Roosa Kimberlyn, Lee Yiseul, Luo Ruiyan, Kirpich Alexander, Rothenberg Richard, Hyman James M, Yan Ping, Chowell Gerardo
Department of Population Health Sciences, School of Public Health, Georgia State University, Atlanta, GA 30302, USA.
Department of Mathematics, Center for Computational Science, Tulane University, New Orleans, LA 70118, USA.
J Clin Med. 2020 Feb 22;9(2):596. doi: 10.3390/jcm9020596.
The ongoing COVID-19 epidemic continues to spread within and outside of China, despite several social distancing measures implemented by the Chinese government. Limited epidemiological data are available, and recent changes in case definition and reporting further complicate our understanding of the impact of the epidemic, particularly in the epidemic's epicenter. Here we use previously validated phenomenological models to generate short-term forecasts of cumulative reported cases in Guangdong and Zhejiang, China. Using daily reported cumulative case data up until 13 February 2020 from the National Health Commission of China, we report 5- and 10-day ahead forecasts of cumulative case reports. Specifically, we generate forecasts using a generalized logistic growth model, the Richards growth model, and a sub-epidemic wave model, which have each been previously used to forecast outbreaks due to different infectious diseases. Forecasts from each of the models suggest the outbreaks may be nearing extinction in both Guangdong and Zhejiang; however, the sub-epidemic model predictions also include the potential for further sustained transmission, particularly in Zhejiang. Our 10-day forecasts across the three models predict an additional 65-81 cases (upper bounds: 169-507) in Guangdong and an additional 44-354 (upper bounds: 141-875) cases in Zhejiang by February 23, 2020. In the best-case scenario, current data suggest that transmission in both provinces is slowing down.
尽管中国政府实施了多项社交距离措施,但当前的新冠疫情仍在中国境内外持续蔓延。现有流行病学数据有限,且病例定义和报告的近期变化使我们对疫情影响的理解更加复杂,尤其是在疫情的中心地区。在此,我们使用先前经过验证的现象学模型对中国广东和浙江的累计报告病例数进行短期预测。利用截至2020年2月13日中国国家卫生健康委员会每日报告的累计病例数据,我们报告了未来5天和10天的累计病例报告预测。具体而言,我们使用广义逻辑增长模型、理查兹增长模型和子疫情波模型进行预测,这些模型此前曾分别用于预测不同传染病的爆发。每个模型的预测结果均表明,广东和浙江的疫情可能接近尾声;然而,子疫情模型的预测还包括进一步持续传播的可能性,尤其是在浙江。我们通过这三个模型进行的10天预测显示,到2020年2月23日,广东预计新增65 - 81例病例(上限:169 - 507例),浙江预计新增44 - 354例病例(上限:141 - 875例)。在最佳情况下,目前的数据表明两省的传播速度正在放缓。