Evidence map›Paper›PMID 38758410›Full record

ArticleTropical animal health and production2024

Novel estimation of African swine fever transmission parameters within smallholder villages in Lao P.D.R.

Nina Matsumoto, Michael P Ward, Tariq Halasa, Kathrin Schemann, Syseng Khounsy, Bounlom Douangngeun, Watthana Thepagna, Phouvong Phommachanh, Jarunee Siengsanan-Lamont, James R Young and 3 more

Abstract read
In one paragraph

Article in Tropical animal health and production, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Review
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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.

Nina MatsumotoSydney School of Veterinary Science, Faculty of Science, The University of Sydney, Camden, NSW, 2570, Australia.
Michael P WardSydney School of Veterinary Science, Faculty of Science, The University of Sydney, Camden, NSW, 2570, Australia.ORCID http://orcid.org/0000-0002-9921-4986
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 KhounsyNational Animal Health Laboratory, Department of Livestock and Fisheries, Ministry of Agriculture and Forestry, Vientiane, Lao People's Democratic Republic.
Bounlom DouangngeunNational Animal Health Laboratory, Department of Livestock and Fisheries, Ministry of Agriculture and Forestry, Vientiane, Lao People's Democratic Republic.
Watthana ThepagnaNational Animal Health Laboratory, Department of Livestock and Fisheries, Ministry of Agriculture and Forestry, Vientiane, Lao People's Democratic Republic.
Phouvong PhommachanhNational Animal Health Laboratory, Department of Livestock and Fisheries, Ministry of Agriculture and Forestry, Vientiane, Lao People's Democratic Republic.
Jarunee Siengsanan-LamontMahidol-Oxford Tropical Medicine Research Unit, Faculty of Tropical Medicine, Mahidol University, Bangkok, Thailand.
James R YoungSydney School of Veterinary Science, Faculty of Science, The University of Sydney, Camden, NSW, 2570, Australia.ORCID http://orcid.org/0000-0001-5398-5219
Jenny-Ann L M L ToribioSydney School of Veterinary Science, Faculty of Science, The University of Sydney, Camden, NSW, 2570, Australia.
Russell D BushSydney School of Veterinary Science, Faculty of Science, The University of Sydney, Camden, NSW, 2570, Australia.
Stuart D BlacksellSydney School of Veterinary Science, Faculty of Science, The University of Sydney, Camden, NSW, 2570, Australia. stuart.blacksell@ndm.ox.ac.uk.

Funding

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

Abstract

African Swine Fever (ASF) disease transmission parameters are crucial for making response and control decisions when faced with an outbreak, yet they are poorly quantified for smallholder and village contexts within Southeast Asia. Whilst disease-specific factors - such as latent and infectious periods - should remain reasonably consistent, host, environmental and management factors are likely to affect the rate of disease spread. These differences are investigated using Approximate Bayesian Computation with Sequential Monte-Carlo methods to provide disease parameter estimates in four naïve pig populations in villages of Lao People's Democratic Republic. The villages represent smallholder pig farmers of the Northern province of Oudomxay and the Southern province of Savannakhet, and the model utilised field mortality data to validate the transmission parameter estimates over the course of multiple model generations. The basic reproductive number between-pigs was estimated to range from 3.08 to 7.80, whilst the latent and infectious periods were consistent with those published in the literature for similar genotypes in the region (4.72 to 6.19 days and 2.63 to 5.50 days, respectively). These findings demonstrate that smallholder village pigs interact similarly to commercial pigs, however the spread of disease may occur slightly slower than in commercial study groups. Furthermore, the findings demonstrated that despite diversity across the study groups, the disease behaved in a consistent manner. This data can be used in disease control programs or for future modelling of ASF in smallholder contexts.

Indexed as

African Swine FeverBayes TheoremAfrican Swine Fever VirusAnimal HusbandryAnimalsBasic Reproduction NumberDisease OutbreaksLaosMonte Carlo MethodSus scrofaSwineAfrican swine feverApproximate Bayesian computationDisease modellingLaoPigSmallholder villageTransmission parameters

Identifiers

PMID38758410
PMCPMC11101325

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LicenceCC BY
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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.