Featuring forecasts of 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.
New forecasts will be published Wednesday, June 10 by 9 p.m. ET.
Click on the plus (+) symbol to open the section and view the forecast.
CANADA
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.
FRANCE
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.
GERMANY
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.
ITALY
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 NETHERLANDS
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.
SPAIN
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.
UNITED KINGDOM
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.
UNITED STATES
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.
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 – 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.
COLLABORATIVE RESEARCH: CORONAVIRUS GENOMIC ANALYSIS
To understand the transmission dynamics and evolutionary patterns of the SARS-CoV-2 virus, researchers in the School of Public Health and department of Computer Science in the College of Arts & Sciences use the methods of phylogenetics.
The research webpage features plots of two networks and situation reports accompanying each update.
Learn more: publichealth.gsu.edu/genomic-coronavirus
SCHOLARLY/ACADEMIC RESOURCES
A dynamic modeling tool for illustrating the impact of population-wide interventions on the healthcare demand from COVID19
English version: A dynamic modeling tool for illustrating the impact of population-wide interventions on the healthcare demand from COVID19
Spanish version: A dynamic modeling tool for illustrating the impact of population-wide interventions on the healthcare demand from COVID19
MEDIA/NEWS REPORTS
The New York Times: Can the N.F.L. really return to normal this fall?
The Wall Street Journal: New coronavirus outbreak in China prompts limited lockdown
CNN: A month after reopening, Georgia coronavirus cases continue slow and steady
BBC: Horizon’s Coronavirus Special, Part 2; segment starts at 9:27 and ends at 10:40
Georgia State News: A Perfect Storm: Q&A with Dr. Gerardo Chowell
Politico: Trump’s plans to reopen the country face major obstacles
CBS46 Atlanta: Digital misinformation on coronavirus creating dangerous situation, researchers say
Georgia State Alumni Association: Tracking coronavirus and how we move forward
NBC News: Official coronavirus death tolls are only an estimate, and that is a problem
Inverse: Why scientists say we may be “intermittent social distancing” until 2022
WSB-TV Atlanta: Social media being used as a tool to track coronavirus
NBC News: In Georgia and elsewhere in South, governors begin lifting coronavirus
NPR: Why ‘death rates’ from coronavirus can be deceiving
CBS46 Atlanta: Medical model projects 82,000 coronavirus deaths by August
Georgia State News: Scientists are joining the race to unravel how the new coronavirus operates – and find effective treatments
The New York Times: Infected but feeling fine – the unwitting coronavirus spreaders
The New York Times: Can the Olympics take place in July (this July)?
Daily Mail (UK): Cuomo is to launch an anti-body test to identify who has recovered from coronavirus
Nature: Covert coronavirus infections could be seeding new outbreaks
The Hill: SARS-CoV-2 in people and the environment: What’s coming?
BuzzFeed News: What is social distancing? How staying away from others can help stop the coronavirus spread
Los Angeles Times: True number of U.S. coronavirus cases is far above official tally, scientists say
Forbes: What percentage have COVID-19 coronavirus but do not know it
The Washington Post: Nigeria’s experience containing Ebola may help with coronavirus response, expert says
The Washington Post: El Salvador’s president says the country has no coronavirus cases, declares national quarantine
Georgia State: Panther Report News
STAT: Once widely criticized, the Wuhan quarantine bought the world time to prepare for COVID-19
Al Jazeera: ‘Diseases know no borders’: Cooperation key in COVID-19 response
Nature: What the cruise-ship outbreaks reveal about COVID-19
Univision News: How to protect yourself from the coronavirus living with others and in a single space
BuzzFeed News: Silent carriers are helping spread the coronavirus. Here’s what we know about them.
Medical News Today: COVID-19 – Social distancing, drugs trials offer hope
Daily Mail (UK): New York scientists develop first US blood test that can detect who has already had coronavirus and is immune
World Economic Forum: People with mild or no symptoms could be spreading COVID-19
The Dallas Morning News: Collin County cities intend to issue shelter-in-place orders, McKinney mayor says
Medical News Today: Why social distancing is key in containing the new coronavirus
Univision News: President Trump: gatherings should be limited to 10 people
Nettavisen (Norway): Professor of epidemiology: the pandemic can last one to two years
Proceso Magazine (Mexico): The brutal Chinese recipe against the coronavirus
El País (Mexico): The pandemic that everyone knew was coming and no one knew how to stop
AF Medios (Mexico): Universities develop self-diagnosis app for COVID-19
Complex: Tracking when the NFL, NBA, MLB, and more sports will return to action
BuzzFeed News: Here’s what public health experts think our pandemic summer will look like
The Wall Street Journal: How far can the coronavirus travel in the air?
BuzzFeed News: Here’s what public health experts have to say about using public restrooms during the coronavirus pandemic
Harvard Business Review: A plan to safely reopen the U.S. despite inadequate testing
BuzzFeed News: Thinking about expanding your quarantine circle? Here’s what public health experts say
BuzzFeed News: The CDC released new death rate estimates for the coronavirus. Many scientists say they’re too low.
FEATURED RESEARCHERS
Dr. Gerardo Chowell
Dr. Gerardo Chowell is professor of mathematical epidemiology and chair of the Department of Population Health Sciences. He also holds an external affiliation as a Senior Research Fellow at the Division of International Epidemiology and Population Studies at the Fogarty International Center, National Institutes of Health.
Before joining Georgia State University’s School of Public Health, Dr. Chowell was an associate professor in the School of Human Evolution and Social Change at Arizona State University.
Learn more about Dr. Gerardo Chowell
Contact: gchowell@gsu.edu
Kimberlyn Roosa
Kimberlyn Roosa is currently a doctoral student and graduate research assistant in the Department of Population Health Sciences.
As a Second Century Initiative (2CI) Fellow, she focuses on research in infectious disease dynamics and mathematical epidemiology, which allows her to combine a strong quantitative background with her passion for public health.
Kimberlyn is interested in continuing this research while working to make mathematical methods more accessible to other public health researchers.
Contact: kroosa1@student.gsu.edu
Amna Tariq
Amna Tariq is a doctoral student and graduate research assistant in the Department of Population Health Sciences. She is a Second Century Initiative (2CI) Fellow under the big data cluster. Prior to embarking on the doctoral journey, Amna completed a Bachelors in Dental Surgery (Pakistan) in 2013 and a Masters of Public Health from Georgia State University in 2017.
Her research interests include mathematical modeling of infectious diseases and exploring quantitative methods for analyzing disease outbreaks to better understand and predict the ongoing and upcoming infectious disease epidemics.
Contact: atariq1@student.gsu.edu
Yiseul Lee
Yiseul Lee is a researcher in the Department of Population of Health Sciences.
Yiseul graduated in 2019 with a Masters of Public Health with a concentration in epidemiology from Georgia State University.
She is interested in data analysis and infectious disease modeling.
Contact: ylee97@gsu.edu