ArticlePloS one2017
Modeling the live-pig trade network in Georgia: Implications for disease prevention and control.
Article in PloS one, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers, 1 of them a synthesis that pooled it.
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Who cites it
17 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Simulating contact networks for livestock disease epidemiology: a systematic review.Journal of the Royal Society, Interface · 2023Pooled it
- Understanding Smallholder Pigkeepers' Awareness and Perceptions of African Swine Fever and Its Control Measures in Ukraine.Pathogens (Basel, Switzerland) · 2024Article
- Network analysis of pig movement data as an epidemiological tool: an Austrian case study.Scientific reports · 2023Article
- Innovative Research Offers New Hope for Managing African Swine Fever Better in Resource-Limited Smallholder Farming Settings: A Timely Update.Pathogens (Basel, Switzerland) · 2023Review
- Complex network analysis to understand trading partnership in French swine production.PloS one · 2022Article
- Network analysis of live pig movements in North Macedonia: Pathways for disease spread.Frontiers in veterinary science · 2022Article
- A Review of Risk Factors of African Swine Fever Incursion in Pig Farming within the European Union Scenario.Pathogens (Basel, Switzerland) · 2021Review
- Descriptive and Multivariate Analysis of the Pig Sector in North Macedonia and Its Implications for African Swine Fever Transmission.Frontiers in veterinary science · 2021Article
- Article
- Modelling infectious viral diseases in swine populations: a state of the art.Porcine health management · 2020Review
- Application of network analysis and cluster analysis for better prevention and control of swine diseases in Argentina.PloS one · 2020Article
- Simulation modeling of influenza transmission through backyard pig trade networks in a wildlife/livestock interface area.Tropical animal health and production · 2019Article
- Identifying outbreaks of Porcine Epidemic Diarrhea virus through animal movements and spatial neighborhoods.Scientific reports · 2019Article
- Epidemiological considerations on African swine fever in Europe 2014-2018.Porcine health management · 2019Review
- Relevant Measures to Prevent the Spread of African Swine Fever in the European Union Domestic Pig Sector.Frontiers in veterinary science · 2018Review
- Descriptive and multivariate analysis of the pig sector in Georgia and its implications for disease transmission.PloS one · 2018Article
- Third wave of African swine fever infection in Armenia: Virus demonstrates the reduction of pathogenicity.Veterinary world · 2018Article
Corrections and comments
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Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Live pig trade patterns, drivers and characteristics, particularly in backyard predominant systems, remain largely unexplored despite their important contribution to the spread of infectious diseases in the swine industry. A better understanding of the pig trade dynamics can inform the implementation of risk-based and more cost-effective prevention and control programs for swine diseases. In this study, a semi-structured questionnaire elaborated by FAO and implemented to 487 farmers was used to collect data regarding basic characteristics about pig demographics and live-pig trade among villages in the country of Georgia, where very scarce information is available. Social network analysis and exponential random graph models were used to better understand the structure, contact patterns and main drivers for pig trade in the country. Results indicate relatively infrequent (a total of 599 shipments in one year) and geographically localized (median Euclidean distance between shipments = 6.08 km; IQR = 0-13.88 km) pig movements in the studied regions. The main factors contributing to live-pig trade movements among villages were being from the same region (i.e., local trade), usage of a middleman or a live animal market to trade live pigs by at least one farmer in the village, and having a large number of pig farmers in the village. The identified villages' characteristics and structural network properties could be used to inform the design of more cost-effective surveillance systems in a country which pig industry was recently devastated by African swine fever epidemics and where backyard production systems are predominant.
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