A longitudinal environmental surveillance study for SARS-CoV-2 from the emergency department of a teaching hospital in Hong Kong.

BACKGROUND: Understanding factors associated with SARS-CoV-2 exposure risk in the hospital setting may help improve infection control measures for prevention. AIM: To monitor SARS-CoV-2 exposure risk among healthcare workers and to identify risk factors associated with SARS-CoV-2 detection. METHODS: Surface and air samples were collected longitudinally over 14 months spanning 2020-2022 at the Emergency Department (ED) of a teaching hospital in Hong Kong. SARS-CoV-2 viral RNA was detected by real-time reverse-transcription polymerase chain reaction. Ecological factors associated with SARS-CoV-2 detection were analysed by logistic regression. A sero-epidemiological study was conducted in January-April 2021 to monitor SARS-CoV-2 seroprevalence. A questionnaire was used to collect information on job nature and use of personal protective equipment (PPE) of the participants. FINDINGS: SARS-CoV-2 RNA was detected at low frequencies from surfaces (0.7%, N = 2562) and air samples (1.6%, N = 128). Crowding was identified as the main risk factor, as weekly ED attendance (OR = 1.002, P=0.04) and sampling after peak-hours of ED attendance (OR = 5.216, P=0.03) were associated with the detection of SARS-CoV-2 viral RNA from surfaces. The low exposure risk was corroborated by the zero seropositive rate among 281 participants by April 2021. CONCLUSION: Crowding may introduce SARS-CoV-2 into the ED through increased attendances. Multiple factors may have contributed to the low contamination of SARS-CoV-2 in the ED, including hospital infection control measures for screening ED attendees, high PPE compliance among healthcare workers, and various public health and social measures implemented to reduce community transmission in Hong Kong where a dynamic zero COVID-19 policy was adopted.

Prediction of upcoming global infection burden of influenza seasons after relaxation of public health and social measures during the COVID-19 pandemic: a modelling study

Background The transmission dynamics of influenza were affected by public health and social measures (PHSMs) implemented globally since early 2020 to mitigate the COVID-19 pandemic. We aimed to assess the effect of COVID-19 PHSMs on the transmissibility of influenza viruses and to predict upcoming influenza epidemics. Methods For this modelling study, we used surveillance data on influenza virus activity for 11 different locations and countries in 2017-22. We implemented a data-driven mechanistic predictive modelling framework to predict future influenza seasons on the basis of pre-COVID-19 dynamics and the effect of PHSMs during the COVID-19 pandemic. We simulated the potential excess burden of upcoming influenza epidemics in terms of fold rise in peak magnitude and epidemic size compared with pre-COVID-19 levels. We also examined how a proactive influenza vaccination programme could mitigate this effect. Findings We estimated that COVID-19 PHSMs reduced influenza transmissibility by a maximum of 17.3% (95% CI 13.3-21.4) to 40.6% (35.2-45.9) and attack rate by 5.1% (1.5-7.2) to 24.8% (20.8-27.5) in the 2019-20 influenza season. We estimated a 10-60% increase in the population susceptibility for influenza, which might lead to a maximum of 1-5-fold rise in peak magnitude and 1-4-fold rise in epidemic size for the upcoming 2022-23 influenza season across locations, with a significantly higher fold rise in Singapore and Taiwan. The infection burden could be mitigated by additional proactive one-off influenza vaccination programmes. Interpretation Our results suggest the potential for substantial increases in infection burden in upcoming influenza seasons across the globe. Strengthening influenza vaccination programmes is the best preventive measure to reduce the effect of influenza virus infections in the community. Copyright (C) 2022 The Author(s). Published by Elsevier Ltd.

Hospitalizations and mortality during the first year of the COVID-19 pandemic in Hong Kong, China: An observational study

Background: Hong Kong followed a strict COVID-19 elimination strategy in 2020. We estimated the impact of the COVID-19 pandemic responses on all-cause and cause-specific hospitalizations and deaths in 2020. Methods: Interrupted time-series analysis using negative binomial regression accounting for seasonality and long-term trend was used on weekly 2010–2020 data to estimate the change in hospitalization risk and excess mortality occurring both within and out of hospitals. Findings: In 2020, as compared to a 2010–2019 baseline, we observed an overall reduction in all-cause hospitalizations, and a concurrent increase in deaths. The overall hospitalization reduction (per 100,000 population) was 4809 (95% CI: 4692, 4926) in 2020, with respiratory diseases (632, 95% CI: 607, 658) and cardiovascular diseases (275, 95% CI: 264, 286) contributing most. The overall excess mortality (per 100,000 population) was 25 (95% CI: 23, 27) in 2020, mostly among individuals with pre-existing cardiovascular diseases (12, 95% CI: 11, 13). A reduction in excess in-hospital mortality (−10 per 100,000, 95% CI: −12, −8) was accompanied by an increase in excess out-of-hospital mortality (32, 95% CI: 29, 34). Interpretation: The COVID-19 pandemic might have caused indirect impact on population morbidity and mortality likely through changed healthcare seeking particularly in youngest and oldest individuals and those with cardiovascular diseases. Better healthcare planning is needed during public health emergencies with disruptions in healthcare services. Funding: Health and Medical Research Fund, Collaborative Research Fund, AIR@InnoHK and RGC Senior Research Fellow Scheme, Hong Kong. © 2022 The Authors

Local Surveillance of the COVID-19 Outbreak

Given the worldwide pandemic of the novel coronavirus disease 2019 (COVID-19) and its continuing threat brought by the emergence of virus variants, there are great demands for accurate surveillance and monitoring of outbreaks. A valuable metric for assessing the current risk posed by an outbreak is the time-varying reproduction number ((Formula presented.)). Several methods have been proposed to estimate (Formula presented.) using different types of data. We developed a new tool that integrated two commonly used approaches into a unified and user-friendly platform for the estimation of time-varying reproduction numbers. This tool allows users to perform simulations and yield real-time tracking of local epidemic of COVID-19 with an R package. Copyright © 2022 Liu, Xu, Bai, Xu, Lau, Cowling and Du.

RiskEstim: A Software Package to Quantify COVID-19 Importation Risk

We present an R package developed to quantify coronavirus disease 2019 (COVID-19) importation risk. Quantifying and visualizing the importation risk of COVID-19 from inbound travelers is urgent and imperative to trigger public health responses, especially in the early stages of the COVID-19 pandemic and emergence of new SARS-CoV-2 variants. We provide a general modeling framework to estimate COVID-19 importation risk using estimated pre-symptomatic prevalence of infection and air traffic data from the multi-origin places. We use Hong Kong as a case study to illustrate how our modeling framework can estimate the COVID-19 importation risk into Hong Kong from cities in Mainland China in real time. This R package can be used as a complementary component of the pandemic surveillance system to monitor spread in the next pandemic.

COVID-19 Importation Risk From Olympic Athletes Prior to the Tokyo 2020 Olympics

The COVID-19 pandemic delayed the Tokyo 2020 Olympics for 1 year and sparked an unprecedented outbreak in Japan in early July 2021 due to the relaxation of social distancing measures for foreign arrivals. Approximately 11,000 athletes from 205 countries would gather at the Tokyo Olympics held from July 23 through August 8, 2021. Based on the prevalence of infection in different source locations and athlete numbers, we estimated that seven countries would introduce least one infection of COVID-19 to Tokyo and at most eleven unidentified infections after the three requested COVID-19 tests.</p>

The race between contact tracing and transmission: A framework for resource allocation during an emerging pathogen epidemic

B Background: b The epidemics of severe acute respiratory syndrome (SARS) in Hong Kong generates the need to evaluate the effectiveness of control measures. B Methods and materials: b An individual-based mathematical model was developed alongside a resource-constrained contact tracing process for SARS outbreak. B Conclusion: b An improved understanding of the transmission dynamics of the SARS outbreak under different scenarios of contact tracing approach helps design the optimal control strategies with the given resources to control new emerging disease in the future. [Extracted from the article] Copyright of International Journal of Infectious Diseases is the property of Elsevier B.V. and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Case Fatality Risk of the First Pandemic Wave of Coronavirus Disease 2019 (COVID-19) in China

BACKGROUND: To assess the case fatality risk (CFR) of COVID-19 in mainland China, stratified by region and clinical category, and estimate key time-to-event intervals. METHODS: We collected individual information and aggregated data on COVID-19 cases from publicly available official sources from 29 December 2019 to 17 April 2020. We accounted for right-censoring to estimate the CFR and explored the risk factors for mortality. We fitted Weibull, gamma, and log-normal distributions to time-to-event data using maximum-likelihood estimation. RESULTS: We analyzed 82 719 laboratory-confirmed cases reported in mainland China, including 4632 deaths and 77 029 discharges. The estimated CFR was 5.65% (95% confidence interval [CI], 5.50-5.81%) nationally, with the highest estimate in Wuhan (7.71%) and lowest in provinces outside Hubei (0.86%). The fatality risk among critical patients was 3.6 times that of all patients and 0.8-10.3-fold higher than that of mild-to-severe patients. Older age (odds ratio [OR], 1.14 per year;95% CI, 1.11-1.16) and being male (OR, 1.83;95% CI, 1.10-3.04) were risk factors for mortality. The times from symptom onset to first healthcare consultation, to laboratory confirmation, and to hospitalization were consistently longer for deceased patients than for those who recovered. CONCLUSIONS: Our CFR estimates based on laboratory-confirmed cases ascertained in mainland China suggest that COVID-19 is more severe than the 2009 H1N1 influenza pandemic in hospitalized patients, particularly in Wuhan. Our study provides a comprehensive picture of the severity of the first wave of the pandemic in China. Our estimates can help inform models and the global response to COVID-19.

Coronaviruses

Coronaviruses of humans were first identified more than 60 years ago from individuals with respiratory infections, mainly mild. Two different viruses, 229E and OC43 were initially recognized. Because of difficulty in isolating them using standard techniques, many of the early studies of their occurrence were seroepidemiologic. They were confirmed to be worldwide in distribution, and, in the North Temperate Zone, mainly occurring in the winter season. With the development of the reverse transcriptase polymerase chain reaction (PCR) technique, two additional distinct viruses have been identified, HKU1 and NL63. The four viruses have now been recognized as important in the etiology of common respiratory infections, second only to the rhinoviruses.In 2002, a previously unrecognized betacoronavirus emerged from a zoonotic reservoir in Southern China and spread during the following year to several major cities of the world. The resulting illness was termed Severe Acute Respiratory Syndrome (SARS) because of its potential lethality. More than 8,000 probable cases were reported during 2003, mainly from Hong Kong and mainland China, producing social and economic disruption in those areas affected. A constant feature of the outbreak was the importance of nosocomial spread. In spite of an estimated basic reproductive number higher than influenza, the outbreak was ended, in large part because of control of in-hospital transmission. In 2012, another betacoronavirus has emerged in the Arabian peninsula which is producing a somewhat similar illness, termed Middle East Respiratory Syndrome (MERS), also marked by extensive nosocomial transmission. The outcome of this emergence is currently unknown. FAU - Monto, Arnold S.

Short- and potential long-term adverse health outcomes of COVID-19: a rapid review.

The coronavirus disease 2019 (COVID-19) pandemic has resulted in millions of patients infected worldwide and indirectly affecting even more individuals through disruption of daily living. Long-term adverse outcomes have been reported with similar diseases from other coronaviruses, namely Middle East Respiratory Syndrome (MERS) and Severe Acute Respiratory Syndrome (SARS). Emerging evidence suggests that COVID-19 adversely affects different systems in the human body. This review summarizes the current evidence on the short-term adverse health outcomes and assesses the risk of potential long-term adverse outcomes of COVID-19. Major adverse outcomes were found to affect different body systems: immune system (including but not limited to Guillain-Barré syndrome and paediatric inflammatory multisystem syndrome), respiratory system (lung fibrosis and pulmonary thromboembolism), cardiovascular system (cardiomyopathy and coagulopathy), neurological system (sensory dysfunction and stroke), as well as cutaneous and gastrointestinal manifestations, impaired hepatic and renal function. Mental health in patients with COVID-19 was also found to be adversely affected. The burden of caring for COVID-19 survivors is likely to be huge. Therefore, it is important for policy makers to develop comprehensive strategies in providing resources and capacity in the healthcare system. Future epidemiological studies are needed to further investigate the long-term impact on COVID-19 survivors.

Ecologic association between influenza and COVID-19 mortality rates in European countries.

Ecologic studies investigating COVID-19 mortality determinants, used to make predictions and design public health control measures, generally focused on population-based variable counterparts of individual-based risk factors. Influenza is not causally associated with COVID-19, but shares population-based determinants, such as similar incidence/mortality trends, transmission patterns, efficacy of non-pharmaceutical interventions, comorbidities and underdiagnosis. We investigated the ecologic association between influenza mortality rates and COVID-19 mortality rates in the European context. We considered the 3-year average influenza (2014-2016) and COVID-19 (31 May 2020) crude mortality rates in 34 countries using EUROSTAT and ECDC databases and performed correlation and regression analyses. The two variables - log transformed, showed significant Spearman's correlation ρ = 0.439 (P = 0.01), and regression coefficients, b = 0.743 (95% confidence interval, 0.272-1.214; R2 = 0.244; P = 0.003), b = 0.472 (95% confidence interval, 0.067-0.878; R2 = 0.549; P = 0.02), unadjusted and adjusted for confounders (population size and cardiovascular disease mortality), respectively. Common significant determinants of both COVID-19 and influenza mortality rates were life expectancy, influenza vaccination in the elderly (direct associations), number of hospital beds per population unit and crude cardiovascular disease mortality rate (inverse associations). This analysis suggests that influenza mortality rates were independently associated with COVID-19 mortality rates in Europe, with implications for public health preparedness, and implies preliminary undetected SARS-CoV-2 spread in Europe.