Spatiotemporal patterns and association with climate for malaria elimination in Lao PDR: a hierarchical modelling analysis with two-step Bayesian model selection
Issued Date
2024-12-01
Resource Type
eISSN
14752875
Scopus ID
2-s2.0-85200434464
Pubmed ID
39098946
Journal Title
Malaria Journal
Volume
23
Issue
1
Rights Holder(s)
SCOPUS
Bibliographic Citation
Malaria Journal Vol.23 No.1 (2024)
Suggested Citation
Rotejanaprasert C., Malaphone V., Mayxay M., Chindavongsa K., Banouvong V., Khamlome B., Vilay P., Vanisavaeth V., Maude R.J. Spatiotemporal patterns and association with climate for malaria elimination in Lao PDR: a hierarchical modelling analysis with two-step Bayesian model selection. Malaria Journal Vol.23 No.1 (2024). doi:10.1186/s12936-024-05064-0 Retrieved from: https://repository.li.mahidol.ac.th/handle/20.500.14594/100440
Title
Spatiotemporal patterns and association with climate for malaria elimination in Lao PDR: a hierarchical modelling analysis with two-step Bayesian model selection
Corresponding Author(s)
Other Contributor(s)
Abstract
Background: The government of Lao PDR has increased efforts to control malaria transmission in order to reach its national elimination goal by 2030. Weather can influence malaria transmission dynamics and should be considered when assessing the impact of elimination interventions but this relationship has not been well characterized in Lao PDR. This study examined the space–time association between climate variables and Plasmodium falciparum and Plasmodium vivax malaria incidence from 2010 to 2022. Methods: Spatiotemporal Bayesian modelling was used to investigate the monthly relationship, and model selection criteria were used to evaluate the performance of the models and weather variable specifications. As the malaria control and elimination situation was spatially and temporally dynamic during the study period, the association was examined annually at the provincial level. Results: Malaria incidence decreased from 2010 to 2022 and was concentrated in the southern regions for both P. falciparum and P. vivax. Rainfall and maximum humidity were identified as most strongly associated with malaria during the study period. Rainfall was associated with P. falciparum incidence in the north and central regions during 2010–2011, and with P. vivax incidence in the north and central regions during 2012–2015. Maximum humidity was persistently associated with P. falciparum and P. vivax incidence in the south. Conclusions: Malaria remains prevalent in Lao PDR, particularly in the south, and the relationship with weather varies between regions but was strongest for rainfall and maximum humidity for both species. During peak periods with suitable weather conditions, vector control activities and raising public health awareness on the proper usage of intervention measures, such as indoor residual spraying and personal protection, should be prioritized.