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2019 nCOV

Preliminary analysis of the 2019 nCOV outbreak in Wuhan city

New paper

Early epidemiological analysis of the 2019-nCoV outbreak 
based on a crowdsourced data 

Kaiyuan Sun, Jenny Chen, Cécile Viboud.  medRxiv link
This web page is routinely update as new information is available.
Last analysis considers the situation as of Jan.29, 2020.
Preliminary assessment of the international spreading risk associated with the 2019 nCOV outbreak in Wuhan city
Starting in December 2019, Chinese health authorities have been closely monitoring a cluster of pneumonia cases in the city of Wuhan, in Hubei Province. It has been determined that the causing agent of the viral pneumonia among affected individuals is a new coronavirus (2019-nCoV). As of January 29, 2020, a total of 6,088 cases have been detected and confirmed in Mainland China, with more than 70 additional cases detected and confirmed internationally in Japan, Thailand, South Korea, Taiwan, Singapore, Vietnam, United States, France, Australia, Nepal, Canada, Cambodia, Sri Lanka, United Arab Emirates, Finland, and Germany. By using the cases detected outside China we are providing estimates of size of the Wuhan outbreak as of January 29th, 2020.​ By using an estimate of 10 days from exposure to detection and an effective population of 20 million people in Wuhan catchment area the estimated median size of the Wuhan outbreak is 31,200 infections [95% CI: 23,400-40,400]. Technical details are in the full report available below. 
Spreading risk analysis
Here we use a detailed individual based mobility model to estimate  the risk of international dissemination. Our model simulates the mobility of people across more than 3,200 census areas in about 190 different countries. The mobility among subpopulations integrates the mobility by global air travel (obtained from the International Air Transport Association and Official Airline Guide databases) and the short-scale mobility between adjacent subpopulations. Based on the number of infected individuals detected in Wuhan (China) the model estimates two main quantities:
  • Relative importation risk: for each location Y, the platform evaluates the probability P(Y) that a single infected individual is traveling from the index areas to that specific destination Y. In other words, given the occurrence of one exported case, P(Y) is the probability that the disease carrier will appear in location Y, with respect to any other possible location.

  • Exported cases: the model estimates the probability P(n) of exporting a given number of cases n from the origin of the disease outbreak. In order to calculate the distribution P, the average time from exposure to symptoms onset/detection and inability of traveling of infected individuals must be provided.
A full list of destination ranked according to risk is available upon request or using the interactive online dashboard here.  The platform reports also a validation of the risk analysis using the latest data available.
Real time situation reports on nCov within China based on digital data streams
DXY.cn, a Chinese online community for physicians and health care professionals, provides real-time situation reports of  the 2019 nCov oubreak in China. The information reported includes cumulative nCov case counts, outbreak maps,  and real time streaming of health authority announcements (directly or through state media) in Chinese. Link: http://3g.dxy.cn/newh5/view/pneumonia.

We closely monitor updates on DXY.cn as well as other publicly available data sources and extract key information in near real-time. A majority of the reports are being summarized in English with key epidemiological information on newly reported cases at the subnational level, as well as individual-level patient information on age, gender, travel history, symptom-onset and hospitalization dates. The individual level data are further processed into a line-list database for further quantitative analysis. We also keep track of research development on transmission estimates and the  natural history of nCov disease (R0, generation time)  when sufficient evidence is available.

​Full reports

Preliminary assessment of the International Spreading Risk Associated with the 2019 novel Coronavirus (2019-nCoV) outbreak in Wuhan 
(Jan.29 , 2020)

Preliminary assessment of the International Spreading Risk Associated with the 2019 novel Coronavirus (2019-nCoV) outbreak in Wuhan 
(Jan.27 , 2020)
​
Preliminary assessment of the International Spreading Risk Associated with the 2019 novel Coronavirus (2019-nCoV) outbreak in Wuhan 
(Jan.26 , 2020)
​
Preliminary assessment of the International Spreading Risk Associated with the 2019 novel Coronavirus (2019-nCoV) outbreak in Wuhan 
​(Jan.24, 2020)
​
​Preliminary assessment of the International Spreading Risk Associated with the 2019 novel Coronavirus (2019-nCoV) outbreak in Wuhan  (Jan.21, 2020)
Preliminary assessment of the International Spreading Risk Associated with the 2019 novel Coronavirus (2019-nCoV) outbreak in Wuhan 
​(Jan.23, 2020)
​
​Preliminary assessment of the International Spreading Risk Associated with the 2019 novel Coronavirus (2019-nCoV) outbreak in Wuhan City (Jan.20, 2020)

​Preliminary assessment of the International Spreading Risk Associated with the 2019 novel Coronavirus (2019-nCoV) outbreak in Wuhan City (Jan.17,2020)
Interactive analysis platform
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view platform

Risk analysis  dashboard
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view full dashboard

Situation Report Mainland China Dashboard
view full site

Collaboration

NORTHEASTERN UNIVERSITY
M. Chinazzi, J. T. Davis, A. Pastore y Piontti, X. Xiong, A. Vespignani

ISI FOUNDATION
C. Gioannini, M. Litvinova, L. Rossi,  

FRED HUTCHINSON CANCER 
RESEARCH CENTER

M.E. Halloran

UNIVERSITY OF FLORIDA
I.M. Longini Jr.

NIH Fogarty Institute
K.Sun, C. Viboud

Bruno Kessler Foundation
M.Ajelli, S.Merler

Air traffic connections from Wuhan to the rest of the world
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Northeastern University
GLEAMviz.org

Large Network Visualization Tool

Complex Networks Collaboratory

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OUR LOCATION

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   LINKS

  • Northeastern University
  • Network Science Institute
  • GLEAMviz.org
  • Large Network Visualization Tool
  • Complex Networks Collaboratory

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