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Bayesian Spatiotemporal Modeling of Routinely Collected Data to Assess the Effect of Health Programs in Malaria Incidence During Pregnancy in Burkina Faso

Authors
  • Rouamba, Toussaint1, 2
  • Samadoulougou, Sekou3, 4
  • Tinto, Halidou1
  • Alegana, Victor A.5, 6
  • Kirakoya-Samadoulougou, Fati2
  • 1 Clinical Research Unit of Nanoro, Institute for Research in Health Sciences, National Center for Scientific and Technological Research, 528, Avenue Kumda-Yoore, BP 218 Ouagadougou CMS 11, Ouagadougou, Burkina Faso , Ouagadougou (Burkina Faso)
  • 2 Center for research in epidemiology, Biostatistics and Clinical Research, School of Public Health, University libre de Bruxelles (ULB), Route de Lennik, 808 B-1070 Bruxelles, Brussels, Belgium , Brussels (Belgium)
  • 3 Centre for Research on Planning and Development (CRAD), Laval University, Quebec, G1V 0A6, Canada , Quebec (Canada)
  • 4 Evaluation Platform on Obesity Prevention, Quebec Heart and Lung Institute, Quebec, G1V 4G5, Canada , Quebec (Canada)
  • 5 Kenya Medical Research Institute - Wellcome Trust Research Programme, Nairobi, Kenya , Nairobi (Kenya)
  • 6 Geography and Environmental Science, University of Southampton, Southampton, SO17 1BJ, UK , Southampton (United Kingdom)
Type
Published Article
Journal
Scientific Reports
Publisher
Springer Nature
Publication Date
Feb 14, 2020
Volume
10
Issue
1
Identifiers
DOI: 10.1038/s41598-020-58899-3
Source
Springer Nature
License
Green

Abstract

Control of malaria in pregnancy (MiP) remains a major challenge in Burkina Faso. Surveillance of the burden due to MiP based on routinely collected data at a fine-scale level, followed by an appropriate analysis and interpretation, may be crucial for evaluating and improving the effectiveness of existing control measures. We described the spatio-temporal dynamics of MiP at the community-level and assessed health program effects, mainly community-based health promotion, results-based financing, and intermittent-preventive-treatment with sulphadoxine-pyrimethamine (IPTp-SP). Community-aggregated monthly MiP cases were downloaded from Health Management Information System and combined with covariates from other sources. The MiP spatio-temporal pattern was decomposed into three components: overall spatial and temporal trends and space-time interaction. Bayesian hierarchical spatio-temporal Poisson models were used to fit the MiP incidence rate and assess health program effects. The overall annual incidence increased between 2015 and 2017. The findings reveal spatio-temporal heterogenicity throughout the year, which peaked during rainy season. From the model without covariates, 96 communities located mainly in the Cascades, South-West, Center-West, Center-East, and Eastern regions, exhibited significant relative-risk levels. The combined effect (significant reducing effect) of RBF, health promotion and IPTp-SP strategies was greatest in 17.7% (17/96) of high burden malaria communities. Despite intensification of control efforts, MiP remains high at the community-scale. The provided risk maps are useful tools for highlighting areas where interventions should be optimized, particularly in high-risk communities.

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