Objective
The purpose of this study was to employ simulations to model the probability of mortality from COVID-19 (i.e., coronavirus) for older adults in the United States (U.S.) given at best and at worst cases.
Methods
This study first examined current epidemiological reports to better understand the risk of mortality from COVID-19. Past epidemiological studies from severe acute respiratory syndrome or SARS were also examined given similar virology. Next, at best and at worst mortality cases were considered with the goal of estimating the probability of mortality. To accomplish this for the general population, microdata from the National Health Interview Survey pooled sample (2016, 2017, and 2018 IPUMS NHIS with a sample of 34,881 adults at least 60 years of age) were utilized. Primary measures included age and health status (diabetes, body mass index, and hypertension). A logit regression with 100,000 simulations was employed to derive the estimates and probabilities.
Results
Age exhibited a positive association for the probability of death with an odds ratio (OR) of 1.22 (p<0.05, 1.05-1.42, 95% C.I.). A positive association was also found for obesity (OR 1.03, p<0.01, 1.02-1.04 95% C.I.) and hypertension (OR 1.36, p<0.01, 1.09-1.66 95% C.I.) for the at best case. Diabetes was significant but only for the at best case.
Discussion
This study found mortality increased with age and was notable for the 74-79 age group for the at best case and the 70-79 age group of the at worst case. Obesity was also important and suggested a higher risk for mortality. Hypertension also exhibited greater risk but the increase was minimal. Given the volume of information and misinformation, these findings can be applied by health professionals, gerontologists, social workers, and local policymakers to better inform older adults about mortality risks and, in the process, re-establish public trust.
Public health professionals can use these results to better understand why certain interventions have not shown promise. Equally important, healthcare workers can use this research to evaluate which type of treatment plans may delay institutionalization and improve the quality of life for older adults. Implications for rehabilitation With on-going global aging, understanding the association between disability and institutional entry is important in devising successful rehabilitation interventions. Semi-nonparametric is preferred to probit and shows ambulatory and cognitive impairments present high risk for institutional entry (long-term care). Informal caregiving and home-based care require further examination as forms of rehabilitation/therapy for certain types of disabilities.
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