Ranking malaria risk factors to guide malaria control efforts in African highlands.
Ranking malaria risk factors to guide malaria control efforts in African highlands.
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DOI：
10.1371/journal.pone.0008022
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发表时间：
2009-11-25
期刊：
影响因子：
3.7
通讯作者：
Coosemans M
中科院分区：
文献类型：
--
作者：
Protopopoff N;Van Bortel W;Speybroeck N;Van Geertruyden JP;Baza D;D'Alessandro U;Coosemans M
疟疾在大多数非洲高地重新出现，使没有免疫力的人口面临致命的流行病。更好地了解影响高原地区传播的因素对于改进目标明确的疟疾控制战略至关重要。根据现有文献，建立了高原地区潜在疟疾风险因素的概念模型。此外，这些因素对疟疾的相对重要性可以通过“分类和回归树”来估计，这是疟疾领域尚未使用的一种统计方法。这种CART方法用于分析布隆迪高地的疟疾风险因素。结果表明，按蚊密度是疟疾高流行的最佳预测因子。降雨量少、无病媒控制、最低温度高和繁殖地附近的房屋按重要性顺序与按蚊密度高相关。在布隆迪高地，在降雨量低时监测按蚊密度可能能够预测流行病。概念模型与CART分析相结合，是一种决策支持工具，可以通过确定主要风险因素，为预防和控制疟疾做出重要贡献。
Malaria is re-emerging in most of the African highlands exposing the non immune population to deadly epidemics. A better understanding of the factors impacting transmission in the highlands is crucial to improve well targeted malaria control strategies. A conceptual model of potential malaria risk factors in the highlands was built based on the available literature. Furthermore, the relative importance of these factors on malaria can be estimated through “classification and regression trees”, an unexploited statistical method in the malaria field. This CART method was used to analyse the malaria risk factors in the Burundi highlands. The results showed that Anopheles density was the best predictor for high malaria prevalence. Then lower rainfall, no vector control, higher minimum temperature and houses near breeding sites were associated by order of importance to higher Anopheles density. In Burundi highlands monitoring Anopheles densities when rainfall is low may be able to predict epidemics. The conceptual model combined with the CART analysis is a decision support tool that could provide an important contribution toward the prevention and control of malaria by identifying major risk factors.
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DOI：
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影响因子：
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