Lara Goscé

Background: Residents of care homes for older people are at risk of illness and hospitalisation from respiratory infections. Care home industry pay and conditions may contribute to the risk that staff will transmit infection to residents at times when respiratory viruses are circulating. We sought to understand post-pandemic care home providers’ policies and practices on care home testing for COVID-19, sickness absence due to respiratory infections and consequent shift backfill in English care homes, and to explore the costs to providers of outbreaks of respiratory infections. Methods: In mid-2024, we interviewed 11 senior managers from 10 privately owned care homes or care home groups across England providing services to older people. The sample was diverse in terms of region, size of provider and Care Quality Commission rating. Interview transcripts were analysed using the framework approach and findings tabulated. Results: At the time of the interviews, none of the care homes conducted asymptomatic COVID-19 testing. A minority required staff with respiratory infection symptoms to test for COVID-19. Policy for most providers was to only pay Statutory Sick Pay (SSP) to symptomatic staff. Few offered enhanced sickness pay. Care homes backfilled vacant shifts by offering other employed staff the extra shifts, calling in internal bank staff, zero-hours contractors, or care agency staff. Outbreaks of respiratory illness could increase costs for providers in replacement staffing, personal protective equipment, cleaning hours and equipment, additional administrative duties, and loss of income from new residents due to home closure. Conclusions: Care homes’ COVID-19 testing and sickness pay policies were in line with current public health guidance on COVID-19 testing and SSP regulations. Pay and conditions have been linked to presenteeism in the social care sector and may contribute to the risks of staff transmission to residents at times when respiratory infections are highly prevalent. Although regular staff testing combined with self-isolation for those who test positive may be effective in reducing transmission of infection, such policies require careful design given the important financial implications for care workers, care home providers and for the wider public health and care sector.

While a range of interventions exists for tuberculosis (TB), their potential impact and cost-effectiveness are seldom directly compared across settings with different TB epidemiologies and structural drivers. Here we calibrated a deterministic TB model to epidemiological indicators from Brazil, India and South Africa. We implemented seven interventions across countries focusing on prevention, screening and diagnosis and treatment, as well as prison screening (Brazil) and nutritional supplementation (India). We standardized scale-up (2025–2030), coverage (80% of the target population) and strength of evidence using published efficacy data. We estimated the epidemiological impact and incremental cost-effectiveness ratios (ICERs), expressed as costs per disability-adjusted life year (DALY) averted, through 2050. Only three interventions prevented >10% of incident TB episodes by 2050: vaccination (median 15–28% across countries), symptom-agnostic community-wide screening (31–38%) and prison screening (23%). Other interventions had limited impact, ranging from 0% (shorter drug-susceptible treatment) to 5% (nutritional supplementation). ICERs varied widely by intervention and setting. Shorter drug-resistant treatment was cost-saving across settings, with the next lowest ICERs for prison screening (US$146 per DALY) and nutritional supplementation (US$281 per DALY). Interventions with meaningful epidemiological impact can be cost-effective but must target populations beyond clinic-diagnosed individuals and their households. Achieving such potential requires a shift in priorities regarding funding, policy and product development.

Background: Regular severe acute respiratory syndrome coronavirus 2 testing of care home staff was introduced to reduce transmission following significant morbidity, mortality and disruption for residents early in the pandemic. However, evidence was lacking on benefits relative to disadvantages. Objectives: The VIVALDI-Clinical Trial aimed to investigate whether regular asymptomatic staff testing for severe acute respiratory syndrome coronavirus 2, alongside funding for sick pay and agency backfill, was feasible and effective in reducing severe coronavirus disease discovered in 2019-related outcomes in residents. Design and methods: VIVALDI-Clinical Trial comprised five interlinking work packages. A cluster randomised controlled trial was conducted from January to August 2023. The ‘Test to Care’ intervention was coproduced with the care sector. Settings and participants: Eighty-one residential/nursing homes in England providing care to adults aged ≥ 65 years. Forty-one homes were randomised to intervention and 40 to control. Interventions: Care homes were randomised 1 : 1 to intervention (twice weekly staff testing, staff sick pay and agency backfill) or control arm (national testing guidance at time of trial). Main outcome measure: Primary outcome was incidence of coronavirus disease discovered in 2019-related hospital admissions in residents. Data sources: Health data from routine national data sets were used alongside aggregate data from participating homes. Health economic and modelling analyses evaluated costs and cost-effectiveness of staff testing. Interviews with care home managers explored post-pandemic policies on staff testing, sickness pay and absence. A process evaluation was conducted to understand intervention roll-out. A mixed-study design investigated the impact of coronavirus disease discovered in 2019 outbreaks on care home residents’ quality of life. Stakeholder engagement was undertaken to enable the sector to coproduce recommendations for policy-makers. Results: The trial stopped early for futility due to site recruitment and primary outcome incidence being lower than expected. There was no significant difference in resident coronavirus disease discovered in 2019-linked hospital admission incidence between intervention and control arms (incidence rate ratio 1.19, 95% confidence interval 0.55 to 2.58; p = 0.66). The process evaluation found that changing epidemiology, policy and social norms around coronavirus disease discovered in 2019 shaped the uptake and maintenance of testing. Interviews with care home managers suggested most homes no longer test staff, even when symptomatic, and do not pay for sickness absence outside of statutory sick pay. Modelling concluded that regular staff testing, when combined with non-pharmaceutical interventions preventing transmission among residents, is an effective strategy to reduce cases and deaths among care home residents that could also lead to significant cost savings. There was lower-than-expected quality of life for 43 residents from 9 care homes without outbreak and 1 home with recent coronavirus disease discovered in 2019 outbreak, with older residents experiencing greater benefits from social care support. Limitations: Intervention acceptability was initially high, but waned because of the changing epidemiological, policy and social context. Conclusions: Contextual changes undermined our ability to evaluate the intervention’s impact. However, trial set-up was achieved in < 3 months, and we present findings on the feasibility and economic implications of routine testing and impact of disease control measures on residents’ quality of life. Costs associated with severe acute respiratory syndrome coronavirus 2 testing including support payments for care home staff and for care homes to fund agency staff backfill were funded by the United Kingdom Health Security Agency. Future work: Our approach provides a model for agile interventional studies in care homes. Research training and capacity building for care home staff are important to ensure that future trials can be delivered efficiently in this setting. Funding: This synopsis presents independent research funded by the National Institute for Health and Care Research (NIHR) Health and Social Care Delivery Research programme as award number NIHR154310.

Population-wide screening may accelerate the decline of tuberculosis (TB) incidence, but the optimal screening algorithm and duration must weigh resource considerations. We calibrated a deterministic transmission model to TB epidemiology in Viet Nam. We simulated three population-wide screening algorithms from 2025: sputum nucleic acid amplification tests (NAAT, Xpert MTB/RIF Ultra) only; chest radiography (CXR) followed by NAAT; and CXR-only without microbiological confirmation. We determined the annual screening rounds required to reduce pulmonary TB prevalence below 50 per 100,000 people. Cost-effectiveness was assessed using incremental cost-effectiveness ratios (ICERs), representing the additional costs (in US$) per disability-adjusted life year (DALY) averted compared to business-as-usual by 2050. Additionally, we evaluated the impact of NAAT cartridges costing US$1 each. NAAT-based algorithms required at least six rounds to reach the prevalence threshold, while CXR-only required three. NAAT-only achieved a prevalence reduction consistent with the ACT3 trial after three rounds. The CXR+NAAT algorithm averted 4.29m DALYs (95%UI:2.86-6.14) at US$225 (95%UI:85–520) per DALY averted compared with business-as-usual. The front-loaded investment of US$161m (95%UI:111–224) annually during the intervention resulted in average annual cost savings of US$12.7m (95%UI:6.7-21.4) up to 2050 compared to the business-as-usual counterfactual. Reducing the cost of NAAT to US$1 led to a 50% and 15% reduction in budget impact and a 63% and 26% reduction in the estimated ICER for the NAAT-only and CXR+NAAT algorithms, respectively. In Viet Nam, population-wide screening could achieve ambitious policy goals. Substantial front-loaded investment is immediately followed by persistent cost savings and could be further offset by more affordable NAATs.

Background: Non-pharmaceutical interventions were used widely in care homes for older people during the COVID-19 pandemic, but there have been few randomised trials to support policy decisions. We aimed to evaluate the effect of biweekly asymptomatic staff testing with support funding for sick pay and agency staffing on the clinical outcomes of residents. Methods: We conducted a cluster randomised unblinded superiority trial, aiming to recruit up to 280 residential and/or nursing homes in England providing care to adults aged >65 years. Homes were randomised 1:1 to the control arm, which followed national testing policy (comprising symptomatic plus outbreak testing at trial initiation) or intervention (additional twice weekly asymptomatic staff testing for SARS-CoV-2, staff sick pay and agency backfill). Outcomes were evaluated using health data from routine national datasets in combination with aggregate data from participating homes. The primary outcome was the incidence of COVID-19-related hospital admissions in residents. Results: The trial was conducted from January to August 2023, with 41 care homes randomised to intervention and 40 randomised to control included in the analysis. The trial was stopped early as it was not adequately powered for the primary outcome due to site recruitment and primary outcome events being substantially lower than expected. There was no significant difference in the primary outcome of resident COVID-linked hospital admission incidence between intervention and control arms (22.7/1000 person-years vs 15.0/1000 person-years, incidence rate ratio 1.19, 95%CI 0.55–2.58, P = 0.66; incidence rate difference 4.0, 95%CI −14.3 to 22.2). Trial set up took less than three months. Most trial outcomes were derived from routinely collected data. Recorded uptake of staff testing in the intervention arm was low (mean per home each week 14.4%). Conclusion: This trial was not well-powered to evaluate the impact of the intervention on the primary outcome, and recorded uptake of staff testing was low. However, our pre-existing care home network underpinned by linked routinely collected data provides a model for more agile interventional studies in the care home setting. ClinicalTrials.gov registration: NCT05639205.

Purpose: To describe the development of an intervention (‘ Test to Care’ ) maintaining biweekly asymptomatic SARS-CoV-2 testing amongst care home staff. Methods: Diverse inputs were sequentially integrated: 1 ) A behaviour change wheel (BCW) analysis of the results from a systematic review of barriers and facilitators to staff testing for SARS-CoV-2 from 14 international studies to generate initial intervention content ideas; 2 ) A series of eight stakeholder events with UK care home staff and policy makers (N=∼70) to iteratively operationalise emerging intervention content; 3 ) Confirmatory thematic analysis of barriers and facilitators to biweekly asymptomatic SARS-CoV-2 testing from four focus groups (N=15) to check temporal relevance of the intervention; 4) Intervention specification via programme theory and a logic model. Results: Narrative programme theory and a simple logic model described ‘ Test to Care ’. It showed the primary intervention function was ‘ incentivisation’, addressing agency backfill and sick pay. Secondary intervention functions included: ‘ education ’ and ‘ persuasion ’ to staff through communications and social marketing (i.e., posters and emails with embedded short videos); and ‘ environmental/social restructuring ’ and ‘ enablement ’ which invited managers to initiate and support implementation (i.e., the location of testing, management support and poster locations). Conclusions: Our integrative approach to intervention development produced an evidence-based, theoretically-informed intervention tailored to its specific implementation context. The diversity of included inputs were essential to overcome the relative weaknesses and strengths of each input source (e.g., the historical timeframe of published studies in the review, and the sampling biases associated with focus group participation). What is already known on this subject?: During the global COVID-19 pandemic, compliance with SARS-CoV-2 testing and other non-pharmaceutical interventions amongst care home staff was enforced through intervention functions such as ‘coercion’ and ‘restriction’ (e.g., mandatory routine testing). However, little is known about how to maintain testing when these intervention functions are removed. Intervention development guidance suggests optimal processes should combine the published literature, stakeholder engagement, and programme theory. However, few examples illustrate this process in detail. What does this study add?: We present a worked example of using diverse inputs to systematically develop an intervention within a compressed time frame: a typical behaviour change wheel analysis of findings (i.e., barriers and facilitators) from international published studies, novel iterative stakeholder input to add/remove and operationalise intervention content, and sense-checking the emerging intervention’s relevance within the context in which the intervention will be used. Uniquely, the study also shows how narrative programme theory and logic models can be used to illustrate an intervention and its purported functions: numerous intervention functions are required (i.e., ‘incentivisation’, ‘education’, ‘persuasion’, ‘environmental/social restructuring’ and ‘enablement’), as are varied behaviour change techniques addressing a range of important mechanisms of action (i.e., ‘knowledge’, ‘beliefs about consequences’, ‘professional role and identity’, ‘social influence’, ‘environmental context and resource’, ‘behavioural regulation’ and ‘memory attention and decision-making’).

Background Care home residents are at high risk of severe outcomes following respiratory infection due to age, co-morbidities, and close contact with staff and other residents. Frequent staff testing could potentially reduce respiratory infection cases in residents, but evidence is limited. This study uses historical COVID-19 data in England to assess the impact of varying staff testing rates under different transmission scenarios to inform response during future pandemics. Methods We developed a compartmental model of SARS-CoV-2 transmission in England, with three population strata: general population, care home staff, and residents. The model was calibrated using prevalence data from January 2021 to March 2022 and testing rates from the VIVALDI Study (ISRCTN14447421). We conducted a scenario analysis projecting resident cases and deaths over 12 months under varying staff testing frequencies (monthly, twice-monthly, weekly, twice-weekly, daily) assuming a new dominant strain. We also explored the impact of testing when combined with a hypothetical low-cost highly-effective public health and social measures. Findings Staff testing alone has little impact on reducing cases and deaths in the resident population. Daily testing could avert only 3.8% (95%UI: 3.1-4.4%) cases and 3.5% (95%UI: 2.3-4.4%) deaths compared to a baseline testing of less than one test per month. When combined with public health and social measures, however, the effect is large. Daily staff testing, combined with public health and social measures, can reduce resident cases by 54% (95%UI: 50-58%) and deaths by 50% (95%UI: 26-59%). Additionally, if testing frequency is reduced but there is still a public health and social measure, the effect size decreases, however there are potential cost savings (£0.7 to £3.4 million). Interpretation Increasing staff testing alone is insufficient to significantly reduce SARS-CoV-2 cases and deaths in care home residents. However, combining testing with some form of a public health and social measure aimed at reducing transmission among residents, is epidemiologically effective and cost-effective in most scenarios and possibly cost saving.

Tuberculosis (TB) has long been associated with poverty and displacement, through food insecurity, overcrowding, poor living conditions and reduced access to healthcare, which significantly increase the risk of both disease and poor health outcomes.1 Meanwhile, the climate crisis is likely to affect environmental conditions and increase extreme weather events and, consequently, migration and displacement, further exacerbating this important structural driver of TB.2