Impact of non-pharmaceutical interventions on SARS-CoV-2 outbreaks in English care homes: a modelling study

A model-based assessment of social isolation practices for COVID-19 outbreak response in residential care facilities

BACKGROUND

Residential aged-care facilities (RACFs, also called long-term care facilities, aged care homes, or nursing homes) have elevated risks of respiratory infection outbreaks and associated disease burden. During the COVID-19 pandemic, social isolation policies were commonly used in these facilities to prevent and mitigate outbreaks. We refer specifically to general isolation policies that were intended to reduce contact between residents, without regard to confirmed infection status. Such policies are controversial because of their association with adverse mental and physical health indicators and there is a lack of modelling that assesses their effectiveness.

METHODS

In consultation with the Australian Government Department of Health and Aged Care, we developed an agent-based model of COVID-19 transmission in a structured population, intended to represent the salient characteristics of a residential care environment. Using our model, we generated stochastic ensembles of simulated outbreaks and compared summary statistics of outbreaks simulated under different mitigation conditions. Our study focuses on the marginal impact of general isolation (reducing social contact between residents), regardless of confirmed infection. For a realistic assessment, our model included other generic interventions consistent with the Australian Government's recommendations released during the COVID-19 pandemic: isolation of confirmed resident cases, furlough (mandatory paid leave) of staff members with confirmed infection, and deployment of personal protective equipment (PPE) after outbreak declaration.

RESULTS

In the absence of any asymptomatic screening, general isolation of residents to their rooms reduced median cumulative cases by approximately 27%. However, when conducted concurrently with asymptomatic screening and isolation of confirmed cases, general isolation reduced the median number of cumulative infections by only 12% in our simulations.

CONCLUSIONS

Under realistic sets of assumptions, our simulations showed that general isolation of residents did not provide substantial benefits beyond those achieved through screening, isolation of confirmed cases, and deployment of PPE. Our results also highlight the importance of effective case isolation, and indicate that asymptomatic screening of residents and staff may be warranted, especially if importation risk from the outside community is high. Our conclusions are sensitive to assumptions about the proportion of total contacts in a facility accounted for by casual interactions between residents.

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.

Predictions from standard epidemiological models of consequences of segregating and isolating vulnerable people into care facilities

OBJECTIVES

Since the declaration of the COVID-19 pandemic, many governments have imposed policies to reduce contacts between people who are presumed to be particularly vulnerable to dying from respiratory illnesses and the rest of the population. These policies typically address vulnerable individuals concentrated in centralized care facilities and entail limiting social contacts with visitors, staff members, and other care home residents. We use a standard epidemiological model to investigate the impact of such circumstances on the predicted infectious disease attack rates, for interacting robust and vulnerable populations.

METHODS

We implement a general susceptible-infectious-recovered (SIR) compartmental model with two populations: robust and vulnerable. The key model parameters are the per-individual frequencies of within-group (robust-robust and vulnerable-vulnerable) and between-group (robust-vulnerable and vulnerable-robust) infectious-susceptible contacts and the recovery times of individuals in the two groups, which can be significantly longer for vulnerable people.

RESULTS

Across a large range of possible model parameters including degrees of segregation versus intermingling of vulnerable and robust individuals, we find that concentrating the most vulnerable into centralized care facilities virtually always increases the infectious disease attack rate in the vulnerable group, without significant benefit to the robust group.

CONCLUSIONS

Isolated care homes of vulnerable residents are predicted to be the worst possible mixing circumstances for reducing harm in epidemic or pandemic conditions.

Evaluating the impact of testing strategies for the detection of nosocomial COVID-19 in English hospitals through data-driven modeling

Introduction

During the first wave of the COVID-19 pandemic 293,204 inpatients in England tested positive for SARS-CoV-2. It is estimated that 1% of these cases were hospital-associated using European centre for disease prevention and control (ECDC) and Public Health England (PHE) definitions. Guidelines for preventing the spread of SARS-CoV-2 in hospitals have developed over time but the effectiveness and efficiency of testing strategies for preventing nosocomial transmission has not been explored.

Methods

Using an individual-based model, parameterised using multiple datasets, we simulated the transmission of SARS-CoV-2 to patients and healthcare workers between March and August 2020 and evaluated the efficacy of different testing strategies. These strategies were: 0) Testing only symptomatic patients on admission; 1) Testing all patients on admission; 2) Testing all patients on admission and again between days 5 and 7, and 3) Testing all patients on admission, and again at days 3, and 5-7. In addition to admissions testing, patients that develop a symptomatic infection while in hospital were tested under all strategies. We evaluated the impact of testing strategy, test characteristics and hospital-related factors on the number of nosocomial patient infections.

Results

Modelling suggests that 84.6% (95% CI: 84.3, 84.7) of community-acquired and 40.8% (40.3, 41.3) of hospital-associated SARS-CoV-2 infections are detectable before a patient is discharged from hospital. Testing all patients on admission and retesting after 3 or 5 days increases the proportion of nosocomial cases detected by 9.2%. Adding discharge testing increases detection by a further 1.5% (relative increase). Increasing occupancy rates, number of beds per bay, or the proportion of admissions wrongly suspected of having COVID-19 on admission and therefore incorrectly cohorted with COVID-19 patients, increases the rate of nosocomial transmission. Over 30,000 patients in England could have been discharged while incubating a non-detected SARS-CoV-2 infection during the first wave of the COVID-19 pandemic, of which 3.3% could have been identified by discharge screening. There was no significant difference in the rates of nosocomial transmission between testing strategies or when the turnaround time of the test was increased.

Discussion

This study provides insight into the efficacy of testing strategies in a period unbiased by vaccines and variants. The findings are relevant as testing programs for SARS-CoV-2 are scaled back, and possibly if a new vaccine escaping variant emerges.

Effectiveness of social distancing measures and lockdowns for reducing transmission of COVID-19 in non-healthcare, community-based settings

Social distancing measures (SDMs) are community-level interventions that aim to reduce person-to-person contacts in the community. SDMs were a major part of the responses first to contain, then to mitigate, the spread of SARS-CoV-2 in the community. Common SDMs included limiting the size of gatherings, closing schools and/or workplaces, implementing work-from-home arrangements, or more stringent restrictions such as lockdowns. This systematic review summarized the evidence for the effectiveness of nine SDMs. Almost all of the studies included were observational in nature, which meant that there were intrinsic risks of bias that could have been avoided were conditions randomly assigned to study participants. There were no instances where only one form of SDM had been in place in a particular setting during the study period, making it challenging to estimate the separate effect of each intervention. The more stringent SDMs such as stay-at-home orders, restrictions on mass gatherings and closures were estimated to be most effective at reducing SARS-CoV-2 transmission. Most studies included in this review suggested that combinations of SDMs successfully slowed or even stopped SARS-CoV-2 transmission in the community. However, individual effects and optimal combinations of interventions, as well as the optimal timing for particular measures, require further investigation. This article is part of the theme issue 'The effectiveness of non-pharmaceutical interventions on the COVID-19 pandemic: the evidence'.

Learning from the covid-19 outbreaks in long-term care facilities: a systematic review

BACKGROUND

The COVID-19 pandemic has devastatingly affected Long-Term Care Facilities (LTCF), exposing aging people, staff members, and visitors. The world has learned through the pandemic and lessons can be taken to adopt effective measures to deal with COVID-19 outbreaks in LTCF. We aimed to systematically review the available evidence on the effect of measures to minimize the risk of transmission of COVID-19 in LTCs during outbreaks since 2021.

METHODS

The search method was guided by the preferred reporting items for systematic reviews (PRISMA) and the reporting guideline synthesis without meta-analysis (SWiM) in systematic reviews. The search was performed in April 2023. Observational and interventional studies from the databases of PubMed, Web of Science, Scopus, Cochrane Systematic Reviews, CINAHL, and Academic Search were systematically reviewed. We included studies conducted in the LTCF with outbreaks that quantitatively assess the effect of non-pharmacological measures on cases of COVID-19. Two review authors independently reviewed titles for inclusion, extracted data, and undertook the risk of bias according to pre-specified criteria. The quality of studies was analyzed using the Joanna Briggs Institute Critical Appraisal.

RESULTS

Thirteen studies were included, with 8442 LTCF experiencing COVID-19 outbreaks and 598 thousand participants (residents and staff members). Prevention and control of COVID-19 infection interventions were grouped into three themes: strategic, tactical, and operational measures. The strategic measures reveal the importance of COVID-19 prevention and control as LTCF structural characteristics, namely the LTCF size, new admissions, infection control surveillance, and architectural structure. At the tactical level, the lack of personal and long staff shifts is related to COVID-19's spread. Operational measures with a favorable effect on preventing COVID-19 transmission are sufficient. Personal protective equipment stock, correct mask use, signaling, social distancing, and resident cohorting.

CONCLUSIONS

Operational, tactical, and strategic approaches may have a favorable effect on preventing the spread of COVID-19 in LTCFs experiencing outbreaks. Given the heterogeneous nature of the measures, performing a meta-analysis was not possible. Future research should use more robust study designs to explore similar infection control measures in LTCFs during endemic situations with comparable outbreaks.

TRIAL REGISTRATION

The protocol of this systematic review was registered in PROSPERO (CRD42020214566).

Impact of the first COVID-19 epidemic wave in a large French network of nursing homes: a cross-sectional study

BACKGROUND

Nursing homes (NHs) have been particularly affected by COVID-19. The aim of this study is to estimate the burden of COVID-19 and to investigate factors associated with mortality during the first epidemic wave in a large French NHs network.

METHODS

An observational cross-sectional study was conducted in September-October 2020. 290 NHs were asked to complete an online questionnaire covering the first epidemic wave on facilities and resident characteristics, number of suspected/confirmed COVID-19 deaths, and preventive/control measures taken at the facility level. Data were crosschecked using routinely collected administrative data on the facilities. The statistical unit of the study was the NH. Overall COVID-19 mortality rate was estimated. Factors associated with COVID-19 mortality were investigated using a multivariable multinomial logistic regression. The outcome was classified in 3 categories: "no COVID-19 death in a given NH", occurrence of an "episode of concern" (at least 10% of the residents died from COVID-19), occurrence of a "moderate episode" (deaths of COVID-19, less than 10% of the residents).

RESULTS

Of the 192 (66%) participating NHs, 28 (15%) were classified as having an "episode of concern". In the multinomial logistic regression, moderate epidemic magnitude in the NHs county (adjusted OR = 9.3; 95%CI=[2.6-33.3]), high number of healthcare and housekeeping staff (aOR = 3.7 [1.2-11.4]) and presence of an Alzheimer's unit (aOR = 0.2 [0.07-0.7]) were significantly associated with an "episode of concern".

CONCLUSIONS

We found a significant association between the occurrence of an "episode of concern" in a NH and some of its organizational characteristics and the epidemic magnitude in the area. These results can be used to improve the epidemic preparedness of NHs, particularly regarding the organization of NHs in small units with dedicated staff. Factors associated with COVID-19 mortality and preventive measures taken in nursing homes in France during the first epidemic wave.

Collateral impacts of pandemic COVID-19 drive the nosocomial spread of antibiotic resistance: A modelling study

BACKGROUND

Circulation of multidrug-resistant bacteria (MRB) in healthcare facilities is a major public health problem. These settings have been greatly impacted by the Coronavirus Disease 2019 (COVID-19) pandemic, notably due to surges in COVID-19 caseloads and the implementation of infection control measures. We sought to evaluate how such collateral impacts of COVID-19 impacted the nosocomial spread of MRB in an early pandemic context.

METHODS AND FINDINGS

We developed a mathematical model in which Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) and MRB cocirculate among patients and staff in a theoretical hospital population. Responses to COVID-19 were captured mechanistically via a range of parameters that reflect impacts of SARS-CoV-2 outbreaks on factors relevant for pathogen transmission. COVID-19 responses include both "policy responses" willingly enacted to limit SARS-CoV-2 transmission (e.g., universal masking, patient lockdown, and reinforced hand hygiene) and "caseload responses" unwillingly resulting from surges in COVID-19 caseloads (e.g., abandonment of antibiotic stewardship, disorganization of infection control programmes, and extended length of stay for COVID-19 patients). We conducted 2 main sets of model simulations, in which we quantified impacts of SARS-CoV-2 outbreaks on MRB colonization incidence and antibiotic resistance rates (the share of colonization due to antibiotic-resistant versus antibiotic-sensitive strains). The first set of simulations represents diverse MRB and nosocomial environments, accounting for high levels of heterogeneity across bacterial parameters (e.g., rates of transmission, antibiotic sensitivity, and colonization prevalence among newly admitted patients) and hospital parameters (e.g., rates of interindividual contact, antibiotic exposure, and patient admission/discharge). On average, COVID-19 control policies coincided with MRB prevention, including 28.2% [95% uncertainty interval: 2.5%, 60.2%] fewer incident cases of patient MRB colonization. Conversely, surges in COVID-19 caseloads favoured MRB transmission, resulting in a 13.8% [-3.5%, 77.0%] increase in colonization incidence and a 10.4% [0.2%, 46.9%] increase in antibiotic resistance rates in the absence of concomitant COVID-19 control policies. When COVID-19 policy responses and caseload responses were combined, MRB colonization incidence decreased by 24.2% [-7.8%, 59.3%], while resistance rates increased by 2.9% [-5.4%, 23.2%]. Impacts of COVID-19 responses varied across patients and staff and their respective routes of pathogen acquisition. The second set of simulations was tailored to specific hospital wards and nosocomial bacteria (methicillin-resistant Staphylococcus aureus, extended-spectrum beta-lactamase producing Escherichia coli). Consequences of nosocomial SARS-CoV-2 outbreaks were found to be highly context specific, with impacts depending on the specific ward and bacteria evaluated. In particular, SARS-CoV-2 outbreaks significantly impacted patient MRB colonization only in settings with high underlying risk of bacterial transmission. Yet across settings and species, antibiotic resistance burden was reduced in facilities with timelier implementation of effective COVID-19 control policies.

CONCLUSIONS

Our model suggests that surges in nosocomial SARS-CoV-2 transmission generate selection for the spread of antibiotic-resistant bacteria. Timely implementation of efficient COVID-19 control measures thus has 2-fold benefits, preventing the transmission of both SARS-CoV-2 and MRB, and highlighting antibiotic resistance control as a collateral benefit of pandemic preparedness.

Modelling the impact of repeat asymptomatic testing policies for staff on SARS-CoV-2 transmission potential

Repeat asymptomatic testing in order to identify and quarantine infectious individuals has become a widely-used intervention to control SARS-CoV-2 transmission. In some workplaces, and in particular health and social care settings with vulnerable patients, regular asymptomatic testing has been deployed to staff to reduce the likelihood of workplace outbreaks. We have developed a model based on data available in the literature to predict the potential impact of repeat asymptomatic testing on SARS-CoV-2 transmission. The results highlight features that are important to consider when modelling testing interventions, including population heterogeneity of infectiousness and correlation with test-positive probability, as well as adherence behaviours in response to policy. Furthermore, the model based on the reduction in transmission potential presented here can be used to parameterise existing epidemiological models without them having to explicitly simulate the testing process. Overall, we find that even with different model paramterisations, in theory, regular asymptomatic testing is likely to be a highly effective measure to reduce transmission in workplaces, subject to adherence. This manuscript was submitted as part of a theme issue on "Modelling COVID-19 and Preparedness for Future Pandemics".

COVID-19 in French nursing homes during the second pandemic wave: a mixed-methods cross-sectional study

INTRODUCTION

French nursing homes were deeply affected by the first wave of the COVID-19 pandemic, with 38% of all residents infected and 5% dying. Yet, little was done to prepare these facilities for the second pandemic wave, and subsequent outbreak response strategies largely duplicated what had been done in the spring of 2020, regardless of the unique needs of the care home environment.

METHODS

A cross-sectional, mixed-methods study using a retrospective, quantitative data from residents of 14 nursing homes between November 2020 and mid-January 2021. Four facilities were purposively selected as qualitative study sites for additional in-person, in-depth interviews in January and February 2021.

RESULTS

The average attack rate in the 14 participating nursing facilities was 39% among staff and 61% among residents. One-fifth (20) of infected residents ultimately died from COVID-19 and its complications. Failure to thrive syndrome (FTTS) was diagnosed in 23% of COVID-19-positive residents. Those at highest risk of death were men (HR=1.78; 95% CI: 1.18 to 2.70; p=0.006), with FTTS (HR=4.04; 95% CI: 1.93 to 8.48; p<0.001) or in facilities with delayed implementation of universal FFP2 masking policies (HR=1.05; 95% CI: 1.02 to 1.07; p<0.001). The lowest mortality was found in residents of facilities with a partial (HR=0.30; 95% CI: 0.18 to 0.51; p<0.001) or full-time physician on staff (HR=0.20; 95% CI: 0.08 to 0.53; p=0.001). Significant themes emerging from qualitative analysis centred on (1) the structural, chronic neglect of nursing homes, (2) the negative effects of the top-down, bureaucratic nature of COVID-19 crisis response, and (3) the counterproductive effects of lockdowns on both residents and staff.

CONCLUSION

Despite high resident mortality during the first pandemic wave, French nursing homes were ill-prepared for the second, with risk factors (especially staffing, lack of medical support, isolation/quarantine policy, etc) that affected case fatality and residents' and caregivers' overall well-being and mental health.