Universal Urban Spreading Pattern of COVID-19 and Its Underlying Mechanism (preprint)

Currently, the global situation of COVID-19 is aggravating, pressingly calling for efficient control and prevention measures. Understanding spreading pattern of COVID-19 has been widely recognized as a vital step for implementing non-pharmaceutical measures. Previous studies investigated such an issue in large-scale (e.g., inter-country or inter-state) scenarios while urban spreading pattern still remains an open issue. Here, we fill this gap by leveraging the trajectory data of 197,808 smartphone users (including 17,808 anonymous confirmed cases) in 9 cities in China. We find a universal spreading pattern in all cities: the spatial distribution of confirmed cases follows a power-law-like model and the spreading centroid is time-invariant. Moreover, we reveal that human mobility in a city drives the spatialtemporal spreading process: long average travelling distance results in a high growth rate of spreading radius and wide spatial diffusion of confirmed cases. With such insight, we adopt Kendall model to simulate urban spreading of COVID-19 that can well fit the real spreading process. Our results unveil the underlying mechanism behind the spatial-temporal urban evolution of COVID-19, and can be used to evaluate the performance of mobility restriction policies implemented by many governments and to estimate the evolving spreading situation of COVID-19.

A population-based retrospective study of the spread of COVID-19 from Wuhan to Henan province, China (preprint)

The epidemic of COVID-19 has now spread globally and affected over 110 countries. As of Mar 10th, using publicly available data and official news reports in Henan province, we tracked a total of 1272 cases and a retrospective study was conducted to investigate the related factors in COVID-19 spread and control. We confirmed 554 primary patients had travel or residential history of Wuhan in the recent 2 weeks. Secondary cases accounted for 77.9% (141/181) among all the patients aged 61 or older, in whom contacted with unconfirmed returnees from Wuhan was responsible for 27.0% (38/141). The median incubate period is 7 (IQR, 4-10) days by analyzing time information in 469 cases. For 442 patients with discharge dates, the duration from onset to cure is 19 (IQR, 15-23) days. The time from onset to seeking care at a hospital varied in age groups, and differed between primary and secondary cases. Patients visiting different hospitals affected the time from seeking care to cure. Thus, our results showed the spread of COVID-19 and factors associated with outcomes of patients in Henan province, which helps to understand the epidemiological features outside of the epidemic area and control the disease in other regions and countries.

Spread and control of COVID-19 in China and their associations with population movement, public health emergency measures, and medical resources (preprint)

ABSTRACT BACKGROUND The COVID-19 epidemic, first emerged in Wuhan during December 2019, has spread globally. While the mass population movement for Chinese New Year has significantly influenced spreading the disease, little direct evidence exists about the relevance to epidemic and its control of population movement from Wuhan, local emergency response, and medical resources in China. METHODS Spearman's correlation analysis was performed between official data of confirmed COVID-19 cases from Jan 20th to Feb 19th, 2020 and real-time travel data and health resources data. RESULTS There were 74,675 confirmed COVID-19 cases in China by Feb 19th, 2020. The overall fatality rate was 2.84%, much higher in Hubei than in other regions (3.27% vs 0.73%). The index of population inflow from Hubei was positively correlated with total (Provincial r=0.9159, p<0.001; City r=0.6311, p<0.001) and primary cases (Provincial r=0.8702, p<0.001; City r=0.6358, p<0.001). The local health emergency measures (eg, city lockdown and traffic control) were associated with reduced infections nationwide. Moreover, the number of public health employees per capita was inversely correlated with total cases (r=-0.6295, p<0.001) and infection rates (r=-0.4912, p<0.01). Similarly, cities with less medical resources had higher fatality (r=-0.4791, p<0.01) and lower cure rates (r=0.5286, p<0.01) among the confirmed cases. CONCLUSIONS The spread of the COVID-19 in China in its early phase was attributed primarily to population movement from Hubei, and effective governmental health emergency measures and adequate medical resources played important roles in subsequent control of epidemic and improved prognosis of affected individuals.