Spatial and Temporal Hotspot Analysis of COVID-19 in Toronto

Afia Amoako, Mabel Carabali, Erjia Ge, Ashleigh R Tuite, David N Fisman
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Abstract

The COVID-19 pandemic in Toronto, Canada was unequal for its 2.7 million residents. As a dynamic pandemic, COVID-19 trends might have also varied over space and time. We conducted a spatiotemporal hotspot analysis of COVID-19 over the first four major waves of COVID-19 using three different applications of Moran’s I to highlight the variable experience of COVID-19 infections in Toronto, while describing the potential impact of socioeconomic and sociodemographic factors on increased risk of COVID-19 exposure and infection. Results highlight potential clustering of COVID-19 case rate hot spots in areas with higher concentrations of immigrant and low-income residents and cold spots in areas with more affluent and non-immigrant residents during the first three waves. By the fourth wave, case rate clustering patterns were more dynamic. In all, a better understanding of the unequal COVID-19 pandemic experience in Toronto needs to also consider the dynamic nature of the pandemic.
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多伦多 COVID-19 的时空热点分析
加拿大多伦多的 COVID-19 大流行对其 270 万居民来说是不平等的。作为一种动态流行病,COVID-19 的趋势也可能随时间和空间而变化。我们利用莫兰 I 的三种不同应用对 COVID-19 的前四次大流行进行了时空热点分析,以突出 COVID-19 在多伦多的不同感染情况,同时描述社会经济和社会人口因素对 COVID-19 暴露和感染风险增加的潜在影响。结果显示,在前三波中,COVID-19 病例率热点可能集中在移民和低收入居民较集中的地区,而冷点则集中在较富裕和非移民居民较集中的地区。到了第四波,病例率的聚类模式更具动态性。总之,要更好地理解多伦多 COVID-19 大流行的不平等经历,还需要考虑该大流行的动态性质。
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