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• W2788759568 abstract "Climate change is the biggest global health threat of the twenty-first century, responsible directly or indirectly for approximately 12.6 million of all deaths globally and projected to cause an additional 250,000 deaths each year. A key area of concern is how climate change will influence the incidence, and spread of infectious diseases such as malaria. Approximately 3.3 billion, or half of the world’s population, are at risk from malaria and under climate change projections; this number is estimated to rise by 1.6 million by the year 2030 and by 1.8 million by the year 2050. Thus, understanding climate change and malaria risk is of significant public health concern, and this is particularly important for East Africa where current research shows that the disease is already spreading into areas where communities were previously unexposed to the disease.Studies on the impact of climate change on malaria transmission show that even the smallest variation in temperature can have an exponential change in the transmission of the disease. Temperature changes facilitate faster development of the parasite within the mosquito, faster reproduction of the mosquitoes, and more biting by the mosquitoes. Rainfall is also a driver of malaria transmission and can influence the development of the mosquito by creating suitable habitats for larvae and increasing mosquito abundance. Malaria is a disease with a complex transmission cycle which is also influenced at the local level, mainly by land cover, land use and land use change. These changes can introduce the mosquito into new locations, thus extending their range, creating suitable micro-habitat conditions for mosquitoes to breed, and also increasing mosquito abundance.While climate change does influence the global distribution of malaria, the spatial extent within regions will be determined by local land use factors and by other non-climatic factors. The latter include biological, social, demographic and cultural factors, along with human behaviour, drug resistance and public health interventions. At a local level, these factors can influence malaria transmission independently or by modifying the effects of climate change. Therefore, quantifying and understanding the impact of climate change needs consideration of the interactions between these other factors, climate change and malaria transmission.While there exist multiple lines of evidence for the influence of climate change on malaria and the risk posed to vulnerable communities, there is insufficient understanding of the factors influencing the spread of the disease at the community level. There is a need for more robust risk assessments that not only consider the impact of climate change on malaria transmission, but also consider differences in topography, characteristics of the landscape, land use activities and other factors influencing risk. An integrated risk assessment is suitable as this can incorporate, at a biophysical level, an understanding of how climate change will impact on the current burden of the disease and at a social level, identify vulnerable populations, how susceptible they are to this risk and their capacity to respond. This PhD study therefore aims to determine risk of malaria infection in a highland and a lowland rural community in East Africa, in the context of climate change, climate variability, land use and other local factors to suggest suitable adaptation strategies.This study adopted a participatory systems approach, incorporating trans-disciplinary thinking from climate change science, malaria ecology and epidemiology, land use and land use change, social science and public health. Stakeholder engagement and contribution at different levels was used to provide useful and context-specific insights into factors influencing malaria risk at a community level. A mix of quantitative and qualitative data was collected in western Kenya, between August 2014 and February 2015, through focus group discussions, key informant interviews and secondary data analysis. This data was then analysed and integrated using Bayesian belief network models to estimate risk of malaria infection under current and future climate conditions and to evaluate the efficacy of different adaptation options in reducing this risk.The results of the Bayesian belief network model showed that at the highland study site, there was a significant increase in risk under future climate scenarios, but not so in the lowland study site. This difference in risk is mainly driven by changes in temperature. The model also showed that this risk is seven and a half times more significant if the influence of local factors, such as perception, health-seeking behaviour, information provision and utility, malaria prevention and malaria treatment are not considered in the model.This thesis identified three areas of interventions as main adaptation options: i) reducing exposure; ii) decreasing generic susceptibility and iii) increasing coping capacity. It further determined that in order to achieve sustainable adaptation strategies, it is critical to consider: i) community engagement; ii) multi-sectoral collaboration, ii) integrated early warning systems, and; iv) gender-differentiated vulnerability. Collaboration and integration between sectors will lead to stronger and more sustainable programs, and engaging the community early on during the risk assessment and adaptation process ensures that their views and needs are included into adaptation solutions, which will increase the prospects for long term program success and sustainability. This study has demonstrated that local stakeholders’ values and interests will influence different adaptation outcomes. This highlights the importance of tailoring adaptation strategies to local circumstances, which has useful implications for development of climate change and health policy." @default.
• W2788759568 created "2018-03-06" @default.
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• W2788759568 date "2017-07-01" @default.
• W2788759568 modified "2023-09-25" @default.
• W2788759568 title "Climate Change and Malaria: An Integrated Risk Assessment of Rural Communities in East Africa" @default.
• W2788759568 doi "https://doi.org/10.25904/1912/1634" @default.
• W2788759568 hasPublicationYear "2017" @default.
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