ArticlePLOS digital health2025
Assessment of digital payment for agents in mass chemoprevention campaigns: The Karangué Fay project in Senegal.
Article in PLOS digital health, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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12 authors.
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Abstract
The payment of healthcare agents is a critical component of organizing mass health campaigns. This study examined the effects of digital payments during seasonal malaria chemoprevention (SMC) campaigns in Senegal. A quasi-experimental three-arm before-after/here-elsewhere design was implemented between March and June 2023: mandatory digital payment in Kounkané, voluntary in Koussanar, and cash-based control in Bantaco. Mixed methods were employed, and ethical approval was granted by Senegal's National Ethics Committee (CNERS). A total of 299 agents participated, with 181 surveyed before and 118 after the intervention. Participants were distributed across Kounkané (48.8%), Koussanar (35.8%), and Bantaco (15.4%). Community health workers comprised the majority (90.9%). Median age was 32 years, with a median tenure of three years; 50.8% were male and 65.2% married. All agents owned at least one mobile money account, with Wave (96%) and Orange Money (90%) being the most common. Reliability criteria included security (95%), ease of use (90.3%), and cash availability (79.2%). Karangué Fay digital payments were perceived as secure (82.4%), reliable (83.1%), faster (78.2%), transparent (91.3%), and confidential (95.2%). Compared to cash, digital payments were significantly preferred for transaction security, speed, and usability (p < 0.001). Qualitative interviews highlighted traceability, transparency, and efficiency but noted limitations linked to internet connectivity. Digital payments were highly acceptable to SMC agents, improving engagement and performance. They also contributed to better campaign coverage across different implementation phases, underscoring their potential to strengthen health systems in low-resource settings.
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