Parasitology



Effects of meteorological factors on epidemic malaria in Ethiopia: a statistical modelling approach based on theoretical reasoning


T. A. ABEKU a1a2c1, S. J. DE VLAS a1, G. J. J. M. BORSBOOM a1, A. TADEGE a3, Y. GEBREYESUS a3, H. GEBREYOHANNES a3, D. ALAMIREW a4, A. SEIFU a4, N. J. D. NAGELKERKE a1a5 and J. D. F. HABBEMA a1
a1 Department of Public Health, Erasmus MC, University Medical Center Rotterdam, The Netherlands
a2 Disease Control and Vector Biology Unit, Department of Infectious and Tropical Diseases, London School of Hygiene and Tropical Medicine, UK
a3 National Meteorological Services Agency, Addis Ababa, Ethiopia
a4 Disease Prevention and Control Department, Ministry of Health, Addis Ababa, Ethiopia
a5 Department of Medical Statistics, Leiden University Medical Center, The Netherlands

Article author query
abeku t   [PubMed][Google Scholar] 
de vlas s   [PubMed][Google Scholar] 
borsboom g   [PubMed][Google Scholar] 
tadege a   [PubMed][Google Scholar] 
gebreyesus y   [PubMed][Google Scholar] 
gebreyohannes h   [PubMed][Google Scholar] 
alamirew d   [PubMed][Google Scholar] 
seifu a   [PubMed][Google Scholar] 
nagelkerke n   [PubMed][Google Scholar] 
habbema j   [PubMed][Google Scholar] 

Abstract

This study was conducted to quantify the association between meteorological variables and incidence of Plasmodium falciparum in areas with unstable malaria transmission in Ethiopia. We used morbidity data pertaining to microscopically confirmed cases reported from 35 sites throughout Ethiopia over a period of approximately 6–7 years. A model was developed reflecting biological relationships between meteorological and morbidity variables. A model that included rainfall 2 and 3 months earlier, mean minimum temperature of the previous month and P. falciparum case incidence during the previous month was fitted to morbidity data from the various areas. The model produced similar percentages of over-estimation (19·7% of predictions exceeded twice the observed values) and under-estimation (18·6% were less than half the observed values). Inclusion of maximum temperature did not improve the model. The model performed better in areas with relatively high or low incidence (>85% of the total variance explained) than those with moderate incidence (55–85% of the total variance explained). The study indicated that a dynamic immunity mechanism is needed in a prediction model. The potential usefulness and drawbacks of the modelling approach in studying the weather–malaria relationship are discussed, including a need for mechanisms that can adequately handle temporal variations in immunity to malaria.

(Received September 10 2003)
(Revised November 21 2003)
(Accepted November 26 2003)


Key Words: malaria; Plasmodium falciparum; highland; epidemic; climate; Ethiopia; linear mixed model.

Correspondence:
c1 Disease Control and Vector Biology Unit, Department of Infectious and Tropical Diseases, London School of Hygiene and Tropical Medicine, Keppel Street, London WC1E 7HT, UK. Tel: +44 (0) 20 7612 7861. Fax: +44 (0) 20 7580 9075. E-mail: tarekegn.abeku@lshtm.ac.uk


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