ArticleBMJ open2022
Policies to prevent zoonotic spillover: protocol for a systematic scoping review of evaluative evidence.
Article in BMJ open, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 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
3 citing papers in PubMed, 4 citations in OpenAlex.
- Wildlife policy, the food system and One Health: a complex systems analysis of unintended consequences for the prevention of emerging zoonoses in China, the Democratic Republic of the Congo and the Philippines.BMJ global health · 2025Article
- Integrating animal welfare into the WHO pandemic treaty: a thematic analysis of civil society perspectives and comparison with treaty drafting.Frontiers in veterinary science · 2024Article
- Policies to prevent zoonotic spillover: a systematic scoping review of evaluative evidence.Globalization and health · 2023Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
13 authors at 4 institutions in 3 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
introductionThe increasing incidence of pathogen transmission from animals to humans (zoonotic spillover events) has been attributed to behavioural practices and ecological and socioeconomic change. As these events sometimes involve pathogens with epidemic or pandemic potential, they pose a serious threat to population health. Public policies may play a key role in preventing these events. The aim of this review is to identify evaluations of public policies that target the determinants of zoonotic spillover, examining approaches taken to evaluation, choice of outcomes measures and evidence of effectiveness. Our approach to identifying and analysing this literature will be informed by a One Health lens, acknowledging the interconnectedness of human, animal and environmental health. METHODS AND ANALYSIS: A systematic scoping review methodology will be used. To identify articles, we will search Medline, SCOPUS, Web of Science and Global Health in May 2021 using search terms combining animal health and the animal-human interface, public policy, prevention and zoonoses. We will screen titles and abstracts and extract data according to published guidelines for scoping reviews. All evaluations of public policies aiming to prevent zoonotic spillover events will be eligible for inclusion. We will summarise key data from each study, mapping policies along the spillover pathway and outlining the range of policies, approaches to evaluation and outcome measures. Review findings will provide a useful reference for researchers and practitioners, outlining the state of the evaluative evidence around policies to prevent zoonotic spillover. ETHICS AND DISSEMINATION: Formal ethical approval is not required, because the study does not involve primary data collection. The findings of this study will be disseminated through a peer-reviewed publication, presentations and summaries for key stakeholders.
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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.