Abstract
BackgroundUnderstanding spatio-temporal variation in malaria incidence provides a basis for effective disease control planning and monitoring.MethodsMonthly surveillance data between 1991 and 2006 for Plasmodium vivax and Plasmodium falciparum malaria across 128 counties were assembled for Yunnan, a province of China with one of the highest burdens of malaria. County-level Bayesian Poisson regression models of incidence were constructed, with effects for rainfall, maximum temperature and temporal trend. The model also allowed for spatial variation in county-level incidence and temporal trend, and dependence between incidence in June–September and the preceding January–February.ResultsModels revealed strong associations between malaria incidence and both rainfall and maximum temperature. There was a significant association between incidence in June–September and the preceding January–February. Raw standardised morbidity ratios showed a high incidence in some counties bordering Myanmar, Laos and Vietnam, and counties in the Red River valley. Clusters of counties in south-western and northern Yunnan were identified that had high incidence not explained by climate. The overall trend in incidence decreased, but there was significant variation between counties.ConclusionDependence between incidence in summer and the preceding January–February suggests a role of intrinsic host-pathogen dynamics. Incidence during the summer peak might be predictable based on incidence in January–February, facilitating malaria control planning, scaled months in advance to the magnitude of the summer malaria burden. Heterogeneities in county-level temporal trends suggest that reductions in the burden of malaria have been unevenly distributed throughout the province.
Highlights
Understanding spatio-temporal variation in malaria incidence provides a basis for effective disease control planning and monitoring
Spatial, intraannual and inter-epidemic patterns of malaria in Yunnan were explored using a Bayesian analysis of time-series data on reported Plasmodium falciparum and Plasmodium vivax clinical events over 16 years
Descriptive analysis In Yunnan, there was a total of 250,070 cases of P. vivax malaria documented over the 16 years of observation (1991–2006), representing a crude incidence of 3.12 cases per 100,000 person years at risk
Summary
Understanding spatio-temporal variation in malaria incidence provides a basis for effective disease control planning and monitoring. The south-western province of Yunnan has one of the highest malaria burdens in China This province has international borders with Laos, Myanmar and Vietnam and impedance of effective malaria control and repeated epidemics have been associated with social and economic migration of people across these borders [3,4]. As with other vector-borne diseases, malaria typically shows temporal and spatial variations that are driven by climatic, ecological and human factors [5,6,7,8,9]. These correlates can be used to predict the spatio-temporal distribution of disease burden and guide the cost-effective allocation of intervention resources in space and time. Spatial, intraannual and inter-epidemic patterns of malaria in Yunnan were explored using a Bayesian analysis of time-series data on reported Plasmodium falciparum and Plasmodium vivax clinical events over 16 years
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