Previously submitted to: JMIR Public Health and Surveillance (no longer under consideration since Mar 04, 2020)
Date Submitted: Mar 3, 2020
Warning: This is an author submission that is not peer-reviewed or edited. Preprints - unless they show as "accepted" - should not be relied on to guide clinical practice or health-related behavior and should not be reported in news media as established information.
An evaluation model of 2019-nCoV prevention effectiveness based on immigration data in China
ABSTRACT
Background:
As of the end of February 2020, 2019-nCoV is currently well controlled in China. However, the virus is now spreading globally.
Objective:
This study aimed to evaluate the effectiveness of outbreak prevention and control measures in a region.
Methods:
A model is built for find the best fit for two sets of data (the number of daily new diagnosed, and the risk value of incoming immigration population). The parameters (offset and time window) in the model can be used as the evaluation of effectiveness of outbreak prevention and control.
Results:
Through study, it is found that the parameter offset and time window in the model can accurately reflect the prevention effectiveness. Some related data and public news confirm this result. And this method has advantages over the method using R0 in two aspects.
Conclusions:
If the epidemic situation is well controlled, the virus is not terrible. Now the daily new diagnosed patients in most regions of China is quickly reduced to zero or close to zero. Chinese can do a good job in the face of huge epidemic pressure. Therefore, if other countries can do well in prevention and control, the epidemic in those places can also pass quickly.
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