ArticleHealth policy and planning2024
The role of constraints and information gaps in driving risky medicine purchasing practices in four African countries.
Article in Health policy and planning, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
4 citing papers in PubMed, 5 citations in OpenAlex.
- Logics of acquiring medicines from informal retailers in four African countries.Global health action · 2025Article
- Can public education campaigns equitably counter the use of substandard and falsified medical products in African countries?Health policy and planning · 2025Article
- Assessing knowledge, attitudes, and practices and demand-side interventions for combating substandard and falsified medicines: a scoping review.Journal of pharmaceutical policy and practice · 2025Review
- Perceptions and practices on substandard and falsified medicines in humans and animals in Wakiso district, Uganda: A qualitative study.PloS one · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
10 authors at 3 institutions in 3 countries.
Funding
Abstract
Substandard and falsified (SF) medical products pose a major threat to public health and socioeconomic development, particularly in low- and middle-income countries. In response, public education campaigns have been developed to alert consumers about the risks of SF medicines and provide guidance on 'safer' practices, along with other demand- and supply-side measures. However, little is currently known about the potential effectiveness of such campaigns while structural constraints to accessing quality-assured medicines persist. This paper analyses survey data on medicine purchasing practices, information and constraints from four African countries (Ghana, Nigeria, Sierra Leone and Uganda; n > 1000 per country). Using multivariate regression and structural equation modelling, we present what we believe to be the first attempt to tease apart, statistically, the effects of an information gap vs structural constraints in driving potential public exposure to SF medicines. The analysis confirms that less privileged groups (including, variously, those in rural settlements, with low levels of formal education, not in paid employment, often women and households with a disability or long-term sickness) are disproportionately potentially exposed to SF medicines; these same demographic groups also tend to have lower levels of awareness and experience greater levels of constraint. Despite the constraints, our models suggest that public health education may have an important role to play in modifying some (but not all) risky practices. Appropriately targeted public messaging can thus be a useful part of the toolbox in the fight against SF medicines, but it can only work effectively in combination with wider-reaching reforms to address higher-level vulnerabilities in pharmaceutical supply chains in Africa and expand access to quality-assured public-sector health services.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.