Evidence map›Paper›PMID 29120101›Full record

ArticleTransboundary and emerging diseases2018

Inferring within-herd transmission parameters for African swine fever virus using mortality data from outbreaks in the Russian Federation.

C Guinat, T Porphyre, A Gogin, L Dixon, D U Pfeiffer, S Gubbins

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Article in Transboundary and emerging diseases, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 41 papers.

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0cells of the map it votes in
41citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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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

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3 · Its place in the literature

Who cites it

41 citing papers in PubMed.

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  7. Optimizing contact tracing for avian influenza in poultry flocks.Journal of the Royal Society, Interface · 2025
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4 · The record

Corrections and comments

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5 · Who and what money

Authors and funding

6 authors.

C GuinatVeterinary Epidemiology, Economics and Public Health Group, Royal Veterinary College, Hatfield, Hertfordshire, UK.
T PorphyreThe Roslin Institute, University of Edinburgh, Roslin, Midlothian, UK.
A GoginEuropean Food Safety Authority, Parma, Italy.
L DixonThe Pirbright Institute, Pirbright, Surrey, UK.
D U PfeifferVeterinary Epidemiology, Economics and Public Health Group, Royal Veterinary College, Hatfield, Hertfordshire, UK.
S GubbinsThe Pirbright Institute, Pirbright, Surrey, UK.ORCID http://orcid.org/0000-0003-0538-4173

Funding

Biotechnology and Biological Sciences Research Council BBS/E/I/00007036Biotechnology and Biological Sciences Research Council BBS/E/I/00007037
6 · The paper itself

Abstract

Mortality data are routinely collected for many livestock and poultry species, and they are often used for epidemiological purposes, including estimating transmission parameters. In this study, we infer transmission rates for African swine fever virus (ASFV), an important transboundary disease of swine, using mortality data collected from nine pig herds in the Russian Federation with confirmed outbreaks of ASFV. Parameters in a stochastic model for the transmission of ASFV within a herd were estimated using approximate Bayesian computation. Estimates for the basic reproduction number varied amongst herds, ranging from 4.4 to 17.3. This was primarily a consequence of differences in transmission rate (range: 0.7-2.2), but also differences in the mean infectious period (range: 4.5-8.3 days). We also found differences amongst herds in the mean latent period (range: 5.8-9.7 days). Furthermore, our results suggest that ASFV could be circulating in a herd for several weeks before a substantial increase in mortality is observed in a herd, limiting the usefulness of mortality data as a means of early detection of an outbreak. However, our results also show that mortality data are a potential source of data from which to infer transmission parameters, at least for diseases which cause high mortality.

Indexed as

African Swine FeverAfrican Swine Fever VirusAnimalsBasic Reproduction NumberBayes TheoremDisease OutbreaksRussiaSwineapproximate Bayesian computationdisease controlepidemiologymodellingmortality datapigs

Identifiers

PMID29120101
PMCPMC5887875

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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.