Key result
Sub-Saharan Africa CVD prevention models primarily evaluate pharmacological primary prevention, neglecting primordial strategies and equity.
Why the study?
Sub-Saharan Africa has experienced an increasing CVD burden over the last two decades, prompting an examination of decision analytic models used to evaluate CVD prevention interventions.
Systematic Review (n=27)
There is a need for increased transparency in model building, validation, and documentation, as well as a greater focus on primordial prevention and equity in CVD prevention models in Sub-Saharan Africa.
Models for CVD prevention in Sub-Saharan Africa overlook equity and primordial prevention with limited validation; challenges their reliability for guiding strategies.
BACKGROUND: This systematic review sought to examine the application of decision analytic models (DAMs) to evaluate cardiovascular disease (CVD) prevention interventions in sub-Saharan Africa (SSA), a region that has experienced an increasing CVD burden in the last two decades. METHODS: We searched seven databases and identified model-based economic evaluations of interventions targeting CVD prevention among adult populations in SSA. All articles were screened by two reviewers, data was extracted, and narrative synthesis was performed. Quality assessment was performed using the Philips checklist. RESULTS: The review included 27 articles from eight SSA countries. The majority of the studies evaluated interventions for primary CVD prevention, with primordial prevention interventions being the least evaluated. Markov models were the most commonly used modelling method. Seven studies incorporated equity dimensions in the modelling, which were assessed mainly through subgroup analysis. The mean quality score of the papers was 68.9% and most studies reported data challenges while only three studies conducted model validation. CONCLUSIONS: The review finds few studies modelling the impact of interventions targeting primordial prevention and those evaluating equitable strategies for improving access to CVD prevention. There is a need for increased transparency in model building, validation and documentation.
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Oguta et al. (2025) conducted a systematic review in Cardiovascular disease prevention (n=27). Decision analytic models for cardiovascular disease prevention was evaluated on Application and characteristics of decision analytic models (DAMs). Decision analytic models for cardiovascular disease prevention in Sub-Saharan Africa primarily evaluated pharmacological interventions for primary prevention using Markov models, with limited focus on primordial prevention or equity.
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