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気候変動と感染症 : 医学研究と地域情報学のクロスオーバー ; Climate Change and Infectious Diseases: Crossover between Medical Research and Area Informatics

気候変動と感染症 : 医学研究と地域情報学のクロスオーバー ; Climate Change and Infectious Diseases: Crossover between Medical Research and Area Informatics

Abstract

Climate change can influence human health in various ways. The influence on infectious diseases is considered particularly important. This chapter deals with the application of an area informatics approach to study in the medical field, particularly the epidemiology of infectious diseases. In recent years, models to predict the effects of climate change on the incidence of infectious diseases in certain areas using time and space as "rulers" have been developed. This approach appears to be applicable to all infectious diseases if important factors mediating the transfer of the effects of climate change to the incidence of infectious disease and the mediation mechanism are understood.Infection is based on the relationship between the host and its parasite (pathogen). In some cases, an intermediate host(s) and/or vector(s) may also be involved in the establishment of infection. All the biological factors involved in infection are influenced individually by climate change. It is important to take the route of transmission of each infectious disease and all biological factors involved in its transmission into consideration when evaluating the effect of climate change on infectious diseases.In this paper, an overview of the importance of climate change effects on infectious diseases is followed by an explanation of representative infectious diseases transmitted through oral, respiratory and skin routes and direct contact and the possible effects of climate change on these infectious diseases. These explanations help the reader understand the important factors involved in the transfer of climate change effects. Next, the direct effect of climate change on the host is considered, with an explanation of some models used to predict change in the risk map(geographical distribution of pathogens or vectors) due to future climate change. In addition, a model we developed to predict future cholera epidemics using local climate data is introduced.Finally, the extent to which climate change studies overlap area informatics is ...

Country
Japan
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Keywords

climate change, infectious disease, 感染症, コレラ, cholera, エルニーニョ現象, 気候変動, El Niño Southern Oscillation, 292.3

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citations
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
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