An Integrated Modelling Approach to Climate Change and Malaria Vulnerability Assessments
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Author(s)
Achieng, OE
Sahin, O
Chu, C
Brendan, M
Year published
2016
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Show full item recordAbstract
Malaria is one of the key research concerns in climate change-health relationships. Numerous
risk assessments and modelling studies providing evidence that the transmission range of malaria will
expand with rising temperatures resulting in adverse impacts on vulnerable communities. This risk is
significant in East Africa whereby current research shows an expansion of malaria into the highland
areas due to changes in temperature and rainfall. 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 ...
View more >Malaria is one of the key research concerns in climate change-health relationships. Numerous risk assessments and modelling studies providing evidence that the transmission range of malaria will expand with rising temperatures resulting in adverse impacts on vulnerable communities. This risk is significant in East Africa whereby current research shows an expansion of malaria into the highland areas due to changes in temperature and rainfall. 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 complexity of factors influencing the spread of the disease at the community level. This paper considers assessment of risk of malaria infection due to climate change, from systems perspective. Drawing upon published literature, we apply systems approach to propose a detailed conceptual model that illustrates causal relationships between the multiple drivers of malaria transmission in line with the current Intergovernmental Panel on Climate Change recommendations for risk and vulnerability assessments. We suggest that this framework can be applied at a community level using both quantitative and qualitative methods with stakeholder engagement and in conjunction with Bayesian Belief Network to models to: explore how policy and management interventions can reduce the risk of malaria infection and; provide targeted adaptation strategies that incorporates both the scientific and the community perspectives.
View less >
View more >Malaria is one of the key research concerns in climate change-health relationships. Numerous risk assessments and modelling studies providing evidence that the transmission range of malaria will expand with rising temperatures resulting in adverse impacts on vulnerable communities. This risk is significant in East Africa whereby current research shows an expansion of malaria into the highland areas due to changes in temperature and rainfall. 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 complexity of factors influencing the spread of the disease at the community level. This paper considers assessment of risk of malaria infection due to climate change, from systems perspective. Drawing upon published literature, we apply systems approach to propose a detailed conceptual model that illustrates causal relationships between the multiple drivers of malaria transmission in line with the current Intergovernmental Panel on Climate Change recommendations for risk and vulnerability assessments. We suggest that this framework can be applied at a community level using both quantitative and qualitative methods with stakeholder engagement and in conjunction with Bayesian Belief Network to models to: explore how policy and management interventions can reduce the risk of malaria infection and; provide targeted adaptation strategies that incorporates both the scientific and the community perspectives.
View less >
Conference Title
Environmental Modelling and Software for Supporting a Sustainable Future, Proceedings - 8th International Congress on Environmental Modelling and Software, iEMSs 2016
Volume
4
Copyright Statement
Copyright remains with the author(s) 2016. The attached file is reproduced here in accordance with the copyright policy of the publisher. For information about this conference please refer to the conference’s website or contact the author(s).
Subject
Other biomedical and clinical sciences not elsewhere classified
Other health sciences not elsewhere classified