An integrated risk and epidemiological model to estimate risk-stratified COVID-19 outcomes for Los Angeles County: March 1, 2020—March 1, 2021

Abstract

The objective of this study was to use available data on the prevalence of COVID-19 risk factors in subpopulations and epidemic dynamics at the population level to estimate probabilities of severe illness and the case and infection fatality rates (CFR and IFR) stratified across subgroups representing all combinations of the risk factors age, comorbidities, obesity, and smoking status. We focus on the first year of the epidemic in Los Angeles County (LAC) (March 1, 2020–March 1, 2021), spanning three epidemic waves. A relative risk modeling approach was developed to estimate conditional effects from available marginal data. A dynamic stochastic epidemic model was developed to produce time-varying population estimates of epidemic parameters including the transmission and infection observation rate. The epidemic and risk models were integrated to produce estimates of subpopulation-stratified probabilities of disease progression and CFR and IFR for LAC. The probabilities of disease progression and CFR and IFR were found to vary as extensively between age groups as within age categories combined with the presence of absence of other risk factors, suggesting that it is inappropriate to summarize epidemiological parameters for age categories alone, let alone the entire population. The fine-grained subpopulation-stratified estimates of COVID-19 outcomes produced in this study are useful in understanding disparities in the effect of the epidemic on different groups in LAC, and can inform analyses of targeted subpopulation-level policy interventions.

Correlates of Coronavirus Disease 2019 Inpatient Mortality at a Southern California Community Hospital With a Predominantly Hispanic/Latino Adult Population

“…Our findings generally agree with published studies and meta-analyses [ 1–21 , 25–34 ] reporting increasing age, male sex, medical comorbidities, and multiple laboratory abnormalities as COVID-19 mortality risk factors. This concurrence supports the concept of a shared set of mortality risk factors among inpatients with COVID-19 irrespective of study population origin.…”

“…Patients were hospitalized with COVID-19 at Pomona Valley Hospital Medical Center (PVHMC) between March 9, 2020 and April 30, 2021, a period corresponding with 2 initial COVID-19 surges in LAC [ 25 ]. The PVHMC is an accredited 412-bed, not-for-profit, independent, acute care community hospital providing a range of healthcare services in eastern LAC and western San Bernardino County.…”

The Effect of Socio-Demographic Factors in Health-Seeking Behaviors among Bangladeshi Residents during the First Wave of COVID-19

“…Public awareness is the prerequisite to implementing the control interventions for combatting the COVID-19 pandemic; however, such awareness is governed by an individual’s health safety practices and attitudes [ 3 , 22 ]. It is predicted from various epidemiological models that without preventive measures to contain the spread of COVID-19, the world would confront a steep rise in the number of cases [ 23 , 24 , 25 , 26 ]. These scenarios have driven numerous nations to take steps aimed at “flattening the curve” to dodge a sudden surge in COVID-19 cases.…”

Time-dependent risk of COVID-19 death with overwhelmed health-care capacity in Japan, 2020–2022

“…First, as described in many meta-analyses and other factor analysis studies on the CFR, we estimated it using a confirmed case count [38,54,[56][57][58][59][60][61][62][63][64][65][66][67][68]. Confirmatory diagnosis involves ascertainment bias; the elevated CFR during the pandemic's peak may partly be related to the lower frequency of diagnosis, whereas IFR and CFR diverged significantly [55,[69][70][71]. Second, the confirmed deaths could have been smaller than the actual total number of deaths.…”