Center for Neural Engineering, Department of Engineering Science and Mechanics, The Pennsylvania State University, University Park, PA 16802.
Department of Public Health Sciences, The Pennsylvania State University College of Medicine, Hershey, PA 17033.
Proc Natl Acad Sci U S A. 2021 Jul 13;118(28). doi: 10.1073/pnas.2026664118.
The coronavirus disease 2019 (COVID-19) pandemic is heterogeneous throughout Africa and threatening millions of lives. Surveillance and short-term modeling forecasts are critical to provide timely information for decisions on control strategies. We created a strategy that helps predict the country-level case occurrences based on cases within or external to a country throughout the entire African continent, parameterized by socioeconomic and geoeconomic variations and the lagged effects of social policy and meteorological history. We observed the effect of the Human Development Index, containment policies, testing capacity, specific humidity, temperature, and landlocked status of countries on the local within-country and external between-country transmission. One-week forecasts of case numbers from the model were driven by the quality of the reported data. Seeking equitable behavioral and social interventions, balanced with coordinated country-specific strategies in infection suppression, should be a continental priority to control the COVID-19 pandemic in Africa.
2019 年冠状病毒病（COVID-19）大流行在整个非洲呈现出异质性，威胁着数百万人的生命。监测和短期建模预测对于提供有关控制策略的决策的及时信息至关重要。我们创建了一种策略，该策略可根据整个非洲大陆内外国家/地区的病例来帮助预测国家级病例的发生，该策略通过社会经济和地缘经济变化以及社会政策和气象历史的滞后效应进行参数化。我们观察了人类发展指数，遏制政策，检测能力，特定湿度，温度和内陆国家地位对国内和国家之间的本地和外部传播的影响。该模型的病例数的一周预测受到报告数据质量的驱动。寻求公平的行为和社会干预措施，并与感染抑制方面的协调一致的国家特定策略相平衡，应成为非洲控制 COVID-19 大流行的大陆优先事项。
