BACKGROUND: Artemisinin-based combination therapies (ACTs) are first-line treatment for uncomplicated malaria in sub-Saharan Africa, but emerging artemisinin partial resistance threatens efficacy. Multiple first-line treatments (MFTs) represent a proposed strategy to delay resistance emergence by deploying several ACTs simultaneously, sequentially, or using other strategies rather than relying on a single first-line therapy.
STUDY DESIGN: This 28-month implementation program (June 2020 - October 2022) with and extension only on Mfangano Island until January 2024, deployed adaptive cycling of four artemisinin-based combinations across health facilities in Western Kenya using geographic allocation:
INTERVENTION COUNTY - HOMA BAY:
- Homa Bay Mainland (n=approximately 40,000 patients treated): Sequential deployment with 8-month cycling using crowding-out approach: Baseline (AL) → DHA-PIP (8 months) → AS+AQ (8 months) → AL (8 months)
- Mfangano Island (n=approximately 21,000 patients treated): Extended single MFT deployment: Baseline (AL) → AS+PYD (39 months). This extension allowed longer follow-up surveillance of the most recent combination ACT in Kenya where data was not previously monitored.
COMPARISON COUNTY - MIGORI:
- Continued artemether-lumefantrine (AL) monotherapy throughout study period (n=32,835 patients treated) PARTICIPANTS: Adults and children ≥5 years diagnosed with uncomplicated Plasmodium falciparum malaria at participating health facilities. Excluded: pregnant women and children <5 years due to medication restrictions and lack of pediatric formulations.
OUTCOMES MEASURED:
Primary Outcomes (reported in Cole et al., Malaria Journal 2024):
- Health systems feasibility was assessed through commodity management, human resources adequacy, information system functionality, and implementation barriers/facilitators analysis
- Economic costs of MFT deployment including start-up and implementation phases, calculated per facility and per patient were sought after
- Stakeholder acceptability among policymakers, healthcare workers, and patients assessed through key informant interviews and surveys was analyzed.
Secondary Outcomes (reported in companion manuscript recently submitted for peer-review):
- Prevalence of antimalarial resistance markers in dhfr (N51I, C59R, S108N, I164L), dhps (S436H, A437G, K540E, A581G), mdr1 (N86Y, Y184F), and k13 (A578S, A675V) genes
- Temporal trends in resistance marker prevalence over four timepoints (September 2020, August-October 2021, May-July 2022, November 2023-January 2024)
- Geographic distribution of resistance patterns across study sites
- Complexity of infection (COI) determined by molecular methods
METHODS:
- Sample collection: Dried blood spots (n=310) from malaria-positive patients at four timepoints
- Molecular analysis: Targeted amplicon deep sequencing using Oxford Nanopore Technology
- Health systems assessment: Semi-structured questionnaires, key informant interviews, exit interviews, cost analysis using activity-based costing
- Statistical analysis: Chi-square tests, Cochran-Armitage trend tests, machine learning models for resistance prediction SETTING: Government and faith-based health facilities in Homa Bay County facilities received MFTs and Migori County (control) where AL was the only ACT used in Western Kenya, a malaria-endemic region with high transmission intensity.
ETHICAL APPROVAL: Strathmore University Institutional Scientific and Ethics Review Committee (SU-ISERC 1730/20) and Kenya National Commission for Science, Technology and Innovation (NACOSTI).
