Table_1_Disentangling transport movement patterns of trucks either transporting pigs or while empty within a swine production system before and during the COVID-19 epidemic.docx

Transport of pigs between sites occurs frequently as part of genetic improvement and age segregation. However, a lack of transport biosecurity could have catastrophic implications if not managed properly as disease spread would be imminent. However, there is a lack of a comprehensive study of vehicle movement trends within swine systems in the Midwest. In this study, we aimed to describe and characterize vehicle movement patterns within one large Midwest swine system representative of modern pig production to understand movement trends and proxies for biosecurity compliance and identify potential risky behaviors that may result in a higher risk for infectious disease spread. Geolocation tracking devices recorded vehicle movements of a subset of trucks and trailers from a production system every 5 min and every time tracks entered a landmark between January 2019 and December 2020, before and during the COVID-19 pandemic. We described 6,213 transport records from 12 vehicles controlled by the company. In total, 114 predefined landmarks were included during the study period, representing 5 categories of farms and truck wash facilities. The results showed that trucks completed the majority (76.4%, 2,111/2,762) of the recorded movements. The seasonal distribution of incoming movements was similar across years (P > 0.05), while the 2019 winter and summer seasons showed higher incoming movements to sow farms than any other season, year, or production type (P < 0.05). More than half of the in-movements recorded occurred within the triad of sow farms, wean-to-market stage, and truck wash facilities. Overall, time spent at each landmark was 9.08% higher in 2020 than in 2019, without seasonal highlights, but with a notably higher time spent at truck wash facilities than any other type of landmark. Network analyses showed high connectivity among farms with identifiable clusters in the network. Furthermore, we observed a decrease in connectivity in 2020 compared with 2019, as indicated by the majority of network parameter values. Further network analysis will be needed to understand its impact on disease spread and control. However, the description and quantification of movement trends reported in this study provide findings that might be the basis for targeting infectious disease surveillance and control.

不同场点间的生猪转运是遗传改良与年龄分群管理的常规环节。但若运输生物安全管理不到位，则可能引发灾难性后果，因为疫病传播将迫在眉睫。然而，目前针对美国中西部生猪养殖系统内运输车辆流动趋势的全面研究仍较为匮乏。本研究以代表现代生猪生产模式的美国中西部某大型生猪养殖系统为研究对象，旨在刻画其运输车辆的流动模式，解析流动趋势与生物安全合规性的替代指标，并识别可能提升传染病传播风险的潜在风险行为。2019年1月至2020年12月（新冠疫情暴发前后）期间，该养殖系统的部分货运卡车及半挂车搭载了定位追踪设备，每5分钟记录一次车辆位置，且每当车辆驶入地标场点时同步更新轨迹。本研究共整理得到该公司12台车辆的6213条运输记录。研究期间共纳入114个预定义地标场点，涵盖5类猪场及车辆洗消设施。结果显示，卡车完成了记录在册的流动任务中的绝大多数（76.4%，2111/2762）。不同年度的进场流动季节分布相似（P>0.05）；但2019年冬季与夏季的母猪场进场流动量显著高于其他季节、年度或生产类型场点（P<0.05）。超半数记录在册的进场流动均发生在母猪场、断奶到出栏阶段场点及车辆洗消中心这三类场点之间。整体而言，2020年车辆在各场点的停留时长较2019年提升9.08%，且无显著季节差异，但车辆在洗消中心的停留时长显著高于其他类型场点。网络分析结果显示，各场点间连通性较高，且网络中存在可识别的集群结构。此外，多数网络参数值均显示，2020年场点间连通性较2019年有所下降。后续需开展进一步的网络分析，以明确其对疫病传播与防控的影响。但本研究对流动趋势的描述与量化分析结果，可为传染病监测与防控工作提供针对性的参考依据。