Bayesian spatiotemporal modeling of routinely collected data to assess the effect of health programs in malaria incidence during pregnancy in Burkina Faso

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.

10.1038/s41598-020-58899-3

2045-2322

Rouamba, Toussaint

6c1b9f83-cf67-4594-96a6-ab29fd0af593

Samadoulougou, Sekou

acd5e8cf-d12a-4294-80e4-a87c6e23d2de

Tinto, Halidou

8f149b48-e65f-4ae7-9e4e-5d7923e61c85

Alegana, Victor A.

f5bd6ab7-459e-4122-984f-2bdb5f906d82

Kirakoya-Samadoulougou, Fati

7198d2b2-fc56-4251-a9b6-3fe512c105a5

1 December 2020

Rouamba, Toussaint

6c1b9f83-cf67-4594-96a6-ab29fd0af593

Samadoulougou, Sekou

acd5e8cf-d12a-4294-80e4-a87c6e23d2de

Tinto, Halidou

8f149b48-e65f-4ae7-9e4e-5d7923e61c85

Alegana, Victor A.

f5bd6ab7-459e-4122-984f-2bdb5f906d82

Kirakoya-Samadoulougou, Fati

7198d2b2-fc56-4251-a9b6-3fe512c105a5

Rouamba, Toussaint, Samadoulougou, Sekou, Tinto, Halidou, Alegana, Victor A. and Kirakoya-Samadoulougou, Fati (2020) Bayesian spatiotemporal modeling of routinely collected data to assess the effect of health programs in malaria incidence during pregnancy in Burkina Faso. Scientific Reports, 10 (1), [2618]. (doi:10.1038/s41598-020-58899-3).

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Accepted/In Press date: 19 January 2020

e-pub ahead of print date: 14 February 2020

Published date: 1 December 2020

Additional Information: Funding Information: We thank the Directorate General of Studies and Sectoral Statistics of the Ministry of Health of Burkina Faso for access freely to the National Health Management Information database. We acknowledge the reviewers for their valuable comments and suggestions that contributed to improving the scientific value of the manuscript. T.R is funded through a travel grant from ARES-CCD; V.A.A is funded through a Wellcome Trust Training Fellowship (number 211208). Funding Information: The authors declare that they have no financial or non-financial competing interests. This research (data analysis and manuscript writing) was conducted with the support of a travel grant from the Academy for Research and Higher Education - Commission for Development Cooperation (ARES-CCD) funded by the Belgian government. Publisher Copyright: © 2020, The Author(s).