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.

Challenges and Approaches to Establishing Multi-Pathogen Serosurveillance: Findings from the 2023 Serosurveillance Summit.

Multiplex-based serological surveillance is a valuable but underutilized tool to understand gaps in population-level exposure, susceptibility, and immunity to infectious diseases. Assays for which blood samples can be tested for antibodies against several pathogens simultaneously, such as multiplex bead immunoassays, can more efficiently integrate public health surveillance in low- and middle-income countries. On March 7-8, 2023 a group of experts representing research institutions, multilateral organizations, private industry, and country partners met to discuss experiences, identify challenges and solutions, and create a community of practice for integrated, multi-pathogen serosurveillance using multiplex bead assay technologies. Participants were divided into six working groups: 1) supply chain; 2) laboratory assays; 3) seroepidemiology; 4) data analytics; 5) sustainable implementation; and 6) use case scenarios. These working groups discussed experiences, challenges, solutions, and research needs to facilitate integrated, multi-pathogen serosurveillance for public health. Several solutions were proposed to address challenges that cut across working groups.

Informing an investment case for Japanese encephalitis vaccine introduction in Bangladesh.

Japanese encephalitis virus (JEV) is a major threat to human health. Bangladesh is considering introducing a JEV vaccine; however, the investment case is hampered by a limited understanding of key aspects of JEV ecology. We conducted a seroprevalence study in a high-incidence region using an assay that limits cross-reactivity with dengue virus. We also trapped mosquitoes and collected information about potential host species. We used mathematical models to recover risk factors for infection and underlying probabilities of severe disease and death. We observed 19.0% [95% confidence interval (CI):17.1 to 21.1] of JEV antibodies. On average, 0.7% (95% CI: 0.2 to 2.0) of the susceptible population gets infected yearly, with pig proximity being the main human infection risk factor. Our traps captured 10 different mosquito species that have been linked with JEV transmission. We estimated that 1 in 1000 infections results in severe disease, 1 in 10,000 results in death, and 76% of severe cases are missed by surveillance.

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.

Results of a nationally representative seroprevalence survey of chikungunya virus in Bangladesh.

There is an increasing global burden from chikungunya virus (CHIKV). Bangladesh reported a major epidemic in 2017, however, it was unclear if there had been prior widespread transmission. We conducted a nationally representative seroprevalence survey in 70 randomly selected communities immediately prior to the epidemic. We found 69/2,938 (2.4%) of sampled individuals were seropositive to CHIKV. Being seropositive to dengue virus (aOR 3.13 [95% CIs: 1.86-5.27]), male sex (aOR 0.59 [95% CIs: 0.36-0.99]), and community presence of Aedes aegypti mosquitoes (aOR: 1.80, 95% CI: 1.05-3.07) were significantly associated with CHIKV seropositivity. Using a spatial prediction model, we estimated that across the country, 4.99 (95% CI: 4.89 - 5.08) million people had been previously infected. These findings highlight high population susceptibility prior to the major outbreak and that previous outbreaks must have been spatially isolated.

Estimating geographical spread of Streptococcus pneumoniae within Israel using genomic data.

Understanding how pathogens spread across geographical space is fundamental for control measures such as vaccination. Streptococcus pneumoniae (the pneumococcus) is a respiratory bacterium responsible for a large proportion of infectious disease morbidity and mortality globally. Even in the post-vaccination era, the rates of invasive pneumococcal disease (IPD) remain stable in most countries, including Israel. To understand the geographical spread of the pneumococcus in Israel, we analysed 1174 pneumococcal genomes from patients with IPD across multiple regions. We included the evolutionary distance between pairs of isolates inferred using whole-genome data within a relative risk (RR) ratio framework to capture the geographical structure of S. pneumoniae. While we could not find geographical structure at the overall lineage level, the extra granularity provided by whole-genome sequence data showed that it takes approximately 5 years for invasive pneumococcal isolates to become fully mixed across the country.This article contains data hosted by Microreact.

Dynamics of measles immunity from birth and following vaccination.

Measles remains a major threat to human health despite widespread vaccination. While we know that maternal antibodies can impair vaccine-induced immunity, the relative contributions of pre-existing immunity levels, maternal and infant characteristics on vaccine responses remain unclear, hampering evidence-based vaccination policy development. Here we combine serological data from 1,505 individuals (aged 0-12 years) in a mother-infant cohort and in a child cohort with empirical models to reconstruct antibody trajectories from birth. We show that while highly heterogeneous across a population, measles antibody evolution is strongly predictive from birth at the individual level, including following vaccination. Further, we find that caesarean section births were linked with 2.56 (95% confidence interval: 1.06-6.37) increased odds of primary vaccine failure, highlighting the long-term immunological consequences of birth route. Finally, we use our new understanding of antibody evolution to critically assess the population-level consequences of different vaccination schedules, the results of which will allow country-level evaluations of vaccine policy.

The genetic diversity of Nipah virus across spatial scales.

BACKGROUND: Nipah virus (NiV), a highly lethal virus in humans, circulates in Pteropus bats throughout South and Southeast Asia. Difficulty in obtaining viral genomes from bats means we have a poor understanding of NiV diversity. METHODS: We develop phylogenetic approaches applied to the most comprehensive collection of genomes to date (N=257, 175 from bats, 73 from humans) from six countries over 22 years (1999-2020). We divide the four major NiV sublineages into 15 genetic clusters. Using Approximate Bayesian Computation fit to a spatial signature of viral diversity, we estimate the presence and the average size of genetic clusters per area. RESULTS: We find that, within any bat roost, there are an average of 2.4 co-circulating genetic clusters, rising to 5.5 clusters at areas of 1500-2000km2. We estimate that each genetic cluster occupies an average area of 1.3million km2 (95%CI: 0.6-2.3 million), with 14 clusters in an area of 100,000km2 (95%CI: 6-24). In the few sites in Bangladesh and Cambodia where genomic surveillance has been concentrated, we estimate that most clusters have been identified, but only ∼15% of overall NiV diversity has been uncovered. CONCLUSION: Our findings are consistent with entrenched co-circulation of distinct lineages, even within roosts, coupled with slow migration over larger spatial scales.

Antigenic distance between primary and secondary dengue infections correlates with disease risk.

Many pathogens continuously change their protein structure in response to immune-driven selection, resulting in weakened protection even in previously exposed individuals. In addition, for some pathogens, such as dengue virus, poorly targeted immunity is associated with increased risk of severe disease through a mechanism known as antibody-dependent enhancement. However, it remains unclear whether the antigenic distances between an individual's first infection and subsequent exposures dictate disease risk, explaining the observed large-scale differences in dengue hospitalizations across years. Here, we develop a framework that combines detailed antigenic and genetic characterization of viruses with details on hospitalized cases from 21 years of dengue surveillance in Bangkok, Thailand, to identify the role of the antigenic profile of circulating viruses in determining disease risk. We found that the risk of hospitalization depended on both the specific order of infecting serotypes and the antigenic distance between an individual's primary and secondary infections, with risk maximized at intermediate antigenic distances. These findings suggest that immune imprinting helps determine dengue disease risk and provide a pathway to monitor the changing risk profile of populations and to quantifying risk profiles of candidate vaccines.

Protective Role of NS1-Specific Antibodies in the Immune Response to Dengue Virus through Antibody-Dependent Cellular Cytotoxicity.

BACKGROUND: Dengue virus (DENV) non-structural protein 1 (NS1) has multiple functions within infected cells, on the cell surface, and in secreted form, and is highly immunogenic. Immunity from previous DENV infections is known to exert both positive and negative effects on subsequent DENV infections, but the contribution of NS1-specific antibodies to these effects is incompletely understood. METHODS: We investigated the functions of NS1-specific antibodies and their significance in DENV infection. We analyzed plasma samples collected in a prospective cohort study prior to symptomatic or subclinical secondary DENV infection. We measured binding to purified recombinant NS1 protein and to NS1-expressing CEM cells, antibody-mediated NK cell activation by plate-bound NS1 protein, and antibody-dependent cellular cytotoxicity (ADCC) of NS1-expressing target cells. RESULTS: We found that antibody responses to NS1 were highly serotype-cross-reactive and that subjects who experienced subclinical DENV infection had significantly higher antibody responses to NS1 in pre-infection plasma than subjects who experienced symptomatic infection. We observed strong positive correlations between antibody binding and NK activation. CONCLUSIONS: These findings demonstrate the involvement of NS1-specific antibodies in ADCC and provide evidence for a protective effect of NS1-specific antibodies in secondary DENV infection.

Chikungunya seroprevalence, force of infection, and prevalence of chronic disability after infection in endemic and epidemic settings: a systematic review, meta-analysis, and modelling study.

BACKGROUND: Chikungunya is an arboviral disease transmitted by Aedes aegypti and Aedes albopictus mosquitoes with a growing global burden linked to climate change and globalisation. We aimed to estimate chikungunya seroprevalence, force of infection (FOI), and prevalence of related chronic disability and hospital admissions in endemic and epidemic settings. METHODS: In this systematic review, meta-analysis, and modelling study, we searched PubMed, Ovid, and Web of Science for articles published from database inception until Sept 26, 2022, for prospective and retrospective cross-sectional studies that addressed serological chikungunya virus infection in any geographical region, age group, and population subgroup and for longitudinal prospective and retrospective cohort studies with data on chronic chikungunya or hospital admissions in people with chikungunya. We did a systematic review of studies on chikungunya seroprevalence and fitted catalytic models to each survey to estimate location-specific FOI (ie, the rate at which susceptible individuals acquire chikungunya infection). We performed a meta-analysis to estimate the proportion of symptomatic patients with laboratory-confirmed chikungunya who had chronic chikungunya or were admitted to hospital following infection. We used a random-effects model to assess the relationship between chronic sequelae and follow-up length using linear regression. The systematic review protocol is registered online on PROSPERO, CRD42022363102. FINDINGS: We identified 60 studies with data on seroprevalence and chronic chikungunya symptoms done across 76 locations in 38 countries, and classified 17 (22%) of 76 locations as endemic settings and 59 (78%) as epidemic settings. The global long-term median annual FOI was 0·007 (95% uncertainty interval [UI] 0·003-0·010) and varied from 0·0001 (0·00004-0·0002) to 0·113 (0·07-0·20). The highest estimated median seroprevalence at age 10 years was in south Asia (8·0% [95% UI 6·5-9·6]), followed by Latin America and the Caribbean (7·8% [4·9-14·6]), whereas median seroprevalence was lowest in the Middle East (1·0% [0·5-1·9]). We estimated that 51% (95% CI 45-58) of people with laboratory-confirmed symptomatic chikungunya had chronic disability after infection and 4% (3-5) were admitted to hospital following infection. INTERPRETATION: We inferred subnational heterogeneity in long-term average annual FOI and transmission dynamics and identified both endemic and epidemic settings across different countries. Brazil, Ethiopia, Malaysia, and India included both endemic and epidemic settings. Long-term average annual FOI was higher in epidemic settings than endemic settings. However, long-term cumulative incidence of chikungunya can be similar between large outbreaks in epidemic settings with a high FOI and endemic settings with a relatively low FOI. FUNDING: International Vaccine Institute.

Integration of population-level data sources into an individual-level clinical prediction model for dengue virus test positivity.

The differentiation of dengue virus (DENV) infection, a major cause of acute febrile illness in tropical regions, from other etiologies, may help prioritize laboratory testing and limit the inappropriate use of antibiotics. While traditional clinical prediction models focus on individual patient-level parameters, we hypothesize that for infectious diseases, population-level data sources may improve predictive ability. To create a clinical prediction model that integrates patient-extrinsic data for identifying DENV among febrile patients presenting to a hospital in Thailand, we fit random forest classifiers combining clinical data with climate and population-level epidemiologic data. In cross-validation, compared to a parsimonious model with the top clinical predictors, a model with the addition of climate data, reconstructed susceptibility estimates, force of infection estimates, and a recent case clustering metric significantly improved model performance.

Comparing the Performance of Three Models Incorporating Weather Data to Forecast Dengue Epidemics in Reunion Island, 2018-2019.

We developed mathematical models to analyze a large dengue virus (DENV) epidemic in Reunion Island in 2018-2019. Our models captured major drivers of uncertainty including the complex relationship between climate and DENV transmission, temperature trends, and underreporting. Early assessment correctly concluded that persistence of DENV transmission during the austral winter 2018 was likely and that the second epidemic wave would be larger than the first one. From November 2018, the detection probability was estimated at 10%-20% and, for this range of values, our projections were found to be remarkably accurate. Overall, we estimated that 8% and 18% of the population were infected during the first and second wave, respectively. Out of the 3 models considered, the best-fitting one was calibrated to laboratory entomological data, and accounted for temperature but not precipitation. This study showcases the contribution of modeling to strengthen risk assessments and planning of national and local authorities.

Household immunity and individual risk of infection with dengue virus in a prospective, longitudinal cohort study.

Although it is known that household infections drive the transmission of dengue virus (DENV), it is unclear how household composition and the immune status of inhabitants affect the individual risk of infection. Most population-based studies to date have focused on paediatric cohorts because more severe forms of dengue mainly occur in children, and the role of adults in dengue transmission is understudied. Here we analysed data from a multigenerational cohort study of 470 households, comprising 2,860 individuals, in Kamphaeng Phet, Thailand, to evaluate risk factors for DENV infection. Using a gradient-boosted regression model trained on annual haemagglutination inhibition antibody titre inputs, we identified 1,049 infections, 90% of which were subclinical. By analysing imputed infections, we found that individual antibody titres, household composition and antibody titres of other members in the same household affect an individual's risk of DENV infection. Those individuals living in households with high average antibody titres, or households with more adults, had a reduced risk of infection. We propose that herd immunity to dengue acts at the household level and may provide insight into the drivers of the recent change in the shifting age distribution of dengue cases in Thailand.

Transplacental transfer efficiency of maternal antibodies against influenza A(H1N1)pdm09 virus and dynamics of naturally acquired antibodies in Chinese children: a longitudinal, paired mother-neonate cohort study.

BACKGROUND: The 2009 pandemic H1N1 influenza A virus (A(H1N1)pdm09 virus) evolves rapidly and has continued to cause severe infections in children since its emergence in 2009. We aimed to characterise the kinetics of maternally and naturally acquired antibodies against historical A(H1N1)pdm09 strains and to assess the extent to which the response to heterologous strains following infection or vaccination affects observed A(H1N1)pdm09 strain-specific antibody titres in a Chinese paediatric population. METHODS: In this retrospective study, we used residual serum samples from 528 mother-neonate pairs from a non-interventional, longitudinal cohort study in southern China conducted from Sept 20, 2013, to Aug 24, 2018, from six local hospitals in Anhua County, Hunan Province, China. Mother-neonate pairs were eligible for inclusion if the neonates were born after Sept 20, 2013, and their mothers had resided in the study sites for at least 3 months. We tested samples with a haemagglutination inhibition (HAI) assay to measure antibody levels against three historical A(H1N1)pdm09 strains that were antigenically similar to the strains that circulated during the 2009 pandemic (A/Hunan-Kaifu/SWL4204/2009 [SWL4204/09 strain], A/Hunan-Daxiang/SWL1277/2016 [SWL1277/16 strain], and A/Hunan-Yanfeng/SWL185/2018 [SWL185/18 strain]). We also determined the seroprevalence, geometric mean titres (GMTs), transfer ratio of maternal antibodies, and the dynamics of maternally and naturally acquired antibodies in children, from birth to 3 years of age. FINDINGS: 1066 mother-neonate pairs were enrolled in the original cohort between Sept 20, 2013, and Oct 14, 2015. Of these, 528 pairs (523 mothers, 528 neonates) were selected for the present study. The median age of the mothers was 25 years (IQR 23 to 29). 291 (55%) of 528 children were boys and 237 (45%) were girls, and most children (452 [86%]) were breastfed before the age of 6 months. The GMTs and the seroprevalence for the SWL4204/09 strain were higher than those for the SWL1277/16 and SWL185/18 strains among mothers (GMTs: 10·4 [95% CI 9·8 to 11·1] vs 9·3 [8·7 to 9·8] vs 8·0 [7·5 to 8·4], p<0·0001; seroprevalence: 11·1% [95% CI 8·5 to 14·1] vs 6·9% [4·9 to 9·4] vs 4·6% [3·0 to 6·8], p=0·0003) and among neonates (GMTs: 10·7 [10·0 to 11·5] vs 9·4 [8·8 to 10·0] vs 8·1 [7·6 to 8·6], p<0·0001; seroprevalence: 13·4% [10·7 to 16·7] vs 8·7% [6·5 to 11·5] vs 6·1% [4·2 to 8·5], p=0·0002). Regardless of the A(H1N1)pdm09-specific strain, maternal antibodies could be transferred efficiently via the placenta (mean transfer ratios: 1·10 for SWL4204/09 vs 1·09 for SWL1277/16 vs 1·06 for SWL185/18; p=0·93). The A(H1N1)pdm09 strain-specific antibodies waned below the protective threshold of 1:40 within 2 months after birth. After maternal antibody waning, there were periodic increases and decreases in HAI antibody titres against three A(H1N1)pdm09 strains, and such increases were all significantly associated with a higher immune response to heterologous strains. Vaccination against the SWL4204/09 strain was associated with a poor response to the SWL185/18 strain (ß-0·20, 95% CI -0·28 to -0·13; p<0·0001). INTERPRETATION: Our findings suggest low pre-existing immunity against influenza A(H1N1)pdm09 virus among unvaccinated Chinese adult female and paediatric populations. This evidence, together with the rapid decay of maternal antibodies and the observed cross-reactivity among different A(H1N1)pdm09 strains, highlights the importance of accelerating maternal and paediatric influenza vaccination in China. FUNDING: The Key Program of the National Natural Science Foundation of China. TRANSLATION: For the Chinese translation of the abstract see Supplementary Materials section.

A systematic review of the data, methods and environmental covariates used to map Aedes-borne arbovirus transmission risk.

BACKGROUND: Aedes (Stegomyia)-borne diseases are an expanding global threat, but gaps in surveillance make comprehensive and comparable risk assessments challenging. Geostatistical models combine data from multiple locations and use links with environmental and socioeconomic factors to make predictive risk maps. Here we systematically review past approaches to map risk for different Aedes-borne arboviruses from local to global scales, identifying differences and similarities in the data types, covariates, and modelling approaches used. METHODS: We searched on-line databases for predictive risk mapping studies for dengue, Zika, chikungunya, and yellow fever with no geographical or date restrictions. We included studies that needed to parameterise or fit their model to real-world epidemiological data and make predictions to new spatial locations of some measure of population-level risk of viral transmission (e.g. incidence, occurrence, suitability, etc.). RESULTS: We found a growing number of arbovirus risk mapping studies across all endemic regions and arboviral diseases, with a total of 176 papers published 2002-2022 with the largest increases shortly following major epidemics. Three dominant use cases emerged: (i) global maps to identify limits of transmission, estimate burden and assess impacts of future global change, (ii) regional models used to predict the spread of major epidemics between countries and (iii) national and sub-national models that use local datasets to better understand transmission dynamics to improve outbreak detection and response. Temperature and rainfall were the most popular choice of covariates (included in 50% and 40% of studies respectively) but variables such as human mobility are increasingly being included. Surprisingly, few studies (22%, 31/144) robustly tested combinations of covariates from different domains (e.g. climatic, sociodemographic, ecological, etc.) and only 49% of studies assessed predictive performance via out-of-sample validation procedures. CONCLUSIONS: Here we show that approaches to map risk for different arboviruses have diversified in response to changing use cases, epidemiology and data availability. We identify key differences in mapping approaches between different arboviral diseases, discuss future research needs and outline specific recommendations for future arbovirus mapping.