue (DENV) case reports across the Philippines and assayed for serological markers of short-term (IgM) and long-term (IgG) ZIKV exposure. Using mixture models, we re-evaluated ZIKV IgM/G seroprevalence thresholds and used catalytic models to quantify the force of infection (attack rate, AR) from age-accumulated ZIKV exposure. While we observed extensive ZIKV/DENV IgG cross-reactivity, not all individuals with active DENV presented with elevated ZIKV IgG, and a proportion of dengue-negative cases (DENV IgG-) were ZIKV IgG-positive (14.3%, 9/63). We identified evidence of long-term, yet not short-term, ZIKV exposure across Philippine regions (ZIKV IgG+: 31.5%, 314/997) which was geographically uncorrelated with DENV exposure. In contrast to the DENV AR (12.7% (95%CI: 9.1-17.4%)), the ZIKV AR was lower (5.7% (95%CI: 3-11%)) across the country. Our results provide evidence of widespread ZIKV exposure across the Philippines and suggest the need for studies to identify ZIKV infection risk factors over time to better prepare for potential future outbreaks.

Climate predicts geographic and temporal variation in mosquito-borne disease dynamics on two continents

Climate drives population dynamics through multiple mechanisms, which can lead to seemingly context-dependent effects of climate on natural populations. For climate-sensitive diseases, such as dengue, chikungunya, and Zika, climate appears to have opposing effects in different contexts. Here we show that a model, parameterized with laboratory measured climate-driven mosquito physiology, captures three key epidemic characteristics across ecologically and culturally distinct settings in Ecuador and Kenya: the number, timing, and duration of outbreaks. The model generates a range of disease dynamics consistent with observed Aedes aegypti abundances and laboratory-confirmed arboviral incidence with variable accuracy (28–85% for vectors, 44–88% for incidence). The model predicted vector dynamics better in sites with a smaller proportion of young children in the population, lower mean temperature, and homes with piped water and made of cement. Models with limited calibration that robustly capture climate-virus relationships can help guide intervention efforts and climate change disease projections.

The effects of climate on vector-borne disease systems are highly context-dependent. Here, the authors incorporate laboratory-measured physiological traits of the mosquito Aedes aegypti into climate-driven mechanistic models to predict number, timing, and duration of outbreaks in Ecuador and Kenya.

Asynchronicity of endemic and emerging mosquito-borne disease outbreaks in the Dominican Republic

Mosquito-borne viruses threaten the Caribbean due to the region's tropical climate and seasonal reception of international tourists. Outbreaks of chikungunya and Zika have demonstrated the rapidity with which these viruses can spread. Concurrently, dengue fever cases have climbed over the past decade. Sustainable disease control measures are urgently needed to quell virus transmission and prevent future outbreaks. Here, to improve upon current control methods, we analyze temporal and spatial patterns of chikungunya, Zika, and dengue outbreaks reported in the Dominican Republic between 2012 and 2018. The viruses that cause these outbreaks are transmitted by Aedes mosquitoes, which are sensitive to seasonal climatological variability. We evaluate whether climate and the spatio-temporal dynamics of dengue outbreaks could explain patterns of emerging disease outbreaks. We find that emerging disease outbreaks were robust to the climatological and spatio-temporal constraints defining seasonal dengue outbreak dynamics, indicating that constant surveillance is required to prevent future health crises.

Age-dependent seroprevalence of dengue and chikungunya: inference from a cross-sectional analysis in Esmeraldas Province in coastal Ecuador

OBJECTIVES

There are few population-based estimates for prevalence of past exposure to dengue and chikungunya viruses despite common epidemiological features. Here, we have developed a novel statistical method to study patterns of age-dependent prevalence of immunity in a population following exposures to two viruses which share similar epidemiological features including mode of transmission and induction of long-lasting immunity. This statistical technique accounted for sociodemographic characteristics associated with individuals and households.

SETTINGS

The data consist of a representative sample from an ongoing longitudinal birth cohort set-up in a tropical district in coastal Ecuador (Esmeraldas).

PARTICIPANTS

We collected data and blood samples from 319 individuals belonging to 152 households following epidemics of the infections in 2015 in Latin America.

PRIMARY OUTCOME

Plasma was tested for the presence of specific IgG antibodies to dengue and chikungunya viruses by commercial ELISA and defined a bivariate binary outcome indicating individuals' past exposure status to dengue and chikungunya (ie, presence/absence of IgG antibodies to dengue or chikungunya or both).

RESULTS

Dengue seroprevalence increased rapidly with age reaching 97% (95% credible interval (CrI): 93%-99%) by 60 years. Chikungunya seroprevalence peaked at 42% (95% CrI: 18%-66%) around 9 years of age and averaged 27% (95% CrI: 8.7%-51.6%) for all ages. Rural areas were more likely to be associated with dengue-only exposure while urban areas and shorter distance to the nearest household were associated with exposures to both. Women living in urban settings were more likely to be chikungunya seropositive while rural men were more likely to be dengue seropositive.

CONCLUSION

Dengue seroprevalence was strongly age dependent consistent with endemic exposure while that of chikungunya peaked in childhood consistent with the recent emergence of the virus in the study area. Our findings will inform control strategies for the two arboviruses in Ecuador including recommendations by the WHO on dengue vaccination.

Hidden heterogeneity and its influence on dengue vaccination impact

The CYD-TDV vaccine was recently developed to combat dengue, a mosquito-borne viral disease that afflicts millions of people each year throughout the tropical and subtropical world. Its rollout has been complicated by recent findings that vaccinees with no prior exposure to dengue virus (DENV) experience an elevated risk of severe disease in response to their first DENV infection subsequent to vaccination. As a result of these findings, guidelines for use of CYD-TDV now require serological screening prior to vaccination to establish that an individual does not fall into this high-risk category. These complications mean that the public health impact of CYD-TDV vaccination is expected to be higher in areas with higher transmission. One important practical difficulty with tailoring vaccination policy to local transmission contexts is that DENV transmission is spatially heterogeneous, even at the scale of neighborhoods or blocks within a city. This raises the question of whether models based on data that average over spatial heterogeneity in transmission could fail to capture important aspects of CYD-TDV impact in spatially heterogeneous populations. We explored this question with a deterministic model of DENV transmission and CYD-TDV vaccination in a population comprised of two communities with differing transmission intensities. Compared to the full model, a version of the model based on the average of the two communities failed to capture benefits of targeting the intervention to the high-transmission community, which resulted in greater impact in both communities than we observed under even coverage. In addition, the model based on the average of the two communities substantially overestimated impact among vaccinated individuals in the low-transmission community. In the event that the specificity of serological screening is not high, this result suggests that models that ignore spatial heterogeneity could overlook the potential for harm to this segment of the population.

Mapping global variation in dengue transmission intensity

Intervention planning for dengue requires reliable estimates of dengue transmission intensity. However, current maps of dengue risk provide estimates of disease burden or the boundaries of endemicity rather than transmission intensity. We therefore developed a global high-resolution map of dengue transmission intensity by fitting environmentally driven geospatial models to geolocated force of infection estimates derived from cross-sectional serological surveys and routine case surveillance data. We assessed the impact of interventions on dengue transmission and disease using Wolbachia-infected mosquitoes and the Sanofi-Pasteur vaccine as specific examples. We predicted high transmission intensity in all continents straddling the tropics, with hot spots in South America (Colombia, Venezuela, and Brazil), Africa (western and central African countries), and Southeast Asia (Thailand, Indonesia, and the Philippines). We estimated that 105 [95% confidence interval (CI), 95 to 114] million dengue infections occur each year with 51 (95% CI, 32 to 66) million febrile disease cases. Our analysis suggests that transmission-blocking interventions such as Wolbachia, even at intermediate efficacy (50% transmission reduction), might reduce global annual disease incidence by up to 90%. The Sanofi-Pasteur vaccine, targeting only seropositive recipients, might reduce global annual disease incidence by 20 to 30%, with the greatest impact in high-transmission settings. The transmission intensity map presented here, and made available for download, may help further assessment of the impact of dengue control interventions and prioritization of global public health efforts.

Children as sentinels of tuberculosis transmission: disease mapping of programmatic data

BACKGROUND

Identifying hotspots of tuberculosis transmission can inform spatially targeted active case-finding interventions. While national tuberculosis programs maintain notification registers which represent a potential source of data to investigate transmission patterns, high local tuberculosis incidence may not provide a reliable signal for transmission because the population distribution of covariates affecting susceptibility and disease progression may confound the relationship between tuberculosis incidence and transmission. Child cases of tuberculosis and other endemic infectious disease have been observed to provide a signal of their transmission intensity. We assessed whether local overrepresentation of child cases in tuberculosis notification data corresponds to areas where recent transmission events are concentrated.

METHODS

We visualized spatial clustering of children < 5 years old notified to Peru's National Tuberculosis Program from two districts of Lima, Peru, from 2005 to 2007 using a log-Gaussian Cox process to model the intensity of the point-referenced child cases. To identify where clustering of child cases was more extreme than expected by chance alone, we mapped all cases from the notification data onto a grid and used a hierarchical Bayesian spatial model to identify grid cells where the proportion of cases among children < 5 years old is greater than expected. Modeling the proportion of child cases allowed us to use the spatial distribution of adult cases to control for unobserved factors that may explain the spatial variability in the distribution of child cases. We compare where young children are overrepresented in case notification data to areas identified as transmission hotspots using molecular epidemiological methods during a prospective study of tuberculosis transmission conducted from 2009 to 2012 in the same setting.

RESULTS

Areas in which childhood tuberculosis cases are overrepresented align with areas of spatial concentration of transmission revealed by molecular epidemiologic methods.

CONCLUSIONS

Age-disaggregated notification data can be used to identify hotspots of tuberculosis transmission and suggest local force of infection, providing an easily accessible source of data to target active case-finding intervention.

Estimates of the global burden of Japanese encephalitis and the impact of vaccination from 2000-2015

Japanese encephalitis (JE) is a mosquito-borne disease, known for its high mortality and disability rate among symptomatic cases. Many effective vaccines are available for JE, and the use of a recently developed and inexpensive vaccine, SA 14-14-2, has been increasing over the recent years particularly with Gavi support. Estimates of the local burden and the past impact of vaccination are therefore increasingly needed, but difficult due to the limitations of JE surveillance. In this study, we implemented a mathematical modelling method (catalytic model) combined with age-stratifed case data from our systematic review which can overcome some of these limitations. We estimate in 2015 JEV infections caused 100,308 JE cases (95% CI: 61,720-157,522) and 25,125 deaths (95% CI: 14,550-46,031) globally, and that between 2000 and 2015 307,774 JE cases (95% CI: 167,442-509,583) were averted due to vaccination globally. Our results highlight areas that could have the greatest benefit from starting vaccination or from scaling up existing programs and will be of use to support local and international policymakers in making vaccine allocation decisions.

Considerations for the 2030 Sustainable Development Goals for dengue

Dengue circulates endemically in many tropical and subtropical regions. In 2012, the World Health Organization (WHO) set out goals to reduce dengue mortality and morbidity by 50% and 25%, respectively, between 2010 and 2020. These goals will not be met. This is, in part, due to existing interventions being insufficiently effective to prevent spread. Further, complex and variable patterns of disease presentation coupled with imperfect surveillance systems mean that even tracking changes in burden is rarely possible. As part of the Sustainable Development Goals, WHO will propose new dengue-specific goals for 2030. The 2030 goals provide an opportunity for focused action on tackling dengue burden but should be carefully developed to be ambitious but also technically feasible. Here we discuss the potential for clearly defined case fatality rates and the rollout of new and effective intervention technologies to form the foundation of these future goals. Further, we highlight how the complexity of dengue epidemiology limits the feasibility of goals that instead target dengue outbreaks.