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

Published online by Cambridge University Press:  13 May 2004

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

Keywords

malariaPlasmodium falciparumhighlandepidemicclimateEthiopialinear mixed model
Type
Research Article
Information
Parasitology , Volume 128 , Issue 6 , June 2004 , pp. 585 - 593
Copyright
2004 Cambridge University Press

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