Decision-support tools to build climate resilience against emerging infectious diseases in Europe and beyond

Improving risk analysis of the environmental drivers of the spillover, emergence/re-emergence and spread of Crimean-Congo haemorrhagic fever virus, Marburg virus and Middle East respiratory syndrome coronavirus in the East Africa Region

INTRODUCTION

Emerging and/or re-emerging infectious diseases (EIDs) in the East Africa region are associated with climate change-induced environmental drivers. There is a need for a comprehensive understanding of these environmental drivers and to adopt an integrated risk analysis (IRA) framework for addressing a combination of the biological, environmental and socioeconomic factors that increase population vulnerabilities to EID risks to inform biological risk mitigation and cross-sectoral decision-making. The aim of this integrative review was to identify knowledge gaps and contribute to a holistic understanding about the environmental drivers of Crimean-Congo haemorrhagic fever virus (CCHFV), Marburg virus (MARV) and Middle East respiratory syndrome coronavirus (MERS-CoV) infections in the East Africa Region to improve IRA processes at the environment-animal-human exposure interface.

METHODS

An integrative review search was carried out to identify relevant studies and reports from 2000 to 2024. Searches were conducted in bibliographic databases and global institutional websites. Inclusion criteria were studies and reports (in English) addressing environmental drivers of CCHFV, MARV and MERS-CoV infections across countries in the East Africa region, existing risk frameworks/methodological tools and/or One Health policy recommendations for risk analysis of environmentally driven biological threats.

RESULTS

Of the total number of studies retrieved from database searches (n=18 075) and website searches (n=44), 242 studies and reports combined were included in the review with the majority covering the environmental drivers (n=137), the risk frameworks/methodological tools (n=73) and the policy recommendations (n=32). We identified 10 categories of environmental drivers, four thematic groups of risk frameworks and three categories of policy recommendations. Overall, many of the included records on the risk frameworks/methodological tools expounded on the adoption of ecological niche modelling (ENM) for environmental monitoring of potential transmission pathways of EIDs and other biological threats.

CONCLUSION

This integrative review recommends the adoption of specialised risk mapping approaches such as ENM for environmental monitoring of EIDs under IRA processes. Findings from the review were used for the conceptualisation of an IRA framework for addressing environmentally driven EIDs.

Increasing the resolution of malaria early warning systems for use by local health actors

BACKGROUND

The increasing availability of electronic health system data and remotely-sensed environmental variables has led to the emergence of statistical models capable of producing malaria forecasts. Many of these models have been operationalized into malaria early warning systems (MEWSs), which provide predictions of malaria dynamics several months in advance at national and regional levels. However, MEWSs rarely produce predictions at the village-level, the operational scale of community health systems and the first point of contact for the majority of rural populations in malaria-endemic countries.

METHODS

This study developed a hyper-local MEWS for use within a health-system strengthening intervention in rural Madagascar. It combined bias-corrected, village-level case notification data with remotely sensed environmental variables at spatial scales as fine as a 10 m resolution. A spatio-temporal hierarchical generalized linear regression model was trained on monthly malaria case data from 195 communities from 2017 to 2020 and evaluated via cross-validation. The model was then integrated into an automated workflow with environmental data updated monthly to create a continuously updating MEWS capable of predicting malaria cases up to three months in advance at the village-level. Predictions were transformed into indicators relevant to health system actors by estimating the quantities of medical supplies required at each health clinic and the number of cases remaining untreated at the community level.

RESULTS

The statistical model was able to accurately reproduce village-level case data, performing nearly five times as well as a null model during cross-validation. The dynamic environmental variables, particularly those associated with standing water and rice field dynamics, were strongly associated with malaria incidence, allowing the model to accurately predict future incidence rates. The MEWS represented an improvement of over 50% compared to existing stock order quantification methods when applied retrospectively.

CONCLUSION

This study demonstrates the feasibility of developing an automatic, hyper-local MEWS leveraging remotely-sensed environmental data at fine spatial scales. As health system data become increasingly digitized, this method can be easily applied to other regions and be updated with near real-time health data to further increase performance.

Present and future suitability of invasive and urban vectors through an environmentally driven mosquito reproduction number

Temperature and water availability significantly influence mosquito population dynamics. We have developed a method, integrating experimental data with insights from mosquito and thermal biology, to calculate the basic reproduction number ([Formula: see text]) for urban mosquito species Aedes albopictus and Aedes aegypti. [Formula: see text] represents the number of female mosquitoes produced by one female during her lifespan, indicating suitability for growth. Environmental conditions, including temperature, rainfall and human density, influence [Formula: see text] by altering key mosquito life cycle traits. Validation using data from Spain and Europe confirms the approach's reliability. Our analysis suggests that temperature increases may not uniformly benefit Ae. albopictus proliferation but could boost Ae. aegypti expansion. We suggest using vector [Formula: see text] maps, leveraging climate and environmental data, to predict areas susceptible to invasive mosquito population growth. These maps aid resource allocation for intervention strategies, supporting effective vector surveillance and management efforts.

Assessing and correcting neighborhood socioeconomic spatial sampling biases in citizen science mosquito data collection

Climatic, ecological, and socioeconomic factors are facilitating the spread of mosquito-borne diseases, heightening the importance of vector surveillance and control. Citizen science is proving to be an effective tool to track mosquito populations, but methods are needed to detect and account for small scale sampling biases in citizen science surveillance. In this article we combine two types of traditional mosquito surveillance records with data from the Mosquito Alert citizen science system to explore the ways in which the socioeconomic characteristics of urban neighborhoods result in sampling biases in citizen scientists' mosquito reports, while also shaping the spatial distribution of mosquito populations themselves. We use Barcelona, Spain, as an example, and focus on Aedes albopictus, an invasive vector species of concern worldwide. Our results suggest citizen scientists' sampling effort is focused more in Barcelona's lower and middle income census tracts than in its higher income ones, whereas Ae. albopictus populations are concentrated in the city's upper-middle income tracts. High resolution estimates of the spatial distribution of Ae. albopictus risk can be improved by controlling for citizen scientists' sampling effort, making it possible to provide better insights for efficiently targeting control efforts. Our methodology can be replicated in other cities faced with vector mosquitoes to improve public health responses to mosquito-borne diseases, which impose massive burdens on communities worldwide.

Pulmonary vascular disease, environmental pollution, and climate change

Pollution and climate change constitute a combined, grave and pervasive threat to humans and to the life-support systems on which they depend. Evidence shows a strong association between pollution and climate change on cardiovascular and respiratory diseases, and pulmonary vascular disease (PVD) is no exception. An increasing number of studies has documented the impact of environmental pollution and extreme temperatures on pulmonary circulation and the right heart, on the severity and outcomes of patients with pulmonary arterial hypertension and chronic thromboembolic pulmonary hypertension (PH), on the incidence of pulmonary embolism, and the prevalence and severity of diseases associated with PH. Furthermore, the downstream consequences of climate change impair health care systems' accessibility, which could pose unique obstacles in the case of PVD patients, who require a complex and sophisticated network of health interventions. Patients, caretakers and health care professionals should thus be included in the design of policies aimed at adaptation to and mitigation of current challenges, and prevention of further climate change. The purpose of this review is to summarize the available evidence concerning the impact of environmental pollution and climate change on the pulmonary circulation, and to propose measures at the individual, healthcare and community levels directed at protecting patients with PVD.

Alike but not the same: Psychological profiles of COVID-19 vaccine skeptics

One of the challenges of the SARS-CoV-2 pandemic was a widespread skepticism about vaccination. To elucidate the underlying mental and emotional predispositions, we examined a sample of 1428 participants using latent profile analysis (LPA) on selected personality trait variables, mental health status, and measures of irrational beliefs. LPA revealed five distinct profiles: two classes of non-skeptics and three of skeptics. The smaller non-skeptic class reported the highest rates of mental health problems, along with high levels of neuroticism, hostility, interpersonal sensitivity, and external locus of control. The larger non-skeptic class was psychologically well-balanced. Conversely, the skeptic groups shared strong distrust of COVID-19 vaccination but differed in emotional and mental profiles, leading to graded differences in endorsing extreme conspiracy beliefs. This suggests that vaccine skepticism is not solely a result of mental illness or emotional instability; rather extreme skepticism manifests as a nuanced, graded phenomenon contingent on personality traits and conspirational beliefs.