Hospital length of stay in a mixed Omicron and Delta epidemic in New South Wales, Australia

Abstract

Aim: To estimate the length of stay distributions of hospitalised COVID-19 cases during a mixed Omicron-Delta epidemic in New South Wales, Australia (16 Dec 2021 -- 7 Feb 2022), and compare these to estimates produced over a Delta-only epidemic in the same population (1 Jul 2021 -- 15 Dec 2022). Background: The distribution of the duration that clinical cases of COVID-19 occupy hospital beds (the `length of stay') is a key factor in determining how incident caseloads translate into health system burden as measured through ward and ICU occupancy. Results: Using data on the hospital stays of 19,574 individuals, we performed a competing-risk survival analysis of COVID-19 clinical progression. During the mixed Omicron-Delta epidemic, we found that the mean length of stay for individuals who were discharged directly from ward without an ICU stay was, for age groups 0-39, 40-69 and 70+ respectively, 2.16 (95\% CI: 2.12--2.21), 3.93 (95\% CI: 3.78--4.07) and 7.61 days (95\% CI: 7.31--8.01), compared to 3.60 (95\% CI: 3.48--3.81), 5.78 (95\% CI: 5.59--5.99) and 12.31 days (95\% CI: 11.75--12.95) across the preceding Delta epidemic (15 Jul 2021 -- 15 Dec 2021). We also considered data on the stays of individuals within the Hunter New England Local Health District, where it was reported that Omicron was the only circulating variant, and found mean ward-to-discharge length of stays of 2.05 (95\% CI: 1.80--2.30), 2.92 (95\% CI: 2.50--3.67) and 6.02 days (95\% CI: 4.91--7.01) for the same age groups.

The health impact of long COVID during the 2021-2022 Omicron wave in Australia: a quantitative burden of disease study

“…Acute COVID-19 morbidity is sub-divided into community cases, and hospitalised cases that are either ward only or include an ICU admission – approximately 8% of cases in hospital have been estimated as requiring ICU admission during the first four months of the Omicron wave. 24 Symptom duration estimates for hospitalised patients were based on findings from a New South Wales (NSW) study by Tobin et al 25 , which estimated hospital stay duration during December (at the start of the Omicron wave). These duration estimates were weighted across the three age categories presented by Tobin et al 25 (0-39 year olds, 40-69 year olds and 70+ year olds) based on the proportion hospitalised in each age group.…”

“…24 Symptom duration estimates for hospitalised patients were based on findings from a New South Wales (NSW) study by Tobin et al 25 , which estimated hospital stay duration during December (at the start of the Omicron wave). These duration estimates were weighted across the three age categories presented by Tobin et al 25 (0-39 year olds, 40-69 year olds and 70+ year olds) based on the proportion hospitalised in each age group. A percentage split of 72% mild and 28% moderate acute illness for non-hospitalised cases was based on findings by Menni et al 26 , which indicated that the odds of moderate severity illness was reduced by approximately 44% for Omicron compared to Delta infections.…”

“…The prevalence of each symptom (calculated as a risk difference in symptom frequency between COVID-19 survivors and COVID-negative controls) and duration (from 1 week post-infection for mild/moderate cases, and 4-weeks postinfection for those hospitalised), were extracted from the literature (Appendix 1). 6,[15][16][17][18][19] For each symptom, an estimate of severity, as a disability weight (DW), was taken from the GBD study. 20 Some long COVID symptoms do not have direct health states for which DWs exist in the GBD -in these cases, best estimates have been determined from related health states.…”

Modelling the adjustment of COVID-19 response and exit from dynamic zero-COVID in China

“…As a best-case scenario, we use 100% and 200% of the maximum number of hospital beds designated for COVID-19 patients in Hong Kong in May 2022 (which correspond to its baseline/regular and surged capacity, respectively) as the benchmarks for health system capacity constraints across mainland China during reopening (Table S3). Assuming an average hospitalisation duration of 8 days 15,16 , these constraints correspond to a daily incidence of 1.1 and 2.2 hospitalisations per 10,000 population, which also correspond to 21-42% of hospital beds in secondary/tertiary hospitals and 15-25% of all the existing hospital beds across all Chinese provinces (Figure S2, Table S5 and Table S6).…”

Epidemiologic and economic modelling of optimal COVID-19 policy: public health and social measures, masks and vaccines in Victoria, Australia

“…10 Morbidity was calculated separately for high and low virulence variant infections by altering the duration of illness and length of hospital stay. 11,12 Morbidity from long COVID was estimated based on reported symptoms and their prevalence and duration (by age, severity of infection, vaccination status, and viral variant), each assigned a disability weight from the GBD study. 10,13-16 For each COVID-19 death we estimated future HALY loss (discounted at 3%), assuming people dying of COVID-19 have twice the mortality and 1.5 times the morbidity of the average person of the same sex and age (Appendix section 4).…”