Veterinary Public Health, Kasetsart University, Kamphaeng Saen, Nakhon Pathom, Thailand.
Department of Livestock Development, Ministry of Agriculture and Cooperatives, Bangkok, Thailand.
PeerJ. 2023 May 9;11:e15359. doi: 10.7717/peerj.15359. eCollection 2023.
African swine fever (ASF) is a serious contagious viral disease of pigs that affects the pig industry. This study aimed to evaluate the possible African swine fever (ASF) distribution using network analysis and a diffusion model through live pig, carcass, and pig product movement data.
Empirical movement data from Thailand for the year 2019 were used, and expert opinions were sought to evaluate network properties and the diffusion model. The networks were presented as live pig movement and carcass movement data at the provincial and district levels. For network analysis, a descriptive network analysis was performed using outdegree, indegree, betweenness, fragmentation, and power law distribution, and cutpoints were used to describe movement patterns. For the diffusion model, we simulated each network using spatially different infected locations, patterns, and initial infection sites. Based on expert opinions, the initial infection site, the probability of ASF occurrence, and the probability of the initial infected adopter were selected for the appropriated network. In this study, we also simulated networks under varying network parameters to predict the infection speed.
The total number of movements recorded was 2,594,364. These were divided into 403,408 (403,408/2,594,364; 15.55%) for live pigs and 2,190,956 (2,190,956/2,594,364; 84.45%) for carcasses. We found that carcass movement at the provincial level showed the highest outdegree (mean = 342.554, standard deviation (SD) = 900.528) and indegree values (mean = 342.554, SD = 665.509). In addition, the outdegree and indegree presented similar mean values and the degree distributions of both district networks followed a power-law function. The network of live pigs at provincial level showed the highest value for betweenness (mean = 0.011, SD = 0.017), and the network of live pigs at provincial level showed the highest value for fragmentation (mean = 0.027, SD = 0.005). Our simulation data indicated that the disease occurred randomly due to live pig and carcass movements along the central and western regions of Thailand, causing the rapid spread of ASF. Without control measures, it could spread to all provinces within 5- and 3-time units and in all districts within 21- and 30-time units for the network of live pigs and carcasses, respectively. This study assists the authorities to plan control and preventive measures and limit economic losses caused by ASF.
非洲猪瘟（ASF）是一种严重的传染性猪病，对养猪业有影响。本研究旨在通过生猪、胴体和猪肉产品的流动数据，利用网络分析和扩散模型评估可能的非洲猪瘟分布情况。
使用了泰国 2019 年的实际流动数据，并征求了专家意见，以评估网络属性和扩散模型。网络呈现为省级和区级的生猪流动和胴体流动数据。对于网络分析，采用了描述性网络分析，包括出度、入度、中间度、碎片化和幂律分布，并使用切点来描述流动模式。对于扩散模型，我们使用空间上不同的感染位置、模式和初始感染点来模拟每个网络。根据专家意见，为适当的网络选择了初始感染点、ASF 发生概率和初始感染采用者的概率。在本研究中，我们还模拟了不同网络参数下的网络，以预测感染速度。
记录的总移动次数为 2,594,364 次。这些移动次数分为 403,408 次（403,408/2,594,364；15.55%）用于生猪，2,190,956 次（2,190,956/2,594,364；84.45%）用于胴体。我们发现，省级的胴体流动表现出最高的出度（平均值=342.554，标准差（SD）=900.528）和入度值（平均值=342.554，SD=665.509）。此外，出度和入度呈现相似的平均值，两个地区网络的度分布都遵循幂律函数。省级生猪网络的中间度最高（平均值=0.011，SD=0.017），省级生猪网络的碎片化程度最高（平均值=0.027，SD=0.005）。我们的模拟数据表明，由于泰国中、西部地区的生猪和胴体流动，疾病随机发生，导致非洲猪瘟迅速传播。如果没有控制措施，在网络的生猪和胴体中，疾病可能在 5-3 个时间单位内传播到所有省份，在 21-30 个时间单位内传播到所有地区。本研究有助于当局规划控制和预防措施，限制 ASF 造成的经济损失。
