Predicting adherence to postdischarge malaria chemoprevention in Malawian pre-school children: A prognostic multivariable analysis.
Melf-Jakob KühlThandile Nkosi-GondweFeiko O Ter KuileKamija S PhiriMehmajeet PannuMavuto MukakaBjarne RobberstadIngunn Marie Stadskleiv EngebretsenPublished in: PLOS global public health (2023)
Chemoprevention with antimalarials is a key strategy for malaria control in sub-Saharan Africa. Three months of postdischarge malaria chemoprevention (PDMC) reduces malaria-related mortality and morbidity in pre-school children recently discharged from hospital following recovery from severe anemia. Research on adherence to preventive antimalarials in children is scarce. We aimed to investigate the predictors for caregivers' adherence to three courses of monthly PDMC in Malawi. We used data from a cluster randomized implementation trial of PDMC in Malawi (n = 357). Modified Poisson regression for clustered data was used to obtain relative risks of predictors for full adherence to PDMC. We did not find a conclusive set of predictors for PDMC adherence. The distribution of households across a socio-economic index and caregivers' education showed mixed associations with poor adherence. Caregivers of children with four or more malaria infections in the past year were associated with reduced adherence. With these results, we cannot confirm the associations established in the literature for caregiver adherence to artemisinin-based combination therapies (ACTs). PDMC combines multiple factors that complicate adherence. Our results may indicate that prevention interventions introduce a distinct complexity to ACT adherence behavior. Until we better understand this relationship, PDMC programs should ensure high program fidelity to sustain adherence by caregivers during implementation.
Keyphrases
- healthcare
- glycemic control
- emergency department
- systematic review
- plasmodium falciparum
- electronic health record
- type diabetes
- primary care
- public health
- randomized controlled trial
- chronic kidney disease
- study protocol
- cardiovascular events
- clinical trial
- metabolic syndrome
- machine learning
- insulin resistance
- physical activity
- risk factors
- phase ii
- skeletal muscle
- placebo controlled
- big data