Publication: Spatiotemporal distributed lag modelling of multiple Plasmodium species in a malaria elimination setting
Issued Date
2021-01-01
Resource Type
ISSN
14770334
09622802
09622802
Other identifier(s)
2-s2.0-85101049163
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Mahidol University
Rights Holder(s)
SCOPUS
Bibliographic Citation
Statistical Methods in Medical Research. Vol.30, No.1 (2021), 22-34
Suggested Citation
Chawarat Rotejanaprasert, Duncan Lee, Nattwut Ekapirat, Prayuth Sudathip, Richard J. Maude Spatiotemporal distributed lag modelling of multiple Plasmodium species in a malaria elimination setting. Statistical Methods in Medical Research. Vol.30, No.1 (2021), 22-34. doi:10.1177/0962280220938977 Retrieved from: https://repository.li.mahidol.ac.th/handle/123456789/77120
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Title
Spatiotemporal distributed lag modelling of multiple Plasmodium species in a malaria elimination setting
Abstract
In much of the Greater Mekong Sub-region, malaria is now confined to patches and small foci of transmission. Malaria transmission is seasonal with the spatiotemporal patterns being associated with variation in environmental and climatic factors. However, the possible effect at different lag periods between meteorological variables and clinical malaria has not been well studied in the region. Thus, in this study we developed distributed lagged modelling accounting for spatiotemporal excessive zero cases in a malaria elimination setting. A multivariate framework was also extended to incorporate multiple data streams and investigate the spatiotemporal patterns from multiple parasite species via their lagged association with climatic variables. A simulation study was conducted to examine robustness of the methodology and a case study is provided of weekly data of clinical malaria cases at sub-district level in Thailand.