A Review of Dengue's Historical and Future Health Risk from a Changing Climate

The current status of arboviruses with major epidemiological significance in Europe

Currently, an increasing impact of some arboviruses has been observed in Europe, mainly Dengue (DENV), Chikungunya (CHIKV), Zika (ZIKV), West Nile (WNV), and Crimean-Congo hemorrhagic fever (CCHFV) analyzed through a One Health perspective that considers their expansion across the continent. Arboviruses are primarily transmitted by vectors such as mosquitoes and ticks, with human activities and climate change playing crucial roles in their spread. The review highlights the ecological and epidemiological aspects of arboviruses, emphasizing the roles of diverse hosts and reservoirs, including humans, animals, and vectors, in their life cycles. The influence of climate change on the ecology of the vector, which potentially favors the arbovirus transmission, is also reviewed. Focusing on diagnosis, prevention and in the absence of specific treatments, the importance of understanding vector-host interactions and environmental impacts to develop effective control and prevention strategies is emphasized. Ongoing research on vaccines and therapies is crucial to mitigate the public health impact of these diseases.

Epidemiological characteristics and transmission dynamics of dengue fever in China

China has experienced successive waves of dengue epidemics over the past decade. Nationwide data on 95,339 dengue cases, 89 surveillance sites for mosquito density and population mobility between 337 cities during 2013-20 were extracted. Weekly dengue time series including time trends and harmonic terms were fitted using seasonal regression models, and the amplitude and peak timing of the annual and semiannual cycles were estimated. A data-driven model-inference approach was used to simulate the epidemic at city-scale and estimate time-evolving epidemiological parameters. We found that the geographical distribution of dengue cases was expanding, and the main imported areas as well as external sources of imported cases changed. Dengue cases were predominantly concentrated in southern China and it exhibited an annual peak of activity, typically peaking in September. The annual amplitude of dengue epidemic varied with latitude (F = 19.62, P = 0.0001), mainly characterizing by large in southern cities and small in northern cities. The effective reproduction number Reff across cities is commonly greater than 1 in several specific months from July to November, further confirming the seasonal fluctuations and spatial heterogeneity of dengue epidemics. The results of this national study help to better informing interventions for future dengue epidemics in China.

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.

Two decades of endemic dengue in Bangladesh (2000-2022): trends, seasonality, and impact of temperature and rainfall patterns on transmission dynamics

The objectives of this study were to compare dengue virus (DENV) cases, deaths, case-fatality ratio [CFR], and meteorological parameters between the first and the recent decades of this century (2000-2010 vs. 2011-2022) and to describe the trends, seasonality, and impact of change of temperature and rainfall patterns on transmission dynamics of dengue in Bangladesh. For the period 2000-2022, dengue cases and death data from Bangladesh's Ministry of Health and Family Welfare's website, and meteorological data from the Bangladesh Meteorological Department were analyzed. A Poisson regression model was performed to identify the impact of meteorological parameters on the monthly dengue cases. A forecast of dengue cases was performed using an autoregressive integrated moving average model. Over the past 23 yr, a total of 244,246 dengue cases were reported including 849 deaths (CFR = 0.35%). The mean annual number of dengue cases increased 8 times during the second decade, with 2,216 cases during 2000-2010 vs. 18,321 cases during 2011-2022. The mean annual number of deaths doubled (21 vs. 46), but the overall CFR has decreased by one-third (0.69% vs. 0.23%). Concurrently, the annual mean temperature increased by 0.49 °C, and rainfall decreased by 314 mm with altered precipitation seasonality. Monthly mean temperature (Incidence risk ratio [IRR]: 1.26), first-lagged rainfall (IRR: 1.08), and second-lagged rainfall (IRR: 1.17) were significantly associated with monthly dengue cases. The increased local temperature and changes in rainfall seasonality might have contributed to the increased dengue cases in Bangladesh.

Enabling countries to manage outbreaks: statistical, operational, and contextual analysis of the early warning and response system (EWARS-csd) for dengue outbreaks

Introduction

Dengue is currently the fastest-spreading mosquito-borne viral illness in the world, with over half of the world's population living in areas at risk of dengue. As dengue continues to spread and become more of a health burden, it is essential to have tools that can predict when and where outbreaks might occur to better prepare vector control operations and communities' responses. One such predictive tool, the Early Warning and Response System for climate-sensitive diseases (EWARS-csd), primarily uses climatic data to alert health systems of outbreaks weeks before they occur. EWARS-csd uses the robust Distribution Lag Non-linear Model in combination with the INLA Bayesian regression framework to predict outbreaks, utilizing historical data. This study seeks to validate the tool's performance in two states of Colombia, evaluating how well the tool performed in 11 municipalities of varying dengue endemicity levels.

Methods

The validation study used retrospective data with alarm indicators (mean temperature and rain sum) and an outbreak indicator (weekly hospitalizations) from 11 municipalities spanning two states in Colombia from 2015 to 2020. Calibrations of different variables were performed to find the optimal sensitivity and positive predictive value for each municipality.

Results

The study demonstrated that the tool produced overall reliable early outbreak alarms. The median of the most optimal calibration for each municipality was very high: sensitivity (97%), specificity (94%), positive predictive value (75%), and negative predictive value (99%; 95% CI).

Discussion

The tool worked well across all population sizes and all endemicity levels but had slightly poorer results in the highly endemic municipality at predicting non-outbreak weeks. Migration and/or socioeconomic status are factors that might impact predictive performance and should be further evaluated. Overall EWARS-csd performed very well, providing evidence that it should continue to be implemented in Colombia and other countries for outbreak prediction.

Quantifying the impact of Wolbachia releases on dengue infection in Townsville, Australia

From October 2014 to February 2019, local authorities in Townsville, North Queensland, Australia continually introduced Wolbachia-infected mosquitoes to control seasonal outbreaks of dengue infection. In this study, we develop a mathematical modelling framework to estimate the effectiveness of this intervention as well as the relative dengue transmission rates of Wolbachia-infected and wild-type mosquitoes. We find that the transmission rate of Wolbachia-infected mosquitoes is reduced approximately by a factor of 20 relative to the uninfected wild-type population. In addition, the Townsville Wolbachia release program led to a 65% reduction in predicted dengue incidence during the release period and over 95% reduction in the 24 months that followed. Finally, to investigate the potential impact of other Wolbachia release programs, we use our estimates of relative transmissibility to calculate the relationship between the reproductive number of dengue and the proportion of Wolbachia-infected mosquitoes in the vector population.

Assessing the Relationship between Annual Surface Temperature Changes and the Burden of Dengue: Implications for Climate Change and Global Health Outcomes

Dengue fever remains a significant global health concern, imposing a substantial burden on public health systems worldwide. Recent studies have suggested that climate change, specifically the increase in surface temperatures associated with global warming, may impact the transmission dynamics of dengue. This study aimed to assess the relationship between annual surface temperature changes from 1961 to 2019 and the burden of dengue in 185 countries. The dengue burden was evaluated for 2019 using disability-adjusted life years (DALYs) and the annual rate of change (ARC) in DALY rates assessed from 1990 to 2019. A cross-sectional and ecological analysis was conducted using two publicly available datasets. Regression coefficients (β) and 95% confidence intervals (CI) were used to examine the relationship between annual surface temperature changes and the burden of dengue. The results revealed a significant negative relationship between mean surface temperatures and DALY rates in 2019 (β = -16.9, 95% CI -26.9 to -6.8). Similarly, a significant negative relationship was observed between the temperature variable and the ARC (β = -0.99, 95% CI -1.66 to -0.32). These findings suggest that as temperatures continue to rise, the burden of dengue may globally decrease. The ecology of the vector and variations in seasons, precipitation patterns, and humidity levels may partially contribute to this phenomenon. Our study contributes to the expanding body of evidence regarding the potential implications of climate change for dengue dynamics. It emphasizes the critical importance of addressing climate change as a determinant of global health outcomes.

Climate change and Aedes albopictus risks in China: current impact and future projection

BACKGROUND

Future distribution of dengue risk is usually predicted based on predicted climate changes using general circulation models (GCMs). However, it is difficult to validate the GCM results and assess the uncertainty of the predictions. The observed changes in climate may be very different from the GCM results. We aim to utilize trends in observed climate dynamics to predict future risks of Aedes albopictus in China.

METHODS

We collected Ae. albopictus surveillance data and observed climate records from 80 meteorological stations from 1970 to 2021. We analyzed the trends in climate change in China and made predictions on future climate for the years 2050 and 2080 based on trend analyses. We analyzed the relationship between climatic variables and the prevalence of Ae. albopictus in different months/seasons. We built a classification tree model (based on the average of 999 runs of classification and regression tree analyses) to predict the monthly/seasonal Ae. albopictus distribution based on the average climate from 1970 to 2000 and assessed the contributions of different climatic variables to the Ae. albopictus distribution. Using these models, we projected the future distributions of Ae. albopictus for 2050 and 2080.

RESULTS

The study included Ae. albopictus surveillance from 259 sites in China found that winter to early spring (November-February) temperatures were strongly correlated with Ae. albopictus prevalence (prediction accuracy ranges 93.0-98.8%)-the higher the temperature the higher the prevalence, while precipitation in summer (June-September) was important predictor for Ae. albopictus prevalence. The machine learning tree models predicted the current prevalence of Ae. albopictus with high levels of agreement (accuracy > 90% and Kappa agreement > 80% for all 12 months). Overall, winter temperature contributed the most to Ae. albopictus distribution, followed by summer precipitation. An increase in temperature was observed from 1970 to 2021 in most places in China, and annual change rates varied substantially from -0.22 ºC/year to 0.58 ºC/year among sites, with the largest increase in temperature occurring from February to April (an annual increase of 1.4-4.7 ºC in monthly mean, 0.6-4.0 ºC in monthly minimum, and 1.3-4.3 ºC in monthly maximum temperature) and the smallest in November and December. Temperature increases were lower in the tropics/subtropics (1.5-2.3 ºC from February-April) compared to the high-latitude areas (2.6-4.6 ºC from February-April). The projected temperatures in 2050 and 2080 by this study were approximately 1-1.5 °C higher than those projected by GCMs. The estimated current Ae. albopictus risk distribution had a northern boundary of north-central China and the southern edge of northeastern China, with a risk period of June-September. The projected future Ae. albopictus risks in 2050 and 2080 cover nearly all of China, with an expanded risk period of April-October. The current at-risk population was estimated to be 960 million and the future at-risk population was projected to be 1.2 billion.

CONCLUSIONS

The magnitude of climate change in China is likely to surpass GCM predictions. Future dengue risks will expand to cover nearly all of China if current climate trends continue.

The Changing Climate and Pregnancy Health

PURPOSE OF REVIEW

Climate change is the biggest public health threat of the twenty-first century but its impact on the perinatal period has only recently received attention. This review summarizes recent literature regarding the impacts of climate change and related environmental disasters on pregnancy health and provides recommendations to inform future adaptation and mitigation efforts.

RECENT FINDINGS

Accumulating evidence suggests that the changing climate affects pregnancy health directly via discrete environmental disasters (i.e., wildfire, extreme heat, hurricane, flood, and drought), and indirectly through changes in the natural and social environment. Although studies vary greatly in design, analytic methods, and assessment strategies, they generally converge to suggest that climate-related disasters are associated with increased risk of gestational complication, pregnancy loss, restricted fetal growth, low birthweight, preterm birth, and selected delivery/newborn complications. Window(s) of exposure with the highest sensitivity are not clear, but both acute and chronic exposures appear important. Furthermore, socioeconomically disadvantaged populations may be more vulnerable. Policy, clinical, and research strategies for adaptation and mitigation should be continued, strengthened, and expanded with cross-disciplinary efforts. Top priorities should include (a) reinforcing and expanding policies to further reduce emission, (b) increasing awareness and education resources for healthcare providers and the public, (c) facilitating access to quality population-based data in low-resource areas, and (d) research efforts to better understand mechanisms of effects, identify susceptible populations and windows of exposure, explore interactive impacts of multiple exposures, and develop novel methods to better quantify pregnancy health impacts.

Dengue: A Growing Problem With New Interventions

Dengue is the disease caused by 1 of 4 distinct, but closely related dengue viruses (DENV-1-4) that are transmitted by Aedes spp. mosquito vectors. It is the most common arboviral disease worldwide, with the greatest burden in tropical and sub-tropical regions. In the absence of effective prevention and control measures, dengue is projected to increase in both disease burden and geographic range. Given its increasing importance as an etiology of fever in the returning traveler or the possibility of local transmission in regions in the United States with competent vectors, as well as the risk for large outbreaks in endemic US territories and associated states, clinicians should understand its clinical presentation and be familiar with appropriate testing, triage, and management of patients with dengue. Control and prevention efforts reached a milestone in June 2021 when the Advisory Committee on Immunization Practices (ACIP) recommended Dengvaxia for routine use in children aged 9 to 16 years living in endemic areas with laboratory confirmation of previous dengue virus infection. Dengvaxia is the first vaccine against dengue to be recommended for use in the United States and one of the first to require laboratory testing of potential recipients to be eligible for vaccination. In this review, we outline dengue pathogenesis, epidemiology, and key clinical features for front-line clinicians evaluating patients presenting with dengue. We also provide a summary of Dengvaxia efficacy, safety, and considerations for use as well as an overview of other potential new tools to control and prevent the growing threat of dengue .