Mathematical Modeling and Epidemic Prediction of Covid-19 and Its Significance to Epidemic Prevention and Control Measures

Background: Since receiving unexplained pneumonia patients at the Jinyintan Hospital in Wuhan, China in December 2019, the new coronavirus (COVID-19) 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 COVID-19, which will be conducive to the intervention and prevention of COVID-19 by departments at all levels in mainland China and buy more time for clinical trials. Methods: Based on the transmission mechanism of COVID-19 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 COVID-19 in mainland China can reach 36,343 after one week (February 8, 2020) and the number of basic regeneration 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 regeneration 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 COVID-19 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 COVID-19 are cured, the antibodies left in their bodies may prevent them from reinfecting COVID-19 for a longer period of time. Yichi Li1, Bowen Wang2, Ruiyang Peng3, Chen Zhou4, Yonglong Zhan5, Zhuoxun Liu6, Xia Jiang7 and Bin Zhao1* 1School of Science, Hubei University of Technology, China 2School of Electrical and Electronic Engineering, Hubei University of Technology, China 3School of Computer, Hubei Polytechnic University, China 4School of Economics and Management, Hubei University of Technology, China 5School of Computer Science, Hubei University of Technology, China 6Normal School of Vocational and Technical Education, HuBei University of Technology, China 7Hospital, Hubei University of Technology, China Bin Zhao, et al., Annals of Infectious Disease and Epidemiology Remedy Publications LLC. 2020 | Volume 5 | Issue 1 | Article 1052 2 Introduction Since December 2019, many unexplained cases of pneumonia with cough, dyspnea, fatigue, and fever as the main symptoms have occurred in Wuhan, China in a short period of time [1,2]. China's health authorities and CDC quickly identified the pathogen of such cases as a new type of coronavirus, which the World Health Organization (WHO) named COVID-19 on January 10, 2020 [3]. On January 22, 2020, the Information Office of the State Council of the People's Republic of China held a press conference introduced the relevant situation of pneumonia prevention and control of new coronavirus infection. On the same day, the People's Republic of China's CDC released a plan for the prevention and control of pneumonitis of new coronavirus infection, including the COVID-19 epidemic Research, specimen collection and testing, tracking and management of close contacts, and propaganda, education and risk communication to the public [4]. Wuhan, China is the origin of COVID-19 and one of the Cities most affected by it. The Mayor of Wuhan stated at a press conference on January 31, 2020 that Wuhan is urgently building Vulcan Mountain Hospital and Thunder Mountain Hospital patients will be officially admitted on February 3 and February 6 [5]. By 24:00 on February 6, 2020, a total of 31,161 confirmed cases, including 636 deaths, were reported in the Chinese mainland, 22,112 confirmed cases, including 618 deaths, were reported in Hubei province, and 11,618 confirmed cases, including 478 deaths, and were reported in Wuhan city. The spread of COVID-19 and various interventions have had an incalculable negative impact on People's daily lives and the normal functioning of society. Cities in China's Hubei Province have issued varying degrees of closures and traffic restrictions [6]. In fact, there are many imminent questions about the spread of COVID-19. How many people will be infected tomorrow? When will the inflection point of the infection rate appear? How many people will be infected during the peak period? Can existing interventions effectively control the COVID-19? What mathematical models are available to help us answer these questions? The COVID-19 is a novel coronavirus that was only discovered in December 2019, so data on the outbreak is still insufficient, and medical means such as clinical trials are still in a difficult exploratory stage [7]. So far, epidemic data have been difficult to apply directly to existing mathematical models, and questions need to be addressed as to how effective the existing emergency response has been and how to invest medical resources more scientifically in the future and so on. Based on this, this article aims to study the gaps in this part.