ArticleBMC veterinary research2020
A 'what-if' scenario: Nipah virus attacks pig trade chains in Thailand.
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.
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Who cites it
7 citing papers in PubMed, 12 citations in OpenAlex.
- From antibiotic to antiviral: computational screening reveals a multi-targeting antibiotic from Streptomyces spp. against Nipah virus fusion proteins.Molecular diversity · 2025Article
- A Stable and Dependable Visual Technique for On-Site Nipah Virus Nucleic Acids Detection.Scientific reports · 2025Article
- Pandemic-Proofing: Intercepting Zoonotic Spillover Events.Pathogens (Basel, Switzerland) · 2024Review
- An emerging zoonotic disease to be concerned about - a review of the nipah virus.Journal of health, population, and nutrition · 2024Review
- Approaches for disease prioritization and decision-making in animal health, 2000-2021: a structured scoping review.Frontiers in veterinary science · 2023Article
- Henipaviruses-A constant threat to livestock and humans.PLoS neglected tropical diseases · 2022Review
- Two decades of one health surveillance of Nipah virus in Thailand.One health outlook · 2021Article
Corrections and comments
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Authors and funding
8 authors at 5 institutions in 3 countries.
Funding
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.
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