Escuela de Ingenierias, Universidad Pontificia Bolivariana, Medellin, Colombia.
Escuela de Matemáticas, Universidad Nacional de Colombia, Medellin, Colombia.
J Travel Med. 2022 Dec 27;29(8). doi: 10.1093/jtm/taac100.
The COVID-19 pandemic has challenged health services and governments in Canada and around the world. Our research aims to evaluate the effect of domestic and international air travel patterns on the COVID-19 pandemic in Canadian provinces and territories.
Air travel data were obtained through licensed access to the 'BlueDot Intelligence Platform', BlueDot Inc. Daily provincial and territorial COVID-19 cases for Canada and global figures, including mortality, cases recovered and population data were downloaded from public datasets. The effects of domestic and international air travel and passenger volume on the number of local and non-local infected people in each Canadian province and territory were evaluated with a semi-Markov model. Provinces and territories are grouped into large (>100 000 confirmed COVID-19 cases and >1 000 000 inhabitants) and small jurisdictions (≤100 000 confirmed COVID-19 cases and ≤1 000 000 inhabitants).
Our results show a clear decline in passenger volumes from March 2020 due to public health policies, interventions and other measures taken to limit or control the spread of COVID-19. As the measures were eased, some provinces and territories saw small increases in passenger volumes, although travel remained below pre-pandemic levels. During the early phase of disease introduction, the burden of illness is determined by the connectivity of jurisdictions. In provinces with a larger population and greater connectivity, the burden of illness is driven by case importation, although local transmission rapidly replaces imported cases as the most important driver of increasing new infections. In smaller jurisdictions, a steep increase in cases is seen after importation, leading to outbreaks within the community.
Historical travel volumes, combined with data on an emerging infection, are useful to understand the behaviour of an infectious agent in regions of Canada with different connectivity and population size. Historical travel information is important for public health planning and pandemic resource allocation.
COVID-19 大流行对加拿大和世界各地的卫生服务和政府构成了挑战。我们的研究旨在评估国内和国际航空旅行模式对加拿大各省和地区 COVID-19 大流行的影响。
通过获得许可访问 BlueDot Inc. 的“BlueDot 智能平台”来获取航空旅行数据。从公共数据集下载加拿大和全球的每日省级和地区 COVID-19 病例数据，包括死亡率、已康复病例和人口数据。使用半马尔可夫模型评估国内和国际航空旅行以及旅客量对每个加拿大省和地区本地和非本地感染人数的影响。将省份和地区分为大（>100000 例确诊 COVID-19 病例和>100 万居民）和小司法管辖区（≤100000 例确诊 COVID-19 病例和≤100 万居民）。
我们的结果表明，由于采取了公共卫生政策、干预措施和其他措施来限制或控制 COVID-19 的传播，2020 年 3 月以来旅客量明显下降。随着措施的放松，一些省份和地区的旅客量略有增加，尽管旅行仍低于大流行前的水平。在疾病传入的早期阶段，疾病负担由司法管辖区的连通性决定。在人口较多且连通性较强的省份，疾病负担是由病例输入驱动的，尽管随着新感染病例增加，本地传播迅速取代输入病例成为最重要的驱动因素。在较小的司法管辖区，输入后病例急剧增加，导致社区内爆发。
历史旅行量结合新兴感染的数据，有助于了解加拿大不同连通性和人口规模地区的传染病的行为。历史旅行信息对于公共卫生规划和大流行病资源分配很重要。
