Featuring weekly forecasts of state level hotspots in the United States and archived global cases and deaths of COVID-19, the novel coronavirus. The forecasts based on deaths provides additional information to compare the forecasts based on global cases. Researchers in the School of Public Health have found forecasts based on deaths are less affected by temporal variations in testing rates.
Forecasts are updated every Tuesday by 9 p.m. ET. Please contact gchowell@gsu.edu for more information.
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UNITED STATES
The Sub-epidemic Model – Cases – US Hotspot State Level Forecasts captures a diversity of epidemic trajectories including stable incidence patterns with sustained or damped oscillations. Researchers in the School of Public Health fit the model to cumulative reported cases to forecast future trends in reported cases.
Scroll right to review the most recent forecasts in alphabetical order by State.
ARCHIVED FORECASTS AND FIGURES
The Generalized Logistic Growth Model (GLM) – China forecasts are simple models that allow for a range of early growth dynamics and, with sufficient data, can help infer the size of the outbreak. Researchers in the School of Public Health fit the model to cumulative reported cases to forecast future trends in reported cases.
The Mechanistic Transmission Model – China forecasts are transmission models that track the number of individuals in different epidemiological states throughout the outbreak, where the states include susceptible, exposed, infectious, isolated, and recovered individuals. Researchers in the School of Public Health use this model to generate forecasts of future reported case counts and to assess the impact of enhanced public health interventions, such as rapid diagnosis and effective isolation of a higher proportion of symptomatic individuals.
The well-known Richards Model – China forecasts are a simple extension of the logistic growth model. Researchers in the School of Public Health fit the model to cumulative reported cases to forecast future trends in reported cases.
The Sub-epidemic Model – China captures a diversity of epidemic trajectories including stable incidence patterns with sustained or damped oscillations. Researchers in the School of Public Health fit the model to cumulative reported cases to forecast future trends in reported cases.
The Sub-epidemic Model – Iran captures a diversity of epidemic trajectories including stable incidence patterns with sustained or damped oscillations. Researchers in the School of Public Health fit the model to cumulative reported cases to forecast future trends in reported cases.
The Sub-epidemic Model – Canada captures a diversity of epidemic trajectories including stable incidence patterns with sustained or damped oscillations. Researchers in the School of Public Health fit the model to cumulative reported cases to forecast future trends in reported cases.
The Sub-epidemic Model – Canada captures a diversity of epidemic trajectories including stable incidence patterns with sustained or damped oscillations. Researchers in the School of Public Health fit the model to cumulative reported deaths to forecast future trends in reported deaths.
The Sub-epidemic Model – Germany captures a diversity of epidemic trajectories including stable incidence patterns with sustained or damped oscillations. Researchers in the School of Public Health fit the model to cumulative reported cases to forecast future trends in reported cases.
The Sub-epidemic Model – Germany captures a diversity of epidemic trajectories including stable incidence patterns with sustained or damped oscillations. Researchers in the School of Public Health fit the model to cumulative reported deaths to forecast future trends in reported deaths.
The Sub-epidemic Model – The Netherlands captures a diversity of epidemic trajectories including stable incidence patterns with sustained or damped oscillations. Researchers in the School of Public Health fit the model to cumulative reported cases to forecast future trends in reported cases.
The Sub-epidemic Model – The Netherlands captures a diversity of epidemic trajectories including stable incidence patterns with sustained or damped oscillations. Researchers in the School of Public Health fit the model to cumulative reported deaths to forecast future trends in reported deaths.
The Sub-epidemic Model – United Kingdom captures a diversity of epidemic trajectories including stable incidence patterns with sustained or damped oscillations. Researchers in the School of Public Health fit the model to cumulative reported cases to forecast future trends in reported cases.
The Sub-epidemic Model – United Kingdom captures a diversity of epidemic trajectories including stable incidence patterns with sustained or damped oscillations. Researchers in the School of Public Health fit the model to cumulative reported deaths to forecast future trends in reported deaths.
The Sub-epidemic Model – Republic of Korea captures a diversity of epidemic trajectories including stable incidence patterns with sustained or damped oscillations. Researchers in the School of Public Health fit the model to cumulative reported cases to forecast future trends in reported cases.
The Transmission Potential – Singapore figure is measured by the effective reproduction number, which quantifies the temporal variation in the average number of secondary cases generated per case during the course of an outbreak (after considering multiple factors including behavior changes, cultural factors, and the implementation of public health measures). Estimates of R >1 indicate sustained transmission; whereas, R <1 implies that the outbreak is slowing down and the incidence trend is declining. Hence, maintaining R<1 is required to bring an outbreak under control.
The Generalized Logistic Growth Model (GLM) – United States forecasts are simple models that allow for a range of early growth dynamics and, with sufficient data, can help infer the size of the outbreak. Researchers in the School of Public Health fit the model to cumulative reported cases to forecast future trends in reported cases.
The well-known Richards Model – United States forecasts are a simple extension of the logistic growth model. Researchers in the School of Public Health fit the model to cumulative reported cases to forecast future trends in reported cases.
The Sub-epidemic Model – France captures a diversity of epidemic trajectories including stable incidence patterns with sustained or damped oscillations. Researchers in the School of Public Health fit the model to cumulative reported cases to forecast future trends in reported cases.
The Sub-epidemic Model – France captures a diversity of epidemic trajectories including stable incidence patterns with sustained or damped oscillations. Researchers in the School of Public Health fit the model to cumulative reported deaths to forecast future trends in reported deaths.
The Sub-epidemic Model – Italy captures a diversity of epidemic trajectories including stable incidence patterns with sustained or damped oscillations. Researchers in the School of Public Health fit the model to cumulative reported cases to forecast future trends in reported cases.
The Sub-epidemic Model – Italy captures a diversity of epidemic trajectories including stable incidence patterns with sustained or damped oscillations. Researchers in the School of Public Health fit the model to cumulative reported deaths to forecast future trends in reported deaths.
The Sub-epidemic Model – Spain captures a diversity of epidemic trajectories including stable incidence patterns with sustained or damped oscillations. Researchers in the School of Public Health fit the model to cumulative reported cases to forecast future trends in reported cases.
The Sub-epidemic Model – Spain captures a diversity of epidemic trajectories including stable incidence patterns with sustained or damped oscillations. Researchers in the School of Public Health fit the model to cumulative reported deaths to forecast future trends in reported deaths.
The Generalized Logistic Growth Model (GLM) – United States forecasts are simple models that allow for a range of early growth dynamics and, with sufficient data, can help infer the size of the outbreak. Researchers in the School of Public Health fit the model to cumulative reported cases to forecast future trends in reported cases.
The Sub-epidemic Model – Cases – Daily State Level Forecasts captures a diversity of epidemic trajectories including stable incidence patterns with sustained or damped oscillations. Researchers in the School of Public Health fit the model to cumulative reported cases to forecast future trends in reported cases.
The Sub-epidemic Model – United States captures a diversity of epidemic trajectories including stable incidence patterns with sustained or damped oscillations. Researchers in the School of Public Health fit the model to cumulative reported cases to forecast future trends in reported cases.
The Sub-epidemic Model – United States captures a diversity of epidemic trajectories including stable incidence patterns with sustained or damped oscillations. Researchers in the School of Public Health fit the model to cumulative reported deaths to forecast future trends in reported deaths.
