Modelling the influence of temperature and rainfall on malaria incidence in four endemic provinces of Zambia using semiparametric Poisson regression

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• 作者：Nzooma M. Shimaponda-Mataa^a ; ^b ; ^{nzomataa@gmail.com} ; Enala Tembo-Mwase^c ; Michael Gebreslasie^d ; Thomas N.O. Achia^e ; Samson Mukaratirwa^b
• 关键词：R-INLA ; R version of integrated Laplace ; NDVI ; normalised difference vegetation index ; WHO ; World Health Organisation ; LS ; Lusaka ; LP ; Luapula ; NW ; North-western ; W ; Western ; CSO ; Central Statistical Office ; HMIS ; Health Management Information System ; MOH ; Ministry of Health ; LST ; land surface temperature ; MODIS ; Moderate Resolution Imaging Spectroradiometer ; USGS ; U. S. Geological Survey ; LP DAAC ; Land Processes Distributed Active Archive Centre ; CHIRPS ; Climate Hazards Group InfraRed Precipita
• 刊名：Acta Tropica
• 出版年：2017
• 出版时间：February 2017
• 年：2017
• 卷：166
• 期：Complete
• 页码：81-91
• 全文大小：2439 K
• 卷排序：166

文摘

In Zambia, the role of climatic factors on malaria, has not been determined in combination of space and time in modelling. The reversal in malaria reduction after the year 2010 and its variation by transmission zones make it critical. Semiparametric Poisson regression modelled a strong positive association between malaria incidence and precipitation. Malaria risk was 95% and 68% lower in Lusaka and Western (APR = 0.05 and 0.31, 95% CI = 0.04 – 0.06 and 0.25 – 0.41 respectively) compared to Luapula. The unique behaviour and effects of minimum and maximum temperatures are an indication of geographical region effects.