Transmission dynamics of dengue and chikungunya in a changing climate: do we understand the eco-evolutionary response?

Adapting to the shifting landscape: Implications of climate change for malaria control: A review

Malaria, a global public health challenge, continues to affect millions of lives, particularly in regions where its transmission is endemic. The interplay between climate change and malaria dynamics has emerged as a critical concern, reshaping the landscape of this vector-borne disease. This review publication, titled "Adapting to the shifting landscape: Implications of climate change for malaria control," explores the multifaceted relationship between climate change and the control of malaria. The paper begins by dissecting the influence of climate change on malaria dynamics, including alterations in temperature, precipitation, and other climatic factors that impact the habitat and life cycle of malaria vectors. It delves into the evolving ecology and behavior of malaria vectors in response to changing climatic conditions, emphasizing the importance of understanding these adaptations. As a response to this shifting landscape, the review discusses adaptive strategies for malaria control, ranging from vector control measures to the utilization of climate data in early warning systems. Community engagement and education are highlighted as essential components of these strategies, recognizing the vital role of local communities in effective malaria control efforts. The paper also identifies future directions and research needs, underscoring the importance of staying ahead of the evolving climate-malaria relationship. This review underscores the urgency of adapting to the changing landscape of malaria transmission driven by climate change. It emphasizes the significance of proactively addressing climate-related challenges to enhance malaria control and protect the health and well-being of vulnerable populations.

Precision Prediction for Dengue Fever in Singapore: A Machine Learning Approach Incorporating Meteorological Data

OBJECTIVE

This study aimed to improve dengue fever predictions in Singapore using a machine learning model that incorporates meteorological data, addressing the current methodological limitations by examining the intricate relationships between weather changes and dengue transmission.

METHOD

Using weekly dengue case and meteorological data from 2012 to 2022, the data was preprocessed and analyzed using various machine learning algorithms, including General Linear Model (GLM), Support Vector Machine (SVM), Gradient Boosting Machine (GBM), Decision Tree (DT), Random Forest (RF), and eXtreme Gradient Boosting (XGBoost) algorithms. Performance metrics such as Mean Absolute Error (MAE), Root Mean Square Error (RMSE), and R-squared (R2) were employed.

RESULTS

From 2012 to 2022, there was a total of 164,333 cases of dengue fever. Singapore witnessed a fluctuating number of dengue cases, peaking notably in 2020 and revealing a strong seasonality between March and July. An analysis of meteorological data points highlighted connections between certain climate variables and dengue fever outbreaks. The correlation analyses suggested significant associations between dengue cases and specific weather factors such as solar radiation, solar energy, and UV index. For disease predictions, the XGBoost model showed the best performance with an MAE = 89.12, RMSE = 156.07, and R2 = 0.83, identifying time as the primary factor, while 19 key predictors showed non-linear associations with dengue transmission. This underscores the significant role of environmental conditions, including cloud cover and rainfall, in dengue propagation.

CONCLUSION

In the last decade, meteorological factors have significantly influenced dengue transmission in Singapore. This research, using the XGBoost model, highlights the key predictors like time and cloud cover in understanding dengue's complex dynamics. By employing advanced algorithms, our study offers insights into dengue predictive models and the importance of careful model selection. These results can inform public health strategies, aiming to improve dengue control in Singapore and comparable regions.

Patterns of Aedes aegypti abundance, survival, human-blood feeding and relationship with dengue risk, Kenya

Dengue virus (DENV) transmission risk is influenced by the bionomic traits of the key vector, Aedes aegypti. We investigated patterns of abundance, survival, and human blood-feeding of Ae. aegypti populations in two environments in Kenya: peri-urban Rabai (coastal Region, dengue-endemic) and rural Kerio Valley (Rift Valley Region, no reported dengue outbreak). In both environments, Ae. aegypti survival (estimated by parity), was inversely correlated with vector abundance, and this was influenced by weather conditions, notably temperature and relative humidity. In Rabai, Ae. aegypti mostly fed on humans (human blood index=51%), a pattern that corroborates with dengue cases in the coastal region. Aedes aegypti additionally, exhibited opportunistic feeding (livestock, rodents, reptiles, birds), suggesting the risk of human exposure to zoonotic pathogens via spillover transmission events aided by the vector. Abundance and human blood-feeding rates were consistently lower in Kerio Valley likely related to the degree of urbanization. Remarkably, the periods of high human feeding in Rabai coincided with high vector survival rates, a trend that could potentially drive intense DENV transmission at certain times of the year. We found a genetic influence of Ae. aegypti on the degree of anthropophagy but this could be influenced by potential seasonal shifts in human feeding. The findings of this study have implications both for DENV transmission risk and vector control strategies, but also in modeling which should integrate vector bionomic factors beyond vector abundance.

Climate and vector-borne diseases in Indonesia: a systematic literature review and critical appraisal of evidence

Climate is widely known as an important driver to transmit vector-borne diseases (VBD). However, evidence of the role of climate variability on VBD risk in Indonesia has not been adequately understood. We conducted a systematic literature review to collate and critically review studies on the relationship between climate variability and VBD in Indonesia. We searched articles on PubMed, Scopus, and Google Scholar databases that are published until December 2021. Studies that reported the relationship of climate and VBD, such as dengue, chikungunya, Zika, and malaria, were included. For the reporting, we followed the guidelines of the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) statement. A total of 66 out of 284 studies were reviewed. Fifty-two (78.8%) papers investigated dengue, 13 (19.7%) papers studied malaria, one (1.5%) paper discussed chikungunya, and no (0%) paper reported on Zika. The studies were predominantly conducted in western Indonesian cities. Most studies have examined the short-term effect of climate variability on the incidence of VBD at national, sub-national, and local levels. Rainfall (n = 60/66; 90.9%), mean temperature (T_mean) (n = 50/66; 75.8%), and relative humidity (RH) (n = 50/66; 75.8%) were the common climatic factors employed in the studies. The effect of climate on the incidence of VBD was heterogenous across locations. Only a few studies have investigated the long-term effects of climate on the distribution and incidence of VBD. The paucity of high-quality epidemiological data and variation in methodology are two major issues that limit the generalizability of evidence. A unified framework is required for future research to assess the impacts of climate on VBD in Indonesia to provide reliable evidence for better policymaking.

Climate change and human health in the Eastern Mediterranean and Middle East: Literature review, research priorities and policy suggestions

Human health is linked to climatic factors in complex ways, and climate change can have profound direct and indirect impacts on the health status of any given region. Susceptibility to climate change is modulated by biological, ecological and socio-political factors such as age, gender, geographic location, socio-economic status, occupation, health status and housing conditions, among other. In the Eastern Mediterranean and Middle East (EMME), climatic factors known to affect human health include extreme heat, water shortages and air pollution. Furthermore, the epidemiology of vector-borne diseases (VBDs) and the health consequences of population displacement are also influenced by climate change in this region. To inform future policies for adaptation and mitigation measures, and based on an extensive review of the available knowledge, we recommend several research priorities for the region. These include the generation of more empirical evidence on exposure-response functions involving climate change and specific health outcomes, the development of appropriate methodologies to evaluate the physical and psychological effects of climate change on vulnerable populations, determining how climate change alters the ecological determinants of human health, improving our understanding of the effects of long-term exposure to heat stress and air pollution, and evaluating the interactions between adaptation and mitigation strategies. Because national boundaries do not limit most climate-related factors expected to impact human health, we propose that adaptation/mitigation policies must have a regional scope, and therefore require collaborative efforts among EMME nations. Policy suggestions include a decisive region-wide decarbonisation, the integration of environmentally driven morbidity and mortality data throughout the region, advancing the development and widespread use of affordable technologies for the production and management of drinking water by non-traditional means, the development of comprehensive strategies to improve the health status of displaced populations, and fostering regional networks for monitoring and controlling the spread of infectious diseases and disease vectors.

Adaptation of a Human Diagnostic Kit to Detect Dengue, Zika, and Chikungunya Viruses in Mosquito Samples (Aedes aegypti and Aedes albopictus): A Contribution to Public Health in the International Triple Border (Brazil, Paraguay, and Argentina)

Objective: The objective of this work was to adapt a diagnostic kit developed for humans to identify Dengue (DENV1, DENV2, DENV3, DENV4), Zika (ZIKV) and Chikungunya virus (CHIKV) in females of Aedes aegypti and Aedes albopictus and to verify if the occurrence of mosquitoes infected with these three arboviruses are being found in regions with high occurrence of these diseases in humans. Materials and Methods: For this purpose, live mosquitoes were captured between January and June 2020 using 3,476 traps permanently installed in the field were used. After capture, the species were identified, then the females were placed in a pool of 2 to 10 specimens and sent to the laboratory for detection of DENV1, DENV2, DENV3, DENV4, ZIKV and CHIKV by RT-PCR using a commercial human kit for arboviruses. Results: Of the 76 mosquito pools collected, six (7.9%) pools tested positive for the DENV2 virus. The DENV-positive mosquitoes were collected in regions with a high incidence of reported cases of Dengue or in adjacent areas. Conclusion: The absence of kits for the detection of these arboviruses in Aedes is a limiting factor and the adequacy of commercial kits, already used for the diagnosis of arboviruses in humans, the results presented demonstrate that it is possible to identify the presence of DENV2 in mosquitoes with the respective kit, reinforcing the use of RT-qPCR as a robust diagnostic tool for epidemiological surveillance allowing managers to receive timely results for decision-making regarding prevention and control actions.

Dengue, Chikungunya, and Zika: Spatial and Temporal Distribution in Rio de Janeiro State, 2015–2019

Simultaneous spatial circulation of urban arboviral diseases, such as dengue, chikungunya, and Zika, is a major challenge. In this ecological study of urban arboviruses performed from 2015 to 2019, we analyzed the spatial and temporal dynamics of these arboviruses in all 92 municipalities and nine health regions of Rio de Janeiro state. Annual cumulative incidences are presented for all three arboviruses throughout the study period. Spatial analyses of the three studied arboviruses showed distinct behaviors among municipalities and health regions. Co-circulation of the three arboviruses in the state and a heterogeneous spatiotemporal pattern was observed for each disease and region, with dengue having a higher annual incidence during the five years of the study, as well as two consecutive epidemic years in the state. The increase in transmission in different regions of the state in one year culminated in an epidemic in the state in the following year. A high annual cumulative incidence of chikungunya occurred in municipalities from 2017 to 2019 and of Zika only in 2016. Some municipalities with higher population densities showed higher incidences for some arboviruses and appeared to contribute to the dissemination to cities of lower demographic density and maintenance of these urban arboviruses. Thus, regions recording increased incidences of the three diseases in their territories for long periods should be considered municipal poles, as they initiated and sustained high transmission within their region.

Chikungunya Manifestations and Viremia in Patients WhoPresented to the Fever Clinic at Bangkok Hospital for Tropical Diseases during the 2019 Outbreak in Thailand

Chikungunya virus is an Alphavirus belonging to the family Togaviridae that is transmitted to humans by an infected Aedes mosquito. Patients develop fever, inflammatory arthritis, and rash during the acute stage of infection. Although the illness is self-limiting, atypical and severe cases are not uncommon, and 60% may develop chronic symptoms that persist for months or even for longer durations. Having a distinct periodical epidemiologic outbreak pattern, chikungunya virus reappeared in Thailand in December 2018. Here, we describe a cohort of acute chikungunya patients who had presented to the Bangkok Hospital for Tropical Diseases during October 2019. Infection was detected by a novel antigen kit and subsequently confirmed by real-time RT-PCR using serum collected at presentation to the Fever Clinic. Other possible acute febrile illnesses such as influenza, dengue, and malaria were excluded. We explored the sequence of clinical manifestations at presentation during the acute phase and associated the viral load with the clinical findings. Most of the patients were healthy individuals in their forties. Fever and arthralgia were the predominant clinical manifestations found in this patient cohort, with a small proportion of patients with systemic symptoms. Higher viral loads were associated with arthralgia, and arthralgia with the involvement of the large joints was more common in female patients.