How Many Adults Are at Risk of Serious Illness If Infected with Coronavirus? Updated Data April 23, 2020 Issue Brief About four in ten adults (37.6%) ages 18 and older in the U.S. (92.6 million people) have a higher risk of developing serious illness if they become infected with the novel coronavirus, due to their older age (65 and older) or health condition. The share who have a higher risk varies across the country. An estimated 5.1 million of these adults are uninsured.
Urban and Rural Differences in Coronavirus Pandemic Preparedness April 23, 2020 Issue Brief The coronavirus outbreak has hit densely populated urban areas of the United States first and hardest. Some health systems have experienced surges of patients, raising concerns that there are not enough hospital beds, staffing, and equipment. The novel coronavirus was slower to spread to rural areas in the U.S., but…
COVID-19 and Workers at Risk: Examining the Long-Term Care Workforce April 23, 2020 Issue Brief The highly transmissible nature of the coronavirus combined with the congregate nature of long-term care facility settings and the close and personal contact that many long-term care workers have with patients puts them at elevated risk of infection. This analysis focuses on the characteristics of the 4.5 million people who work in long-term care settings, based on the 2018 American Community Survey.
KFF Analysis: Number of Coronavirus Cases, Distribution of $30B in CARES Act funding and Medicare Advantage Penetration by State April 22, 2020 Fact Sheet Number of Coronavirus Cases, Distribution of $30B in CARES Act funding and Medicare Advantage Penetration by State State Number of COVID-19 Cases on April 21, 2020 Percent of Total COVID-19 Cases First Distribution of CARES Act Payments Percent of Total Money Distributed Percent of Medicare Beneficiaries in Medicare Advantage, 2020…
The National Disaster Medical System (NDMS) and the COVID-19 Pandemic April 22, 2020 Issue Brief This explainer describes the National Disaster Medical System (NDMS), explores how it has been used in the past, and assesses how it is already being used or has been proposed to be used to fill gaps in the current response to the COVID-19 pandemic.
Growing Data Underscore that Communities of Color are Being Harder Hit by COVID-19 April 21, 2020 Blog A growing number of states are reporting racial and ethnic data for coronavirus cases and deaths. These data suggest that the virus is having disproportionate effects on communities of color.
Addressing the Justice-Involved Population in Coronavirus Response Efforts April 20, 2020 Issue Brief Addressing health care needs of people moving into and out of the criminal justice system and staff who work them is an important component of coronavirus response efforts and protecting and promoting public health within the communities in which correctional facilities are located. This brief provides data on spread of coronavirus within correctional facilities, discusses the health risks for the justice-involved population and the staff who work with them, identifies the role Medicaid can play in response efforts for justice-involved individuals, and highlights other steps correctional systems can take to mitigate risk of coronavirus for the justice-involved population and promote public health.
This Week in Coronavirus: April 10 to April 17 April 17, 2020 Blog Every Friday we’ll recap our new policy analysis, polling, and updates on coronavirus from the past week.
What Testing Capacity Do We Need? April 17, 2020 Blog This post looks at potential benchmarks for estimating the number of coronavirus tests needed in the United States and compares them to current national, and state level, testing levels.
COVID-19 Models: Can They Tell Us What We Want to Know? April 16, 2020 Blog This blog gives a primer on epidemiological models for Covid-19 (coronavirus). It describes the uses and the types of models used, then lists a number of examples of different types of models and some key findings. The post also describes the limitations and assumptions related to these models, and how to use the information they provide more effectively.