The Analysis of Patterns of Two COVID-19 Outbreak Clusters in China

Abstract

Since the emergence of COVID-19, there have been many local outbreaks with foci at shopping malls in China. We compared and analyzed the epidemiological and spatiotemporal characteristics of local COVID-19 outbreaks in two commercial locations, a department store building (DSB) in Baodi District, Tianjin, and the Xinfadi wholesale market (XFD) in Fengtai District, Beijing. The spread of the infection at different times was analyzed by the standard deviation elliptical method. The spatial transfer mode demonstrated that outbreaks started at the center of each commercial location and spread to the periphery. The number of cases and the distance from the central outbreak showed an inverse proportional logarithmic function shape. Most cases were distributed within a 10 km radius; infected individuals who lived far from the outbreak center were mainly infected by close-contact transmission at home or in the workplace. There was no efficient and rapid detection method at the time of the DSB outbreak; the main preventative measure was the timing of COVID-19 precautions. Emergency interventions (closing shopping malls and home isolation) were initiated five days before confirmation of the first case from the shopping center. In contrast, XFD closed after the first confirmed cases appeared, but those infected during this outbreak benefitted from efficient nucleic acid testing. Quick results and isolation of infected individuals were the main methods of epidemic control in this area. The difference in the COVID-19 epidemic patterns between the two shopping malls reflects the progress of Chinese technology in the prevention and control of COVID-19.

Modelling the spatiotemporal spread of COVID-19 outbreaks and prioritization of the risk areas in Toronto, Canada

“…For instance, a few studies evaluated the spread of COVID-19 over space and time by visually comparing multiple maps to observe the spatial distribution of new or cumulative cases using multiple time points during the early stages of the pandemic ( Cuadros et al, 2020 ; Gao et al, 2021 ; Yu et al, 2021 ; Feng et al, 2020 ). Standard deviation ellipse (SDE), a popular spatial statistical method, is often implemented in outbreak studies to model the spread of disease over time to analyze the spatiotemporal spread of an infectious disease by using the mean centre of the spatial distribution of the geographical elements as the centre and calculates the standard deviation of SDE in the X and Y axis ( Wang et al, 2022 ; Li et al, 2022 ; Gesler, 1986 ). Multiple days of SDE maps are often compared to observe the differences in directions between multiple time periods.…”

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“…However, the reliability of the model is unclear when new parameters are introduced [8,18]. Second, the originally assumed constant transition rates were adjusted to a time-dependent function to fit the real data [7,[19][20][21][22][23][24][25][26][27]. For example, Cheynet et al [20][21][22][23][24], expanding on the work of Peng et al [7], used multiple functional forms to fit cure and mortality rates.…”