ABSTRACT
ObjectivesTo examine whether and to what extent hospital strain will increase the risk of death from Covid-19. DesignRetrospective cohort study. SettingEngland. ParticipantsData on all the 147,276 Covid-19 deaths and 601,084 hospitalized Covid-19 patients in England during the period between 9 April 2020 and 11 March 2022 were extracted on a daily basis from the UK Health Security Agency. Main outcome measuresThe number of Covid-19 patients currently in hospitals was used as the measure of hospital strain. Daily case fatality was estimated as the measure of risk of death from Covid-19. The study was divided into 4 periods, which represented largely the wild, Alpha, Delta and Omicron waves. Weighted linear regression models were used to assess the association between hospital strain and Covid-19 fatality with adjustment for potential confounders including vaccination score, hospital admission rate, percentage of deaths outside hospitals, study period and interaction between patients currently in hospitals and study period. ResultsThe daily case fatality from Covid-19 increased linearly as the number of patients currently in hospitals increased in the 4 study periods except the Omicron wave. After adjusting for potential confounders, an increase in 1000 patients currently in hospitals was associated with a relative increase of 6.3% (95% CI: 5.9%~6.8%), 1.4% (95% CI: 1.3% ~ 1.5%) and 12.7% (95% CI: 10.8%~14.7%) in daily case fatality during study periods 1, 2 and 3 respectively. Compared with the lowest number of patients currently in hospitals, the highest number was associated with a relative increase of 188.0% (95% CI: 165.9%~211.6%), 69.9% (95% CI: 59.0%~81.8%) and 58.2% (95% CI: 35.4%~89.0%) in daily case fatality in the first 3 study periods respectively. Sensitivity analyses using the number of patients in ventilation beds as the measure of hospital strain showed similar results. ConclusionsThe risk of death from Covid-19 was linearly associated with the number of patients currently in hospitals, suggesting any (additional) effort to ease hospital strain or maintain care quality be beneficial during large outbreaks of Covid-19 and likely of other similar infectious diseases. Summary boxO_ST_ABSWhat is already known on this topicC_ST_ABS- During the Covid-19 pandemic, tremendous efforts have been made in many countries to suppress epidemic peaks and strengthen hospital services so as to avoid hospital strain with an ultimate aim to reduce the risk of death from Covid-19. - These efforts were made according to the widely held belief that hospital strain would increase the risk of Covid-19 death but good empirical evidence was largely lacking to support the hypothesis. - A few small studies showed that shortage in intensive care was associated with an increased Covid-19 fatality but strains may occur in many areas in the healthcare system besides intensive care and they may all increase the risk of death from Covid-19. - The totality of hospital strain can be approximated by the number of patients currently in hospitals but its effects on the risk of Covid-19 death has not been demonstrated. What this study adds- We found the risk of death from Covid-19 was linearly associated with the number of patients currently in hospitals before the Omicron period. - Compared with the lowest number of patients currently in hospitals in an outbreak, the highest number could be associated with a relative increase in the risk of death between 58.2% and 188.0%. - The number of patients currently in hospitals during the Omicron period was not found associated with the risk of death but there remains uncertainty if the number of patients currently in hospitals reached a level much higher than that actually occurred in England or in places other than England. How this study might affect research, practice, or policy- Facing the on-going Covid-19 pandemic and future outbreaks alike, the linear relation between hospital strain and fatality suggests importantly any (additional) effort to reduce hospital strain would be beneficial during a large Covid-19 outbreak.
Subject(s)
COVID-19 , Death , Communicable DiseasesABSTRACT
Objective: In this study, we use the time-dependent reproduction number (Rt) to comprise the COVID transmissibility across different countries.Methods: We used data from Jan 20, 2019, to Feb 29, 2020, on the number of newly confirmed cases, obtained from the reports published by the CDC, to infer the incidence of infectious over time. A two-step procedure was used to estimate the Rt. The first step used data on known index-secondary cases pairs, from publicly available case reports, to estimate the serial interval distribution. The second step estimated the Rt jointly from the incidence data and the information data in the first step. Rt was then used to simulate the epidemics across all major cities in China and typical countries worldwide. Results: Based on a total of 126 index-secondary cases pairs from 4 international regions, we estimated that the serial interval for SARS-2-CoV was 4.18 (IQR 1.92 – 6.65) days. Domestically, Rt of China, Hubei province, Wuhan had fallen below 1.0 on 9 Feb, 10 Feb and 13 Feb (Rt were 0.99±0.02, 0.99±0.02 and 0.96±0.02), respectively. Internationally, as of 26 Feb, statistically significant periods of COVID spread (Rt >1) were identified for most regions, except for Singapore (Rt was 0.92±0.17).Conclusions: The epidemic in China has been well controlled, but the worldwide pandemic has not been well controlled. Worldwide preparedness and vulnerability against COVID-19 should be regarded with more care.
Subject(s)
COVID-19ABSTRACT
Background: On the present trajectory, COVID is inevitably becoming a global epidemic, leading to concerns regarding the pandemic potential in China and other countries. Objective: In this study, we use the time-dependent reproduction number (Rt) to comprise the COVID transmissibility across different countries. Methods: We used data from Jan 20, 2019, to Feb 29, 2020, on the number of newly confirmed cases, obtained from the reports published by the CDC, to infer the incidence of infectious over time. A two-step procedure was used to estimate the Rt. The first step used data on known index-secondary cases pairs, from publicly available case reports, to estimate the serial interval distribution. The second step estimated the Rt jointly from the incidence data and the information data in the first step. Rt was then used to simulate the epidemics across all major cities in China and typical countries worldwide. Results: Based on a total of 126 index-secondary cases pairs from 4 international regions, we estimated that the serial interval for SARS-2-CoV was 4.18 (IQR 1.92 - 6.65) days. Domestically, Rt of China, Hubei province, Wuhan had fallen below 1.0 on 9 Feb, 10 Feb and 13 Feb (Rt were 0.99 {+/-} 0.02, 0.99 {+/-} 0.02 and 0.96 {+/-} 0.02), respectively. Internationally, as of 26 Feb, statistically significant periods of COVID spread (Rt >1) were identified for most regions, except for Singapore (Rt was 0.92 {+/-} 0.17). Conclusions: The epidemic in China has been well controlled, but the worldwide pandemic has not been well controlled. Worldwide preparedness and vulnerability against COVID-19 should be regarded with more care.