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. 2006 May 15:5:20.
doi: 10.1186/1476-072X-5-20.

Spatio-temporal analysis of the role of climate in inter-annual variation of malaria incidence in Zimbabwe

Musawenkoi L H Mabaso  1 , Penelope Vounatsou, Stanely Midzi, Joaquim Da Silva, Thomas Smith
Affiliations

Spatio-temporal analysis of the role of climate in inter-annual variation of malaria incidence in Zimbabwe

Musawenkoi L H Mabaso et al. Int J Health Geogr. .

Abstract

Background: On the fringes of endemic zones climate is a major determinant of inter-annual variation in malaria incidence. Quantitative description of the space-time effect of this association has practical implications for the development of operational malaria early warning system (MEWS) and malaria control. We used Bayesian negative binomial models for spatio-temporal analysis of the relationship between annual malaria incidence and selected climatic covariates at a district level in Zimbabwe from 1988-1999.

Results: Considerable inter-annual variations were observed in the timing and intensity of malaria incidence. Annual mean values of average temperature, rainfall and vapour pressure were strong positive predictors of increased annual incidence whereas maximum and minimum temperature had the opposite effects. Our modelling approach adjusted for unmeasured space-time varying risk factors and showed that while year to year variation in malaria incidence is driven mainly by climate, the resultant spatial risk pattern may to large extent be influenced by other risk factors except during high and low risk years following the occurrence of extremely wet and dry conditions, respectively.

Conclusion: Our model revealed a spatially varying risk pattern that is not attributable only to climate. We postulate that only years characterized by extreme climatic conditions may be important for developing climate based MEWS and for delineating areas prone to climate driven epidemics. However, the predictive value of climatic risk factors identified in this study still needs to be evaluated.

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Figures

Figure 1
Figure 1
(A) Annual malaria incidence rate (cases per 1000 person years) (B) proportion of annual monthly cases (C) percentage concentration of malaria case load during the peak transmission month and (D) peak month during the malaria transmission season in Zimbabwe from 1988–1999.
Figure 2
Figure 2
Inter-annual variations in malaria incidence rate (cases per 1000 person years), rainfall (mm), vapour pressure (hPa), NDVI (Normalized Difference Vegetation Index), average, maximum and minimum temperatures (°C) in Zimbabwe between 1988 and 1999.
Figure 3
Figure 3
Geographic distribution of smoothed malaria incidence (cases per 1000 person years) by year between 1988 and 1999 in Zimbabwe from a spatial-temporal model.
See this image and copyright information in PMC

References

    1. Baird JK, Agyel SO, Utz GC, Koram K, Barcus MJ, Jones TR, Fryauff DJ, Binka FN, Hoffman SL, Nkrumah FN. Seasonal malaria attack rates in infants and young children in Northern Ghana. Am J Trop Med Hyg. 2002;66:280–286. - PubMed
    1. Thomson M, Indeje M, Connor S, Dilley M, Ward N. Malaria early warning and seasonal climate forecasts. Lancet. 2003;362:280. doi: 10.1016/S0140-6736(03)14135-9. - DOI - PubMed
    1. WHO . Climate change and human health, risks and responses. Geneva: World Health Organization; 2003.
    1. Da Silva J, Garanganga B, Teveredzi V, Marx SM, Mason SJ, Connor SJ. Improving epidemic malaria planning, preparedness and response in Southern Africa. Malar J. 2004;3:37. doi: 10.1186/1475-2875-3-37. - DOI - PMC - PubMed
    1. le Sueur D, Sharp BL. Malaria Forecasting Project: Report on Workshop on Reducing Climate Related Vulnerability in Southern Africa. Victoria Falls, Zimbabwe. Washington, D.C, USA: Office of Global Programs, National Oceanic and Atmospheric Administration; 1996. pp. 65–73.

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