ArticleBMJ global health2018
Appraising the value of evidence generation activities: an HIV modelling study.
Article in BMJ global health, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
What it found
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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.
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Who cites it
5 citing papers in PubMed.
- Modeling policy decisions to mitigate the risk of emerging arboviral diseases under ecological changes in Uganda: Proposing a one Health in all policies approach.One health (Amsterdam, Netherlands) · 2026Article
- Article
- Bayesian validation framework for dynamic epidemic models.Epidemics · 2021Article
- Practical metrics for establishing the health benefits of research to support research prioritisation.BMJ global health · 2020Article
- The importance of local epidemic conditions in monitoring progress towards HIV epidemic control in Kenya: a modelling study.Journal of the International AIDS Society · 2018Article
Corrections and comments
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Authors and funding
7 authors.
Funding
Abstract
introductionThe generation of robust evidence has been emphasised as a priority for global health. Evidence generation spans a wide range of activities including clinical trials, surveillance programmes and health system performance measurement. As resources for healthcare and research are limited, the desirability of research expenditure should be assessed on the same basis as other healthcare resources, that is, the health gains from research must be expected to exceed the health opportunity costs imposed as funds are diverted to research rather than service provision.
methodsWe developed a transmission and costing model to examine the impact of generating additional evidence to reduce uncertainties on the evolution of a generalised HIV epidemic in Zambia.
resultsWe demonstrate three important points. First, we can quantify the value of additional evidence in terms of the health gain it is expected to generate. Second, we can quantify the health opportunity cost imposed by research expenditure. Third, the value of evidence generation depends on the budgetary policies in place for managing HIV resources under uncertainty. Generating evidence to reduce uncertainty is particularly valuable when decision makers are required to strictly adhere to expenditure plans and when transfers of funds across geographies/programmes are restricted.
conclusionBetter evidence can lead to health improvements in the same way as direct delivery of healthcare. Quantitative appraisals of evidence generation activities are important and should reflect the impact of improved evidence on population health, evidence generation costs and budgetary policies in place.
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Registered trials
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