Abstract
To describe the geographical heterogeneity of COVID-19 across prefectures in mainland China, we estimated doubling times from daily time series of the cumulative case count between 24 January and 24 February 2020. We analyzed the prefecture-level COVID-19 case burden using linear regression models and used the local Moran's I to test for spatial autocorrelation and clustering. Four hundred prefectures (~98% population) had at least one COVID-19 case and 39 prefectures had zero cases by 24 February 2020. Excluding Wuhan and those prefectures where there was only one case or none, 76 (17.3% of 439) prefectures had an arithmetic mean of the epidemic doubling time <2 d. Low-population prefectures had a higher per capita cumulative incidence than high-population prefectures during the study period. An increase in population size was associated with a very small reduction in the mean doubling time (-0.012, 95% CI, -0.017, -0.006) where the cumulative case count doubled ≥3 times. Spatial analysis revealed high case count clusters in Hubei and Heilongjiang and fast epidemic growth in several metropolitan areas by mid-February 2020. Prefectures in Hubei and neighboring provinces and several metropolitan areas in coastal and northeastern China experienced rapid growth with cumulative case count doubling multiple times with a small mean doubling time.
Highlights
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February 2020, indicating high numbers surrounded by high numbers, high numbers surrounded by had doubled by 16 February 2020, indicating high numbers surrounded by high numbers, high numbers surrounded by low numbers, low numbers surrounded by high numbers, and low numbers surrounded by low numbers
Purple color represents that jurisdictions without cases by 16 February 2020, or jurisdictions outside mainland China (Hong Kong, Macau, and Taiwan)
Summary
The coronavirus disease 2019 (COVID-19) pandemic, caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), began in Wuhan and soon spread globally. Prior studies have investigated SARS-CoV-2 transmission dynamics in mainland. Population mobility data was found to be highly predictive of COVID-19 importation risk from Wuhan to other Chinese cities in early 2020 [2]; population flow from Wuhan to 296 prefectures was found to drive the spatiotemporal distribution of COVID-19 cases in China in the spring of 2020 [3]. Detailed descriptions of Epidemiologia 2021, 2, 95–113.
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