Evidence map›Paper›PMID 37891177›Full record

ArticleNature communications2023

Using drivers and transmission pathways to identify SARS-like coronavirus spillover risk hotspots.

Renata L Muylaert, David A Wilkinson, Tigga Kingston, Paolo D'Odorico, Maria Cristina Rulli, Nikolas Galli, Reju Sam John, Phillip Alviola, David T S Hayman

Abstract read
In one paragraph

Article in Nature communications, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.

0numbers the graph read from it
0cells of the map it votes in
15citing papers in PubMed
–field-weighted citation impact
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

15 citing papers in PubMed.

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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

9 authors.

Renata L MuylaertSchool of Veterinary Science, Massey University, Palmerston North, New Zealand. R.deLaraMuylaert@massey.ac.nz.ORCID 0000-0002-6466-6210
David A WilkinsonUMR ASTRE, CIRAD, INRAE, Université de Montpellier, Plateforme Technologique CYROI, Sainte-Clotilde, La Réunion, France.
Tigga KingstonDepartment of Biological Sciences, Texas Tech University, Lubbock, TX, USA.ORCID 0000-0003-3552-5352
Paolo D'OdoricoDepartment of Environmental Science, Policy, and Management, University of California, Berkeley, Berkeley, CA, USA.ORCID 0000-0002-0007-5833
Maria Cristina RulliDepartment of Civil and Environmental Engineering, Politecnico di Milano, Milan, Italy.ORCID 0000-0002-9694-4262
Nikolas GalliDepartment of Civil and Environmental Engineering, Politecnico di Milano, Milan, Italy.ORCID 0000-0002-6746-5350
Reju Sam JohnDepartment of Physics, Faculty of Science, University of Auckland, Auckland, New Zealand.
Phillip AlviolaInstitute of Biological Sciences, University of the Philippines- Los Banos, Laguna, Philippines.
David T S HaymanSchool of Veterinary Science, Massey University, Palmerston North, New Zealand.ORCID 0000-0003-0087-3015

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The emergence of SARS-like coronaviruses is a multi-stage process from wildlife reservoirs to people. Here we characterize multiple drivers-landscape change, host distribution, and human exposure-associated with the risk of spillover of zoonotic SARS-like coronaviruses to help inform surveillance and mitigation activities. We consider direct and indirect transmission pathways by modeling four scenarios with livestock and mammalian wildlife as potential and known reservoirs before examining how access to healthcare varies within clusters and scenarios. We found 19 clusters with differing risk factor contributions within a single country (N = 9) or transboundary (N = 10). High-risk areas were mainly closer (11-20%) rather than far ( < 1%) from healthcare. Areas far from healthcare reveal healthcare access inequalities, especially Scenario 3, which includes wild mammals and not livestock as secondary hosts. China (N = 2) and Indonesia (N = 1) had clusters with the highest risk. Our findings can help stakeholders in land use planning, integrating healthcare implementation and One Health actions.

Indexed as

Severe acute respiratory syndrome-related coronavirusAnimalsAnimals, WildHumansLivestockMammalsRisk Factors

Identifiers

PMID37891177
PMCPMC10611769

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.