基于SIR模型的新型冠状病毒肺炎预测分析

Prediction and Analysis of Novel Coronavirus Pneumonia Based on SIR Model

本文利用Python爬虫技术,获取国家卫健委每日发布的新冠肺炎相关病例(确诊、疑似、治愈、死亡)数据,基于疫情初期数据用SIR模型建立疫情变化趋势图,再结合政府制定的一系列干预政策,考虑其他影响疫情发展的因素,用改进的SIR模型对疫情进行预测,并对疫情的发展阶段和趋势进行评估,得出在政府干预下,新冠肺炎疫情高峰下降及结束时间提前,肯定了政府干预措施的必要性,为世界各国建立有效的疫情防控提供参考。

This paper using python crawler technology,access to National Health and Family Planning Commission COVID released daily related cases(diagnosis,suspected,cured,death)data,research data,builds the epidemic trends,using the SEIR model and improved SEIR model to forecast the outbreak,and combined with the a series of interventions formulated by the government,to evaluate epidemic stages of development and trends,and affirmed the necessity of government intervention,so as to provide the references for the countries around the world to establish effective epidemic prevention and control.