期刊
MALARIA JOURNAL
卷 12, 期 -, 页码 -出版社
BMC
DOI: 10.1186/1475-2875-12-452
关键词
Distributed lag non-linear model; Generalized linear Poisson model; Plasmodium vivax malaria; Time series analysis; Weather variables
资金
- Medical Research Council [MR/J012343/1]
- MRC [MR/J012343/1] Funding Source: UKRI
- Medical Research Council [MR/J012343/1] Funding Source: researchfish
Background: Transmission of Plasmodium vivax malaria is dependent on vector availability, biting rates and parasite development. In turn, each of these is influenced by climatic conditions. Correlations have previously been detected between seasonal rainfall, temperature and malaria incidence patterns in various settings. An understanding of seasonal patterns of malaria, and their weather drivers, can provide vital information for control and elimination activities. This research aimed to describe temporal patterns in malaria, rainfall and temperature, and to examine the relationships between these variables within four counties of Yunnan Province, China. Methods: Plasmodium vivax malaria surveillance data (1991-2006), and average monthly temperature and rainfall were acquired. Seasonal trend decomposition was used to examine secular trends and seasonal patterns in malaria. Distributed lag non-linear models were used to estimate the weather drivers of malaria seasonality, including the lag periods between weather conditions and malaria incidence. Results: There was a declining trend in malaria incidence in all four counties. Increasing temperature resulted in increased malaria risk in all four areas and increasing rainfall resulted in increased malaria risk in one area and decreased malaria risk in one area. The lag times for these associations varied between areas. Conclusions: The differences detected between the four counties highlight the need for local understanding of seasonal patterns of malaria and its climatic drivers.
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