Outcomes of SARS-CoV-2 Omicron Variant Infections Compared With Seasonal Influenza and Respiratory Syncytial Virus Infections in Adults Attending the Emergency Department: A Multicenter Cohort Study

Near real-time severe acute respiratory illness surveillance characterising influenza and COVID-19 epidemiology in hospitalised adults, 2021-22

OBJECTIVES

We report the findings of a novel enhanced syndromic surveillance that characterised influenza- and SARS-CoV-2-associated severe acute respiratory illness (SARI) in the 2021/2022 winter season.

METHODS

Prospective cohort study of adults admitted to the Queen Elizabeth University Hospital, Glasgow, with a severe acute respiratory illness. Patient demographics, clinical history, admission details, and outcomes were recorded. Data were available to Public Health Scotland (PHS) and clinicians weekly.

RESULTS

Between November 2021 and May 2022, 1063 hospitalised SARI episodes in 1037 adult patients were identified. Median age was 72.0 years, and 44.5% were male. Most (82.6%) SARI cases had ≥1 co-morbidity; chronic lung disease (50.0%) and malignancy (22.5%) were the most frequently reported. Overall, 229 (22%) and 33 (3%) SARI episodes were SARS-CoV-2 and influenza A PCR positive, respectively. 74.7%, 6.5% and 43.0% SARI episodes received antibiotics, antivirals, and steroids, respectively (54.5%, 11.0% and 51.3% among COVID-19 patients). 1.1% required mechanical ventilation and 7.8% died. Male sex, multimorbidity, frailty, respiratory rate >30, low GCS and chest X-ray consolidation were predictive of in-hospital mortality.

CONCLUSION

Near real-time hospitalised SARI syndromic surveillance characterised the evolving clinical epidemiology of SARS-CoV-2 and influenza, high antimicrobial use, and predictors of inpatient mortality among hospitalised SARI patients.

Intensive care unit-acquired infections more common in patients with COVID-19 than with influenza

Intensive care unit-acquired infections are complicating events in critically ill patients. In this study we analyzed the incidence, microbiological patterns, and outcome in patients with COVID-19 versus influenza in the intensive care unit (ICU). We included all adult patients treated with invasive mechanical ventilation due to (1) COVID-19 between January 2020 and March 2022, and (2) influenza between January 2015 and May 2023 at Sahlgrenska University Hospital, Sweden. Of the 480 participants included in the final analysis, 436 had COVID-19. The incidence rates of ICU-acquired infections were 31.6/1000 and 9.9/1000 ICU-days in the COVID-19 and influenza cohorts, respectively. Ventilator-associated lower respiratory tract infections were most common in both groups. In patients with COVID-19, corticosteroid treatment was associated with an increased risk of ICU-acquired infections and with higher 90-day mortality in case of infection. Furthermore, ICU-acquired infection was associated with a prolonged time in the ICU, with more difficult-to-treat gram-negative infections in late versus early ventilator-associated lower respiratory tract infections. Further research is needed to understand how the association between corticosteroid treatment and incidence and outcome of ICU-acquired infections varies across different patient categories.

Severity of Respiratory Syncytial Virus vs COVID-19 and Influenza Among Hospitalized US Adults

Importance

On June 21, 2023, the Centers for Disease Control and Prevention recommended the first respiratory syncytial virus (RSV) vaccines for adults aged 60 years and older using shared clinical decision-making. Understanding the severity of RSV disease in adults can help guide this clinical decision-making.

Objective

To describe disease severity among adults hospitalized with RSV and compare it with the severity of COVID-19 and influenza disease by vaccination status.

Design, Setting, and Participants

In this cohort study, adults aged 18 years and older admitted to the hospital with acute respiratory illness and laboratory-confirmed RSV, SARS-CoV-2, or influenza infection were prospectively enrolled from 25 hospitals in 20 US states from February 1, 2022, to May 31, 2023. Clinical data during each patient's hospitalization were collected using standardized forms. Data were analyzed from August to October 2023.

Exposures

RSV, SARS-CoV-2, or influenza infection.

Main Outcomes and Measures

Using multivariable logistic regression, severity of RSV disease was compared with COVID-19 and influenza severity, by COVID-19 and influenza vaccination status, for a range of clinical outcomes, including the composite of invasive mechanical ventilation (IMV) and in-hospital death.

Results

Of 7998 adults (median [IQR] age, 67 [54-78] years; 4047 [50.6%] female) included, 484 (6.1%) were hospitalized with RSV, 6422 (80.3%) were hospitalized with COVID-19, and 1092 (13.7%) were hospitalized with influenza. Among patients with RSV, 58 (12.0%) experienced IMV or death, compared with 201 of 1422 unvaccinated patients with COVID-19 (14.1%) and 458 of 5000 vaccinated patients with COVID-19 (9.2%), as well as 72 of 699 unvaccinated patients with influenza (10.3%) and 20 of 393 vaccinated patients with influenza (5.1%). In adjusted analyses, the odds of IMV or in-hospital death were not significantly different among patients hospitalized with RSV and unvaccinated patients hospitalized with COVID-19 (adjusted odds ratio [aOR], 0.82; 95% CI, 0.59-1.13; P = .22) or influenza (aOR, 1.20; 95% CI, 0.82-1.76; P = .35); however, the odds of IMV or death were significantly higher among patients hospitalized with RSV compared with vaccinated patients hospitalized with COVID-19 (aOR, 1.38; 95% CI, 1.02-1.86; P = .03) or influenza disease (aOR, 2.81; 95% CI, 1.62-4.86; P < .001).

Conclusions and Relevance

Among adults hospitalized in this US cohort during the 16 months before the first RSV vaccine recommendations, RSV disease was less common but similar in severity compared with COVID-19 or influenza disease among unvaccinated patients and more severe than COVID-19 or influenza disease among vaccinated patients for the most serious outcomes of IMV or death.

Model-based analysis of the incidence trends and transmission dynamics of COVID-19 associated with the Omicron variant in representative cities in China

BACKGROUND

In 2022, Omicron outbreaks occurred at multiple sites in China. It is of great importance to track the incidence trends and transmission dynamics of coronavirus disease 2019 (COVID-19) to guide further interventions.

METHODS

Given the population size, economic level and transport level similarities, two groups of outbreaks (Shanghai vs. Chengdu and Sanya vs. Beihai) were selected for analysis. We developed the SEAIQRD, ARIMA, and LSTM models to seek optimal modeling techniques for waves associated with the Omicron variant regarding data predictive performance and mechanism transmission dynamics, respectively. In addition, we quantitatively modeled the impacts of different combinations of more stringent interventions on the course of the epidemic through scenario analyses.

RESULTS

The best-performing LSTM model showed better prediction accuracy than the best-performing SEAIQRD and ARIMA models in most cases studied. The SEAIQRD model had an absolute advantage in exploring the transmission dynamics of the outbreaks. Regardless of the time to inflection point or the time to Rt curve below 1.0, Shanghai was later than Chengdu (day 46 vs. day 12/day 54 vs. day 14), and Sanya was later than Beihai (day 16 vs. day 12/day 20 vs. day 16). Regardless of the number of peak cases or the cumulative number of infections, Shanghai was higher than Chengdu (34,350 vs. 188/623,870 vs. 2,181), and Sanya was higher than Beihai (1,105 vs. 203/16,289 vs. 3,184). Scenario analyses suggested that upgrading control level in advance, while increasing the index decline rate and quarantine rate, were of great significance for shortening the time to peak and Rt below 1.0, as well as reducing the number of peak cases and final affected population.

CONCLUSIONS

The LSTM model has great potential for predicting the prevalence of Omicron outbreaks, whereas the SEAIQRD model is highly effective in revealing their internal transmission mechanisms. We recommended the use of joint interventions to contain the spread of the virus.