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Nature ; 582(7812): 389-394, 2020 06.
Article in English | MEDLINE | ID: covidwho-147207


Sudden, large-scale and diffuse human migration can amplify localized outbreaks of disease into widespread epidemics1-4. Rapid and accurate tracking of aggregate population flows may therefore be epidemiologically informative. Here we use 11,478,484 counts of mobile phone data from individuals leaving or transiting through the prefecture of Wuhan between 1 January and 24 January 2020 as they moved to 296 prefectures throughout mainland China. First, we document the efficacy of quarantine in ceasing movement. Second, we show that the distribution of population outflow from Wuhan accurately predicts the relative frequency and geographical distribution of infections with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) until 19 February 2020, across mainland China. Third, we develop a spatio-temporal 'risk source' model that leverages population flow data (which operationalize the risk that emanates from epidemic epicentres) not only to forecast the distribution of confirmed cases, but also to identify regions that have a high risk of transmission at an early stage. Fourth, we use this risk source model to statistically derive the geographical spread of COVID-19 and the growth pattern based on the population outflow from Wuhan; the model yields a benchmark trend and an index for assessing the risk of community transmission of COVID-19 over time for different locations. This approach can be used by policy-makers in any nation with available data to make rapid and accurate risk assessments and to plan the allocation of limited resources ahead of ongoing outbreaks.

Coronavirus Infections/epidemiology , Coronavirus Infections/transmission , Disease Outbreaks/statistics & numerical data , Pneumonia, Viral/epidemiology , Pneumonia, Viral/transmission , Population Dynamics/statistics & numerical data , Spatio-Temporal Analysis , Travel/statistics & numerical data , China/epidemiology , Cities/epidemiology , Coronavirus Infections/diagnosis , Datasets as Topic , Geographic Mapping , Humans , Mobile Applications , Models, Biological , Pandemics , Pneumonia, Viral/diagnosis , Public Health/statistics & numerical data
Sichuan Da Xue Xue Bao Yi Xue Ban ; 51(2): 131-138, 2020 Mar.
Article in Chinese | MEDLINE | ID: covidwho-18396


This review summarizes the ongoing researches regarding etiology, epidemiology, transmission dynamics, treatment, and prevention and control strategies of the coronavirus disease 2019 (COVID-19) caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), with comparison to severe acute respiratory syndrome coronavirus (SARS-CoV), Middle East respiratory syndrome coronavirus (MERS-CoV) and pandemic H1N1 virus. SARS-CoV-2 may be originated from bats, and the patients and asymptomatic carriers are the source of epidemic infection. The virus can be transmitted human-to-human through droplets and close contact, and people at all ages are susceptible to this virus. The main clinical symptoms of the patients are fever and cough, accompanied with leukocytopenia and lymphocytopenia. Effective drugs have been not yet available thus far. In terms of the prevention and control strategies, vaccine development as the primary prevention should be accelerated. Regarding the secondary prevention, ongoing efforts of the infected patients and close contacts quarantine, mask wearing promotion, regular disinfection in public places should be continued. Meanwhile, rapid detection kit for serological monitoring of the virus in general population is expected so as to achieve early detection, early diagnosis, early isolation and early treatment. In addition, public health education on this disease and prevention should be enhanced so as to mitigate panic and mobilize the public to jointly combat the epidemic.

Betacoronavirus , Coronavirus Infections , Pandemics , Pneumonia, Viral , Asymptomatic Diseases , Betacoronavirus/pathogenicity , Clinical Laboratory Techniques , Coronavirus Infections/complications , Coronavirus Infections/diagnosis , Coronavirus Infections/epidemiology , Coronavirus Infections/prevention & control , Coronavirus Infections/transmission , Cough/etiology , Early Diagnosis , Fever/etiology , Humans , Influenza A Virus, H1N1 Subtype , Leukopenia/etiology , Lymphopenia/etiology , Middle East Respiratory Syndrome Coronavirus , Pandemics/prevention & control , Pneumonia, Viral/complications , Pneumonia, Viral/epidemiology , Pneumonia, Viral/prevention & control , Pneumonia, Viral/transmission , SARS Virus , Secondary Prevention , Viral Vaccines
J Evid Based Med ; 13(1): 3-7, 2020 Feb.
Article in English | MEDLINE | ID: covidwho-707


OBJECTIVES: To estimate the basic reproduction number of the Wuhan novel coronavirus (2019-nCoV). METHODS: Based on the susceptible-exposed-infected-removed (SEIR) compartment model and the assumption that the infectious cases with symptoms occurred before 26 January, 2020 are resulted from free propagation without intervention, we estimate the basic reproduction number of 2019-nCoV according to the reported confirmed cases and suspected cases, as well as the theoretical estimated number of infected cases by other research teams, together with some epidemiological determinants learned from the severe acute respiratory syndrome (SARS). RESULTS: The basic reproduction number fall between 2.8 and 3.3 by using the real-time reports on the number of 2019-nCoV-infected cases from People's Daily in China and fall between 3.2 and 3.9 on the basis of the predicted number of infected cases from international colleagues. CONCLUSIONS: The early transmission ability of 2019-nCoV is close to or slightly higher than SARS. It is a controllable disease with moderate to high transmissibility. Timely and effective control measures are needed to prevent the further transmissions.

Basic Reproduction Number , Betacoronavirus , Coronavirus Infections , Pneumonia, Viral , China/epidemiology , Coronavirus Infections/epidemiology , Coronavirus Infections/prevention & control , Coronavirus Infections/transmission , Forecasting , Humans , Models, Theoretical , Pneumonia, Viral/epidemiology , Pneumonia, Viral/prevention & control , Pneumonia, Viral/transmission