State-level RN density and age-adjusted covid-19 mortality: Contribution of the nursing workforce to pandemic response
Louis, R.; Sakib, S. N.; Qinglin, P.; Parker, L. A.; Morris, J. G.
Show abstract
Nurses represent the largest segment of the United States healthcare workforce and played an instrumental role in the countrys response to the COVID-19 pandemic. Yet, little attention has been given to the contribution of this component of the U.S. medical personnel in the nations ability to face public health crisis. We present a cross-sectional, ecological analysis using cumulative annual reports from different national databases to assess the relationship between registered nurse (RN) density at a state level and age-adjusted COVID-19 mortality within the state, using data from 2021 when mortality rates were peaking in the U.S. At the state level, an increase of 1,000 RNs per 100,000 people, was associated with an estimated 24 to 44 fewer COVID-19 deaths per 100,000 residents (B= -0.024, {beta}= -0.146, 95% CI: -0.044 to -0.003, p = .024). In this multivariate analysis including medical co-morbidities, vaccination, health insurance, and poverty level, RN density explained nearly 11% of the variability in COVID-19 mortality among states. Our findings underscore the critical role played by nurses in responding to the COVID-19 pandemic, and the importance of incorporating nursing workforce data into planning for future public health emergencies.
Matching journals
The top 5 journals account for 50% of the predicted probability mass.
Similar papers in this journal
- The COVID-19 health equity twindemic: Statewide epidemiologic trends of SARS-CoV-2 outcomes among racial minorities and in rural America 95%
- Geographic Disparities and Determinants of COVID-19 Incidence Risk in the Greater St. Louis Area, Missouri 93%
- Excess mortality associated with the COVID-19 pandemic among Californians 18–65 years of age, by occupational sector and occupation: March through October 2020 93%
Similar papers in this journal
- Protocol of a Study to Benchmark Occupational Health and Safety in Japan: W2S-Ohpm Study 92%
- Spread of infection and treatment interruption among Japanese workers during the COVID-19 pandemic: a cross-sectional study 92%
- Strategies to Estimate Prevalence of SARS-CoV-2 Antibodies in a Texas Vulnerable Population: Results from Phase I of the Texas Coronavirus Antibody REsponse Survey (TX CARES) 92%
Similar papers in this journal
- Temporal Geospatial Analysis of COVID-19 Pre-infection Determinants of Risk in South Carolina 95%
- Differences in COVID-19 Risk by Race and County-Level Social Determinants of Health Among Veterans 94%
- Identification of Vulnerable Populations and Areas at Higher Risk of COVID-19 Related Mortality in the U.S. 93%
Similar papers in this journal
- Differential Effects of Race/Ethnicity and Social Vulnerability on COVID-19 Positivity, Hospitalization, and Death in the San Francisco Bay Area 95%
- Racial/Ethnic, Biomedical, and Sociodemographic Risk Factors for COVID-19 Positivity and Hospitalization in the San Francisco Bay Area 94%
- Cause of Death by Race and Ethnicity in Minnesota Before and During the COVID-19 Pandemic, 2019-2020 94%
Similar papers in this journal
- Estimating COVID-19 Hospitalizations in the United States with surveillance data using a Bayesian Hierarchical model 92%
- Subphenotyping of COVID-19 patients at pre-admission towards anticipated severity stratification: an analysis of 778 692 Mexican patients through an age-gender unbiased meta-clustering technique 90%
- Patterns of SARS-CoV-2 testing preferences in a national cohort in the United States 90%
"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.