A microplanning model to improve door-to-door health service delivery: the case of Seasonal Malaria Chemoprevention in Sub-Saharan African villages.

Burkina Faso CHW Community health worker Door-to-door Malaria Microplanning Model SMC Satellite imagery Seasonal malaria chemoprevention

Journal

BMC health services research
ISSN: 1472-6963
Titre abrégé: BMC Health Serv Res
Pays: England
ID NLM: 101088677

Informations de publication

Date de publication:
07 Dec 2020
Historique:
received: 26 09 2020
accepted: 25 11 2020
entrez: 8 12 2020
pubmed: 9 12 2020
medline: 15 5 2021
Statut: epublish

Résumé

Malaria incidence has plateaued in Sub-Saharan Africa despite Seasonal Malaria Chemoprevention's (SMC) introduction. Community health workers (CHW) use a door-to-door delivery strategy to treat children with SMC drugs, but for SMC to be as effective as in clinical trials, coverage must be high over successive seasons. We developed and used a microplanning model that utilizes population raster to estimate population size, generates optimal households visit itinerary, and quantifies SMC coverage based on CHWs' time investment for treatment and walking. CHWs' performance under current SMC deployment mode was assessed using CHWs' tracking data and compared to microplanning in villages with varying demographics and geographies. Estimates showed that microplanning significantly reduces CHWs' walking distance by 25%, increases the number of visited households by 36% (p < 0.001) and increases SMC coverage by 21% from 37.3% under current SMC deployment mode up to 58.3% under microplanning (p < 0.001). Optimal visit itinerary alone increased SMC coverage up to 100% in small villages whereas in larger or hard-to-reach villages, filling the gap additionally needed an optimization of the CHW ratio. We estimate that for a pair of CHWs, the daily optimal number of visited children (assuming 8.5mn spent per child) and walking distance should not exceed 45 (95% CI 27-62) and 5 km (95% CI 3.2-6.2) respectively. Our work contributes to extend SMC coverage by 21-63% and may have broader applicability for other community health programs.

Sections du résumé

BACKGROUND BACKGROUND
Malaria incidence has plateaued in Sub-Saharan Africa despite Seasonal Malaria Chemoprevention's (SMC) introduction. Community health workers (CHW) use a door-to-door delivery strategy to treat children with SMC drugs, but for SMC to be as effective as in clinical trials, coverage must be high over successive seasons.
METHODS METHODS
We developed and used a microplanning model that utilizes population raster to estimate population size, generates optimal households visit itinerary, and quantifies SMC coverage based on CHWs' time investment for treatment and walking. CHWs' performance under current SMC deployment mode was assessed using CHWs' tracking data and compared to microplanning in villages with varying demographics and geographies.
RESULTS RESULTS
Estimates showed that microplanning significantly reduces CHWs' walking distance by 25%, increases the number of visited households by 36% (p < 0.001) and increases SMC coverage by 21% from 37.3% under current SMC deployment mode up to 58.3% under microplanning (p < 0.001). Optimal visit itinerary alone increased SMC coverage up to 100% in small villages whereas in larger or hard-to-reach villages, filling the gap additionally needed an optimization of the CHW ratio.
CONCLUSION CONCLUSIONS
We estimate that for a pair of CHWs, the daily optimal number of visited children (assuming 8.5mn spent per child) and walking distance should not exceed 45 (95% CI 27-62) and 5 km (95% CI 3.2-6.2) respectively. Our work contributes to extend SMC coverage by 21-63% and may have broader applicability for other community health programs.

Identifiants

pubmed: 33287825
doi: 10.1186/s12913-020-05972-2
pii: 10.1186/s12913-020-05972-2
pmc: PMC7720067
doi:

Substances chimiques

Antimalarials 0

Types de publication

Clinical Study Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

1128

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Auteurs

André Lin Ouédraogo (AL)

Institute for Disease Modeling, Bill and Melinda Gates Foundation, 500 5th Ave N, Seattle, WA, 98109, USA. aouedraogo@idmod.org.

Julie Zhang (J)

Department of Mathematics and Statistics, University of Washington, Seattle, WA, USA.
Department of Statistics, Stanford University, Palo Alto, CA, USA.

Halidou Tinto (H)

Institut de Recherche en Sciences de la Santé, Clinical Research Unit of Nanoro, Nanoro, Burkina Faso.

Innocent Valéa (I)

Institut de Recherche en Sciences de la Santé, Clinical Research Unit of Nanoro, Nanoro, Burkina Faso.

Edward A Wenger (EA)

Institute for Disease Modeling, Bill and Melinda Gates Foundation, 500 5th Ave N, Seattle, WA, 98109, USA.

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Classifications MeSH