Real-Time Digital Contact Tracing: Development of a System to Control COVID-19 Outbreaks in Nursing Homes and Long-Term Care Facilities

CONTACT: a non-randomised feasibility study of bluetooth-enabled wearables for contact tracing in UK care homes during the COVID-19 pandemic

BACKGROUND

The need for effective non-pharmaceutical infection prevention measures such as contact tracing in pandemics remains in care homes, but traditional approaches to contact tracing are not feasible in care homes. The CONTACT intervention introduces Bluetooth-enabled wearable devices (BLE wearables) as a potential solution for automated contact tracing. Using structured reports and reports triggered by positive COVID-19 cases in homes, we fed contact patterns and trends back to homes to support better-informed infection prevention decisions and reduce blanket application of restrictive measures. This paper reports on the evaluation of feasibility and acceptability of the intervention prior to a planned definitive cluster randomised trial of the CONTACT BLE wearable intervention.

METHODS

CONTACT was a non-randomised mixed-method feasibility study over 2 months in four English care homes. Recruitment was via care home research networks, with individual consent. Data collection methods included routine data from the devices, case report forms, qualitative interviews (with staff and residents), field observation of care, and an adapted version of the NoMaD survey instrument to explore implementation using Normalisation Process Theory. Quantitative data were analysed using descriptive statistical methods. Qualitative data were thematically analysed using a framework approach and Normalisation Process Theory. Intervention and study delivery were evaluated against predefined progression criteria.

RESULTS

Of 156 eligible residents, 105 agreed to wear a device, with 102 (97%) starting the intervention. Of 225 eligible staff, 82% (n = 178) participated. Device loss and damage were significant: 11% of resident devices were lost or damaged, ~ 50% were replaced. Staff lost fewer devices, just 6%, but less than 10% were replaced. Fob wearables needed more battery changes than card-type devices (15% vs. 0%). Structured and reactive feedback was variably understood by homes but unlikely to be acted on. Researcher support for interpreting reports was valued. Homes found information useful when it confirmed rather than challenged preconceived contact patterns. Staff privacy concerns were a barrier to adoption. Study procedures added to existing work, making participation burdensome. Study participation benefits did not outweigh perceived burden and were amplified by the pandemic context. CONTACT did not meet its quantitative or qualitative progression criteria.

CONCLUSION

CONTACT found a large-scale definitive trial of BLE wearables for contact tracing and feedback-informed IPC in care homes unfeasible and unacceptable - at least in the context of shifting COVID-19 pandemic demands. Future research should co-design interventions and studies with care homes, focusing on successful intervention implementation as well as technical effectiveness.

TRIAL REGISTRATION

ISRCTN registration: 11204126 registered 17/02/2021.

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.

Factors influencing long-term care facility performance during the COVID-19 pandemic: a scoping review

BACKGROUND

The COVID-19 pandemic wreaked havoc on long-term care facilities (LTCFs). Some LTCFs performed better than others at slowing COVID-19 transmission. Emerging literature has mostly described infection prevention and control strategies implemented by LTCFs during the pandemic. However, there is a need for a comprehensive review of factors that influenced the performance of LTCFs in containing COVID-19 spread to inform public health policy.

OBJECTIVE

To build on the existing literature, we conducted a scoping review of factors that influenced LTCF performance during the COVID-19 pandemic using a multidimensional conceptual framework of performance.

METHODS

We followed the Joanna Briggs Institute's methodology for scoping reviews. We queried CINAHL, MEDLINE (Ovid), CAIRN, Science Direct, Scopus, and Web of Science for peer-reviewed literature in English or French published between January 1st, 2020 and December 31st, 2021. Retrieved records were screened for context (COVID-19 pandemic), population (LTCFs), interest (internal and external factors that influenced LTCF performance), and outcomes (dimensions of performance: equity, accessibility, reactivity, safety, continuity, efficacy, viability, efficiency). Descriptive characteristics of included articles were summarized. Dimensions of performance as well as internal (e.g., facility characteristics) and external (e.g., visitors) factors identified to have influenced LTCF performance were presented.

RESULTS

We retained 140 articles of which 68% were classified as research articles, 47% originated in North America, and most covered a period between March and July 2020. The most frequent dimensions of performance were "efficacy" (75.7%) and "safety" (75.7%). The most common internal factors were "organizational context" (72.9%) and "human resources" (62.1%), and the most common external factors were "visitors" (27.1%) and "public health guidelines" (25.7%).

CONCLUSIONS

Our review contributes to a global interest in understanding the impact of the COVID-19 pandemic on vulnerable populations residing and working in LTCFs. Though a myriad of factors were reported, a lack of randomized controlled trials makes it impossible to establish causality between the identified factors and LTCF performance. The use of a multidimensional framework can be recommended to evaluate healthcare system performance not merely in terms of efficacy and safety, but alongside other critical dimensions such as efficiency and equity.

TRIAL REGISTRATION

Research Registry ID: researchregistry7026.

The role of digital tools and emerging devices in COVID-19 contact tracing during the first 18 months of the pandemic: a systematic review

BACKGROUND

Contact tracing is a public health intervention implemented in synergy with other preventive measures to curb epidemics, like the coronavirus pandemic. The development and use of digital devices have increased worldwide to enhance the contact tracing process. The aim of the study was to evaluate the effectiveness and impact of tracking coronavirus disease 2019 (COVID-19) patients using digital solutions.

METHODS

Observational studies on digital contact tracing (DCT), published 2020-21, in English were identified through a systematic literature review performed on nine online databases. An ad hoc form was used for data extraction of relevant information. Quality assessment of the included studies was performed with validated tools. A qualitative synthesis of the findings is reported.

RESULTS

Over 8000 records were identified and 37 were included in the study: 24 modelling and 13 population-based studies. DCT improved the identification of close contacts of COVID-19 cases and reduced the effective reproduction number of COVID-19-related infections and deaths by over 60%. It impacted positively on societal and economic costs, in terms of lockdowns and use of resources, including staffing. Privacy and security issues were reported in 27 studies.

CONCLUSIONS

DCT contributed to curbing the COVID-19 pandemic, especially with the high uptake rate of the devices and in combination with other public health measures, especially conventional contact tracing. The main barriers to the implementation of the devices are uptake rate, security and privacy issues. Public health digitalization and contact tracing are the keys to countries' emergency preparedness for future health crises.

Quality in care homes: How wearable devices and social network analysis might help

Social network analysis can support quality improvement in care homes but traditional approaches to social network analysis are not always feasible in care homes. Recalling contacts and movements in a home is difficult for residents and staff and documentary and other sources of individual contacts can be unreliable. Bluetooth enabled wearable devices are a potential means of generating reliable, trustworthy, social network data in care home communities. In this paper, we explore the empirical, theoretical and real-world potential and difficulties in using Bluetooth enabled wearables with residents and staff in care homes for quality improvement. We demonstrate, for the first time, that a relatively simple system built around the Internet of Things, Bluetooth enabled wearables for residents and staff and passive location devices (the CONTACT intervention) can capture social networks and data in homes, enabling social network analysis, measures, statistics and visualisations. Unexpected variations in social network measures and patterns are surfaced, alongside "uncomfortable" information concerning staff time spent with residents. We show how technology might also help identify those most in need of social contact in a home. The possibilities of technology-enabled social network analysis must be balanced against the implementation-related challenges associated with introducing innovations in complex social systems such as care homes. Behavioural challenges notwithstanding, we argue that armed with social network information, care home staff could better tailor, plan and evaluate the effects of quality improvement with the sub-communities that make up a care home community.

'Smart' BLE wearables for digital contact tracing in care homes during the COVID-19 pandemic-a process evaluation of the CONTACT feasibility study

BACKGROUND

Rapid and mass transmission of the SARS-CoV-2 virus amongst vulnerable people led to devastating effects from COVID-19 in care homes. The CONTACT intervention introduced Bluetooth Low Energy 'smart' wearable devices (BLE wearables) as a basis for automated contact tracing in, and feedback on infection risks and patterns to, care homes to try and improve infection prevention and control (IPC). We planned a cluster randomised controlled trial (RCT) of CONTACT. To be feasible, homes had to adopt CONTACT's technology and new ways of working. This paper reports on the process evaluation conducted alongside CONTACT's feasibility study and explains why it lacked the feasibility and acceptability for a definitive RCT.

METHODS

This mixed method process evaluation used Normalisation Process Theory (NPT) qualitative (interviews, field notes, study case report forms and documents, and observation) and quantitative (survey instruments, counts of activity) data to plan, implement, and analyse the mechanisms, effects, and contextual factors that shaped the feasibility and acceptability of the CONTACT intervention.

RESULTS

Thirteen themes within four core NPT constructs explained CONTACT's lack of feasibility. Coherence: the home's varied in the scale and extent of commitment and understanding of the technology and study procedures. Leadership credibility was important but compromised by competing priorities. Management and direct care staff saw CONTACT differently. Work to promote (cognitive participation) and enact (collective action) CONTACT was burdensome and failed to be prioritised over competing COVID-19-related demands on time and scarce human and cognitive resources. Ultimately, staff appraisal of the value of CONTACT-generated information and study procedures (reflexivity) was that any utility for IPC was insufficient to outweigh the perceived burden and complexity involved.

CONCLUSIONS

Despite implementation failure, dismissing BLE wearables' potential for contact tracing is premature. In non-pandemic conditions, with more time, better co-design and integration of theory-driven implementation strategies tailored to care homes' unique contexts, researchers could enhance normalisation in readiness for future pandemic challenges.

TRIAL REGISTRATION

ISRCTN registration: 11,204,126 registered 17/02/2021.

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.

Evaluating the performance of wearable devices for contact tracing in care home environments

COVID-19 has had a devastating impact worldwide, including in care homes where there have been substantial numbers of cases among a very vulnerable population. A key mechanism for managing exposure to the virus and targeting interventions is contact tracing. Unfortunately, environments such as care homes that were most catastrophically impacted by COVID-19 are also those least amenable to traditional contact tracing. A promising alternative to recall and smartphone-based contact tracing approaches is the use of discrete wearable devices that exploit Bluetooth Low Energy (BLE) and Long-Range Wide Area Network (LoRaWAN) technologies. However, the real-world performance of these devices in the context of contact tracing is uncertain. A series of experiments were conducted to evaluate the performance of a wearables system that is based on BLE and LoRaWAN technologies. In each experiment, the number of successful contacts was recorded and the physical distance between two contacts was compared to a calculated distance using the Received Signal Strength Indication (RSSI) to determine the precision, error rate, and duration of proximity. The overall average system contact detection success rate was measured as 75.5%; when wearables were used as per the manufacturer's guidelines the contact detection success rate increased to 81.5%, but when obstructed by everyday objects such as clothing or inside a bag the contact detection success rate was only 64.2%. The calculated distance using RSSI was close to the physical distance in the absence of obstacles. However, in the presence of typical obstacles found in care home settings, the reliability of detection decreased, and the calculated distance usually appeared far from the actual contact point. The results suggest that under real-world conditions there may be a large proportion of contacts that are underestimated or undetected.

Implementation, uptake and use of a digital COVID-19 symptom tracker in English care homes in the coronavirus pandemic: a mixed-methods, multi-locality case study

BACKGROUND

COVID-19 spread rapidly in UK care homes for older people in the early pandemic. National infection control recommendations included remote resident assessment. A region in North-West England introduced a digital COVID-19 symptom tracker for homes to identify early signs of resident deterioration to facilitate care responses. We examined the implementation, uptake and use of the tracker in care homes across four geographical case study localities in the first year of the pandemic.

METHODS

This was a rapid, mixed-methods, multi-locality case study. Tracker uptake was calculated using the number of care homes taking up the tracker as a proportion of the total number of care homes in a locality. Mean tracker use was summarised at locality level and compared. Semi-structured interviews were conducted with professionals involved in tracker implementation and used to explore implementation factors across localities. Template Analysis with the Consolidated Framework for Implementation Research (CFIR) guided the interpretation of qualitative data.

RESULTS

Uptake varied across the four case study localities ranging between 13.8 and 77.8%. Tracker use decreased in all localities over time at different rates, with average use ranging between 18 and 58%. The implementation context differed between localities and the process of implementation deviated over time from the initially planned strategy, for stakeholder engagement and care homes' training. Four interpretative themes reflected the most influential factors appearing to affect tracker uptake and use: (1) the process of implementation, (2) implementation readiness, (3) clarity of purpose/perceived value and (4) relative priority in the context of wider system pressures.

CONCLUSIONS

Our study findings resonate with the digital solutions evidence base prior to the COVID-19 pandemic, suggesting three key factors that can inform future development and implementation of rapid digital responses in care home settings even in times of crisis: an incremental approach to implementation with testing of organisational readiness and attention to implementation climate, particularly the innovation's fit with local contexts (i.e. systems, infrastructure, work processes and practices); involvement of end-users in innovation design and development; and enabling users' easy access to sustained, high-quality, appropriate training and support to enable staff to adapt to digital solutions.

COVID-19 hospitalizations and patients' age at admission: The neglected importance of data variability for containment policies

Introduction

An excess in the daily fluctuation of COVID-19 in hospital admissions could cause uncertainty and delays in the implementation of care interventions. This study aims to characterize a possible source of extravariability in the number of hospitalizations for COVID-19 by considering age at admission as a potential explanatory factor. Age at hospitalization provides a clear idea of the epidemiological impact of the disease, as the elderly population is more at risk of severe COVID-19 outcomes. Administrative data for the Veneto region, Northern Italy from February 1, 2020, to November 20, 2021, were considered.

Methods

An inferential approach based on quasi-likelihood estimates through the generalized estimation equation (GEE) Poisson link function was used to quantify the overdispersion. The daily variation in the number of hospitalizations in the Veneto region that lagged at 3, 7, 10, and 15 days was associated with the number of news items retrieved from Global Database of Events, Language, and Tone (GDELT) regarding containment interventions to determine whether the magnitude of the past variation in daily hospitalizations could impact the number of preventive policies.

Results

This study demonstrated a significant increase in the pattern of hospitalizations for COVID-19 in Veneto beginning in December 2020. Age at admission affected the excess variability in the number of admissions. This effect increased as age increased. Specifically, the dispersion was significantly lower in people under 30 years of age. From an epidemiological point of view, controlling the overdispersion of hospitalizations and the variables characterizing this phenomenon is crucial. In this context, the policies should prevent the spread of the virus in particular in the elderly, as the uncontrolled diffusion in this age group would result in an extra variability in daily hospitalizations.

Discussion

This study demonstrated that the overdispersion, together with the increase in hospitalizations, results in a lagged inflation of the containment policies. However, all these interventions represent strategies designed to contain a mechanism that has already been triggered. Further efforts should be directed toward preventive policies aimed at protecting the most fragile subjects, such as the elderly. Therefore, it is essential to implement containment strategies before the occurrence of potentially out-of-control situations, resulting in congestion in hospitals and health services.

Impact of COVID-19 Outbreak in Healthcare of People with Type 2 Diabetes: Evidence from a Cross-Sectional Study

Objective The aim was to assess the impact of the COVID-19 outbreak on the health care of type 2 diabetes patients and identify the correlated factors. Research Design and Methods A cross-sectional study was carried out from November 2020 to February 2021. The study enrolled 400 adults with type 2 diabetes aged 40–65 with at least one other chronic illness receiving health services in primary care in Vlore, Albania. A short questionnaire based on literature, taking into account the situation of the COVID-19 pandemic, was used for the data collection. The administration of the questionnaire was done by trained nurses. All participants gave their written informed consent before administering the questionnaire. Two-tailed Pearson correlation and linear regression were used to test the correlations.  Results                                                                                Among 400 patients with type 2 diabetes in the study, 53.0% were female and 47.0% were men. Most of the participants were married (n = 303) with a high level of education (54.3%). Treatment was mainly with oral medications (58.0%). Based on body mass index, 63.0% of participants were overweight. Employment status (p = 003), the type of treatment, oral medication vs insulin (p = 001), body mass index (p = 001), and living alone (p = 008) were the more correlated factors.  Conclusions Care of type 2 diabetic patients due to the COVID-19 pandemic is closely associated with social determinants of health and the resources of healthcare settings. The need to address innovative approaches to care including self-care, social support, and e-health is recommended.    

Identifying performance factors of long-term care facilities in the context of the COVID-19 pandemic: a scoping review protocol

BACKGROUND

Long-term care facilities (LTCFs) have been severely affected by the COVID-19 pandemic with serious consequences for the residents. Some LTCFs performed better than others, experiencing lower case and death rates due to COVID-19. A comprehensive understanding of the factors that have affected the transmission of COVID-19 in LTCFs is lacking, as no published studies have applied a multidimensional conceptual framework to evaluate the performance of LTCFs during the pandemic. Much research has focused on infection prevention and control strategies or specific disease outcomes (e.g., death rates). To address these gaps, our scoping review will identify and analyze the performance factors that have influenced the management of COVID-19 in LTCFs by adopting a multidimensional conceptual framework.

METHODS

We will query the CINAHL, MEDLINE (Ovid), CAIRN, Science Direct, and Web of Science databases for peer-reviewed articles written in English or French and published between January 1, 2020 and December 31, 2021. We will include articles that focus on the specified context (COVID-19), population (LTCFs), interest (facilitators and barriers to performance of LTCFs), and outcomes (dimensions of performance according to a modified version of the Ministère de la santé et des services sociaux du Québec conceptual framework). Each article will be screened by at least two co-authors independently followed by data extraction of the included articles by one co-author and a review by the principal investigator.

RESULTS

We will present the results both narratively and with visual aids (e.g., flowcharts, tables, conceptual maps).

DISCUSSION

Our scoping review will provide a comprehensive understanding of the factors that have affected the performance of LTCFs during the COVID-19 pandemic. This knowledge can help inform the development of more effective infection prevention and control measures for future pandemics and outbreaks. The results of our review may lead to improvements in the care and safety of LTCF residents and staff. SCOPING REVIEW REGISTRATION: Research Registry researchregistry7026.

Epidemiology of SARS-CoV-2 infection in nursing facilities and the impact of their clusters in a Japanese core city

Introduction

Nursing facilities are vulnerable to coronavirus disease 2019 (COVID-19) due to the congregate nature of their housing, the older age of the residents, and the variety of their geriatric chronic conditions. Little is known about the impact of nursing facility COVID-19 on the local health system.

Methods

We collected data of COVID-19 cases in Nagasaki city from April 15, 2020 to June 30, 2021. We performed universal screening of the healthcare workers (HCWs) and the users of nursing facilities, once the first case of COVID-19 was detected within that facility. The community-dwelling people received testing if they had symptoms or if they were suspected of having close contact with the positive cases. The epidemiological survey for each COVID-19 case was performed by the public health officers of the local public health center.

Results

Out of 111,773 community-dwelling older adults (age ≥ 65 years) and 20,668 nursing facility users in Nagasaki city, we identified 358 and 71 COVID-19 cases, and 33 and 12 COVID-19 deaths, respectively, during the study period. The incidence rate ratios (IRRs) for COVID-19 and its deaths among the nursing facility users were 1.07 (95% confidence interval (CI), 0.82–1.39) and 1.97 (95%CI, 0.92–3.91) compared with the community-dwelling older adults. Four clusters, which had more than 10 COVID-19 cases, accounted for 60% (65/109) of the overall cases by the HCWs and the users.

Conclusions

The prevention of COVID-19 clusters is important to reduce the number of COVID-19 cases and deaths among the nursing facility population.

Relationships between Community Virus Activity and Cardiorespiratory Rehospitalizations From Post-Acute Care

Objectives:

Quantify the relationship between increasing influenza and respiratory syncytial virus (RSV) community viral activity and cardiorespiratory rehospitalizations among older adults discharged to skilled nursing facilities (SNFs).

Design:

Retrospective cohort.

Setting and Participants:

Adults aged ≥65 years who were hospitalized and then discharged to a US SNF between 2012 and 2015.

Methods:

We linked Medicare Provider Analysis and Review claims to Minimum Data Set version 3.0 assessments, PRISM Climate Group data, and the Centers for Disease Control and Prevention viral testing data. All data were aggregated to US Department of Health and Human Services regions. Negative binomial regression models quantified the relationship between increasing viral activity for RSV and 3 influenza strains (H1N1pdm09, H3N2, and B) and cardiorespiratory rehospitalizations from SNFs. Incidence rate ratios described the relationship between a 5% increase in circulating virus and the rates of rehospitalization for cardiorespiratory outcomes. Analyses were repeated using the same model, but influenza and RSV were considered “in season” or “out of season” based on a 10% positive testing threshold.

Results:

Cardiorespiratory rehospitalization rates increased by approximately 1% for every 5% increase in circulating influenza A(H3N2), influenza B, and RSV, but decreased by 1% for every 5% increase in circulating influenza A(H1N1pdm09). When respiratory viruses were in season (vs out of season), cardiorespiratory rehospitalization rates increased by approximately 6% for influenza A(H3N2), 3% for influenza B, and 5% for RSV, but decreased by 6% for influenza A(H1N1pdm09).

Conclusions and Implications:

The respiratory season is a particularly important period to implement interventions that reduce cardiorespiratory hospitalizations among SNF residents. Decreasing viral transmission in SNFs through practices such as influenza vaccination for residents and staff, use of personal protective equipment, improved environmental cleaning measures, screening and testing of residents and staff, surveillance of viral activity, and quarantining infected individuals may be potential strategies to limit viral infections and associated cardiorespiratory rehospitalizations.

Protecting Nursing Homes and Long-Term Care Facilities From COVID-19: A Rapid Review of International Evidence

OBJECTIVES

The COVID-19 pandemic has highlighted the extreme vulnerability of older people and other individuals who reside in long-term care, creating an urgent need for evidence-based policy that can adequately protect these community members. This study aimed to provide synthesized evidence to support policy decision making.

DESIGN

Rapid narrative review investigating strategies that have prevented or mitigated SARS-CoV-2 transmission in long-term care.

SETTING AND PARTICIPANTS

Residents and staff in care settings such as nursing homes and long-term care facilities.

METHODS

PubMed/Medline, Cochrane Library, and Scopus were systematically searched, with studies describing potentially effective strategies included. Studies were excluded if they did not report empirical evidence (eg, commentaries and consensus guidelines). Study quality was appraised on the basis of study design; data were extracted from published reports and synthesized narratively using tabulated data extracts and summary tables.

RESULTS

Searches yielded 713 articles; 80 papers describing 77 studies were included. Most studies were observational, with no randomized controlled trials identified. Intervention studies provided strong support for widespread surveillance, early identification and response, and rigorous infection prevention and control measures. Symptom- or temperature-based screening and single point-prevalence testing were found to be ineffective, and serial universal testing of residents and staff was considered crucial. Attention to ventilation and environmental management, digital health applications, and acute sector support were also considered beneficial although evidence for effectiveness was lacking. In observational studies, staff represented substantial transmission risk and workforce management strategies were important components of pandemic response. Higher-performing facilities with less crowding and higher nurse staffing ratios had reduced transmission rates. Outbreak investigations suggested that facility-level leadership, intersectoral collaboration, and policy that facilitated access to critical resources were all significant enablers of success.

CONCLUSIONS AND IMPLICATIONS

High-quality evidence of effectiveness in protecting LTCFs from COVID-19 was limited at the time of this study, though it continues to emerge. Despite widespread COVID-19 vaccination programs in many countries, continuing prevention and mitigation measures may be required to protect vulnerable long-term care residents from COVID-19 and other infectious diseases. This rapid review summarizes current evidence regarding strategies that may be effective.

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.

Digital contact tracing, community uptake, and proximity awareness technology to fight COVID-19: a systematic review

Digital contact tracing provides an expeditious and comprehensive way to collect and analyze data on people's proximity, location, movement, and health status. However, this technique raises concerns about data privacy and its overall effectiveness. This paper contributes to this debate as it provides a systematic review of digital contact tracing studies between January 1, 2020, and March 31, 2021. Following the PRISMA protocol for systematic reviews and the CHEERS statement for quality assessment, 580 papers were initially screened, and 19 papers were included in a qualitative synthesis. We add to the current literature in three ways. First, we evaluate whether digital contact tracing can mitigate COVID-19 by either reducing the effective reproductive number or the infected cases. Second, we study whether digital is more effective than manual contact tracing. Third, we analyze how proximity/location awareness technologies affect data privacy and population participation. We also discuss proximity/location accuracy problems arising when these technologies are applied in different built environments (i.e., home, transport, mall, park). This review provides a strong rationale for using digital contact tracing under specific requirements. Outcomes may inform current digital contact tracing implementation efforts worldwide regarding the potential benefits, technical limitations, and trade-offs between effectiveness and privacy.

Nursing homes during the COVID-19 pandemic: a scoping review of challenges and responses

Aim

To describe factors that contributed to the spread and mortality of COVID-19 in nursing homes and provide an overview of responses that were implemented.

Findings

COVID-19 exerted severe challenges on the nursing home population and its staff. Both internal and external factors predisposed nursing homes to an increased propensity of spread.

Message

Substantial learning occurred that will lead to better pandemic preparedness and improve quality of care for nursing home residents at all times.

Introduction

COVID-19 has caused unprecedented challenges in nursing homes. In this scoping review, we aimed to describe factors that contributed to the spread and mortality of COVID-19 in nursing homes and provide an overview of responses that were implemented to try to overcome such challenges.

Methods

The MeSH terms “Nursing homes” and “COVID-19” were searched in MEDLINE Ovid, and English language articles were retrieved that were published between 1 March 2020 and 31 January 2021. Article titles and abstracts were screened by two reviewers, and the results of included articles were grouped by themes.

Results

The search retrieved 348 articles, of which 76 were included in the thematic review. 8 articles related to COVID-19 disease characteristics (e.g. asymptomatic transmission), 24 to resident-related factors (e.g. comorbidities, nutrition, cognition), 13 to facility characteristics (e.g. physical space, occupancy, for-profit status), 21 to staffing (e.g. staffing levels, staff-to-resident ratio, staff multi-employment), and 10 to external factors (e.g. availability of personal protective equipment, prevailing health and social care policies). In terms of responses, identified themes included widespread testing, isolation and cohorting of residents, staff protection and support, promotion of residents’ well-being, and technological innovations.

Conclusion

COVID-19 exerted severe challenges on the nursing home population and its staff. Both internal and external factors predisposed nursing homes to an increased propensity of spread. Numerous strategies were employed to attempt to mitigate the negative impacts. Substantial learning occurred that may not only aid future pandemic preparedness but improve quality of care for nursing home residents at all times.

State of the Art in Adoption of Contact Tracing Apps and Recommendations Regarding Privacy Protection and Public Health: Systematic Review

BACKGROUND

During the COVID-19 pandemic, contact tracing apps have received a lot of public attention. The ongoing debate highlights the challenges of the adoption of data-driven innovation. We reflect on how to ensure an appropriate level of protection of individual data and how to maximize public health benefits that can be derived from the collected data.

OBJECTIVE

The aim of the study was to analyze available COVID-19 contact tracing apps and verify to what extent public health interests and data privacy standards can be fulfilled simultaneously in the process of the adoption of digital health technologies.

METHODS

A systematic review of PubMed and MEDLINE databases, as well as grey literature, was performed to identify available contact tracing apps. Two checklists were developed to evaluate (1) the apps' compliance with data privacy standards and (2) their fulfillment of public health interests. Based on both checklists, a scorecard with a selected set of minimum requirements was created with the goal of estimating whether the balance between the objective of data privacy and public health interests can be achieved in order to ensure the broad adoption of digital technologies.

RESULTS

Overall, 21 contact tracing apps were reviewed. In total, 11 criteria were defined to assess the usefulness of each digital technology for public health interests. The most frequently installed features related to contact alerting and governmental accountability. The least frequently installed feature was the availability of a system of medical or organizational support. Only 1 app out of 21 (5%) provided a threshold for the population coverage needed for the digital solution to be effective. In total, 12 criteria were used to assess the compliance of contact tracing apps with data privacy regulations. Explicit user consent, voluntary use, and anonymization techniques were among the most frequently fulfilled criteria. The least often implemented criteria were provisions of information about personal data breaches and data gathered from children. The balance between standards of data protection and public health benefits was achieved best by the COVIDSafe app and worst by the Alipay Health Code app.

CONCLUSIONS

Contact tracing apps with high levels of compliance with standards of data privacy tend to fulfill public health interests to a limited extent. Simultaneously, digital technologies with a lower level of data privacy protection allow for the collection of more data. Overall, this review shows that a consistent number of apps appear to comply with standards of data privacy, while their usefulness from a public health perspective can still be maximized.

Best Practice Guidance for Digital Contact Tracing Apps: A Cross-disciplinary Review of the Literature

BACKGROUND

Digital contact tracing apps have the potential to augment contact tracing systems and disrupt COVID-19 transmission by rapidly identifying secondary cases prior to the onset of infectiousness and linking them into a system of quarantine, testing, and health care worker case management. The international experience of digital contact tracing apps during the COVID-19 pandemic demonstrates how challenging their design and deployment are.

OBJECTIVE

This study aims to derive and summarize best practice guidance for the design of the ideal digital contact tracing app.

METHODS

A collaborative cross-disciplinary approach was used to derive best practice guidance for designing the ideal digital contact tracing app. A search of the indexed and gray literature was conducted to identify articles describing or evaluating digital contact tracing apps. MEDLINE was searched using a combination of free-text terms and Medical Subject Headings search terms. Gray literature sources searched were the World Health Organization Institutional Repository for Information Sharing, the European Centre for Disease Prevention and Control publications library, and Google, including the websites of many health protection authorities. Articles that were acceptable for inclusion in this evidence synthesis were peer-reviewed publications, cohort studies, randomized trials, modeling studies, technical reports, white papers, and media reports related to digital contact tracing.

RESULTS

Ethical, user experience, privacy and data protection, technical, clinical and societal, and evaluation considerations were identified from the literature. The ideal digital contact tracing app should be voluntary and should be equitably available and accessible. User engagement could be enhanced by small financial incentives, enabling users to tailor aspects of the app to their particular needs and integrating digital contact tracing apps into the wider public health information campaign. Adherence to the principles of good data protection and privacy by design is important to convince target populations to download and use digital contact tracing apps. Bluetooth Low Energy is recommended for a digital contact tracing app's contact event detection, but combining it with ultrasound technology may improve a digital contact tracing app's accuracy. A decentralized privacy-preserving protocol should be followed to enable digital contact tracing app users to exchange and record temporary contact numbers during contact events. The ideal digital contact tracing app should define and risk-stratify contact events according to proximity, duration of contact, and the infectiousness of the case at the time of contact. Evaluating digital contact tracing apps requires data to quantify app downloads, use among COVID-19 cases, successful contact alert generation, contact alert receivers, contact alert receivers that adhere to quarantine and testing recommendations, and the number of contact alert receivers who subsequently are tested positive for COVID-19. The outcomes of digital contact tracing apps' evaluations should be openly reported to allow for the wider public to review the evaluation of the app.

CONCLUSIONS

In conclusion, key considerations and best practice guidance for the design of the ideal digital contact tracing app were derived from the literature.

Deployment of artificial intelligence for radiographic diagnosis of COVID-19 pneumonia in the emergency department

OBJECTIVE

The coronavirus disease 2019 pandemic has inspired new innovations in diagnosing, treating, and dispositioning patients during high census conditions with constrained resources. Our objective is to describe first experiences of physician interaction with a novel artificial intelligence (AI) algorithm designed to enhance physician abilities to identify ground-glass opacities and consolidation on chest radiographs.

METHODS

During the first wave of the pandemic, we deployed a previously developed and validated deep-learning AI algorithm for assisted interpretation of chest radiographs for use by physicians at an academic health system in Southern California. The algorithm overlays radiographs with "heat" maps that indicate pneumonia probability alongside standard chest radiographs at the point of care. Physicians were surveyed in real time regarding ease of use and impact on clinical decisionmaking.

RESULTS

Of the 5125 total visits and 1960 chest radiographs obtained in the emergency department (ED) during the study period, 1855 were analyzed by the algorithm. Among these, emergency physicians were surveyed for their experiences on 202 radiographs. Overall, 86% either strongly agreed or somewhat agreed that the intervention was easy to use in their workflow. Of the respondents, 20% reported that the algorithm impacted clinical decisionmaking.

CONCLUSIONS

To our knowledge, this is the first published literature evaluating the impact of medical imaging AI on clinical decisionmaking in the emergency department setting. Urgent deployment of a previously validated AI algorithm clinically was easy to use and was found to have an impact on clinical decision making during the predicted surge period of a global pandemic.