Evidence map›Paper›PMID 35732674›Full record

ArticleScientific reports2022

Participatory mapping identifies risk areas and environmental predictors of endemic anthrax in rural Africa.

Olubunmi R Aminu, Taya L Forde, Divine Ekwem, Paul Johnson, Luca Nelli, Blandina T Mmbaga, Deogratius Mshanga, Mike Shand, Gabriel Shirima, Markus Walsh and 3 more

Open access · goldAbstract read
In one paragraph

Article in Scientific reports, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
0.4field-weighted citation impact, top 42% of its field
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

7 citing papers in PubMed, 7 citations in OpenAlex.

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  5. InvestigatingbioRxiv : the preprint server for biology · 2025
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

13 authors at 6 institutions in 3 countries.

Olubunmi R AminuInstitute of Biodiversity, Animal Health & Comparative Medicine, University of Glasgow, Glasgow, UK. rhoda.aminu@glasgow.ac.uk.
Taya L FordeInstitute of Biodiversity, Animal Health & Comparative Medicine, University of Glasgow, Glasgow, UK.
Divine EkwemInstitute of Biodiversity, Animal Health & Comparative Medicine, University of Glasgow, Glasgow, UK.
Paul JohnsonInstitute of Biodiversity, Animal Health & Comparative Medicine, University of Glasgow, Glasgow, UK.
Luca NelliInstitute of Biodiversity, Animal Health & Comparative Medicine, University of Glasgow, Glasgow, UK.
Blandina T MmbagaKilimanjaro Christian Medical University College, Moshi, Tanzania.
Deogratius MshangaTanzania Veterinary Laboratory Agency, Northern Zone, Arusha, Tanzania.
Mike ShandSchool of Geographical & Earth Sciences, University of Glasgow, Glasgow, UK.
Gabriel ShirimaNelson Mandela African Institution of Science and Technology, Arusha, Tanzania.
Markus WalshInternational Center for Tropical Agriculture, Selian Agricultural Research Institute, Arusha, Tanzania.
Ruth N ZadoksSydney School of Veterinary Science, University of Sydney, Sydney, Australia.
Roman Biek *Institute of Biodiversity, Animal Health & Comparative Medicine, University of Glasgow, Glasgow, UK.
Tiziana Lembo *Institute of Biodiversity, Animal Health & Comparative Medicine, University of Glasgow, Glasgow, UK.
University of Glasgow · GBNelson Mandela African Institution of Science and Technology · TZInternational Institute of Tropical Agriculture · TZKilimanjaro Christian Medical Centre · TZTanzania National Parks · TZUniversity of Sydney · AU

Funding

Biotechnology and Biological Sciences Research Council BB/R012075/1Gates Foundation 1083453Marie Curie 659223Wellcome TrustWellcome Trust SBF002\1168
6 · The paper itself

Abstract

Disease mapping reveals geographical variability in incidence, which can help to prioritise control efforts. However, in areas where this is most needed, resources to generate the required data are often lacking. Participatory mapping, which makes use of indigenous knowledge, is a potential approach to identify risk areas for endemic diseases in low- and middle-income countries. Here we combine this method with Geographical Information System-based analyses of environmental variables as a novel approach to study endemic anthrax, caused by the spore-forming bacterium Bacillus anthracis, in rural Africa. Our aims were to: (1) identify high-risk anthrax areas using community knowledge; (2) enhance our understanding of the environmental characteristics associated with these areas; and (3) make spatial predictions of anthrax risk. Community members from the Ngorongoro Conservation Area (NCA), northern Tanzania, where anthrax is highly prevalent in both animals and humans, were asked to draw areas they perceived to pose anthrax risks to their livestock on geo-referenced maps. After digitisation, random points were generated within and outside the defined areas to represent high- and low-risk areas, respectively. Regression analyses were used to identify environmental variables that may predict anthrax risk. Results were combined to predict how the probability of being a high-risk area for anthrax varies across space. Participatory mapping identified fourteen discrete high-risk areas ranging from 0.2 to 212.9 km

Indexed as

AnthraxBacillus anthracisAnimalsAnimals, WildDisease OutbreaksLivestockTanzania

Identifiers

PMID35732674
PMCPMC9217952
OpenAlexW4283277800

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.