Evidence map›Paper›PMID 40346370›Full record

ArticleTropical animal health and production2025

Disease outbreak data to inform decision-making: the role of disease spread models in the Lao P.D.R. African Swine Fever epidemic, 2019.

Nina Matsumoto, Tariq Halasa, Kathrin Schemann, Syseng Khounsy, Bounlom Douangngeun, Watthana Thepagna, Phouvong Phommachanh, Jarunee Siengsanan-Lamont, James Young, Jenny-Ann Toribio and 3 more

Abstract read
In one paragraph

Article in Tropical animal health and production, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Review
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.

Nina MatsumotoSydney School of Veterinary Science, The University of Sydney, Camden, NSW, Australia.
Tariq HalasaSection of Animal Welfare and Disease Control, Department of Veterinary and Animal Sciences, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark.
Kathrin SchemannSydney Informatics Hub, The University of Sydney, Camperdown, NSW, Australia.
Syseng KhounsyDepartment of Livestock and Fisheries, Ministry of Agriculture and Forestry, National Animal Health Laboratory, Vientiane, Lao People's Democratic Republic.
Bounlom DouangngeunDepartment of Livestock and Fisheries, Ministry of Agriculture and Forestry, National Animal Health Laboratory, Vientiane, Lao People's Democratic Republic.
Watthana ThepagnaDepartment of Livestock and Fisheries, Ministry of Agriculture and Forestry, National Animal Health Laboratory, Vientiane, Lao People's Democratic Republic.
Phouvong PhommachanhDepartment of Livestock and Fisheries, Ministry of Agriculture and Forestry, National Animal Health Laboratory, Vientiane, Lao People's Democratic Republic.
Jarunee Siengsanan-LamontFaculty of Tropical Medicine, Mahidol-Oxford Tropical Medicine Research Unit, Mahidol University, Bangkok, Thailand.
James YoungSydney School of Veterinary Science, The University of Sydney, Camden, NSW, Australia.ORCID http://orcid.org/0000-0001-5398-5219
Jenny-Ann ToribioSydney School of Veterinary Science, The University of Sydney, Camden, NSW, Australia.
Russell BushSydney School of Veterinary Science, The University of Sydney, Camden, NSW, Australia.
Stuart D BlacksellFaculty of Tropical Medicine, Mahidol-Oxford Tropical Medicine Research Unit, Mahidol University, Bangkok, Thailand. stuart.blacksell@ndm.ox.ac.uk.
Michael P WardSydney School of Veterinary Science, The University of Sydney, Camden, NSW, Australia.

Funding

Defense Threat Reduction Agency HDTRA1-08-D-0007Wellcome TrustWellcome Trust 220211
6 · The paper itself

Abstract

Understanding the spread of African Swine Fever (ASF) between villages in the southeast-Asian, low - middle income country context is critical if this high impact disease is to be controlled by good policy and effective field activities in these resource-poor settings. Using governmental reporting data from the 2019 outbreak of ASF in Lao People's Democratic Republic, spatial clustering techniques were used to identify clusters of outbreak villages. Then Approximate Bayesian Computation with Sequential Monte Carlo was used to estimate the transmission parameters of ASF virus between the villages within these clusters. We used a simple disease spread model to understand the impact of parameter estimation on predicted disease spread and thus decision-making. Six clusters of radius 16 to 153km were identified over the 7 month outbreak period. Within these clusters, the basic reproduction number (R

Indexed as

African Swine FeverDecision MakingDisease OutbreaksEpidemicsAnimalsBayes TheoremLaosSwineAfrican Swine FeverInfectious disease modellingLaos

Identifiers

PMID40346370
PMCPMC12064582

What OpenQuestion holds

Textmetadata
LicenceCC BY
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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.