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Aedes albopictus, a key vector for Dengue, Chikungunya, Zika, and Yellow Fever, is expanding its range beyond its tropical and subtropical origins, driven by suitable climate, population mobility, trade, and urbanization. Since its introduction to Europe, Ae. albopictus has rapidly spread and triggered recurrent outbreaks. Past model attempts have handled vector suitability and vector introduction as independent drivers. Here we develop a highly predictive spatio-temporal vector diffusion model based on climate suitability and human population predictors, integrated in one simultaneous framework. The model explains how short- and long-range spread of Ae. albopictus interacts with vector suitability, predicting areas of presence or absence with high accuracy (99% and 79%). These results show that the expansion of Ae. albopictus in Europe is predictable and provide a basis for anticipating future outbreaks in situations of dependent interacting co-drivers.

Aedes and Culex mosquitoes, known for spreading arboviruses like dengue and West Nile, thrive in cities, posing health risks to urban populations. Climate change can create suitable climatic conditions for these vectors to spread further in Europe. Cities contain numerous landscape and infrastructure elements, such as storm drains, that allow stagnant water build-up facilitating mosquito breeding. Modifying urban infrastructure to prevent water accumulation can reduce mosquito populations, but evidence is limited. The Public Health Agency of Barcelona, Spain, introduced a structural modification of storm drains to prevent water accumulation. Together with the Agency, we designed a randomised controlled trial (RCT) to experimentally assess the effectiveness of these modifications on adult Aedes albopictus and Culex pipiens populations. It is a parallel-arm RCT with equal randomization of 44 drains to receive mosquito-proofing modifications (intervention) or not (control). Primary outcomes are adult mosquito counts and secondary outcomes are larvae and mosquito presence, assessed weekly at each drain until no mosquitoes are detected. Data analyses include generalised linear mixed models to estimate the time-averaged and highest intervention effects, subgroup and sensitivity analyses. The trial results will guide a city-wide expansion of the storm drain modifications and provide valuable evidence to enhance existing vector control measures.

Extreme weather events can lead to infectious disease outbreaks, especially those spread by hematophagous flies, and The Gambia is particularly vulnerable to climate change. To the best of our knowledge, no one has ever documented the relationship between climate variability and change and the distribution of the hematophagous flies belonging to the families Glossinidae, Tabanidae, and Stomoxyinae. This paper aims to study the association of temperature and humidity on the distribution of the above species and their families in The Gambia in the recent past and to provide predictions of species abundance and occurrence in the future. A line transect survey was carried out in all the administrative regions of The Gambia to study the prevalence of the flies. Generalized additive models were used to analyze the relationships between the distribution of the insects and their families and the variability in climate conditions in the recent past and in three different future periods. Regarding the recent past, our results show that temperature has significantly impacted the presence of Glossinidae and Tabanidae species, with maximum temperature being the most important factor. Relative humidity was also statistically significantly associated with Tabanidae species. None of the climate variables was found to be associated with the Tabanus par and Tabanus sufis. Minimum temperature and relative humidity were statistically significantly associated with Glossina morsitan submorsitan, while maximum temperature was statistically significantly associated with Atylotus agrestis and Stomoxys calcitrans. Only relative humidity was statistically significantly associated with the Glossina palpalis gambiense. As for the future projections, the results show that rising temperatures impacted the distribution of Tabanus species, Glossina species, and Stomoxys calcitrans in The Gambia. The distribution of Trypanosoma vectors in The Gambia is mostly influenced by maximum temperature. The research’s conclusions gave climate and public health policymakers crucial information to take into account.

The case fatality ratio (CFR) is a vital metric for assessing the disease severity of novel pathogens. The widely used direct method of CFR estimation—the ratio of total confirmed deaths to total confirmed cases—is inherently simplistic, as it fails to account for the essential time lag between case confirmation to death, and reporting delays. These limitations often lead to biased CFR estimates, particularly in the early stages of outbreaks. This study introduces a novel approach—the distributed-delay method that, like the direct method, utilizes publicly available aggregate time-series data on cases and deaths. It estimates CFR by flexibly incorporating a case-to-death time distribution without requiring a priori assumptions on distribution parameters. Using a fitting approach to forecast case fatalities based on known or assumed case-to-death time distributions, the method consistently recovers true CFR much earlier than the direct method under various simulation settings. These settings reflect variability in disease severity, uncertainties in case-to-death time parameters, and limited knowledge of case-to-death time distributions. It outperforms other methods such as Baud’s, which assumes a non-zero constant case-to-death time, and the Generalized Baud’s method, which allows for a direct comparison with our new approach. While evaluations based on empirical data are challenging, our conclusions are supported by CFR estimates obtained using empirical COVID-19 data from 34 countries. As an added value, this analysis also demonstrates a significant negative association between eventual CFR and the expected case-to-death time within the context of COVID-19 data. Our study highlights the complexities of inferring real-time CFR from aggregate time-series case and death data, highlighting that refining this method can lead to accurate real-time CFR estimations for actual outbreaks.

Expressions in social media can provide a rapid insight into people's reactions to events, such as periods of climatic stress. This study explored the link between climatic stressors and negative sentiment on the X platform in Germany to inform climate-related health policies and interventions. Natural language processing was used to standardize the text, and a comprehensive approach for sentiment analysis was utilized. We then conducted spatiotemporal modeling fitted using integrated nested laplace approximation (INLA). Our findings indicate that higher and lower level of temperature and precipitation is correlated with an increase and decrease in the relative risk of negative sentiments, respectively. The findings of this study illustrate that human sentiment of distress in social media varies with space and time about exposure to climate stressors. This emotional indicator of human exposure and responses to climate stress indicates potential physical and mental health impacts among the affected populations.

Temperature influences the transmission of mosquito-borne pathogens with significant implications for disease risk under climate change. Mathematical models of mosquito-borne infections rely on functions that capture mosquito-pathogen interactions in response to temperature to accurately estimate transmission dynamics. For deriving these functions, experimental studies provide valuable data on the temperature sensitivity of mosquito life-history traits and pathogen transmission. However, the scarcity of experimental data and inconsistencies in methodologies for analysing temperature responses across mosquito species, pathogens, and experiments present major challenges. Here, we introduce a new approach to address these challenges. We apply this framework to study the thermal biology of West Nile virus (WNV). We reviewed existing experimental studies, obtaining temperature responses for eight mosquito-pathogen traits across 15 mosquito species. Using these data, we employed Bayesian hierarchical models to estimate temperature response functions for each trait and their variation between species and experiments. We incorporated the resulting functions into mathematical models to estimate the temperature sensitivity of WNV transmission, focusing on six mosquito species of the genus Culex. Our study finds a general optimal transmission temperature around 24°C among Culex species with only small species-specific deviations. We demonstrate that differing mechanistic assumptions underlying published mosquito population models result in temperature optima estimates that differ by up to 3°C. Additionally, we find substantial variability between trait temperature responses across experiments on the same species, possibly indicating significant intra-species variation in trait performance. We identify mosquito biting rate, lifespan, and egg viability as priorities for future experiments, as they strongly influence estimates of temperature limits, optima, and overall uncertainty in transmission suitability. Experimental studies on vector competence traits are also essential, because limited data on these currently require model simplifications. These data would enhance the accuracy of our estimates, critical for anticipating future shifts in WNV risk under climate change

Background: Controlling Aedes aegypti stands as the primary strategy in curtailing the global threat of vector-borne viral infections such as dengue fever, which is responsible for around 400 million infections and 40 000 fatalities annually. Effective interventions require a precise understanding of Ae aegypti spatiotemporal distribution and behaviour, particularly in urban settings where most infections occur. However, conventionally applied sample-based entomological surveillance systems often fail to capture the high spatial variability of Ae aegypti that can arise from heterogeneous urban landscapes and restricted Aedes flight range.

Methods: In this study, we aimed to address the challenge of capturing the spatial variability of Ae aegypti by leveraging emerging geospatial big data, including openly available satellite and street view imagery, to locate common Ae aegypti breeding habitats. These data enabled us to infer the seasonal suitability for Ae aegypti eggs and larvae at a spatial resolution of 200 m within the municipality of Rio de Janeiro, Brazil.

Findings: The proposed microhabitat and macrohabitat indicators for immature Ae aegypti explained the distribution of Ae aegypti ovitrap egg counts by up to 72% (95% CI 70–74) and larval counts by up to 74% (72–76). Spatiotemporal interpolations of ovitrap counts, using suitability indicators, provided high-resolution insights into the spatial variability of urban immature Ae aegypti that could not be captured with sample-based surveillance techniques alone.

Interpretation: The potential of the proposed method lies in synergising entomological field measurements with digital indicators on urban landscape to guide vector control and address the prevailing spread of Ae aegypti-transmitted viruses. Estimating Ae aegypti distributions considering habitat size is particularly important for targeting novel vector control interventions such as Wolbachia. Funding: German Research Foundation and Austrian Science Fund.

Integration of child-specific adaptation measures into health policies is imperative given children's heightened susceptibility to the health impacts of climate change. Using a document analysis method, we examined 160 national adaptation policies for inclusion of child-relevant measures and identified 19 child health-related adaptation domains. 44 (28%) of 160 countries' policies that were analysed failed to include any domains, 49 (31%) included at least one child-related domain, 62 (39%) included between two and six domains, and five (3%) included at least seven domains. Predominant domains among child-specific adaptation measures included education and awareness raising, followed by community engagement and nutrition. No country addressed children's direct needs in the domain of mental health. National adaptation policies tend towards overly simple conceptualisations of children across four major lenses: age, social role, gender, and agency. Limited inclusion of child-specific measures in national adaptation policies suggests insufficient recognition of and action on children's susceptibility to climate change effects.