Almost half of the world's population is at risk of acquiring dengue virus (DENV) each year. However, no specific licensed prophylactic or antiviral treatment for dengue currently exists. Mosnodenvir, a novel DENV inhibitor, has been shown to inhibit DENV replication in vitro and in animal studies. Here, we provide new insights into the in vivo prophylactic inhibitory effect of mosnodenvir exposure on primary DENV-2 infection by fitting mechanistic within-host models of DENV infection to virological and serological data observed from pre-clinical challenge studies in AG129 mice and rhesus macaques. We estimated a median mosnodenvir concentration achieving 50% of maximal inhibitory effect (IC50) on viral replication of 8.35 (6.82, 9.22) ng ml-1 and 7.61 (5.67, 8.92) ng ml-1 for AG129 mice and rhesus macaques, respectively. A higher concentration is typically required to suppress viral replication in AG129 mice compared with rhesus macaques owing to a higher estimated within-host basic reproduction number (R0) in mice. By integrating multiple data types in a single framework, this study enhances our understanding of the within-host dynamics of primary DENV infection in non-human host species. Furthermore, the methods developed here could possibly assist in quantifying the prophylactic inhibitory effect of mosnodenvir on DENV infections in humans.

Background: Dengue is highly endemic in many tropical and subtropical regions, including Thailand. As no specific treatment is available, vaccination is an important preventive strategy. The Qdenga (TAK-003) live-attenuated quadrivalent dengue vaccine is recommended by the World Health Organization for routine immunisation programmes in high-transmission settings with substantial disease burden. However, an independent country-specific economic evaluation is needed before inclusion in Thailand's National Immunization Program. This study evaluated the cost-effectiveness and budget impact of Qdenga vaccination strategies in Thailand. Methods: Cost-utility and budget impact analyses were conducted using a previously developed dengue transmission model. Qdenga vaccination scenarios, varying by vaccination age, vaccine mode of action (protection against disease only or against both disease and infection), and duration of waning (5 or 10 years), were compared with a no vaccination comparator. Costs and health outcomes, measured in quality-adjusted life years (QALYs), were projected over a 30-year time horizon. Findings: A national vaccination programme cumulatively targeting 15 million children aged 6 years could prevent 1·7 million symptomatic dengue cases and 382,000 hospitalisations. In the base-case analysis, routine vaccination targeting 6-year-olds would generate incremental costs of US$1,186 million and gain of 41,169 QALYs, resulting in an ICER of US$30,458/QALY. This exceeds Thailand's cost-effectiveness threshold (US$4,739/QALY) and yields an incremental net monetary benefit of –US$996 million. The annual government budget impact over the first five years was estimated to vary between US$66·4–70·9 million. Interpretation: Qdenga vaccination could substantially reduce symptomatic dengue cases and hospitalisations in Thailand. However, at its current price, the programme is unlikely to be cost-effective and would have a considerable budget impact. Price negotiation is therefore recommended before inclusion in the national immunisation programme.

Abstract Dengue virus is a severe threat to global health. Novel vaccine and Wolbachia technologies offer a potential path to dengue control; however, it remains unclear how to use these approaches in tandem. Using metapopulation transmission models, we simulated future dengue burden in Brazil. We estimated that w Mel releases in 300 municipalities could avert 12-22% of cases over the next 10 years, while a national vaccination campaign could avert 8-10% of cases in the total population and 39-45% within the vaccinated cohort. Projecting forward 40 years, we found w Mel releases would drive up the mean age of cases beyond increases due to the ageing population and increase population susceptibility to dengue. Finally, w Mel releases can help mitigate the future burden in southern Brazil where climate change is rapidly increasing dengue virus risk. These findings highlight the need to consider the two technologies in parallel to optimise efforts to combat future dengue burden.

Introduction: A limited number of dengue seroprevalence surveys have been conducted across Africa, with only 21 studies reported to date. Implementing new surveys to assess dengue transmission can be costly, time-consuming and resource intensive. In SERODEN we developed new simulation-based methods to calculate the optimal number and age-distribution of existing blood samples –collected in the context of previous household and community-based surveys, most notably against SARS-CoV-2 – to be tested for dengue. We used three different assays, namely the enzyme-linked immunosorbent assay (ELISA) IgG type 1-4, ELISA IgG NS1 type 1-4 and Plaque Reduction Neutralization Test (PRNT) for the 4 dengue serotypes, to characterise age-specific seroprevalence and dengue transmission intensity in 19 locations across Senegal, the Democratic Republic of the Congo (DRC), and Ghana. Method: We designed a simulation-based framework to inform serosurvey design when leveraging existing blood samples. We also developed a Bayesian approach to combine the results obtained from the different assays in unifying age-stratified seroprevalence and force of infection estimates, estimating and accounting for the tests’ specificity and sensitivity. Results: Our simulation-based framework identified the optimal sample sizes and age-distribution of the available blood samples, and overall, we reduced the total number of samples required for testing by 20%. The age-group prioritised for testing depended on the expected transmission intensity, with younger age-groups targeted for testing in high transmission settings. By combining multiple tests, including IgG ELISA type 1-4, ELISA IgG NS1, and PRNTs, we were able to quantify the specificity and sensitivity of each test and the dengue transmission in different African settings. Discussion: Our results unveiled significant heterogeneity in dengue transmission both within and across countries and underscored the endemic nature of dengue transmission in Senegal, DRC, and Ghana. The methods developed in the SERODEN study demonstrates the feasibility and benefits of utilising existing blood samples for the implementation of dengue serosurveys. Conclusion: By leveraging existing resources and combining different tests, we can provide valuable insights into dengue transmission intensity in Africa, which sheds new light on the dengue infection burden and can help inform dengue surveillance.

Introduction: There are limited data on dengue transmission across most of African countries, including Senegal, Ghana, and the Democratic Republic of the Congo (DRC). We aimed to assess the age-stratified dengue seroprevalence and estimate the force of infection (FOI, per-capita risk of dengue infection for a susceptible subject) in these countries. Methods: We surveyed 14 regions in Senegal, 3 cities in Ghana, and 2 cities in DRC, leveraging blood samples collected from previous SARS-CoV-2 serosurveys of individuals aged 0 to 94 years. An Enzyme-Linked Immunosorbent Assay (ELISA) was used to measure IgG antibody levels against purified dengue particles (ELISA-1). A subset of samples was tested by ELISA for IgG against the recombinant nonstructural protein (NS1) of dengue (ELISA-2) and using a Plaque Reduction Neutralization Test (PRNT) for all four dengue serotypes.We used a Bayesian approach to reconstruct results obtained in the study and estimated the force of infection of dengue assuming a time-constant transmission. Results: In total, 8203 samples were tested by IgG ELISA-1: 1486 in Ghana, 3137 in Senegal and 3580 in DRC. Based on the IgG ELISA results, there was significant heterogeneity in the annual per capita risk of dengue infection across regions of Senegal, ranging from 0.2% (95% CrI: 0.1-0.3%) in Dakar to 2.6% (95% CrI: 1.9 -3.6%) in Fatick, corresponding to overall seroprevalence estimates of 5% (95% CrI: 3-8%) and 39% (95% CrI: 32-47%), respectively. In DRC, the average yearly FOI obtained from the IgG ELISA-1 results was 2.9% (95% CrI: 2.2-3.9%) in Kinshasa and 1.4% (95% CrI: 0.9-2.0%) in Matadi, with an overall population seroprevalence of 41% (95% CrI: 34-48%) in Kinshasa and 23% (95% CrI: 17, 32%) in Matadi. There were large heterogeneities in dengue transmission intensity across locations in Ghana, with a higher average yearly FOI in Tamale at 7.1% (95% CrI 5.6-9.6%)] compared to Accra at 2.6% (95% CrI 2.1-3.3%) and Kumasi at 0.5% (95% CrI 0.1-0.8%)​. Based on these results, we estimated that 43%, 11%, and 70% of the Accra, Kumasi, and Tamale populations, respectively, had been exposed to dengue virus. Notably, we found that the integration of the IgG ELISA-2 and PRNT test generated consistent estimates to those obtained with the IgG ELISA-1 test across locations. Conclusion: This three-country seroprevalence study provides evidence that dengue has been circulating at different levels across Ghana, DRC, and Senegal and highlights the large heterogeneity in population immunity and transmission across regions. Dengue surveillance needs to be strengthened in these countries and across Africa to monitor transmission and respond to future outbreaks.

BackgroundDengue poses a significant burden worldwide, and a more comprehensive understanding of the heterogeneity in the intensity of dengue transmission within endemic countries is necessary to evaluate the potential impact of public health interventions.MethodsThis scoping literature review aimed to update a previous study of dengue transmission intensity by collating global age-stratified dengue seroprevalence data published in the Medline, Embase and Web of Science databases from 2014 to 2023. These data were then utilised to calibrate catalytic models and estimate the force of infection (FOI), which is the yearly per-capita risk of infection for a typical susceptible individual.FindingsWe found a total of 66 new publications containing 219 age-stratified seroprevalence datasets across 30 endemic countries. Together with the previously available average FOI estimates, there are now more than 250 dengue average FOI estimates obtained from seroprevalence studies from across the world.InterpretationThe results show large heterogeneities in average dengue FOI both across and within countries. These new estimates can be used to inform ongoing modelling efforts to improve our understanding of the drivers of the heterogeneity in dengue transmission globally, which in turn can help inform the optimal implementation of public health interventions.FundingUK Medical Research Council, Wellcome Trust, Community Jameel, Drugs for Neglected Disease initiative (DNDi) funded by the French Development Agency, Médecins Sans Frontières International; Swiss Agency for Development and Cooperation and UK aid.

We use viral kinetic models fitted to viral load data from in vitro studies to explain why the SARS-CoV-2 Omicron variant replicates faster than the Delta variant in nasal cells, but slower than Delta in lung cells, which could explain Omicron's higher transmission potential and lower severity. We find that in both nasal and lung cells, viral infectivity is higher for Omicron but the virus production rate is higher for Delta, with an estimated approximately 200-fold increase in infectivity and 100-fold decrease in virus production when comparing Omicron with Delta in nasal cells. However, the differences are unequal between cell types, and ultimately lead to the basic reproduction number and growth rate being higher for Omicron in nasal cells, and higher for Delta in lung cells. In nasal cells, Omicron alone can enter via a TMPRSS2-independent pathway, but it is primarily increased efficiency of TMPRSS2-dependent entry which accounts for Omicron's increased activity. This work paves the way for using within-host mathematical models to understand the transmission potential and severity of future variants.

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.

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.

Dengue virus (DENV) is a public health challenge across the tropics and subtropics. Currently, there is no licensed prophylactic or antiviral treatment for dengue. The novel DENV inhibitor JNJ-1802 can significantly reduce viral load in mice and non-human primates. Here, using a mechanistic viral kinetic model calibrated against viral RNA data from experimental in-vitro infection studies, we assess the in-vitro inhibitory effect of JNJ-1802 by characterising infection dynamics of two DENV-2 strains in the absence and presence of different JNJ-1802 concentrations. Viral RNA suppression to below the limit of detection was achieved at concentrations of >1.6 nM, with a median concentration exhibiting 50% of maximal inhibitory effect (IC50) of 1.23x10-02 nM and 1.28x10-02 nM for the DENV-2/RL and DENV-2/16681 strains, respectively. This work provides important insight into the in-vitro inhibitory effect of JNJ-1802 and presents a first step towards a modelling framework to support characterization of viral kinetics and drug effect across different host systems.

Fine-scale geographic variation in the transmission intensity of mosquito-borne diseases is primarily caused by variation in the density of female adult mosquitoes. Therefore, an understanding of fine-scale mosquito population dynamics is critical to understanding spatial heterogeneity in disease transmission and persistence at those scales. However, mathematical models of dengue and malaria transmission, which consider the dynamics of mosquito larvae, generally do not account for the fragmented structure of larval breeding sites. Here, we develop a stochastic metapopulation model of mosquito population dynamics and explore the impact of accounting for breeding site fragmentation when modelling fine-scale mosquito population dynamics. We find that, when mosquito population densities are low, fragmentation can lead to a reduction in population size, with population persistence dependent on mosquito dispersal and features of the underlying landscape. We conclude that using non-spatial models to represent fine-scale mosquito population dynamics may substantially underestimate the stochastic volatility of those populations.

Dengue is the most common arboviral infection of humans, responsible for a substantial disease burden across the tropics. Traditional insecticide-based vector-control programmes have limited effectiveness, and the one licensed vaccine has a complex and imperfect efficacy profile. Strains of the bacterium Wolbachia, deliberately introduced into Aedes aegypti mosquitoes, have been shown to be able to spread to high frequencies in mosquito populations in release trials, and mosquitoes infected with these strains show markedly reduced vector competence. Thus, Wolbachia represents an exciting potential new form of biocontrol for arboviral diseases, including dengue. Here, we review how mathematical models give insight into the dynamics of the spread of Wolbachia, the potential impact of Wolbachia on dengue transmission, and we discuss the remaining challenges in evaluation and development.