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

<p>Abstract</p> <p>Background</p> <p>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 op...

Full description

Bibliographic Details
Main Authors: Da Silva Joaquim, Midzi Stanely, Vounatsou Penelope, Mabaso Musawenkoi LH, Smith Thomas
Format: Article
Language:English
Published: BMC 2006-05-01
Series:International Journal of Health Geographics
Online Access:http://www.ij-healthgeographics.com/content/5/1/20
id doaj-45c1b1960a34418e92407d0745c40aca
record_format Article
spelling doaj-45c1b1960a34418e92407d0745c40aca2020-11-25T00:42:04ZengBMCInternational Journal of Health Geographics1476-072X2006-05-01512010.1186/1476-072X-5-20Spatio-temporal analysis of the role of climate in inter-annual variation of malaria incidence in ZimbabweDa Silva JoaquimMidzi StanelyVounatsou PenelopeMabaso Musawenkoi LHSmith Thomas<p>Abstract</p> <p>Background</p> <p>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.</p> <p>Results</p> <p>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.</p> <p>Conclusion</p> <p>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.</p> http://www.ij-healthgeographics.com/content/5/1/20
collection DOAJ
language English
format Article
sources DOAJ
author Da Silva Joaquim
Midzi Stanely
Vounatsou Penelope
Mabaso Musawenkoi LH
Smith Thomas
spellingShingle Da Silva Joaquim
Midzi Stanely
Vounatsou Penelope
Mabaso Musawenkoi LH
Smith Thomas
Spatio-temporal analysis of the role of climate in inter-annual variation of malaria incidence in Zimbabwe
International Journal of Health Geographics
author_facet Da Silva Joaquim
Midzi Stanely
Vounatsou Penelope
Mabaso Musawenkoi LH
Smith Thomas
author_sort Da Silva Joaquim
title Spatio-temporal analysis of the role of climate in inter-annual variation of malaria incidence in Zimbabwe
title_short Spatio-temporal analysis of the role of climate in inter-annual variation of malaria incidence in Zimbabwe
title_full Spatio-temporal analysis of the role of climate in inter-annual variation of malaria incidence in Zimbabwe
title_fullStr Spatio-temporal analysis of the role of climate in inter-annual variation of malaria incidence in Zimbabwe
title_full_unstemmed Spatio-temporal analysis of the role of climate in inter-annual variation of malaria incidence in Zimbabwe
title_sort spatio-temporal analysis of the role of climate in inter-annual variation of malaria incidence in zimbabwe
publisher BMC
series International Journal of Health Geographics
issn 1476-072X
publishDate 2006-05-01
description <p>Abstract</p> <p>Background</p> <p>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.</p> <p>Results</p> <p>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.</p> <p>Conclusion</p> <p>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.</p>
url http://www.ij-healthgeographics.com/content/5/1/20
work_keys_str_mv AT dasilvajoaquim spatiotemporalanalysisoftheroleofclimateininterannualvariationofmalariaincidenceinzimbabwe
AT midzistanely spatiotemporalanalysisoftheroleofclimateininterannualvariationofmalariaincidenceinzimbabwe
AT vounatsoupenelope spatiotemporalanalysisoftheroleofclimateininterannualvariationofmalariaincidenceinzimbabwe
AT mabasomusawenkoilh spatiotemporalanalysisoftheroleofclimateininterannualvariationofmalariaincidenceinzimbabwe
AT smiththomas spatiotemporalanalysisoftheroleofclimateininterannualvariationofmalariaincidenceinzimbabwe
_version_ 1725284040348532736