Modeling the live-pig trade network in Georgia: Implications for disease prevention and control

Kukielka, Esther A.; Martínez‐López, Beatriz; Beltrán‐Alcrudo, Daniel

doi:10.1371/journal.pone.0178904

Cited by 32 publications

(35 citation statements)

References 31 publications

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“…A number of studies have examined swine movement networks as a main transmission route for disease spread 16,[35][36][37][38][39] , network analysis and epidemiological data have recently been used to assess risk of local areas being exposed to pathogens as a consequence of animal introduction 40 . The approach presented here provides a realistic understanding of PEDV dynamics by capturing long distance spread via animal movements and linking it with epidemiological factors related to local area spread between neighboring farms.…”

Section: Discussionmentioning

confidence: 99%

Identifying outbreaks of Porcine Epidemic Diarrhea virus through animal movements and spatial neighborhoods

Machado

Vilalta

Recamonde‐Mendoza

et al. 2019

Sci Rep

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The spread of pathogens in swine populations is in part determined by movements of animals between farms. However, understanding additional characteristics that predict disease outbreaks and uncovering landscape factors related to between-farm spread are crucial steps toward risk mitigation. This study integrates animal movements with environmental risk factors to identify the occurrence of porcine epidemic diarrhea virus (PEDV) outbreaks. Using weekly farm-level incidence data from 332 sow farms, we applied machine-learning algorithms to quantify associations between risk factors and PEDV outbreaks with the ultimate goal of training predictive models and to identify the most important factors associated with PEDV occurrence. Our best algorithm was able to correctly predict whether an outbreak occurred during one-week periods with >80% accuracy. The most important predictors included pig movements into neighboring farms. Other important neighborhood attributes included hog density, environmental and weather factors such as vegetation, wind speed, temperature, and precipitation, and topographical features such as slope. Our neighborhood-based approach allowed us to simultaneously capture disease risks associated with long-distance animal movement as well as local spatial dynamics. The model presented here forms the foundation for near real-time disease mapping and will advance disease surveillance and control for endemic swine pathogens in the United States.

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Section: Discussionmentioning

confidence: 99%

Identifying outbreaks of Porcine Epidemic Diarrhea virus through animal movements and spatial neighborhoods

Machado

Vilalta

Recamonde‐Mendoza

et al. 2019

Sci Rep

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“…This may be explained because the feasibility of quarantine periods and establishment of quarantine rooms and procedure could be challenging on non-commercial farms where investment and facilities are minimum. This measure becomes particularly relevant when tackling the phenomenon of “emergency sale,” in which farmers from non-commercial holdings attempt to sell infected pigs to minimize their economic losses (87, 94–96). The latest working document elaborated by the Directorate General for Health and Food Safety (15), which contains the majority of measures reviewed in the systematic literature review, aim at the improvement of biosecurity measures dealing with the replacement of animals, facilities design, and management practices, in particular in relation with cleaning and disinfection facilities, in such holdings.…”

Section: Discussionmentioning

confidence: 99%

Relevant Measures to Prevent the Spread of African Swine Fever in the European Union Domestic Pig Sector

et al. 2018

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During the past decade, African swine fever (ASF) has spread from the Caucasus region to eastern European Union countries affecting domestic pig and wild boar populations. In order to avert ASF spread, mitigation measures targeting both populations have been established. However, despite these efforts, ASF has been reported in thirteen different countries (Georgia, Azerbaijan, Armenia, the Russian Federation, Ukraine, Belarus, Estonia, Latvia, Lithuania, Poland, Moldova, Czech Republic, and Romania). In the absence of an effective vaccine or treatment to ASF, introduction and spread of ASF onto domestic pig farms can only be prevented by strict compliance to control measures. This study systematically reviewed available measures to prevent the spread of ASF in the EU domestic pig sector distinguishing between commercial, non-commercial, and outdoor farms. The search was performed in PubMed and using a common browser. A total of 52 documents were selected for the final review process, which included scientific articles, reports, EU documents and official recommendations, among others. From this literature review, 37 measures were identified as preventive measures for the introduction and spread of ASF. Subsequently, these measures were assessed by ASF experts for their relevance in the mitigation of ASF spread on the three mentioned types of farms. All experts agreed that some of the important preventive measures for all three types of farms were: the identification of animals and farm records; strict enforcement of the ban on swill feeding; and containment of pigs, so as to not allow direct or indirect pig–pig and/or pig–wild boar contacts. Other important preventive measures for all farms were education of farmers, workers, and operators; no contact between farmers and farm staff and external pigs; appropriate removal of carcasses, slaughter residues, and food waste; proper disposal of manure and dead animals, and abstaining from hunting activities during the previous 48 h (allowing a 48 h interval between hunting and being in contact with domestic pigs). Finally, all experts identified that the important preventive measures for non-commercial and outdoor farms is to improve access of those farms to veterinarians and health services.

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“…Still, most farmers only bring few new animals (3.2 on average) once a year. The profile of the pig trade dynamics resulting from the questionnaires have been analysed and discussed in detail by Kukielka et al [ 40 ].…”

Section: Discussionmentioning

confidence: 99%

Descriptive and multivariate analysis of the pig sector in Georgia and its implications for disease transmission

et al. 2018

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BackgroundGeorgia is a country in the Caucasus region with a traditional backyard and highly variable pig farming system. The practices of such sectors have seldom been described and analyzed to better understand their implication in the introduction and spread of infectious pig diseases. Moreover, the Georgian pig sector was badly hit by an epidemic of African swine fever in 2007 that quickly spread throughout the region.Materials and methodsWe interviewed 487 pig farmers and 116 butchers using closed questionnaires on socioeconomic issues related to pig production, husbandry practices, biosecurity, marketing and movements, and disease awareness. Surveys were conducted in four regions of Georgia and descriptive statistics were computed. Factorial analyses of mixed data and hierarchical clustering on principal components were applied to study the relationship among collected variables for both farmers and butchers.ResultsResults show that pig farming in Georgia is a non-professional sector, highly heterogeneous by region, characterized by smallholdings of few animals, with low inputs, outdated technologies, and poor biosecurity, which all translates into low outputs and productivity. The hierarchical clustering on principal components confirmed that there are five major production and husbandry strategies, which match the four regions where the study was conducted.ConclusionsOur results are the first step to quantify biosecurity gaps and risky behaviours, develop risk profiles, and identify critical control points across the market chain where to implement mitigation measures. This study provides the baseline information needed to design realistic and sustainable prevention, surveillance and control strategies.

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Modeling the live-pig trade network in Georgia: Implications for disease prevention and control

Cited by 32 publications

References 31 publications

Identifying outbreaks of Porcine Epidemic Diarrhea virus through animal movements and spatial neighborhoods

Identifying outbreaks of Porcine Epidemic Diarrhea virus through animal movements and spatial neighborhoods

Relevant Measures to Prevent the Spread of African Swine Fever in the European Union Domestic Pig Sector

Descriptive and multivariate analysis of the pig sector in Georgia and its implications for disease transmission

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