株式会社極東書店トップ商品一覧Environmental Factors and Malaria Transmission Risk : Modeling the Risk in a Holoendernic Area of Burkina Faso.

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Environmental Factors and Malaria Transmission Risk

Environmental Factors and Malaria Transmission Risk : Modeling the Risk in a Holoendernic Area of Burkina Faso.

・ISBN 978-0-7546-7570-9 hard

お気に入り
著者・編者Yé, Yazoumé / Sankoh, O. A. / Kouyaté, B. et al. (eds.),
出版社(Ashgate, UK)
出版年月2008
ページ数160 pp.
言語ENG
ニュース番号<560-L118>

解説

Malaria remains a deadly disease and a serious public health problem worldwide, but especially in developing countries. In Burkina Faso, malaria accounts for about 20 per cent of under-five mortality cases. The fifth Millennium Development Goal of reducing infant mortality by two thirds by the year 2015 can only be achieved if mortality due to malaria is significantly reduced. WHO recommends early detection and treatment among high-risk groups as one of the strategies for reducing the malaria burden. To be effective, this approach requires an early warning system which enables the health care system to be well-prepared and to allocate scarce resources effectively. Unfortunately, such a system is still not available at the appropriate scale.This book therefore attempts to fill the gap by developing a malaria transmission model at a local (district) scale using appropriate environmental factors. A population-based prospective cohort study was conducted in order to establish to what extent weather at the micro-scale level affects malaria transmission among under-five children in a holoendemic area and whether malaria can be predicted at a local scale using weather parameters as a driving force.The study assessed a randomly selected group of children aged between 6 months and 5 years for 12 months over one dry and one rainy season for active parasite detection. In addition, the study noted prospectively exposure variables such as meteorological factors and mosquito bites by land-based data collection.The book then shows how a dynamic model of malaria transmission was developed and tested using the knowledge generated by this comprehensive time series data and the results provided by different analyses. This dynamic model, driven by temperature and rainfall, successfully simulates seasonal vector abundance and also predicts successfully the monthly malaria incidence.The book puts forward an innovative methodology and modelling used in practice to assess local scale malaria risk using environmental factors. The detailed description of this methodology allows scientists to replicate the study elsewhere in different settings.