ArticleBMJ open2023
Article in BMJ open, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 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
2 citing papers in PubMed, 2 citations in OpenAlex.
- Artificial intelligence for climate-health early warning systems in the Horn of Africa: opportunities, challenges, and a roadmap for action.Globalization and health · 2026Article
- Effect of Supervision or Short Messages (SMS) on the Detection Rate of Diseases Under Surveillance in the Littoral Region of Cameroon: A Randomized Controlled Health Facility-Based Trial.Research and reports in tropical medicine · 2026Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
8 authors at 4 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
introductionCountries in the WHO's African region have found community-based surveillance useful in ensuring the effectiveness of the Integrated Disease Surveillance and Response strategy. This approach encourages community participation in the surveillance system, in addition to early detection of outbreaks and other health threats. Thus, advancements in mobile health have the potential to improve community-based surveillance in Africa. The purpose of this review is to map evidence on available mhealth tools for community-based infectious disease surveillance in Africa. METHODS AND ANALYSIS: The scoping review will follow a mixed-methods approach in line with the framework of Arksey and O'Malley amended by Levac and colleagues and the Joanna Briggs Institute. To retrieve published literature, PubMed, Scopus, Web of Science, Google Scholar and Google databases will be explored. Websites of organisations involved in surveillance activities across the African region will also be explored. Authors will be interested in published literature between 2000 and 2022 in any language. The primary investigator and a second author will independently review the retrieved titles according to the inclusion criteria, while a third reviewer will resolve conflicts that may arise. The review will map evidence according to the key concepts (mhealth, community-based surveillance and Africa) to inform stakeholders and mhealth designers on best practices to adopt involving mhealth approaches at the community level and mhealth tool designs, respectively. Results following the review will be presented according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses: Extension for Scoping Review Guidelines. ETHICS AND DISSEMINATION: Ethical approval is not required for scoping reviews as it does not involve the use of human subjects. This review is the first phase in an overall project on digital health. The findings of the review will be published in a peer-reviewed journal and disseminated at suitable forums and conferences.
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.