Simulation modeling of influenza transmission through backyard pig trade networks in a wildlife/livestock interface area

Mateus-Anzola, Jessica; Wiratsudakul, Anuwat; Rico-Chávez, Óscar; Ojeda-Flores, Rafael

doi:10.1007/s11250-019-01892-4

Cited by 4 publications

(4 citation statements)

References 18 publications

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“…The credible parameters for direct and indirect contact rates were utilized from previous data based on the farm survey, which made our network model more realistic. Our results showed that the level of connectivity amongst farms plays a vital role in the spread of disease, which is consistent with previous studies that used network-based models for disease spread [ 27 , 28 ]. Importantly, Lebl et al (2016) suggested that trade activities were the most important risk factor for disease transmission.…”

Section: Discussionsupporting

confidence: 92%

“…It has been a challenge to understand the epidemic dynamics of infectious diseases as various/complex factors are associated with each other. Network analysis proved useful in understanding disease transmission among farms by estimating potential pathways [ 27 , 40 ]. It opened up opportunities to address the importance of animal movement when developing risk-based surveillance and cost-effective control measures, especially given that systemic records are limited in Vietnam.…”

Section: Discussionmentioning

confidence: 99%

“…Importantly, Lebl et al (2016) suggested that trade activities were the most important risk factor for disease transmission. In addition, one study was conducted using the EpiModel package used in the current study to evaluate the consequence of connectivity in the spread of influenza in pigs [27]. Findings showed that high animal movement significantly raised the risk of disease transmission.…”

Section: Discussionmentioning

confidence: 99%

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A stochastic network-based model to simulate farm-level transmission of African swine fever virus in Vietnam

et al. 2021

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African swine fever virus is highly contagious, and mortality rates reach up to 100% depending on the host, virus dose, and the transmission routes. The main objective of this study was to develop a network-based simulation model for the farm-level transmission of ASF virus to evaluate the impact of changes in farm connectivity on ASF spread in Vietnam. A hypothetical population of 1,000 pig farms was created and used for the network-based simulation, where each farm represented a node, and the connection between farms represented an edge. The three scenarios modelled in this way (baseline, low, and high) evaluated the impact of connectivity on disease transmission. The median number of infected farms was higher as the connectivity increased (low: 659, baseline: 968 and high: 993). In addition, we evaluated the impact of the culling strategy on the number of infected farms. A total of four scenarios were simulated depending on the timing of culling after a farm was infected. We found that the timing of culling at 16, 12, 8, and 6 weeks had resulted in a reduction of the number of median infected farms by 81.92%, 91.63%, 100%, and 100%, respectively. Finally, our evaluation of the implication of stability of ties between farms indicated that if the farms were to have the same trading partners for at least six months could significantly reduce the median number of infected farms to two (95th percentile: 413) than in the basic model. Our study showed that pig movements among farms had a significant influence on the transmission dynamics of ASF virus. In addition, we found that the either timing of culling, reduction in the number of trading partners each farm had, or decreased mean contact rate during the outbreaks were essential to prevent or stop further outbreaks.

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Section: Discussionsupporting

confidence: 92%

Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

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A stochastic network-based model to simulate farm-level transmission of African swine fever virus in Vietnam

et al. 2021

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“…Most of the backyard productive systems surrounding the marshes have low schemes of biosecurity and lack of vaccination against IAV. Likewise, an informal and unregulated animal trade prevails in the region (Mateus-Anzola et al, 2019). Some molecular studies in wild ducks and their environment have been conducted in this Natural Protected Area (Cuevas-Domínguez et al, 2009;Ornelas-Eusebio et al, 2015;Ramírez-Martínez et al, 2018).…”

Section: Introductionmentioning

confidence: 99%

Molecular identification and phylogenetic characterization of influenza A virus at a wildlife–livestock interface in Mexico

Mateus-Anzola¹,

Gaytan-Cruz²,

Montoya-Carrillo³

et al. 2020

Transbound Emerg Dis

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Influenza A virus (IAV) outbreaks constitute a constant threat to public health and pose a remarkable impact on socio-economic systems worldwide. Interactions between wild and domestic birds, humans and swine can lead to spillover events. Backyard livestock systems in proximity to wetlands represent high-risk areas for viral spread. However, some gaps remain in our knowledge of IAV transmission at the wildlife-livestock interface in Mexico. Hence, the study aimed at molecular identification and phylogenetic characterization of IAV in the wild duck-backyard livestock interface at a wetland of Mexico. A total of 875 animals were tested by real-time RT-PCR (qRT-PCR). We detected IAV in 3.68% of the wild ducks sampled during the winter season 2016-2017. Nonetheless, the samples obtained from backyard poultry and swine tested negative. The highest IAV frequency (11.10%) was found in the Mexican duck (Anas diazi). Subtypes H1N1, H3N2 and H5N2 were detected.Phylogenetic analyses revealed that IAV detected in wild birds from the Lerma wetlands was mostly related to swine and poultry IAV strains previously isolated in the United States and Mexico. Except, the UIFMVZ377/H5N2 related to North American waterbirds. In conclusion, the co-circulation of three IAV subtypes in wild ducks close to backyard farms in Mexico, as well as the local identification of influenza viruses genetically related to Mexican and North American IAV strains, highlights the importance of the Lerma marshes for influenza surveillance given the close interaction among wild birds, poultry, pigs and humans.

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A Cloud-based Multi-agent Simulation of African Swine Fever in Hanoi Region

Pham,

Nguyen

2023

2023 IEEE/ACIS 8th International Conference on Big Data, Cloud Computing, and Data Science (BCD)

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Simulation modeling of influenza transmission through backyard pig trade networks in a wildlife/livestock interface area

Cited by 4 publications

References 18 publications

A stochastic network-based model to simulate farm-level transmission of African swine fever virus in Vietnam

A stochastic network-based model to simulate farm-level transmission of African swine fever virus in Vietnam

Molecular identification and phylogenetic characterization of influenza A virus at a wildlife–livestock interface in Mexico

A Cloud-based Multi-agent Simulation of African Swine Fever in Hanoi Region

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