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Industry guide
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Abby Sotomiwa
June 2026·6 min read

Clinical trial and health research incentives in Africa

Clinical trials and cohort health studies in Africa face a participant retention problem that is fundamentally logistical as much as it is scientific. Participants who don't receive their stipends reliably don't return for follow-up visits. The quality of the science depends on the quality of the payment infrastructure.

Africa is an increasingly important region for clinical research — HIV, malaria, tuberculosis, and NCD studies run across Nigeria, Kenya, Uganda, South Africa, and elsewhere. The regulatory environment has improved significantly, and African CROs have developed substantial capacity. The operational weakness that persists across many trials is participant payment.

Cash payment via research nurses creates a paper trail problem and a security concern. Bank transfers require bank account details that many participants don't have. Mobile money works in some markets but not all. The result is trials that disburse slowly, inconsistently, and with documentation gaps that complicate IRB reporting.

Why retention is the central challenge

A longitudinal clinical trial with 30% participant dropout between baseline and 12-month follow-up has compromised its statistical power and may have introduced selection bias — the participants who dropped out may differ systematically from those who stayed. Both problems threaten the validity of the findings and the regulatory submission that depends on them.

The primary reasons African participants give for study dropout are: inconvenience of visit scheduling, perceived lack of benefit from participation, and — consistently — delayed or missed stipend payments. The last one is the most directly addressable.

A participant who has been paid reliably at every visit has a strong concrete reason to return. The research relationship is reciprocal — and that reciprocity is measured in whether the stipend arrived.

Incentive disbursement that works for clinical populations

Clinical research participants span a wide demographic range. In community-based trials, a significant proportion may be unbanked or have irregular banking relationships. The disbursement infrastructure must work without a bank account requirement.

  • →Visit attendance payment: Incentive triggered when the study nurse or coordinator marks the participant as attended in the trial management system. Payment arrives via SMS before the participant leaves the site.
  • →Transport reimbursement: A specific transport allowance delivered separately from the study incentive, acknowledging the cost of travel to the site.
  • →Procedure-specific incentives: Higher payments for visits involving blood draw, biopsy, or other procedures that carry burden for the participant.
  • →Study completion bonus: A larger reward on completion of the full study protocol. Creates a retention incentive for the final visits, which typically have the highest dropout rates.

IRB and ethics committee considerations

IRBs and ethics committees review incentive structures to ensure payments are not coercive — that is, not so large that they impair a participant's voluntary decision to join or continue the study, particularly for low-income populations. The standard guidance is that incentives should compensate for time and inconvenience without creating undue inducement.

Gift card incentives are generally viewed favourably by ethics committees because they have a defined, transparent value, are traceable, and can be structured to avoid cash-equivalent flexibility that might be seen as more coercive. The ability to demonstrate that every incentive was delivered as described in the protocol — with a digital delivery and redemption record — simplifies the ethics reporting process.

Blinding and anonymisation

In blinded trials, the incentive delivery mechanism should not inadvertently reveal treatment arm allocation. Ensure that reward amounts and timing are identical across arms, and that the delivery records cannot be used to infer treatment allocation in a blinded data set.

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