Assessing the role of multiple mechanisms increasing the age of dengue cases in Thailand

The epidemiology and identification of risk factors associated with severe dengue during the 2023 dengue outbreak in Kaohsiung City, Taiwan

After the previous major dengue fever (DF) outbreaks in 2014 and 2015 in Taiwan, the second-largest DF outbreak re-emerged in 2023. A total of 178 patients with laboratory-confirmed dengue virus (DENV) infection, including 92 DENV-1 and 86 DENV-2 cases, were enrolled in this study conducted during the 2023 dengue outbreak in Kaohsiung City, Taiwan. This study aimed to analyze epidemiological characteristics, clinical severity, and risk factors for severe dengue (SD), as well as the diagnostic implications of the non-structural protein 1 (NS1) antigen rapid test. Patients infected with DENV-2 exhibited significantly older age, higher incidence of secondary infections, diabetes mellitus (DM), hypertension (HT), and longer hospital stays than patients infected with DENV-1. Multivariate analysis revealed that older age (age ≥65), secondary dengue infection, DM, and HT were significant independent predictors of SD. Compared with non-SD cases, SD patients were significantly more likely to be older (age ≥65), to exhibit a higher incidence of secondary infections and a greater prevalence of chronic diseases, including DM and HT. Notably, dengue-confirmed patients with negative NS1 results had a shorter duration since symptom onset (p < 0.001). Our DENV-1 and DENV-2 isolates are related to strains from neighboring Asian countries. Our findings emphasize the important factors of old age, secondary infections, and chronic diseases that contributed to dengue severity. We should meticulously manage these high-risk groups to prevent dengue progression. Screening incoming travelers for DF during the epidemic season will be an important measure to prevent the introduction of DENV into Taiwan.

Proceedings of the second annual dengue endgame summit: A call to action

On August 7-9, 2024, the second annual dengue "endgame" summit was held in Syracuse, NY, hosted by the Global Health Institute at SUNY Upstate Medical University. The meeting brought together attendees from around the world, with talks spanning healthcare, government control programs, basic research, and medical countermeasure development efforts. The summit goal was to work toward a better understanding of what dengue control could look like and the steps required to reach such a goal. The objectives of the meeting were to discuss the current global state of dengue, what dengue "control" might look like, and to discuss actionable pathways for achieving dengue control. Topics covered throughout the meeting included DENV immunity and pathogenesis, challenges in countermeasure development, innovative vector control strategies, dengue diagnostics, addressing challenges in science communication, and vaccine hesitancy. Several fundamental knowledge gaps were repeatedly highlighted by the summit attendees and were cited as critical barriers to the development, deployment, and evaluation of effective dengue countermeasures. These gaps include (1) the lack of a broadly applicable immunologic biomarker/correlate of DENV immunity and (2) the lack of universally accepted/applicable metrics for quantifying dengue severity in the setting of countermeasure evaluations. In addition, the lack of clear and consistent international leadership in the global dengue control effort was cited as a barrier to widespread and synergistic research and countermeasure development/deployment activities. Despite these persistent roadblocks, summit attendees expressed optimism that holistic and multi-tiered approaches-incorporating optimal use of existing and nascent countermeasure technologies deployed in collaboration with local communities-could be effective in progressing toward dengue control.

Assessing the global dengue burden: Incidence, mortality, and disability trends over three decades

BACKGROUND

Dengue, the fastest-spreading vector-borne disease (VBD), significantly burdens global health systems. This study analyzed the trends in the global burden of dengue from 1990 to 2021, utilizing data from the Global Burden of Diseases, Injuries, and Risk Factors Study 2021 (GBD 2021).

METHODOLOGY/PRINCIPAL FINDINGS

We retrieved data from GBD 2021 regarding dengue, including the number of incidences and age-standardized incidence rate (ASIR), the number of deaths and age-standardized death rate (ASDR), disability-adjusted life-years (DALYs) and age-standardized DALYs. The estimated annual percentage change (EAPC) of ASIR, ASDR, and standardized DALYs rate was calculated to quantify trends over time. In addition, the correlations between dengue burden and sea level rise, as well as the Socio-Demographic Index (SDI), were evaluated. In this study, it was observed that from 1990 to 2021, the global incidence of dengue escalated from 26.45 million to 58.96 million cases, accompanied by an increase in related deaths from 14,315 to 29,075, and DALYs rising from 1.25 million to 2.08 million years. These data collectively indicate that the disease burden approximately doubled, with South Asia, Southeast Asia, and tropical Latin America being the most severely affected regions. The disease burden remained substantial in middle and low-middle-SDI regions, whereas high-middle and high SDI regions experienced pronounced growth rates in ASIR, ASDR, and age-standardized DALYs rate. Adolescents and the elderly showed higher incidence, yet children under 5 had the highest DALYs. Correlation analyses revealed an inverted U-shaped relationship between the SDI and both the ASDR and age-standardized DALYs rate, and changes in sea level height strongly correlated with the overall dengue burden.

CONCLUSIONS/SIGNIFICANCE

The global dengue burden has surged due to climate change, vector transmission, and population mobility. Increased focus and tailored control strategies are essential, particularly in South Asia, Southeast Asia, and Latin America.

Recommendations for dengue vaccine implementation in the elderly population

Dengue is a mosquito-borne flaviviral disease that is endemic to tropical and subtropical regions, affecting hundreds of millions of people worldwide. Although it was once considered a neglected disease, the incidence and mortality rates of dengue have surged over the past decade, in part due to the expanding distribution of the Aedes spp. vector facilitated by changing climatic factors. While most infections are asymptomatic or cause mild flu-like symptoms, some cases can develop into severe forms, leading to serious complications. The burden of the disease is gradually shifting from primarily affecting children, whose immune systems are immature, to increasingly impacting the older population, who typically experience waning immune responsiveness and comorbidities. With no specific treatment available, the development of a prophylactic vaccine is crucial for long-term control and prevention. School-age children are the primary target group for immunization programs of the two recently licensed dengue vaccines. However, there is limited information on the efficacy of either vaccine among the elderly or of two further immunogenic preparations currently undergoing clinical trials. This review gives an update on dengue vaccine implementation and provides recommendations for the vaccination of persons aged 60 years and above.

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 is 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, has not been assessed. Using 26 y 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 were 1.75 to 4.05 times higher than case-derived FOI. Seroprevalence-derived was moderately correlated with case-derived FOI (correlation coefficient = 0.47) with slightly lower estimates. 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.

Epidemiology of imported travelers with dengue fever in Taiwan from 2011 to 2020

We collected data on imported dengue cases between 2011 and 2020 from Taiwan's Centers for Disease Control to determine changes in the case number and importation rate of dengue. We used open data provided by Taiwan's Centers for Disease Control to extract the number of confirmed imported cases of dengue between 2011 and 2020. From 2011 to 2020, 2883 imported cases of dengue were reported in Taiwan. The importation rate was 25.8 to 46.4 per 100,000 inbound travelers from 2011 to 2020, peaking in 2020. Disease incidence varied between sexes, age groups, seasons (P < .001), and residence from 2011 to 2020. Numerous dengue cases were imported from Indonesia (548 cases), Vietnam (516 cases), and the Philippines (500). For travelers from Taiwan, the risk ratio of becoming infected by dengue was 31,712 for traveling to the Maldives, 3153 to Cambodia, and 996 to Myanmar. In this study, more serotype 1 and 2 strains were reported by Vietnam, and more serotype 3 and 4 strains were reported by Indonesia. Our data indicate that the rate of imported cases of dengue significantly increased annually from 2011 to 2020 in Taiwan, especially during the COVID-19 pandemic (46.4 per 100,000 inbound travelers).

Per vaginal bleeding-an important but ignored feature of dengue

Background

Elderly individuals, those with comorbidities and pregnant women are at a higher risk of developing severe dengue and succumbing to their illness. However, an increased incidence of severe dengue and fatalities are seen in females of the reproductive age. As per vaginal (PV) bleeding is an important complication that has not been well characterized, we sought to determine the frequency, complications and disease outcomes in women who develop PV bleeding.

Methodology/Principal findings

288 adult female patients were recruited from the National Institute of Infectious Diseases Sri Lanka. All clinical features and laboratory investigations were recorded throughout the duration of hospital admission along with treatment received.28/288 (9.72%) reported PV bleeding, with 12/28 (42.85%) developing dengue haemorrhagic fever (DHF) compared to 65/260 (25%) of those who did not have bleeding.Women who developed PV bleeding were more likely to have developed DHF (OR 2.2, 95% CI 0.98 to 5.1, p=0.06), abdominal pain (OR=2.17, 95% CI = 0.99 to 4.69, p = 0.06), vomiting (OR= 2.0, 95% CI= 0.89 to 4.44, p= 0.10), diarhoea (OR= 4.35, 95% CI = 1.908 to 9.610, p= 0.0004) or evidence of any fluid leakage (OR= 1.98, 95% CI = 0.91 to 4.5, p = 0.11). Although not significant, those who had PV bleeding were more likely to have been given intravenous fluids, blood transfusions and colloids.

Conclusions

PV bleeding appears to associate with worse disease outcomes. The possible contribution of PV bleeding to higher incidence of severe dengue and fatality rates observed in many countries, should be further investigated.

Dengue in Pune city, India (2017-2019): a comprehensive analysis

Objectives

To understand the dynamics of dengue disease with special reference to (1) age (2) primary/secondary infections (3) serostatus and (4) serotypes examined during three consecutive years.

Methods

During 3 dengue seasons (2017-19), NS1/IgM ELISAs were used for dengue diagnosis in one of the 15 administrative wards of Pune City, India. Predefined symptoms were recorded at the time of diagnosis/hospitalization. IgG-capture ELISA (Panbio) was used to differentiate primary/secondary infections. DENV serotypes were determined for 260 viral RNA-positive patients.

Results

During the 3 years, 3,014/6,786 (44.4%, 41.4-49.9%) suspected cases were diagnosed as dengue. Use of either NS1 or IgM would have missed 25.5% or 43% of the confirmed dengue cases, respectively. Notably, a higher proportion of secondary dengue cases remained mild while a substantial proportion of primary infections developed warning signs. The symptoms among Dengue/non-dengue patients and primary/secondary infections varied and influenced by age and serostatus. The number and proportion of dengue serotypes varied yearly. A remarkable decline in dengue cases was observed during the COVID-19 pandemic years.

Conclusion

A substantial proportion of primary and secondary dengue patients progress to warning signs/severity or mild infection respectively, underscoring the possible role of non-ADE mechanisms in causing severe dengue that requires hospitalization. Both NS1 and IgM should be used for efficient diagnosis.

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.

Climate, demography, immunology, and virology combine to drive two decades of dengue virus dynamics in Cambodia

The incidence of dengue virus disease has increased globally across the past half-century, with highest number of cases ever reported in 2019 and again in 2023. We analyzed climatological, epidemiological, and phylogenomic data to investigate drivers of two decades of dengue in Cambodia, an understudied endemic setting. Using epidemiological models fit to a 19-y dataset, we first demonstrate that climate-driven transmission alone is insufficient to explain three epidemics across the time series. We then use wavelet decomposition to highlight enhanced annual and multiannual synchronicity in dengue cycles between provinces in epidemic years, suggesting a role for climate in homogenizing dynamics across space and time. Assuming reported cases correspond to symptomatic secondary infections, we next use an age-structured catalytic model to estimate a declining force of infection for dengue through time, which elevates the mean age of reported cases in Cambodia. Reported cases in >70-y-old individuals in the 2019 epidemic are best explained when also allowing for waning multitypic immunity and repeat symptomatic infections in older patients. We support this work with phylogenetic analysis of 192 dengue virus (DENV) genomes that we sequenced between 2019 and 2022, which document emergence of DENV-2 Cosmopolitan Genotype-II into Cambodia. This lineage demonstrates phylogenetic homogeneity across wide geographic areas, consistent with invasion behavior and in contrast to high phylogenetic diversity exhibited by endemic DENV-1. Finally, we simulate an age-structured, mechanistic model of dengue dynamics to demonstrate how expansion of an antigenically distinct lineage that evades preexisting multitypic immunity effectively reproduces the older-age infections witnessed in our data.

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.

Projection of dengue fever transmissibility under climate change in South and Southeast Asian countries

Vector-borne infectious disease such as dengue fever (DF) has spread rapidly due to more suitable living environments. Considering the limited studies investigating the disease spread under climate change in South and Southeast Asia, this study aimed to project the DF transmission potential in 30 locations across four South and Southeast Asian countries. In this study, weekly DF incidence data, daily mean temperature, and rainfall data in 30 locations in Singapore, Sri Lanka, Malaysia, and Thailand from 2012 to 2020 were collected. The effects of temperature and rainfall on the time-varying reproduction number (Rt) of DF transmission were examined using generalized additive models. Projections of location-specific Rt from 2030s to 2090s were determined using projected temperature and rainfall under three Shared Socioeconomic Pathways (SSP126, SSP245, and SSP585), and the peak DF transmissibility and epidemic duration in the future were estimated. According to the results, the projected changes in the peak Rt and epidemic duration varied across locations, and the most significant change was observed under middle-to-high greenhouse gas emission scenarios. Under SSP585, the country-specific peak Rt was projected to decrease from 1.63 (95% confidence interval: 1.39-1.91), 2.60 (1.89-3.57), and 1.41 (1.22-1.64) in 2030s to 1.22 (0.98-1.51), 2.09 (1.26-3.47), and 1.37 (0.83-2.27) in 2090s in Singapore, Thailand, and Malaysia, respectively. Yet, the peak Rt in Sri Lanka changed slightly from 2030s to 2090s under SSP585. The epidemic duration in Singapore and Malaysia was projected to decline under SSP585. In conclusion, the change of peak DF transmission potential and disease outbreak duration would vary across locations, particularly under middle-to-high greenhouse gas emission scenarios. Interventions should be considered to slow down global warming as well as the potential increase in DF transmissibility in some locations of South and Southeast Asia.

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.

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.

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.

Facing the escalating burden of dengue: Challenges and perspectives

Dengue is the most rapidly emerging mosquito-borne infection and, due to climate change and unplanned urbanization, it is predicted that the global burden of dengue will rise further as the infection spreads to new geographical locations. Dengue-endemic countries are often unable to cope with such increases, with health care facilities becoming overwhelmed during each dengue season. Furthermore, although dengue has been predominantly a childhood illness in the past, it currently mostly affects adults in many countries, with higher incidence of severe disease and mortality rates in pregnant women and in those with comorbidities. As there is currently no specific treatment for dengue and no early biomarker to identify those who will progress to develop vascular leakage, all individuals with dengue are closely monitored in case they need fluid management. Furthermore, diagnosing patients with acute dengue is challenging due to the similarity of clinical symptoms during early illness and poor sensitivity and specificity of point-of-care diagnostic tests. Novel vector control methods, such as the release of Wolbachia-infected mosquitoes, have shown promising results by reducing vector density and dengue incidence in clinical trial settings. A new dengue vaccine, TAK-003, had an efficacy of 61.2% against virologically confirmed dengue, 84.1% efficacy against hospitalizations and a 70% efficacy against development of dengue haemorrhagic fever (DHF) at 54 months. While vaccines and mosquito control methods are welcome, they alone are unlikely to fully reduce the burden of dengue, and a treatment for dengue is therefore essential. Several novel antiviral drugs are currently being evaluated along with drugs that inhibit host mediators, such as mast cell products. Although viral proteins such as NS1 contribute to the vascular leak observed in severe dengue, the host immune response to the viral infection also plays a significant role in progression to severe disease. There is an urgent need to discover safe and effective treatments for dengue to prevent disease progression.

Interactions between climate change, urban infrastructure and mobility are driving dengue emergence in Vietnam

Dengue is expanding globally, but how dengue emergence is shaped locally by interactions between climatic and socio-environmental factors is not well understood. Here, we investigate the drivers of dengue incidence and emergence in Vietnam, through analysing 23 years of district-level case data spanning a period of significant socioeconomic change (1998-2020). We show that urban infrastructure factors (sanitation, water supply, long-term urban growth) predict local spatial patterns of dengue incidence, while human mobility is a more influential driver in subtropical northern regions than the endemic south. Temperature is the dominant factor shaping dengue's distribution and dynamics, and using long-term reanalysis temperature data we show that warming since 1950 has expanded transmission risk throughout Vietnam, and most strongly in current dengue emergence hotspots (e.g., southern central regions, Ha Noi). In contrast, effects of hydrometeorology are complex, multi-scalar and dependent on local context: risk increases under either short-term precipitation excess or long-term drought, but improvements in water supply mitigate drought-associated risks except under extreme conditions. Our findings challenge the assumption that dengue is an urban disease, instead suggesting that incidence peaks in transitional landscapes with intermediate infrastructure provision, and provide evidence that interactions between recent climate change and mobility are contributing to dengue's expansion throughout Vietnam.

Non-linear associations between meteorological factors, ambient air pollutants and major mosquito-borne diseases in Thailand

BACKGROUND

Transmission intensity for mosquito-borne diseases are highly heterogenous and multi-factorial. Understanding risk factors associated to disease transmission allow the optimization of vector control. This study sets out to understand and compare the combined anthropogenic and environmental risk factors of four major mosquito-borne diseases, dengue, malaria, chikungunya and Japanese encephalitis in Thailand.

METHODS

An integrated analysis of mosquito-borne diseases, meteorological and ambient air pollutants of 76 provinces of Thailand was conducted over 2003-2021. We explored the use of generalized linear models and generalized additive models to consider both linear and non-linear associations between meteorological factors, ambient air pollutants and mosquito-borne disease incidence. Different assumptions on spatio-temporal dependence and nonlinearity were considered through province-specific and panel models, as well as different spline functions. Disease-specific model evidence was assessed to select best-fit models for epidemiological inference downstream.

RESULTS

Analyses indicated several findings which can be generally applied to all diseases explored: (1) higher AH above mean values was positively associated with disease case counts (2) higher total precipitation above mean values was positively associated with disease case counts (3) extremely high temperatures were negatively associated with disease case counts (4) higher SO2 and PM2.5 surface concentrations were negatively associated with disease case counts. However, the relationships between disease and RH, non-extreme temperatures and CO surface concentration were more mixed, with directions of associations changing across the different diseases considered.

CONCLUSIONS

This study found protective and enhancing effects of meteorological and ambient air pollutant factors on mosquito-borne diseases burdens in Thailand. Further studies should employ these factors to understand and predict risk factors associated with mosquito-borne disease transmission.

Dengue virus serotype did not contribute to clinical severity or mortality in Taiwan's largest dengue outbreak in 2015

BACKGROUND

Dengue virus serotype 2 (DENV-2) was the major serotype in the 2015 dengue outbreak in Taiwan, while DENV-1 and DENV-3 were dominant between 2005 and 2014. We aimed to investigate whether DENV-2 contributed to disease severity and mortality in the outbreak in Kaohsiung city, Taiwan.

METHODS

We collected serum samples from dengue patients to detect the presence of DENV and determine the serotypes by using quantitative reverse transcription-polymerase chain reaction. Our cohorts comprised 105 DENV-1-infected cases and 1,550 DENV-2-infected cases. Demographic data, DENV serotype, and comorbidities were covariates for univariate and multivariate analyses to explore the association with severity and mortality.

RESULTS

The results suggested that DENV-1 persisted and circulated, while DENV-2 was dominant during the dengue outbreak that occurred between September and December 2015. However, DENV-2 did not directly contribute to either severity or mortality. Aged patients and patients with diabetes mellitus (DM) or moderate to severe chronic kidney disease (CKD) had a higher risk of developing severe dengue. The mortality of dengue patients was related to a higher Charlson comorbidity index score and severe dengue. Among DENV-2-infected patients and older patients, preexisting anti-dengue IgG, DM, and moderate to severe CKD were associated with severe dengue. Moreover, female sex and severe dengue were associated with a significantly higher risk of death.

CONCLUSIONS

Our findings highlight the importance of timely serological testing in elderly patients to identify potential secondary infections and focus on the meticulous management of elderly patients with DM or moderate to severe CKD to reduce dengue-related death.

Maternally derived antibody titer dynamics and risk of hospitalized infant dengue disease

Infants less than 1 y of age experience high rates of dengue disease in dengue virus (DENV) endemic countries. This burden is commonly attributed to antibody-dependent enhancement (ADE), whereby concentrations of maternally derived DENV antibodies become subneutralizing, and infection-enhancing. Understanding antibody-related mechanisms of enhanced infant dengue disease risk represents a significant challenge due to the dynamic nature of antibodies and their imperfect measurement processes. Further, key uncertainties exist regarding the impact of long-term shifts in birth rates, population-level infection risks, and maternal ages on the DENV immune landscape of newborns and their subsequent risks of severe dengue disease in infancy. Here, we analyze DENV antibody data from two infant cohorts (N = 142 infants with 605 blood draws) and 40 y of infant dengue hospitalization data from Thailand. We use mathematical models to reconstruct maternally derived antibody dynamics, accounting for discretized measurement processes and limits of assay detection. We then explore possible antibody-related mechanisms of enhanced infant dengue disease risk and their ability to reconstruct the observed age distribution of hospitalized infant dengue cases. We find that ADE mechanisms are best able to reconstruct the observed data. Finally, we describe how the shifting epidemiology of dengue in Thailand, combined with declining birth rates, have decreased the absolute risk of infant dengue disease by 88% over a 40-y period while having minimal impact on the mean age of infant hospitalized dengue disease.

Projecting the future incidence and burden of dengue in Southeast Asia

The recent global expansion of dengue has been facilitated by changes in urbanisation, mobility, and climate. In this work, we project future changes in dengue incidence and case burden to 2099 under the latest climate change scenarios. We fit a statistical model to province-level monthly dengue case counts from eight countries across Southeast Asia, one of the worst affected regions. We project that dengue incidence will peak this century before declining to lower levels with large variations between and within countries. Our findings reveal that northern Thailand and Cambodia will show the biggest decreases and equatorial areas will show the biggest increases. The impact of climate change will be counterbalanced by income growth, with population growth having the biggest influence on increasing burden. These findings can be used for formulating mitigation and adaptation interventions to reduce the immediate growing impact of dengue virus in the region.

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.

Antigenic diversity and dengue disease risk

Many pathogens continuously change their protein structure in response to immune-driven selection, resulting in weakened protection. 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 a mystery whether the antigenic distance between an individual's first infection and subsequent exposures dictate disease risk, explaining the observed large-scale differences in dengue hospitalisations across years. Here we develop an inferential framework that combines detailed antigenic and genetic characterisation of viruses, and hospitalised cases from 21 years of surveillance in Bangkok, Thailand to identify the role of the antigenic profile of circulating viruses in determining disease risk. We find that the risk of hospitalisation depends on both the specific order of infecting serotypes and the antigenic distance between an individual's primary and secondary infections, with risk maximised at intermediate antigenic distances. These findings suggest immune imprinting helps determine dengue disease risk, and provides a pathway to monitor the changing risk profile of populations and to quantifying risk profiles of candidate vaccines.

Advanced Age and Increased Risk for Severe Outcomes of Dengue Infection, Taiwan, 2014-2015

Dengue, a mosquitoborne flavivirus infection, is increasingly a disease of older adults who are more likely to have chronic diseases that confer risk for severe outcomes of dengue infection. In a population-based study in Taiwan, adjusted risks for dengue-related hospitalization, intensive care unit admission, and death increased progressively with age.

Estimating Dengue Transmission Intensity in China Using Catalytic Models Based on Serological Data

In recent decades, the global incidence of dengue has risen sharply, with more than 75% of infected people showing mild or no symptoms. Since the year 2000, dengue in China has spread quickly. At this stage, there is an urgent need to fully understand its transmission intensity and spread in China. Serological data provide reliable evidence for symptomatic and recessive infections. Through a literature search, we included 23 studies that collected age-specific serological dengue data released from 1980 to 2021 in China. Fitting four catalytic models to these data, we distinguished the transmission mechanisms by deviation information criterion and estimated force of infection and basic reproduction number (R₀), important parameters for quantifying transmission intensity. We found that transmission intensity varies over age in most of the study populations, and attenuation of antibody protection is identified in some study populations; the R₀ of dengue in China is between 1.04-2.33. Due to the scarceness of the data, the temporal trend cannot be identified, but data shows that transmission intensity weakened from coastal to inland areas and from southern to northern areas in China if assuming it remained temporally steady during the study period. The results should be useful for the effective control of dengue in China.

Dengue algorithms integrated into the IMCI guidelines: An updated assessment in five Southeast-Asian countries

Background

Dengue is not included explicitly in the WHO Integrated Management of Childhood Illness (IMCI) algorithm. However, the assessment, classification and management of dengue has been incorporated into several IMCI country adaptations. We aimed to evaluate the dengue algorithms incorporated into IMCI guidelines and discuss the need for harmonization, including an extension of the age range for IMCI.

Methods

This study included three steps. First, we investigated dengue algorithms incorporated into five Southeast-Asian (Myanmar, Philippines, Vietnam, Indonesia, Cambodia) country IMCI guidelines through a desk-based analysis. Second, we conducted an expert survey to elicit opinions regarding the integration of dengue and extension of the age range in IMCI. Third, we compared our findings with data from a large multicentric prospective study on acute febrile illness.

Results

We found considerable heterogeneity between the country specific IMCI guidelines in the dengue algorithms as well as classification schemes. Most guidelines did not differentiate between diagnostic algorithms for the detection of dengue versus other febrile illness, and warning signs for progression to severe dengue. Our expert survey resulted in a consensus to further integrate dengue in IMCI and extend the age range for IMCI guidelines beyond 5 years of age. Most of the interviewees responded that their country had a stand-alone clinical guideline for dengue, which was not integrated into the IMCI approach and considered laboratory testing for dengue necessary on day three of consecutive fever. Using data from a large multicentric study of children 5–15 years of age, we could confirm that the likelihood of dengue increased with consecutive fever days. However, a significant proportion of children (36%) would be missed if laboratory testing was only offered on the third consecutive day of fever.

Conclusions

This study supports the extension of the IMCI age range beyond 5 years of age as well as the inclusion of dengue relevant content in the algorithm. Because of the challenge of distinguishing dengue from other febrile illnesses, simple laboratory testing (e.g., full blood count) should be offered at an early stage during the course of the illness. Testing only children with consecutive fever over 3 days may lead to an underdiagnosis of dengue among those with acute febrile illness in children 5–15 years of age. In addition, specific laboratory testing for dengue should be made available to peripheral health facilities.

The Integrated Management of Childhood Illness (IMCI) was developed for the identification and treatment of major childhood illnesses based on a syndromic approach that can be applied by local health care workers in rural health facilities. Dengue represents an important differential diagnosis for children and adolescents with acute febrile illness in Southeast Asia but is not officially included in the fever module of IMCI. Local adaptations in different countries, however, have integrated dengue into their guidelines. We analysed the available local IMCI guidelines in Southeast Asia, conducted an expert survey, and investigated out findings using data from a large multicentric prospective study on acute febrile illness. Our findings support the extension of the age range for IMCI and the inclusion of dengue relevant content. When children presented with fever, the likelihood of dengue increased with consecutive fever days. We were able to quantify how likely dengue is as a cause of fever in children living in endemic areas, stratified by duration of fever. This evidence is useful for policy makers to consider the effect of more specific diagnostic tools for the monitoring of early dengue.