Enjoying Spring Activities During the COVID-19 Pandemic
Spring is a wonderful season to get outside and enjoy the warmer weather. As more individuals get vaccinated, engaging in activities outside of the home will become safer.
Spring is a wonderful season to get outside and enjoy the warmer weather. As more individuals get vaccinated, engaging in activities outside of the home will become safer.
Help your local public health officials and emergency managers to return to their “normal” life of preparing and protecting your community for the next event.
In an effort to combat COVID-19, vaccinations are underway in the United States. IEM’s COVID-19 vaccination models shed some light on this challenge.
IEM worked diligently to innovate tools and systems to track and predict the spread of COVID-19 and provide relief to individuals seeking assistance.
Remote work during the pandemic has raised concerns over how data is used and what practices can be implemented to protect it.
Part 2 of Dr. Rashid Chotani’s presentation on hospital preparedness for seasonal influenza patients and an increase in COVID-19 patients and vaccine access and the anti-vax movement.
The 2020-2021 flu season is expected to be particularly strenuous on health care facilities as it is compounded with the current COVID-19 pandemic. This year it is very important to get the flu shot to prevent the spread of the virus and to minimize the additional strain on local health care systems.
The U.S. Department of Health and Human Services’ (HHS) Crimson Contagion Exercise (a pandemic influenza scenario) required synthetic data on pandemic cases for the players to be able to analyze epidemiological and contract tracing efforts.
IEM’s COVID-19 Projection Dashboard integrates AI and GIS technologies to forecast or predict new coronavirus cases across the country by applying AI and machine learning to confirmed coronavirus cases at the state and county level.
Throughout the pandemic, COVID-19 predictive models have come under criticism for conflicting predictions that have caused some to believe that all models are wrong; however, some models are useful.
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