Evidence map›Paper›PMID 32838786›Full record

ArticleBMC veterinary research2020

A 'what-if' scenario: Nipah virus attacks pig trade chains in Thailand.

Phrutsamon Wongnak, Weerapong Thanapongtharm, Worapan Kusakunniran, Sarattha Karnjanapreechakorn, Krittanat Sutassananon, Wantanee Kalpravidh, Kachen Wongsathapornchai, Anuwat Wiratsudakul

Open access · goldAbstract read
In one paragraph

Article in BMC veterinary research, 2020. 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
1.0field-weighted citation impact, top 22% 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, 12 citations in OpenAlex.

  1. Article
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  6. Henipaviruses-A constant threat to livestock and humans.PLoS neglected tropical diseases · 2022
    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

8 authors at 5 institutions in 3 countries.

Phrutsamon WongnakUniversité Clermont Auvergne, INRAE, VetAgro Sup, UMR EPIA, 63122, Saint-Genès-Champanelle, France.
Weerapong ThanapongtharmDepartment of Livestock Development (DLD), Bangkok, Thailand.
Worapan KusakunniranFaculty of Information and Communication Technology, Mahidol University, Nakhon Pathom, Thailand.
Sarattha KarnjanapreechakornFaculty of Information and Communication Technology, Mahidol University, Nakhon Pathom, Thailand.
Krittanat SutassananonFaculty of Information and Communication Technology, Mahidol University, Nakhon Pathom, Thailand.
Wantanee KalpravidhFood and Agriculture Organization of the United Nations, Global Emergency Centre for Transboundary Animal Diseases (ECTAD), Rome, Italy.
Kachen WongsathapornchaiFood and Agriculture Organization of the United Nations, Regional Office for Asia and the Pacific, Bangkok, Thailand.
Anuwat WiratsudakulDepartment of Clinical Sciences and Public Health, and the Monitoring and Surveillance Center for Zoonotic Diseases in Wildlife and Exotic Animals, Faculty of Veterinary Science, Mahidol University, Nakhon Pathom, Thailand. anuwat.wir@mahidol.edu.ORCID http://orcid.org/0000-0002-1112-3220
Mahidol University · THDepartment of Livestock Development · THFood and Agriculture Organization of the United Nations · ITUNICEF East Asia and Pacific Regional Office · THUniversité Claude Bernard Lyon 1 · FR

Funding

USAID/FAO LOA/RAP/2016/32
6 · The paper itself

Abstract

backgroundNipah virus (NiV) is a fatal zoonotic agent that was first identified amongst pig farmers in Malaysia in 1998, in an outbreak that resulted in 105 fatal human cases. That epidemic arose from a chain of infection, initiating from bats to pigs, and which then spilled over from pigs to humans. In Thailand, bat-pig-human communities can be observed across the country, particularly in the central plain. The present study therefore aimed to identify high-risk areas for potential NiV outbreaks and to model how the virus is likely to spread. Multi-criteria decision analysis (MCDA) and weighted linear combination (WLC) were employed to produce the NiV risk map. The map was then overlaid with the nationwide pig movement network to identify the index subdistricts in which NiV may emerge. Subsequently, susceptible-exposed-infectious-removed (SEIR) modeling was used to simulate NiV spread within each subdistrict, and network modeling was used to illustrate how the virus disperses across subdistricts.

resultsBased on the MCDA and pig movement data, 14 index subdistricts with a high-risk of NiV emergence were identified. We found in our infectious network modeling that the infected subdistricts clustered in, or close to the central plain, within a range of 171 km from the source subdistricts. However, the virus may travel as far as 528.5 km (R

conclusionsIn conclusion, the risk of NiV dissemination through pig movement networks in Thailand is low but not negligible. The risk areas identified in our study can help the veterinary authority to allocate financial and human resources to where preventive strategies, such as pig farm regionalization, are required and to contain outbreaks in a timely fashion once they occur.

Indexed as

Nipah VirusAnimalsChiropteraDecision Support TechniquesDisease OutbreaksHenipavirus InfectionsHumansSwineSwine DiseasesThailandTransportationAnimal movementNetwork modelingNipah virusSpatial risk

Identifiers

PMID32838786
PMCPMC7446211
OpenAlexW3081197235

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.