Forecasting

Machine Learning The authors of this review examine efforts to use machine learning (ML) algorithms during the ongoing pandemic and they focus on two main applications:  diagnosis of COVID-19 and prediction of mortality risk and severity.  Given that it is Read More
Modeling and forecasting the spread of COVID-19 remains a challenge. This report details three regional-scale models for forecasting and assessing the course of the pandemic: 1) exponential growth, 2) self-exciting branching process, and 3) the susceptible–infected–resistant (SIR) compartment model. In presenting Read More
It is urgent to understand the future of severe acute respiratory syndrome-coronavirus 2 (SARS-CoV-2) transmission. This study used estimates of seasonality, immunity, and cross-immunity for human coronavirus OC43 (HCoV-OC43) and HCoV-HKU1 using time-series data from the United States to inform Read More
This study presents new evidence on the potential rise in maternal and child mortality in low-income and middle-income countries if essential health services are disrupted as a result of COVID-19. The authors modeled three hypothetical scenarios in which the coverage Read More
This study estimated the excess number of deaths over 1 year under different COVID-19 incidence scenarios. The authors analyzed 3.8 million health records from the UK and classified more than 20% of the study population as ‘high-risk’, either because they Read More

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