Multifaceted strategies for the control of COVID-19 outbreaks in long-term care facilities in Ontario, Canada

Changes in End-of-Life Symptom Management Prescribing among Long-Term Care Residents during COVID-19

OBJECTIVE

To examine changes in the prescribing of end-of-life symptom management medications in long-term care (LTC) homes during the COVID-19 pandemic.

DESIGN

Retrospective cohort study using routinely collected health administrative data in Ontario, Canada.

SETTING AND PARTICIPANTS

We included all individuals who died in LTC homes between January 1, 2017, and March 31, 2021. We separated the study into 2 periods: before COVID-19 (January 1, 2017, to March 17, 2020) and during COVID-19 (March 18, 2020, to March 31, 2021).

METHODS

For each LTC home, we measured the percentage of residents who died before and during COVID-19 who had a subcutaneous symptom management medication prescription in their last 14 days of life. We grouped LTC homes into quintiles based on their mean prescribing rates before COVID-19, and examined changes in prescribing during COVID-19 and COVID-19 outcomes across quintiles.

RESULTS

We captured 75,438 LTC residents who died in Ontario's 626 LTC homes during the entire study period, with 19,522 (25.9%) dying during COVID-19. The mean prescribing rate during COVID-19 ranged from 46.9% to 79.4% between the lowest and highest prescribing quintiles. During COVID-19, the mean prescribing rate in the lowest prescribing quintile increased by 9.6% compared to before COVID-19. Compared to LTC homes in the highest prescribing quintile, homes in the lowest prescribing quintile experienced the highest proportion of COVID-19 outbreaks (73.4% vs 50.0%), the largest mean outbreak intensity (0.27 vs 0.09 cases/bed), the highest mean total days with a COVID-19 outbreak (72.7 vs 24.2 days), and the greatest proportion of decedents who were transferred and died outside of LTC (22.1% vs 8.6%).

CONCLUSIONS AND IMPLICATIONS

LTC homes in Ontario had wide variations in the prescribing rates of end-of-life symptom management medications before and during COVID-19. Homes in the lower prescribing quintiles had more COVID-19 cases per bed and days spent in an outbreak.

Implementation of the Dementia Isolation Toolkit in long-term care improves awareness but does not reduce moral distress amongst healthcare providers

BACKGROUND

Healthcare providers may experience moral distress when they are unable to take the ethically or morally appropriate action due to real or perceived constraints in delivering care, and this psychological stressor can negatively impact their mental health, leading to burnout and compassion fatigue. This study describes healthcare providers experiences of moral distress working in long-term care settings during the COVID-19 pandemic and measures self-reported levels of moral distress pre- and post-implementation of the Dementia Isolation Toolkit (DIT), a person-centred care intervention designed for use by healthcare providers to alleviate moral distress.

METHODS

Subjective levels of moral distress amongst providers (e.g., managerial, administrative, and front-line employees) working in three long-term care homes was measured pre- and post-implementation of the DIT using the Moral Distress in Dementia Care Survey and semi-structured interviews. Interviews explored participants' experiences of moral distress in the workplace and the perceived impact of the intervention on moral distress.

RESULTS

A total of 23 providers between the three long-term care homes participated. Following implementation of the DIT, subjective levels of moral distress measured by the survey did not change. When interviewed, participants reported frequent experiences of moral distress from implementing public health directives, staff shortages, and professional burnout that remained unchanged following implementation. However, in the post-implementation interviews, participants who used the DIT reported improved self-awareness of moral distress and reductions in the experience of moral distress. Participants related this to feeling that the quality of resident care was improved by integrating principals of person-centered care and information gathered from the DIT.

CONCLUSIONS

This study highlights the prevalence and exacerbation of moral distress amongst providers during the pandemic and the myriad of systemic factors that contribute to experiences of moral distress in long-term care settings. We report divergent findings with no quantitative improvement in moral distress post-intervention, but evidence from interviews that the DIT may ease some sources of moral distress and improve the perceived quality of care delivered. This study demonstrates that an intervention to support person-centred isolation care in this setting had limited impact on overall moral distress during the COVID-19 pandemic.

Cross-sectional study to assess the impact of the COVID-19 pandemic on healthcare services and clinical admissions using statistical analysis and discovering hotspots in three regions of the Greater Toronto Area

OBJECTIVES

The COVID-19 pandemic disrupted healthcare services, leading to the cancellation of non-urgent tests, screenings and procedures, a shift towards remote consultations, stalled childhood immunisations and clinic closures which had detrimental effects across the healthcare system. This study investigates the impact of the COVID-19 pandemic on clinical admissions and healthcare quality in the Peel, York and Toronto regions within the Greater Toronto Area (GTA).

DESIGN

In a cross-sectional study, the negative impact of the pandemic on various healthcare sectors, including preventive and primary care (PPC), the emergency department (ED), alternative level of care (ALC) and imaging, procedures and surgeries is investigated. Study questions include assessing impairments caused by the COVID-19 pandemic and discovering hotspots and critical subregions that require special attention to recover. The measuring technique involves comparing the number of cases during the COVID-19 pandemic with before that, and determining the difference in percentage. Statistical analyses (Mann-Whitney U test, analysis of variance, Dunn's test) is used to evaluate sector-specific changes and inter-relationships.

SETTING

This work uses primary data which were collected by the Black Creek Community Health Centre. The study population was from three regions of GTA, namely, the city of Toronto, York and Peel. For all health sectors, the sample size was large enough to have a statistical power of 0.95 to capture 1% variation in the number of cases during the COVID-19 pandemic compared with before that.

RESULTS

All sectors experienced a significant decline in patient volume during the pandemic. ALC admissions surged in some areas, while IPS patients faced delays. Surgery waitlists increased by an average of 9.75%, and completed IPS procedures decreased in several subregions.

CONCLUSIONS

The COVID-19 pandemic had a universally negative impact on healthcare sectors across various subregions. Identification of the hardest-hit subregions in each sector can assist health officials in crafting recovery policies.

Predictive models for health outcomes due to SARS-CoV-2, including the effect of vaccination: a systematic review

BACKGROUND

The interaction between modelers and policymakers is becoming more common due to the increase in computing speed seen in recent decades. The recent pandemic caused by the SARS-CoV-2 virus was no exception. Thus, this study aims to identify and assess epidemiological mathematical models of SARS-CoV-2 applied to real-world data, including immunization for coronavirus 2019 (COVID-19).

METHODOLOGY

PubMed, JSTOR, medRxiv, LILACS, EconLit, and other databases were searched for studies employing epidemiological mathematical models of SARS-CoV-2 applied to real-world data. We summarized the information qualitatively, and each article included was assessed for bias risk using the Joanna Briggs Institute (JBI) and PROBAST checklist tool. The PROSPERO registration number is CRD42022344542.

FINDINGS

In total, 5646 articles were retrieved, of which 411 were included. Most of the information was published in 2021. The countries with the highest number of studies were the United States, Canada, China, and the United Kingdom; no studies were found in low-income countries. The SEIR model (susceptible, exposed, infectious, and recovered) was the most frequently used approach, followed by agent-based modeling. Moreover, the most commonly used software were R, Matlab, and Python, with the most recurring health outcomes being death and recovery. According to the JBI assessment, 61.4% of articles were considered to have a low risk of bias.

INTERPRETATION

The utilization of mathematical models increased following the onset of the SARS-CoV-2 pandemic. Stakeholders have begun to incorporate these analytical tools more extensively into public policy, enabling the construction of various scenarios for public health. This contribution adds value to informed decision-making. Therefore, understanding their advancements, strengths, and limitations is essential.

COVID-19 outbreaks in long-term care facilities-a nationwide population-based cohort study in Taiwan, May-July 2021

BACKGROUND/PURPOSE

Long-term care facilities (LTCFs) are high-risk settings for the novel coronavirus disease (COVID-19). The aim of the study was to describe the extent and the impacts of 2021 COVID-19 outbreaks on LTCFs in Taiwan.

METHODS

We retrospectively analyzed the data of each COVID-19 outbreak in LTCFs from May 15 to July 31, 2021 in Taiwan. We characterized the features of LTCFs with outbreaks and compared the characteristics of infected staff members and residents of the affected LTCFs.

RESULTS

COVID-19 outbreaks were reported in 16 LTCFs (0.9%). The outbreak was significantly associated with LTCFs with ≥50 beds [adjusted odds ratio (aOR), 6.3; 95%confidence interval [CI], 1.9-21.1] and location of Taipei metropolitan area (aOR, 4.6; 95%CI, 1.7-12.8). Resident cases accounted for 75.4% (203/269) of confirmed cases affected by outbreaks. The 30-day all-cause mortality was 24.2% for residents only and was significantly associated with age ≥65 years [adjusted hazard ratio (aHR, 4.3; 95%CI, 1.7-10.5)], presence of symptoms on diagnosis (aHR, 2.2; 95%CI, 1.3-3.7), and LTCF occupancy rate ≥80% (aHR, 3.0, 95%CI, 1.3-7.4).

CONCLUSION

COVID-19 outbreaks have a critical impact on residents in LTCFs owing to the advanced age and high prevalence of chronic comorbidities in this population. Multi-pronged infection control measures and mass testing are vital for mitigating COVID-19 transmission in LTCFs.

How have mathematical models contributed to understanding the transmission and control of SARS-CoV-2 in healthcare settings? A systematic search and review

Since the onset of the COVID-19 pandemic, mathematical models have been widely used to inform public health recommendations regarding COVID-19 control in healthcare settings. The objective of this study was to systematically review SARS-CoV-2 transmission models in healthcare settings, and to summarize their contributions to understanding nosocomial COVID-19. A systematic search and review of published articles indexed in PubMed was carried out. Modelling studies describing dynamic inter-individual transmission of SARS-CoV-2 in healthcare settings, published by mid-February 2022 were included. Models have mostly focused on acute-care and long-term-care facilities in high-income countries. Models have quantified outbreak risk, showing great variation across settings and pandemic periods. Regarding surveillance, routine testing rather than symptom-based was highlighted as essential for COVID-19 prevention due to high rates of silent transmission. Surveillance impacts depended critically on testing frequency, diagnostic sensitivity, and turn-around time. Healthcare re-organization also proved to have large epidemiological impacts: beyond obvious benefits of isolating cases and limiting inter-individual contact, more complex strategies (staggered staff scheduling, immune-based cohorting) reduced infection risk. Finally, vaccination impact, while highly effective for limiting COVID-19 burden, varied substantially depending on assumed mechanistic impacts on infection acquisition, symptom onset and transmission. Modelling results form an extensive evidence base that may inform control strategies for future waves of SARS-CoV-2 and other viral respiratory pathogens. We propose new avenues for future models of healthcare-associated outbreaks, with the aim of enhancing their efficiency and contributions to decision-making.

The Perpetual Pivot: Understanding Care Partner Experiences in Ontario Long-Term Care Homes during the COVID-19 Pandemic

Long-term care homes (LTCHs) were impacted during the COVID-19 pandemic. With their ever-changing conditions and restrictions, care partners' roles in LTCHs changed drastically. In this cross-sectional study, an electronic survey was used to examine the experiences of care part-ners who were caring for one or more adults in an Ontario LTCH during the pandemic. The survey was circulated through social media (convenience sample) which produced a convenience sample of 81 caregiver participants. Visit characteristics and a comparison in the quality of care in LTCHs was analyzed before the pandemic as well as during the most restrictive times. Visitation lengths and frequencies, other sources of communication such as phone and video calls, and various types of care provided by caregivers such as personal grooming and personal care all decreased significantly during the pandemic. Care partners also reported that the health of their care recipients decreased significantly during restrictive visitation times. Through thematic analysis, we identified three themes: restrictions and changing LTCH conditions created (1) social isolation and an erosion of connection, (2) a communication breakdown, and (3) a lack of person-centered care. Findings from this research can promote the health and wellbeing of residents and care partners within LTCHs.

Evaluating an Integrated Local System Response to the COVID-19 Pandemic: Case Study of East Toronto Health Partners

Introduction

East Toronto Health Partners (ETHP) is a network of organizations that serve residents of East Toronto, Ontario, Canada. ETHP is a newly formed integrated model of care in which hospital, primary care, community providers and patients/families work together to improve population health. We describe and evaluate the evolution of this emerging integrated care system as it responded to a global health crisis.

Description

This paper begins by describing ETHP's pandemic response mapping out over two years of data. To evaluate the response, semi-structured interviews were conducted with 30 decision makers, clinicians, staff, and volunteers who were part of the response. The interviews were thematically analyzed, and emergent themes mapped onto the nine pillars of integrated care.

Discussion

The ETHP pandemic response evolved rapidly. Early siloed responses gave way to collaborative efforts and equity emerged as a central priority. New alliances formed, resources were shared, leaders emerged, and community members stepped forward to contribute. Interviewees identified positives as well as many opportunities for improvement post-pandemic.

Conclusion

The pandemic was a catalyst for change in East Toronto that accelerated existing initiatives to achieve integrated care. The East Toronto experience may serve as a useful guide for other emerging integrated care systems.

Health Care-Associated Infections in Older Adults: Epidemiology and Prevention

Health care-associated infections (HAIs) are a global public health threat, which disproportionately impact older adults. Host factors including aging-related changes, comorbidities, and geriatric syndromes, such as dementia and frailty, predispose older individuals to infection. The HAI risks from medical interventions such as device use, antibiotic use, and lapses in infection control follow older adults as they transfer among a network of interrelated acute and long-term care facilities. Long-term care facilities are caring for patients with increasingly complex needs, and the home-like communal environment of long-term care facilities creates distinct infection prevention challenges.

A Molecular and Epidemiological Investigation of a Large SARS-CoV-2 Outbreak in a Long-Term Care Facility in Luxembourg, 2021

In spring 2021, a long-term care facility (LTCF) of 154 residents in Luxembourg experienced a large severe, acute respiratory-syndrome coronavirus 2 (SARS-CoV-2) outbreak a few days after a vaccination campaign. We conducted an outbreak investigation and a serosurvey two months after the outbreak, compared attack rates (AR) among residents and staff, and calculated hospitalization and case-fatality rates (CFR). Whole genome sequencing (WGS) was performed to detect variants in available samples and results were compared to genomes published on GISAID. Eighty-four (55%) residents and forty-five (26%) staff members tested positive for SARS-CoV-2; eighteen (21%) residents and one (2.2%) staff member were hospitalized, and twenty-three (CFR: 27%) residents died. Twenty-seven (21% of cases) experienced a reinfection. Sequencing identified seventy-seven cases (97% of sequenced cases) with B.1.1.420 and two cases among staff with B.1.351. The outbreak strain B.1.1.420 formed a separate cluster from cases from other European countries. Convalescent and vaccinated residents had higher anti-SARS-CoV-2 IgG antibody concentrations than vaccinated residents without infection (98% vs. 52%, respectively, with >120 RU/mL, p < 0.001). We documented an extensive outbreak of SARS-CoV-2 in an LTCF due to the presence of a specific variant leading to high CFR. Infection in vaccinated residents increased antibody responses. A single vaccine dose was insufficient to mitigate the outbreak.

Assessment of COVID-19 outbreaks in long-term care facilities

BACKGROUND

The B.1.167.2 (Delta) variant quickly became the predominant circulating SARS-CoV-2 strain in the USA during summer 2021. Missouri identified a high number of outbreaks in long-term care facilities (LTCFs) across the state with low vaccination rates among LTCF staff members and poor adherence to mitigation measures within local communities.

AIM

To describe COVID-19 outbreaks that occurred in Missouri LTCFs impacting staff and residents during the surge of the Delta variant.

METHODS

Outbreaks of COVID-19 in 178 LTCFs were identified by the Missouri Department of Health and Senior Services. Case data from LTCFs with the highest burden of disease were analysed to assess disease transmission, vaccination status, and outcomes among residents and staff. Additional investigational measures included onsite visits to facilities with recent COVID-19 outbreaks in communities with substantial transmission to assess mitigation measures.

FINDINGS

During April 22^nd to July 29^th, 2021, 159 COVID-19 cases among 72 staff members and 87 residents were identified in 10 LTCFs. More than 74.7% of resident cases were vaccinated compared to 23.6% of staff cases. Vaccinated residents had a lower proportion of hospitalizations and deaths reported compared to unvaccinated residents. Data analysis and contact-tracing efforts from a sample of the facilities suggest that staff members were likely a major factor in introducing SARS-CoV-2 virus into the facilities. Adherence to COVID-19 mitigation measures varied at the visited facilities.

CONCLUSION

Data showed that vaccination rates varied between staff cases and resident cases in facilities with high-burden outbreaks. Differences were identified in mitigation practices in at least two facilities.

National Weekly SARS-CoV-2 RT-PCR Screening of All Workers in Long-Term Care Facilities Associated with Decrease in Resident Mortality Rate

Introduction Outbreaks of COVID-19 in long-term care facilities (LTCFs) have resulted mainly from disease transmission by asymptomatic health care workers. This study examines whether routine screening tests carried out on health care workers can help in reducing COVID-19 outbreaks, morbidity, and mortality of LTCF residents. Methods The study followed a weekly, nationwide, government-funded screening program of LTCF personnel for SARS-CoV-2, by using reverse transcription polymerase chain reaction as the main testing technology. It included all residents and employees in Israeli LTCFs who were screened weekly during the second wave of COVID-19, during the time period between July 13, 2020, and November 21, 2020. Results During the study period, 1,107 LTCFs were screened on a weekly basis, including 62,159 HCWs and 100,046 residents. The program screened a median of 55,282 (Range 16,249, min 45,910, max 62,159) employees per week, 0.05-1.5% of which were positive for SARS-CoV-2. LTCF mortality in the first wave accounted for 45.3% of all COVID-19 deaths recorded nationally (252 of 556), and in the second wave this ratio was reduced to 30.3% (709 of 2,337) representing a reduction of 33.8% in expected mortality (P<0.001). A significant reduction was detected also in hospitalization rate (13.59% vs. 11.41%, p<0.001) and elder (≥75 years-old) mortality rate (52.89% vs. 41.42%, p<0.001). 214 outbreaks in the second wave were avoided by early identification of SARS-CoV-2 positive HCWs and successful prevention of subsequent infections in the facility. Conclusions and relevance Routine weekly SARS-CoV-2 RT-PCR testing of LTCF employees was associated with reduced national LTCF residents' hospitalizations and mortality rate.

A qualitative study exploring how patient engagement activities were sustained or adapted in Canadian healthcare organizations during the COVID-19 pandemic

BACKGROUND

The COVID-19 pandemic caused disruptions across healthcare systems globally exposing the precarious state of patient engagement across all levels of healthcare. While evidence is emerging to describe how engagement was affected across various settings, insights about how some organizations at the policy and practice level of healthcare were able to sustain or adapt patient engagement activities is lacking.

OBJECTIVE

This paper addresses the following research question: "How were healthcare, government, and patient partner organizations able to sustain or adapt patient engagement activities during the COVID-19 pandemic?"

METHODS

A qualitative descriptive study was conducted to understand how patient engagement activities were maintained or adapted in a variety of healthcare, government, and patient partner organizations in Canada throughout the pandemic. This analysis was part of a larger qualitative, multiple case study where one-to-one interviews were conducted with organizational leaders, managers and patient partners.

RESULTS

The following themes were identified as key aspects of maintaining or adapting patient engagement activities: 1) having an embedded organizational culture of patient engagement; 2) adapting patient engagement activities to focus on COVID-19 response efforts; 3) having patient partners who exercised leadership and advocacy to support patient care and experiences during the pandemic; and 4) leveraging virtual technology as a communication tool to engage patient partners.

CONCLUSION

This paper highlights important insights that may be useful to other health care organizations on how to sustain or adapt patient engagement activities during a healthcare crisis. Having patient engagement embedded within an organization's culture supported by, but not limited to, infrastructure, resources, investments in dedicated staff and patient partner leadership, and communication strategies and tools enabled continued patient engagement activities during the pandemic.

Economic evaluation of COVID-19 rapid antigen screening programs in the workplace

BACKGROUND

Diagnostic testing has been pivotal in detecting SARS-CoV-2 infections and reducing transmission through the isolation of positive cases. We quantified the value of implementing frequent, rapid antigen (RA) testing in the workplace to identify screening programs that are cost-effective.

METHODS

To project the number of cases, hospitalizations, and deaths under alternative screening programs, we adapted an agent-based model of COVID-19 transmission and parameterized it with the demographics of Ontario, Canada, incorporating vaccination and waning of immunity. Taking into account healthcare costs and productivity losses associated with each program, we calculated the incremental cost-effectiveness ratio (ICER) with quality-adjusted life year (QALY) as the measure of effect. Considering RT-PCR testing of only severe cases as the baseline scenario, we estimated the incremental net monetary benefits (iNMB) of the screening programs with varying durations and initiation times, as well as different booster coverages of working adults.

RESULTS

Assuming a willingness-to-pay threshold of CDN$30,000 per QALY loss averted, twice weekly workplace screening was cost-effective only if the program started early during a surge. In most scenarios, the iNMB of RA screening without a confirmatory RT-PCR or RA test was comparable or higher than the iNMB for programs with a confirmatory test for RA-positive cases. When the program started early with a duration of at least 16 weeks and no confirmatory testing, the iNMB exceeded CDN$1.1 million per 100,000 population. Increasing booster coverage of working adults improved the iNMB of RA screening.

CONCLUSIONS

Our findings indicate that frequent RA testing starting very early in a surge, without a confirmatory test, is a preferred screening program for the detection of asymptomatic infections in workplaces.

Using simulation modelling and systems science to help contain COVID-19: A systematic review

This study systematically reviews applications of three simulation approaches, that is, system dynamics model (SDM), agent-based model (ABM) and discrete event simulation (DES), and their hybrids in COVID-19 research and identifies theoretical and application innovations in public health. Among the 372 eligible papers, 72 focused on COVID-19 transmission dynamics, 204 evaluated both pharmaceutical and non-pharmaceutical interventions, 29 focused on the prediction of the pandemic and 67 investigated the impacts of COVID-19. ABM was used in 275 papers, followed by 54 SDM papers, 32 DES papers and 11 hybrid model papers. Evaluation and design of intervention scenarios are the most widely addressed area accounting for 55% of the four main categories, that is, the transmission of COVID-19, prediction of the pandemic, evaluation and design of intervention scenarios and societal impact assessment. The complexities in impact evaluation and intervention design demand hybrid simulation models that can simultaneously capture micro and macro aspects of the socio-economic systems involved.

Testing and vaccination to reduce the impact of COVID-19 in nursing homes: an agent-based approach

BACKGROUND

Efforts to protect residents in nursing homes involve non-pharmaceutical interventions, testing, and vaccine. We sought to quantify the effect of testing and vaccine strategies on the attack rate, length of the epidemic, and hospitalization.

METHODS

We developed an agent-based model to simulate the dynamics of SARS-CoV-2 transmission among resident and staff agents in a nursing home. Interactions between 172 residents and 170 staff based on data from a nursing home in Los Angeles, CA. Scenarios were simulated assuming different levels of non-pharmaceutical interventions, testing frequencies, and vaccine efficacy to reduce transmission.

RESULTS

Under the hypothetical scenario of widespread SARS-CoV-2 in the community, 3-day testing frequency minimized the attack rate and the time to eradicate an outbreak. Prioritization of vaccine among staff or staff and residents minimized the cumulative number of infections and hospitalization, particularly in the scenario of high probability of an introduction. Reducing the probability of a viral introduction eased the demand on testing and vaccination rate to decrease infections and hospitalizations.

CONCLUSIONS

Improving frequency of testing from 7-days to 3-days minimized the number of infections and hospitalizations, despite widespread community transmission. Vaccine prioritization of staff provides the best protection strategy when the risk of viral introduction is high.

Agent-based epidemiological modeling of COVID-19 in localized environments

Epidemiological modeling is used, under certain assumptions, to represent the spread of a disease within a population. Information generated by these models can then be applied to inform public health practices and mitigate risk. To provide useful and actionable preparedness information to administrators and policy makers, epidemiological models must be formulated to model highly localized environments such as office buildings, campuses, or long-term care facilities. In this paper, a highly configurable agent-based simulation (ABS) framework designed for localized environments is proposed. This ABS provides information about risk and the effects of both pharmacological and non-pharmacological interventions, as well as detailed control over the rapidly evolving epidemiological characteristics of COVID-19. Simulation results can inform decisions made by facility administrators and be used as inputs for a complementary decision support system. The application of our ABS to our research lab environment as a proof of concept demonstrates the configurability and insights achievable with this form of modeling, with future work focused on extensibility and integration with decision support.

Examining the association between reported COVID-19 symptoms and testing for COVID-19 in Canada: a cross-sectional survey

OBJECTIVES

Studies on the management of the COVID-19 pandemic through testing have been conducted in countries that have been hardest hit by this pandemic. Considering the importance of testing in containing the spread of COVID-19, it is useful to have evidence on continuing COVID-19 testing even in countries where the prevalence of COVID-19 is relatively low. We, therefore, examined the association between reported COVID-19 symptoms and testing for COVID-19 in Canada.

DESIGN AND SETTINGS

We conducted an online survey using the SurveyMonkey platform between July and October 2020 across Canada.

PARTICIPANTS

A nationally representative sample size of 2790 adult individuals was used.

RESULTS

Our findings show that respondents who reported that they and/or members of their households had COVID-19 symptoms were more likely to test for COVID-19 (adjusted OR, aOR 1.91; 95% CI 1.32 to 2.76) as compared with those who did not report COVID-19 symptoms. The likelihood of testing for COVID-19 was lower among male respondents compared with females (aOR 0.69; 95% CI 0.49 to 0.96), respondents aged 65-84 compared with those aged 18-44 (aOR 0.62; 95% CI 0.42 to 0.93), and respondents in British Columbia compared with those residing in Quebec. Higher odds of testing for COVID-19 were found among respondents who lived in Alberta compared with those who lived in Quebec (aOR 0.42; 95% CI 0.23 to 0.75) and respondents who had postgraduate education compared with those with high school or less education (aOR 1.84; 95% CI 1.01 to 3.36). The association between reported COVID-19 symptoms and testing for COVID-19 was statistically significant among female respondents (aOR 1.52; 95% CI 1.81 to 3.52) but not among male respondents.

CONCLUSIONS

In conclusion, this study provides evidence in support of the hypothesis that there is significant association between reported COVID-19 symptoms and COVID-19 testing among adult Canadians. The study highlights the need for the Canadian government to prioritise subpopulations (ie, males, those aged 65-85, and those with high school or less education) that have lower likelihood of seeking COVID-19 testing to get tested when they have symptoms.

SARS-CoV-2 outbreaks in hospitals and long-term care facilities in Germany: a national observational study

Background

Outbreaks of coronavirus disease (COVID-19) in hospitals and long-term care facilities (LTCFs) pose serious public health threats. We analysed how frequency and size of SARS-CoV-2 outbreaks in hospitals and LTCFs have altered since the beginning of the pandemic, in particular since the start of the vaccination campaign.

Methods

We used mandatory notification data on SARS-CoV-2 cases in Germany and stratified by outbreak cases in hospitals and LTCFs. German vaccination coverage data were analysed. We studied the association of the occurrence of SARS-CoV-2 outbreaks and outbreak cases with SARS-CoV-2 cases in Germany throughout the four pandemic waves. We built also counterfactual scenarios with the first pandemic wave as the baseline.

Findings

By 21 September 2021, there were 4,147,387 SARS-CoV-2 notified cases since March 2020. About 20% of these cases were reported as being related to an outbreak, with 1% of the cases in hospitals and 4% in LTCFs. The median number of outbreak cases in the different phases was smaller (≤5) in hospitals than in LTCFs (>10). In the first and second pandemic waves, we observed strong associations in both facility types between SARS-CoV-2 outbreak cases and total number of notified SARS-CoV-2 cases. However, during the third pandemic wave we observed a decline in outbreak cases in both facility types and only a weak association between outbreak cases and all cases.

Interpretation

The vaccination campaign and non-pharmaceutical interventions have been able to protect vulnerable risk groups in hospitals and LTCFs.

Funding

No specific funding.

Rapid antigen testing as a reactive response to surges in nosocomial SARS-CoV-2 outbreak risk

Healthcare facilities are vulnerable to SARS-CoV-2 introductions and subsequent nosocomial outbreaks. Antigen rapid diagnostic testing (Ag-RDT) is widely used for population screening, but its health and economic benefits as a reactive response to local surges in outbreak risk are unclear. We simulate SARS-CoV-2 transmission in a long-term care hospital with varying COVID-19 containment measures in place (social distancing, face masks, vaccination). Across scenarios, nosocomial incidence is reduced by up to 40-47% (range of means) with routine symptomatic RT-PCR testing, 59-63% with the addition of a timely round of Ag-RDT screening, and 69-75% with well-timed two-round screening. For the latter, a delay of 4-5 days between the two screening rounds is optimal for transmission prevention. Screening efficacy varies depending on test sensitivity, test type, subpopulations targeted, and community incidence. Efficiency, however, varies primarily depending on underlying outbreak risk, with health-economic benefits scaling by orders of magnitude depending on the COVID-19 containment measures in place.

Comparative analyses of eighteen rapid antigen tests and RT-PCR for COVID-19 quarantine and surveillance-based isolation

Background

Rapid antigen (RA) tests are being increasingly employed to detect SARS-CoV-2 infections in quarantine and surveillance. Prior research has focused on RT-PCR testing, a single RA test, or generic diagnostic characteristics of RA tests in assessing testing strategies.

Methods

We have conducted a comparative analysis of the post-quarantine transmission, the effective reproduction number during serial testing, and the false-positive rates for 18 RA tests with emergency use authorization from The United States Food and Drug Administration and an RT-PCR test. To quantify the extent of transmission, we developed an analytical mathematical framework informed by COVID-19 infectiousness, test specificity, and temporal diagnostic sensitivity data.

Results

We demonstrate that the relative effectiveness of RA tests and RT-PCR testing in reducing post-quarantine transmission depends on the quarantine duration and the turnaround time of testing results. For quarantines of two days or shorter, conducting a RA test on exit from quarantine reduces onward transmission more than a single RT-PCR test (with a 24-h delay) conducted upon exit. Applied to a complementary approach of performing serial testing at a specified frequency paired with isolation of positives, we have shown that RA tests outperform RT-PCR with a 24-h delay. The results from our modeling framework are consistent with quarantine and serial testing data collected from a remote industry setting.

Conclusions

These RA test-specific results are an important component of the tool set for policy decision-making, and demonstrate that judicious selection of an appropriate RA test can supply a viable alternative to RT-PCR in efforts to control the spread of disease.

COVID-19 outbreak in a long-term care facility in Kelowna, British Columbia after rollout of COVID-19 vaccine in March 2021

BACKGROUND

In March 2021, a coronavirus disease 2019 (COVID-19) outbreak was declared at a large long-term care and short stay facility in British Columbia, Canada-well after introduction of the vaccination program in long-term care facilities that resulted in a dramatic decline in the number of outbreaks in this type of setting. The objective of this study is to provide the descriptive epidemiology of this outbreak, in the context of partial immunization of both residents and staff at the facility.

METHODS

The cases' information was extracted from a provincial information system (Panorama). Descriptive analysis was performed using Microsoft Excel and SAS. Outbreak management controls included, but were not limited to, asymptomatic testing and efforts to increase vaccination.

RESULTS

Twenty-six cases among the 241 resident and three cases among the 418 staff (corresponding to attack rates of 10% and less than 1%, respectively) were identified. The attack rate in residents was considerably lower than the average attack rate for COVID-19 outbreaks in long-term care facilities before the vaccine rollout. Seventeen resident cases were either partially or fully immunized. Four of the eight hospitalized cases and two of the three deceased cases were partially immunized. Seventeen cases were temporary stay residents. The three staff cases were not vaccinated. Ten cases were identified as part of asymptomatic testing.

CONCLUSION

Introduction of vaccination at facilities contributed to lower attack rates and higher numbers of asymptomatic cases in this outbreak. Screening asymptomatic individuals identified additional cases among vaccinated residents. Findings underscore the importance of achieving high vaccine coverage, including among temporary stay residents, to prevent virus introduction and subsequent unrecognized transmission opportunities.

Agent-based simulations for protecting nursing homes with prevention and vaccination strategies

Due to its high lethality among older people, the safety of nursing homes has been of central importance during the COVID-19 pandemic. With test procedures and vaccines becoming available at scale, nursing homes might relax prohibitory measures while controlling the spread of infections. By control we mean that each index case infects less than one other person on average. Here, we develop an agent-based epidemiological model for the spread of SARS-CoV-2 calibrated to Austrian nursing homes to identify optimal prevention strategies. We find that the effectiveness of mitigation testing depends critically on test turnover time (time until test result), the detection threshold of tests and mitigation testing frequencies. Under realistic conditions and in absence of vaccinations, we find that mitigation testing of employees only might be sufficient to control outbreaks if tests have low turnover times and detection thresholds. If vaccines that are 60% effective against high viral load and transmission are available, control is achieved if 80% or more of the residents are vaccinated, even without mitigation testing and if residents are allowed to have visitors. Since these results strongly depend on vaccine efficacy against infection, retention of testing infrastructures, regular testing and sequencing of virus genomes is advised to enable early identification of new variants of concern.

Non-pharmacological measures implemented in the setting of long-term care facilities to prevent SARS-CoV-2 infections and their consequences: a rapid review

BACKGROUND

Starting in late 2019, COVID-19, caused by the novel coronavirus SARS-CoV-2, spread around the world. Long-term care facilities are at particularly high risk of outbreaks, and the burden of morbidity and mortality is very high among residents living in these facilities.

OBJECTIVES

To assess the effects of non-pharmacological measures implemented in long-term care facilities to prevent or reduce the transmission of SARS-CoV-2 infection among residents, staff, and visitors.

SEARCH METHODS

On 22 January 2021, we searched the Cochrane COVID-19 Study Register, WHO COVID-19 Global literature on coronavirus disease, Web of Science, and CINAHL. We also conducted backward citation searches of existing reviews.

SELECTION CRITERIA

We considered experimental, quasi-experimental, observational and modelling studies that assessed the effects of the measures implemented in long-term care facilities to protect residents and staff against SARS-CoV-2 infection. Primary outcomes were infections, hospitalisations and deaths due to COVID-19, contaminations of and outbreaks in long-term care facilities, and adverse health effects.

DATA COLLECTION AND ANALYSIS

Two review authors independently screened titles, abstracts and full texts. One review author performed data extractions, risk of bias assessments and quality appraisals, and at least one other author checked their accuracy. Risk of bias and quality assessments were conducted using the ROBINS-I tool for cohort and interrupted-time-series studies, the Joanna Briggs Institute (JBI) checklist for case-control studies, and a bespoke tool for modelling studies. We synthesised findings narratively, focusing on the direction of effect. One review author assessed certainty of evidence with GRADE, with the author team critically discussing the ratings.

MAIN RESULTS

We included 11 observational studies and 11 modelling studies in the analysis. All studies were conducted in high-income countries. Most studies compared outcomes in long-term care facilities that implemented the measures with predicted or observed control scenarios without the measure (but often with baseline infection control measures also in place). Several modelling studies assessed additional comparator scenarios, such as comparing higher with lower rates of testing. There were serious concerns regarding risk of bias in almost all observational studies and major or critical concerns regarding the quality of many modelling studies. Most observational studies did not adequately control for confounding. Many modelling studies used inappropriate assumptions about the structure and input parameters of the models, and failed to adequately assess uncertainty. Overall, we identified five intervention domains, each including a number of specific measures. Entry regulation measures (4 observational studies; 4 modelling studies) Self-confinement of staff with residents may reduce the number of infections, probability of facility contamination, and number of deaths. Quarantine for new admissions may reduce the number of infections. Testing of new admissions and intensified testing of residents and of staff after holidays may reduce the number of infections, but the evidence is very uncertain. The evidence is very uncertain regarding whether restricting admissions of new residents reduces the number of infections, but the measure may reduce the probability of facility contamination. Visiting restrictions may reduce the number of infections and deaths. Furthermore, it may increase the probability of facility contamination, but the evidence is very uncertain. It is very uncertain how visiting restrictions may adversely affect the mental health of residents. Contact-regulating and transmission-reducing measures (6 observational studies; 2 modelling studies) Barrier nursing may increase the number of infections and the probability of outbreaks, but the evidence is very uncertain. Multicomponent cleaning and environmental hygiene measures may reduce the number of infections, but the evidence is very uncertain. It is unclear how contact reduction measures affect the probability of outbreaks. These measures may reduce the number of infections, but the evidence is very uncertain. Personal hygiene measures may reduce the probability of outbreaks, but the evidence is very uncertain.  Mask and personal protective equipment usage may reduce the number of infections, the probability of outbreaks, and the number of deaths, but the evidence is very uncertain. Cohorting residents and staff may reduce the number of infections, although evidence is very uncertain. Multicomponent contact -regulating and transmission -reducing measures may reduce the probability of outbreaks, but the evidence is very uncertain. Surveillance measures (2 observational studies; 6 modelling studies) Routine testing of residents and staff independent of symptoms may reduce the number of infections. It may reduce the probability of outbreaks, but the evidence is very uncertain. Evidence from one observational study suggests that the measure may reduce, while the evidence from one modelling study suggests that it probably reduces hospitalisations. The measure may reduce the number of deaths among residents, but the evidence on deaths among staff is unclear.  Symptom-based surveillance testing may reduce the number of infections and the probability of outbreaks, but the evidence is very uncertain. Outbreak control measures (4 observational studies; 3 modelling studies) Separating infected and non-infected residents or staff caring for them may reduce the number of infections. The measure may reduce the probability of outbreaks and may reduce the number of deaths, but the evidence for the latter is very uncertain. Isolation of cases may reduce the number of infections and the probability of outbreaks, but the evidence is very uncertain. Multicomponent measures (2 observational studies; 1 modelling study) A combination of multiple infection-control measures, including various combinations of the above categories, may reduce the number of infections and may reduce the number of deaths, but the evidence for the latter is very uncertain.

AUTHORS' CONCLUSIONS

This review provides a comprehensive framework and synthesis of a range of non-pharmacological measures implemented in long-term care facilities. These may prevent SARS-CoV-2 infections and their consequences. However, the certainty of evidence is predominantly low to very low, due to the limited availability of evidence and the design and quality of available studies. Therefore, true effects may be substantially different from those reported here. Overall, more studies producing stronger evidence on the effects of non-pharmacological measures are needed, especially in low- and middle-income countries and on possible unintended consequences of these measures. Future research should explore the reasons behind the paucity of evidence to guide pandemic research priority setting in the future.