Research Article
Volume 4 Issue 7 - 2020
Mathematical Modeling and Epidemic Prediction Of 2019-Ncov and Its Significance to Epidemic Prevention And Control Measures
Weihua Zhao1, Jinming Cao2 and Bin Zhao3*
1Shenzhen Leading Investment Technology Co., Ltd, Shenzhen, Guangdong, China
2School of Information and Mathematics, Yangtze University, Jingzhou, Hubei, China
3School of Science, Hubei University of Technology, Wuhan, Hubei, China
*Corresponding Author: Bin Zhao, School of Science, Hubei University of Technology, Wuhan, Hubei, China.
Received: February 10, 2020; Published: June 29, 2020




Abstract

Background: Since receiving unexplained pneumonia patients at the Jinyintan Hospital in Wuhan, China in December 2019, the new coronavirus (2019-nCoV) has rapidly spread in Wuhan, China and spread to the entire China and some neighboring countries. We establish the dynamics model of infectious diseases and time series model to predict the trend and short-term prediction of the transmission of 2019-nCoV, which will be conducive to the intervention and prevention of 2019-nCoV by departments at all levels in mainland China and buy more time for clinical trials.

Methods: Based on the transmission mechanism of 2019-nCoV in the population and the implemented prevention and control measures, we establish the dynamic models of the six chambers and establish the time series models based on different mathematical formulas according to the variation law of the original data.

Findings: The results based on time series analysis and kinetic model analysis show that the cumulative diagnosis of pneumonia of 2019-nCoV in mainland China can reach 36,343 after one week (February 8, 2020) and the number of basic regenerations can reach 4.01. The cumulative number of confirmed diagnoses will reach a peak of 87,701 on March 15, 2020; the number of basic regenerations in Wuhan will reach 4.3 and the cumulative number of confirmed cases in Wuhan will reach peak at 76,982 on March 20. Whether in Mainland China or Wuhan, both the infection rate and the basic regeneration number of 2019-nCoV continue to decline and the results of the sensitivity analysis show that the time it takes for a suspected population to be diagnosed as a confirmed population can have a significant impact on the peak size and duration of the cumulative number of diagnoses. Increased mortality leads to additional cases of pneumonia, while increased cure rates are not sensitive to the cumulative number of confirmed cases.

Interpretation: Chinese governments at various levels have intervened in many ways to control the epidemic. According to the results of the model analysis, we believe that the emergency intervention measures adopted in the early stage of the epidemic, such as blocking Wuhan, restricting the flow of people in Hubei province and increasing the support to Wuhan, had a crucial restraining effect on the original spread of the epidemic.

It is a very effective prevention and treatment method to continue to increase investment in various medical resources to ensure that suspected patients can be diagnosed and treated in a timely manner.

Based on the results of the sensitivity analysis, we believe that enhanced treatment of the bodies of deceased patients can be effective in ensuring that the bodies themselves and the process do not result in additional viral infections and once the pneumonia patients with the 2019-nCoV are cured, the antibodies left in their bodies may prevent them from reinfecting 2019-nCoV for a longer period of time.

Keywords: New Coronavirus; Infection Prediction; Infection Prevention and Control; Arimax Model; Seir Model

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Citation: Bin Zhao., et al. “Mathematical Modeling and Epidemic Prediction Of 2019-Ncov And Its Significance to Epidemic Prevention And Control Measures”. EC Emergency Medicine and Critical Care 4.7 (2020): 07-23.

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