School of Mathematical and Natural Sciences, Arizona State University, Phoenix, AZ 85069, USA.
School of Human Evolution and Social Change, Arizona State University, Tempe, AZ 85287, USA.
Math Biosci Eng. 2020 Jul 13;17(5):4891-4904. doi: 10.3934/mbe.2020266.
The outbreak of COVID-19 disrupts the life of many people in the world. The state of Arizona in the U.S. emerges as one of the country's newest COVID-19 hot spots. Accurate forecasting for COVID-19 cases will help governments to implement necessary measures and convince more people to take personal precautions to combat the virus. It is difficult to accurately predict the COVID- 19 cases due to many human factors involved. This paper aims to provide a forecasting model for COVID-19 cases with the help of human activity data from the Google Community Mobility Reports. To achieve this goal, a specific partial differential equation (PDE) is developed and validated with the COVID-19 data from the New York Times at the county level in the state of Arizona in the U.S. The proposed model describes the combined effects of transboundary spread among county clusters in Arizona and human activities on the transmission of COVID-19. The results show that the prediction accuracy of this model is well acceptable (above 94%). Furthermore, we study the effectiveness of personal precautions such as wearing face masks and practicing social distancing on COVID-19 cases at the local level. The localized analytical results can be used to help to slow the spread of COVID- 19 in Arizona. To the best of our knowledge, this work is the first attempt to apply PDE models on COVID-19 prediction with the Google Community Mobility Reports.
新冠疫情的爆发扰乱了全球许多人的生活。美国亚利桑那州成为美国最新的新冠热点地区之一。对新冠病例进行准确预测将有助于政府采取必要措施，并说服更多人采取个人预防措施来对抗病毒。由于涉及许多人为因素，因此很难准确预测新冠病例。本文旨在借助谷歌社区流动性报告中的人类活动数据，为新冠病例提供预测模型。为了实现这一目标，针对美国亚利桑那州的县一级的纽约时报新冠数据，我们开发并验证了一个特定的偏微分方程（PDE）。所提出的模型描述了亚利桑那州县集群之间的跨境传播以及人类活动对新冠传播的综合影响。结果表明，该模型的预测精度非常高（超过 94%）。此外，我们还研究了在地方层面上，戴口罩和保持社交距离等个人预防措施对新冠病例的有效性。局部分析结果可用于帮助减缓亚利桑那州新冠的传播。据我们所知，这是首次利用谷歌社区流动性报告将偏微分方程模型应用于新冠预测。
