Epidemiology of COVID-19 outbreaks in aged care facilities during postvaccine period: a systematic review and meta-analysis

Abstract

Objective

We aimed to define the epidemiology of COVID-19 outbreaks in aged care facilities (ACFs) during the postvaccine period, including vaccine effectiveness (VE) for this high-risk group.

Design

Systematic review and meta-analysis.

Data sources

Ovid Medline, Ovid Embase, Scopus, Web of Science and Cochrane databases were searched through 1 September 2023.

Eligibility criteria

Any original observational studies and trials reporting data on COVID-19 outbreaks among the partially/fully vaccinated residents from ACFs during or after the worldwide implementation of vaccine roll-out.

Data extraction and synthesis

We estimated the attack rate, case fatality rate, mortality rate and VE during postvaccine period. Random effect model was adopted for meta-analysis. Quality assessment on all included studies was performed using the Meta Quality Appraisal Tool.

Results

38 articles were included from 12 countries reporting 79 outbreaks with 1708 confirmed cases of COVID-19 from 78 ACFs. The pooled attack rate was 28% (95% CI 20% to 37%) among the fully vaccinated residents. Two-thirds (62.5%) of the index cases were unvaccinated healthcare professionals (eg, physicians, nurses) and caregivers. Unvaccinated residents had a significantly higher rates (12%) (95% CI 7% to 19%) of mortality compared with the vaccinated residents (2%) (95% CI% 1 to 4%) and the post-COVID-19 vaccine estimates for case fatality rate (13% vs 23%) and hospitalisation rate (17% vs 37%) were substantially lower. VE in preventing disease among residents in ACFs was 73% (95% CI 49% to 86). Overall, the included studies were heterogeneous in nature, however, the risk of bias was low to moderate.

Conclusions

Our study reaffirmed the impact of vaccination as a key public health measure to minimise the burden of COVID-19 in ACFs. Facilities with higher crowding indexes should be prioritised for vaccination and should advocate for higher vaccination targets among staff and residents as a critical intervention strategy to minimise disease burden in this vulnerable population.

Correspondence to Dr Gulam Khandaker; [email protected]

STRENGTHS AND LIMITATIONS OF THIS STUDY

• This is the first study to bring together latest data on global epidemiology of COVID-19 outbreaks among the elderly in aged care facilities following the implementation of the COVID-19 vaccine roll-out.

• A comprehensive and systematic literature search was undertaken across five major bibliographic databases pooling updated data for this high-risk group with rigorous screening and extraction approaches up until 1 September 2023.

• Quality assessment on all the included studies was performed using the Meta Quality Appraisal Tool. All the included studies reported outcomes were from the developed country settings hence, generalisability of the implication of findings across low-income and middle-income countries needs to be interpreted with caution.

• Baseline facility factors, infection prevention and control strategies, reporting outcomes and person-time heterogeneity following vaccination dosages, circulating COVID-19 strain virulence, past infection status of elderly resident across the included studies might limit the interpretation of our findings.

Introduction

The COVID-19 pandemic has caused disproportionately higher morbidity and mortality in older adults, particularly in dedicated aged care facilities (ACFs).¹ As of 4 October 2023, SARS-CoV-2 infection has caused an estimated 771 million cases and 6.9 million deaths with fluctuating waves of new cases stemming from multiple lineage variants across continents.^2–4 Consequently, elderly people residing in ACFs suffered devastating death tolls from COVID-19 with varying case fatality rates (CFRs) in almost all developed countries (eg, Germany (11%), France (32%), Canada (37%), Netherlands (50%), Spain (12%) and Australia (23%), respectively).⁵ Older age, reduced immunity, multiple comorbidities, secondary immunosuppression and the decline in cognitive function among elderly residents in enclosed settings increases the COVID-19 disease severity grade progressing to poor outcomes such as hospitalisation with higher mortality.^6–8 In addition, structural and organisational facility-related factors contribute to the introduction of the SARS-CoV-2 infection resulting in outbreaks with higher attack and CFRs among residents.^{1 9}

ACFs also known as residential care or long-term care (LTC) homes or nursing homes provide institutional care to an individual including their daily needs and personal care. Often the residents in ACFs have complex social, psychological and medical needs.¹⁰ COVID-19 pandemic highlighted the lack of preparation, prevention and mitigation strategies against infectious diseases in these congregate settings.¹¹ Differences in occupying resident health status, care provision across countries, model of care, surveillance strategies, infection control, and prevention policies and practices also differ in various jurisdictions both at international, national, local and facility level. Such heterogeneity plays a vital role in disease transmission and outbreak outcome within the ACFs.^{11 12}

The rapid development of COVID-19 vaccines ushered substantial hope during the pandemic with clinical studies reporting vaccine efficacy of approximately 95% in preventing SARS-CoV-2 infection.^{13 14} However, controversy exists in the estimates of vaccine effectiveness (VE) in the elderly population.^{15 16} A multistate study conducted in the USA among the older adults ≥65 years showed VE estimates of (64%–95%) in preventing hospitalisations following administration COVID-19 vaccine.¹⁷ Monge et al analysed nationwide data of aged care residents in Spain demonstrating mRNA vaccines were effective in preventing infection for the vaccinated (81.8%; 95% CI 81.0% to 82.7%) and risk declined in non-vaccinated residents by up to 81.4% (95% CI 73.3% to 90.3%) both without any prior evidence of infection.¹⁸ The VIVALDI study using the UK nationwide LTC facilities (LTCF) data revealed there was no evidence of protection within 28 days following the first dose of the Pfizer/BioNTech COVID-19 vaccine.¹⁹ Nevertheless, VE during successive COVID-19 infection at^20–26 days, and^27–40 days was found between 56% and 62%, respectively.¹⁹ Therefore, to better understand VE in ACFs, collation of the published evidence and meta-analysis of the VE estimates from postvaccine period outbreaks is necessary.

Globally, ACFs experienced outbreaks early, during and after COVID-19 vaccination with varying attack rates (ARs) and severity of disease outcomes.^{41 42} The risk of outbreak severity and duration may be modified by vaccine uptake in terms of coverage and dosages among both the residents and staff.⁴³ Bailly et al reported an 83% vaccine coverage with an AR of 58% in France, while Orsi et al reported a facility in Italy with 95% coverage experienced an AR of 70%.^{44 45} Therefore, to inform vaccination policies worldwide, it is important to better understand the effect of vaccination on the ARs and CFRs within this setting.

We reported a systematic review and meta-analysis of COVID-19 outbreaks in ACFs during the pre-COVID-19 vaccine period which demonstrated a high AR (45%) and a CFR of 23%.¹ This follow-up study is to define the epidemiology of COVID-19 outbreaks in ACFs during the postvaccine period in terms of AR, CFR, mortality rate (MR) and to estimate VE among elderly ACF residents.

Methods

Search strategy

We systematically searched five major bibliographic databases (Ovid Medline, Ovid Embase, SCOPUS, Web of Science and Cochrane) for literature published after 1 December 2020, and updated on 1 September 2023 covering recently published articles to identify outbreak events during or following vaccine introduction within the ACFs. Search terms included “COVID-19”, “SARS-CoV-2”, “coronavirus, “nursing home”, “long-term care”, “homes for the aged”, “assisted living”, “skilled nursing” and synonymous text and thesaurus words as per the earlier study.¹ The full OVID Medline search strategy, including all terms used, is available in online supplemental file S1, p1. We conducted a rigorous and comprehensive manual search snowballing the references and published studies that cited the included papers on Google Scholar and PubMed. No language limits were applied during the search. We did not register our review protocol.

Study eligibility and quality assessment

We included any original studies reporting data on COVID-19 outbreaks among the partially/fully vaccinated (FV) residents from ACFs during or after the worldwide implementation of vaccine roll-out. We excluded studies lacking COVID-19 vaccination information among residents, systematic reviews, preprint articles and aggregated dataset containing non-extractable data. Two reviewers (MRH and GC) initially screened the title and abstract after retrieval from the databases (figure 1). We used Rayyan QCRI software for screening studies by title and abstract.⁴⁶ Following the initial inclusion of articles, full texts were collected and assessed for eligibility by two reviewers. All screening phases were conducted independently, and the decision was finalised on consensus through discussion. Rigorous checking was performed to ensure eligibility and any differences in opinion were finalised through consensual agreement from a senior author (GK). We excluded studies reporting COVID-19 events from hospitals, communities or nationwide cohort data from ACFs. Multiple publications from similar centres, facilities, author names and period of the outbreaks were cross-checked to avoid duplication and excluded appositely. Authors of the selected articles were contacted to maintain accuracy of data extraction where applicable.

Figure 1. PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) flow chart process for study selection.

Quality assessment on all included studies was performed using Strengthening the reporting of observational studies in epidemiology (STROBE) reporting guidelines for observational studies and the Meta Quality Appraisal Tool. The latter contains a checklist, specifying four criteria: relevancy, reliability, validity and applicability. Each included article was independently assessed against this checklist by two reviewers (MRH and GC). Discrepancies were resolved through consensus and finalised on discussion to report the quality appraisal of all included studies (online supplemental table 1)

Data extraction

Two reviewers (MRH and GC) independently conducted data extraction and results were compared with ensure accuracy. The following data were extracted for all eligible articles: title, author, publication year, journal, city and country of the patient, sample size, type of facility, outbreak number, index case characteristics (age, gender, vaccination status and symptoms status) and duration of the outbreaks, variant detected on the outbreaks and method for confirmation of diagnosis. In addition, demographic characteristics, total residents and staff in the facility, vaccine type, vaccination status, and facility AR, CFR, hospitalisation, and MR among the residents as reported in the studies was gathered. Residents were categorised based on COVID-19 vaccine dose receipt before the onset of an outbreak as reported in the studies with the following: completion of both doses as FV, receipt of only one dose as partially vaccinated (PV) and those who had not received any vaccine as unvaccinated accordingly.

Statistical analysis

The primary key outcome measures of the review were AR, CFR and MR. We defined AR as the proportion of infected residents by the number of total residents at-risk of SARS-CoV-2 infection within the ACF under investigation. All residents within the facility during the outbreak were considered as at-risk population. The proportion of infected residents who experienced death by the total number of infected residents and the total number of at-risk residents within the facility expressed in percentage was defined as CFR and MR, respectively. COVID-19 vaccine status of the residents before the onset of the outbreaks was categorised into four groups: (1) vaccinated (received either a single dose or both doses and/or booster), (2) FV (received both doses ≥14 days prior to the outbreak for all vaccine brands or single dose for Janssen), (3) PV (received only a single dose ≥14 days prior the outbreak for all vaccine brands except Janssen) and (4) unvaccinated (did not receive any doses or received only one dose ≤14 days prior to the outbreak). Pooled estimates of the key outcome measures from the reported studies were estimated using DerSimonian and Laird random effects meta-analysis model following logit transformation of the data. Outcome estimates were expressed in pooled proportion along with a 95% CI. The demographic and epidemiological indices of SARS-CoV-2 during the postvaccine era were presented from the included studies using descriptive analysis. We calculated pooled VE (PVE) extracted from the eligible studies using the following formula: VE=(1−pooled OR)×100 with 95% CI. Between studies, heterogeneity was assessed using I² statistics with a value of ˂30%, 30%–60%, 61%–75% and >75% indicated as low, moderate, substantial and considerable, respectively.⁴⁷ Publication bias was evaluated visually by inspecting the funnel plot and Egger’s test. All statistical analyses were conducted with R software V.4.2.2. using ‘meta’ and ‘metafor’ package.⁴⁸

Patient and public involvement

No patient involved.

Results

Search results and characteristics of included studies

We identified 20 593 studies and after the screening process, 98 articles were eligible for full-text review. A total of 38 articles were ultimately included reporting 5493 residents from 78 ACFs across 12 countries reporting 79 COVID-19 outbreaks with 1708confirmed cases. Articles not fulfilling selection criteria and an aggregated dataset containing non-extractable data were excluded from analysis (n=63) (figure 1).²⁰ Among the 38 included articles, 10 are from the USA, 5 from Italy, 5 from France, 5 from Germany, 3 from Canada, 3 from Spain and Netherlands, and 1 each from the UK, Japan, Serbia, Switzerland and Luxembourg.^{21–40 44 45 49–64} All studies are observational in nature and mostly, outbreaks were described over a period of 6 months (January–July 2021) (table 1). All outbreaks were reported mostly within nursing homes (74.3%, n=58), however, LTC (15.3%, n=12) and skilled nursing facilities (7.6%, n=6) were also included. Index cases were documented only among one-third (20%, n=16) of the total reported outbreaks, and among those more than one-third (37.5%, n=6) of the cases were unvaccinated. In the majority of those index case known outbreaks (62.5%, n=10) facility staff (eg, healthcare professionals and caregivers) were identified as index cases, and residents were found to be the index cases in the remaining events (37%, n=6). We found that unvaccinated healthcare professionals (eg, physicians, nurses), and caregivers comprised one-third of the index cases. Phylogenetic analysis was performed in the majority of the outbreaks (73.4%, n=58) and variants of SARS-CoV-2 reported in higher frequency were alpha (62%, n=36), delta (13.7%, n=8), beta (8.6%, n=5), omicron (3.4, n=2), gamma (1.7%, n=1) and other lineages (10.3%, n=6) (table 1).

Table 1

Characteristics of included studies of postvaccine period outbreaks of SARS-CoV-2 in aged care facilities

Author/year/country	Study design (sample size)	Settings of the outbreak (index case status)	Study period	Participant investigated in the facility (number of the outbreaks)	Identified SARS-CoV-2 variant	COVID-19 vaccine type	Age (years); sex distribution of the COVID-19 cases (M/F)†
Bailly/2021/France44	Prospective cohort (90)	NH (NR)	March–April	R+S (1)	501Y.V2 (Beta)	Pfizer‐BioNTech (BNT162B2)	87 (8.2); NR
Orsi/2021/Italy45	Prospective cohort (20)	NH (S-UV)	February–March	R+S (1)	20I/501Y.V1 (Alpha)	Pfizer‐BioNTech (BNT162B2)	(77–100); 5/15
Sabet/2021/Canada21	Prospective cohort (659)	LTCF (R)	March–April	R (1)	B.1.160; B.1.36	Pfizer‐BioNTech (BNT162B2)	NR
Williams/2021/Canada22	Prospective cohort (164)	LTCF (S– UV)	April–May	R+S (1)	P.1 (Gamma)	Moderna (mRNA‐1273)	NR
Vanker/2022/Canada52	Retrospective cohort (382)	LTCF (NR)	April	R+S (1)	B.1.351 (Beta)	Pfizer‐BioNTech (BNT162B2)	NR
Burugorri-Pierre/2021/ France23	Prospective cohort (176)	NH (R-UV)	March–April	R+HCP (1)	B.1.1.7 (Alpha)	Pfizer‐BioNTech (BNT162B2)	87.8 (7.5); 5/12
Martinot/2021/France24	Cross-sectional (166)	LTCF (NR)	March–May	R+HCP (1)	B.1.1.7 (Alpha)	Pfizer‐BioNTech (BNT162B2)	91 (72–99); 10/14
Lafuente-Lafuente/2022/France25	Retrospective cohort (1768)	NH (NR)	March–April	R (27)	B.1.1.7 (Alpha) B.1.351 (Beta)	Pfizer‐BioNTech (BNT162B2)	88.3 (8.1); 97/268
Blain/2023/France53	Retrospective cohort (540)	NH (NR)	March–April	R (14)	NR	Pfizer‐BioNTech (BNT162B2)	NR
Pletz/2021/Germany26	Prospective cohort (29)	LTCF (R-PV)	January	R (1)	B.1.1.317	Pfizer‐BioNTech (BNT162B2)	85 (6–8); NR
Tober-Lau/2021/Germany27	Prospective cohort (24)	LTCF (HCP)	February–March	R+HCP (1)	B.1.1.7 (Alpha)	Pfizer‐BioNTech (BNT162B2)	NR
Westhölter/2021/Germany28	Cross-sectional (76)	LTCF (NR)	NR	R (1)	NR	Pfizer‐BioNTech (BNT162B2)	NR
Schwarzer/2021/Germany29	Retrospective cohort (66)	NH (R-V)	January–February	R+S (1)	B.1.177.86	Pfizer‐BioNTech (BNT162B2)	NR
Meyer/2022/Germany54	Retrospective cohort (228)	NH (NR)	January–March	R+S (1)	B.1.1.7 (Alpha)	Pfizer‐BioNTech (BNT162B2)	87 (83–92); NR
Pierobon/2021/Italy30	Prospective cohort (138)	NH (HCP)	August–October	R+HCW (1)	B.1.617.2 (Delta)	Pfizer‐BioNTech (BNT162B2)	NR
Faggiano/2021/Italy31	Prospective cohort (49)	NH (HCP-UV)	April–May	R+HCP (1)	B.1.1.7 (Alpha)	Pfizer‐BioNTech (BNT162B2)	89 (71–99); NR
Ripabelli/2021/Italy32	Prospective cohort (95)	NH (R)	October–November	R+HCP (1)	B.1.617.2 (Delta)	Pfizer‐BioNTech (BNT162B2)	89 (66–99); NR
Castaldi/2021/Italy33	Retrospective cohort (165)	NH (HCP-UV)	January–May	R+HCP (1)	B.1.1.7 (Alpha)	Pfizer‐BioNTech (BNT162B2)	88.1 (7.1); 8/26
Matsumura/2022/Japan55	Retrospective cohort (79)	NH (NR)	February–March	R (1)	BA.1.1.2 (Omicron)	Pfizer‐BioNTech (BNT162B2)	89 (86–92); 6/25
Ernst/2023/Luxembourg56	Retrospective cohort (327)	LTCF	February–March	R+S (1)	B.1.1.420 (Beta)	Pfizer‐BioNTech (BNT162B2)	88 (83–91); 23/61
Buskermolen/2022/Netherlands57	Restrospective cohort (31)	NH	July	R	B.1.617.2 (Delta)	Pfizer‐BioNTech (BNT162B2)	87 (71–99); 4/11
Van Ewijk/2022/Netherlands58	Retrospective cohort (105)	LTCF	November–January	R	B.1.617.2 (Delta)	Pfizer‐BioNTech (BNT162B2)	86 (66–106); NR
Čokić/2023/Serbia59	Retrospective cohort (281)	NH	November–December January–February	R+S (2)	B.1.617.2 (Delta) BA.1.1.2 (Omicron)	BBIBP-CorV (Sinopharm) Pfizer‐BioNTech (BNT162B2)	79 (11), 81 (7); 7/15, 17/19
Mateos-Nozal/2021/Spain34	Cross-sectional (47)	NH (NR)	May–June	R (1)	B.1.1.7 (Alpha)	Pfizer‐BioNTech (BNT162B2)	NR
Càmara/2022/Spain35	Prospective cohort (86)	NH (HCP)	April–May	R+HCP (1)	B.1.351 (Beta)	Pfizer‐BioNTech (BNT162B2)	81.5 (71–100); NR
Mauriz/2023/Spain60	Retrospective cohort (103)	LTCF (NR)	December– February	R+S (1)	NR	Pfizer‐BioNTech (BNT162B2)	87.3 (5.8); 16/50
Zürcher/2022/Switzerland61	Retrospective cohort (84)	NH (NR)	January	R+S (1)	B.1.1.7 (Alpha)	Pfizer‐BioNTech (BNT162B2)	86 (70–90); 7/3
Williams/2021/UK36	Prospective cohort (42)	NH (S)	April	R+S (1)	B.1.617.2 (Delta)	Oxford‐AstraZeneca (ChAdOx1 nCoV‐19 adenoviral	81 (78–86); 7/12
Bart/2021/USA37	Retrospective cohort (76)	NH (NR)	July–August	R+S (1)	AY.119 (Delta)	Pfizer‐BioNTech (BNT162B2) and J&J/Janssen	85; 11/42
Cavanaugh/2021/USA38	Prospective cohort (199)	SNF (HCP-UV)	March–April	R+HCP (1)	R.1	Pfizer‐BioNTech (BNT162B2)	NR
Britton/2021/USA39	Retrospective cohort (463)	SNF (NR)	December– February	R (2)	NR	Pfizer‐BioNTech (BNT162B2)	NR
Fisher/2021/USA40	Cross-sectional (33)	LTCF (R-PV)	January	R (1)	B.1.2	Moderna (mRNA‐1273)	84.6; NR
McEllistrem/2021/USA49	Prospective cohort (146)	CLCNH (NR)	December–January	R (1)	NR	Pfizer‐BioNTech (BNT162B2)	74 (70–80); NR
Ye/2021/USA50	Retrospective cohort (91)	NH (NR)	January–February	R (1)	NR	Pfizer‐BioNTech (BNT162B2)	76.4; 28/45
Gounder/2021/USA51	Cross-sectional (186)	SNF (S-V)	May	R+S (1)	NR	NR	NR
Moline/2022/USA62	Retrospective cohort (91)	SNF (NR)	March–April	R (1)	B.1.351 (Beta)	Pfizer‐BioNTech (BNT162B2)	NR
Lewis/2022/USA63	Retrospective cohort (63)	SNF (NR)	April	R (1)	P.1 (Gamma)	Pfizer‐BioNTech (BNT162B2)	NR
Dale/2022/USA64	Retrospective cohort (109)	SNF (NR)	June–July	R (1)	B.1.616.2 (Delta)	Pfizer‐BioNTech (BNT162B2)	65 (27–92); 17/23

*age in years expressed in mean (SD).

†male/female.

HCP, healthcare professional; LTC, long-term care; LTCF, LTC facilities; NH, nursing home; NR, not reported; PV, partially vaccinated; R, resident; RT-PCR, reverse transcriptase PCR; S, staff; SNF, skilled nursing facility; UV, vaccine as unvaccinated.

AR, CFRs, MRs and hospitalisation rate among residents from ACFS

Overall, the pooled AR during the postvaccine period from all included studies was 41% (95% CI 32% to 49% p<0.01) (figure 2). The pooled estimates decreased significantly among FV residents from 30 studies to an AR of 28% (95% CI 20% to 37%, p<0.01) (online supplemental figure 1a). Pooled ARs among unvaccinated residents from the reported 23 studies revealed significantly higher estimates of 69% (95% CI 50% to 83%, p<0.01) (online supplemental figure 1b). The PV residents from 15 studies demonstrated an AR of 30% (95% CI 11% to 58%, p<0.01) (online supplemental file 1). Random effects meta-analysis calculated an overall CFR of 13% (95% CI 10% to 17%, p<0.01) among residents (figure 3). Data from 21 studies showed an overall mean MR of 6.7% (range 0–25, median 5.4 and IQR 7.5) (online supplemental file 1). The pooled MR among the residents from 33 available studies in the postvaccine period was 5% (95% CI 3% to 6%) (figure 4). The mortality estimate was found to be six times lower among the vaccinated residents 2% (95% CI 1% to 4%, p<0.01) compared with the unvaccinated residents 12% (95% CI 7% to 19% p=0.17) (online supplemental file 1). 25 studies reported a pooled hospitalisation rate of 17% (95% CI 13% to 23%, p<0.01) among the confirmed cases of which only 13 articles had information on the vaccination status of hospitalised cases (online supplemental file 1).^{21–23 25–27 32 34–39 44 45 49 50 52 54–56 58 60 62 64} The hospitalisation rates were six times lower between vaccinated 4% (95% CI 2% to 7%, p<0.01) and unvaccinated residents 27% (95% CI 12% to 51%, p<0.01) after pooling available data from a total of 13 and 9 studies, respectively (online supplemental file 1).^{21 25–27 38 44 58 62} Hospitalisation rates among the vaccinated confirmed cases 14% (95% CI 8% to 23%, p<0.01) declined almost three times lower compared with the unvaccinated confirmed cases 48% (95% CI 32% to 64%, p=0.14) (online supplemental file 1). That all the key summary measure point estimates barely wavered in a leave-1-out sensitivity is indicative of robust findings (online supplemental file 1).

Figure 2. Forest plot of overall attack rate among residents in postvaccine outbreaks in aged care facilities.

Figure 3. Forest plot of case fatality rate of residents in postvaccine outbreaks in aged care facilities.

Figure 4. Forest plot of overall mortality rate among residents in postvaccine outbreaks in care facilities.

VE among residents in ACFs

The PVE rate among the FV residents against COVID-19 infection was found to be 73% (95% CI 49% to 86%, p=0.04, I²=41.5%) based on data from the available studies (n=15) (online supplemental figure 7a). All the residents for this pooled effect measure received Pfizer‐BioNTech (BNT162B2) vaccine except in the study by Williams et al from Canada, where residents received Moderna (mRNA-1273) and Čokić et al from Serbia received Sinopharm. The PVE rate from seven studies among the PV residents also showed an estimate of 73% (95% CI 48% to 95%, p=0.01, I²=68.8%) (online supplemental figure 7b). We found the PVE rate for COVID-19-associated hospitalisation and mortality among FV residents in ACFs was 90% (95% CI 68% to 97%, p=0.39, I²=0.0%) and 83% (95% CI 58% to 93%, p=0.86, I²=0.0%), respectively, compared with unvaccinated residents (online supplemental figure 8,9).

Quality assessment of the included studies

The risk of bias was generally low to moderate after considering the observational nature of the studies. However, heterogeneity was observed both within and across studies. Most of the data from the included studies (97%, n=37) were relevant and reliable in quality, however, validity was unclear in nature for only 21% (n=8). Studies without any obvious methodological flaw reporting relevant data were eligible for inclusion and quality was evaluated accordingly (online supplemental table 1).

Publication bias and meta-regression

There was considerable heterogeneity in the estimates of AR on visually inspecting the funnel plot for publication bias. The inverted funnel plot for CFR and the MR was found symmetrical. Meta-regression analysis revealed the facility size based on occupying residents was the only variable that demonstrated a relationship with the pooled AR (ie, small facility (≤50 residents) vs large facility (>50 residents), p=0.01). We did not find any influence on the key summary measures (AR, CFR) with the vaccine coverage, types of variants among residents within the facilities (online supplemental table 3).

Discussion

We found that COVID-19 vaccination across ACFs had a significant impact in reducing the AR, CFR and MR among residents. Our analysis demonstrates that the risk of SARS-CoV-2 infection among both partially and FV residents remains substantially lower compared with unvaccinated older individuals. The pooled AR of unvaccinated residents developing COVID-19 was almost three times higher decreasing from 69% (95% CI 50% to 83%) to 28% (95% CI 20% to 37%) for FV residents. The pooled AR during the postvaccine period was substantially lower at 28% compared with 45% estimated earlier during the prevaccine period.¹ CFR declined by half compared with the prevaccine period (13% vs 23%) and the MR declined nearly two times lower (11%–5%) following nationwide COVID-19 vaccination, prioritising high-risk older residents in the care facilities. These important findings are consistent with the vaccine effect on the severity of disease reported in experimental studies and outcome estimates from observational studies.^{19 65}

Our study findings demonstrated that two doses of COVID-19 vaccines provide substantial protection in reducing the severity of infection, hospitalisation and deaths resulting from COVID-19 infection among residents in ACFs. This finding underscores the importance of ensuring optimum vaccination coverage as breakthrough infections among FV individuals had predictable neutralising antibody titers and were mild in manifestation as reported in earlier studies.^66–68 Due to age-related immunosenescence, multiple comorbidities and reduced neutralising antibodies among FV older adults, there is undoubtedly a pronounced risk of infection among this susceptible group.^69–71 Earlier research also demonstrated that exposure of SARS-CoV-2 among the vaccinated residents induces a more pronounced immune response and prolonged protection.^{72 73} It is, therefore, highly important to prioritise vaccination in older adults including timely booster doses when eligible.⁷⁴ In addition, pre-employment vaccination for new staff and vaccination of new residents to the facility should commence as early as possible to minimise the risk to the broader population in these at-risk settings.

The PVE among PV older adults was about 69% which is higher than what has been reported in previous studies.^{68 75} Most of the included studies had inadequate information relating to timing intervals between vaccination and COVID-19 infection meaning a subgroup analysis of key summary measures based on timeline following vaccination could not be undertaken. However, our findings show important implications for improvising vaccination strategies for countries with a shortage of vaccine supply. Angyal et al showed cellular and humoral immune response among individuals receiving a single dose of COVID-19 vaccine was comparable to a naturally immune person following SARS-CoV-2 infection within weeks to months.⁷⁶

Early in the pandemic, limited COVID-19 vaccine supply delayed vaccination as per the schedule.^{77 78} However, there is a risk delayed or partial vaccination could potentially generate a less robust immune host that might increase the chance of emerging problematic variants.⁷⁹ Therefore, further research is needed to measure effectiveness of partial vaccination and quantify the risk of emerging new variants to devise an appropriate vaccination strategy.

The structural characteristics of the facility during the management of outbreaks contributed to transmission in a few studies.^{25 80} Orsi et al reported a higher AR among residents residing in double occupancy rooms compared with those living in single rooms.⁴⁵ Earlier studies too reported the presence of a higher crowding index (number of residents per room and bathroom in a care facility) was associated with almost two times (9.7% vs 4.5%, p<0.001) the increased incidence of COVID-19 infection.⁸¹ Therefore, facilities with higher crowding indexes should also be prioritised for vaccination and aim for higher vaccination coverage targets of residents, staff and visitors.

Concurrent surveillance programmes among the staff and care providers in a facility are important to minimise transmission within enclosed settings. We found that unvaccinated staff (eg, healthcare professionals), and caregivers comprised two-thirds of the index cases. Half of these index cases were asymptomatic at the time of diagnosis and a routine surveillance testing strategy resulted in the identification of the cases, prompting facility-wide intervention to halt the disease spread.^{21 30 40 45} These findings particularly highlight the importance of vaccine coverage within this subgroup of the population entering ACFs. With ongoing community transmission and mobility of staff across multiple facilities, it is difficult to causally ascertain the linkage of the outbreaks from the index cases.⁵¹ The possibility of transmitting infection from asymptomatic vaccinated persons carries important policy implications. Robust surveillance strategies for residents and staff are essential to identify the index cases early to minimise the risk of transmission within the ACFs.

Vaccine hesitancy and acceptance have been a major concern in earlier studies among healthcare professionals.^{82 83} Biswas et al reported an average prevalence of COVID-19 vaccine hesitancy of 22.5% ranging from 4.3% to 72% worldwide among healthcare workers.⁸⁴ A recent study from USA shows that nurses and assistant nurses are less likely to receive a COVID-19 vaccine compared with physicians, thereby making this workforce both vulnerable to disease and also acting as a potential disease spreader in ACFs.⁸⁵ Despite countries introducing mandates for vaccination among healthcare professionals, these measures might increase staff losses and foment mistrust between staff and institutions resulting in a negative impact on already under-resourced aged care services.⁸⁶

Given the high prevalence of vaccine hesitancy among such high-risk professionals, effective communication and education about COVID-19 vaccines for such high-risk groups should be implemented with careful consideration given to the adoption of mandates.^87–89 Provision of paid sick leave will improve compliance of home isolation for positive cases reducing the risk to colleagues and the residents.⁹⁰

The variance in summary measures (AR, CFR, MR) in our analysis can be attributed to varying protection towards evolving characteristics of variant of concern (VOC) (online supplemental table 2). Phylogenetic analysis and real-time data on genomic sequencing are essential to supplement outbreak management and clearly demonstrate the need for rapid and affordable genomic information for outbreak prevention and management within enclosed settings. Residents fully immunised with mRNA COVID-19 vaccines experienced severe illness from the evolving variants and calculated VE against SARS-CoV-2 infection ranged from 35% to 85% which is consistent with our estimates.⁶⁸ Potential immune escape from mutations in these VOC increases virus transmissibility and reduces the neutralising capacity of antibodies, increasing the risk of infection and severe disease in older adults.^{44 80 91–94} Therefore, further research on developing a pan-COVID-19 vaccine could be an effective intervention in battling this highly variable SARS-CoV-2 pathogen.^{95 96}

This study has several limitations. The majority of the included studies are from high-income countries and contain small sample sizes which limited the generalisability of our findings. Many of the outbreak reports are retrospective in design and subject to selection bias for the effect estimate. Differences in service provision from the care facilities vary from country-to-country housing more vulnerable residents than others, that is, dementia, learning disabilities and skilled nursing homes for assisted living. Such differences affect infection and prevention control policies that may influence the overall surveillance strategies and outcome measures reported in the included studies. Our meta-regression analysis did not find any influence of vaccine coverage, variants of strain on the key summary measures. Multiple factors, for example, heterogeneous testing strategy in different facilities, vaccine-lag time to induce an immune response in an individual, structural factors of a facility influencing transmission dynamics, unknown status of past infection among residents, baseline status of a resident in an unwillingness to receive the vaccine along with resident and staff adherence to routine testing surveillance are important confounding variables to consider when interpreting the findings.^97–100 Following vaccination implementation, relaxation of lockdown and visitation policies happened across countries and determination of the index case is difficult to locate the source of transmission. With multiple stakeholders within the dynamic environment of ACFs such a scenario might have impact on identification of index cases and subsequent disease transmission within the enclosed settings.¹⁰¹ In addition, the therapeutic effect of interventions such as COVID-19 specific antiviral drugs and concurrent multipotent COVID-19 prevention strategies within the facilities, which are beyond the scope of this review, might have influenced our findings. Ascertainment of SARS-CoV-2 infection during surveillance was performed using mass rapid antigen testing (RAT) or a symptom-based testing approach. It is known that RAT tests have varied and low sensitivity leading to underestimation and low specificity, increasing the risk of false-positive cases. There was considerable heterogeneity in the outcomes and person-time following vaccination dosages, which were inconsistently reported. Initially, asymptomatic cases might have developed symptoms later which could have impacted estimation of actual disease onset date, and hence introduced bias in PVE. There were inadequate data to explore the effect of waning immunity on the risk of contracting infection or disease severity among older residents. Additionally, we could not measure VE with time intervals of received doses in the absence of severity of illness, symptomatic status, hospitalisation and mortality endpoints. The VE analyses were not adjusted for potential confounders, for example, baseline health condition, past infection or undetected infection status which may bias the protective effect estimates. Additionally, we could not conduct a subgroup analysis for the outcome measures based on the mRNA vaccine type administered to the investigated cohort. However, despite these limitations, we remain confident in our meta-analysed estimates.

The strengths of this study included a rigorous screening methodology using validated search terms also used in our prevaccine study and included quality reports for meticulous extraction.¹ All studies included in our review were single centre based and of moderate quality. Cumulative published evidence substantially underscores the impact of vaccination in reducing the AR and CFR compared with pre-COVID-19 era estimates.¹

Conclusion

Our findings reaffirm the impact of vaccination as a key public health measure to minimise the COVID-19 disease burden in the ACFs. We found that the minimum VE in ACFs was 73% (95% CI 0.49% to 0.86%) in preventing COVID-19 infection. In addition, we found that ARs (28% vs 45%), CFRs (13% vs 23%) and hospitalisation rates (17% vs 37%) of COVID-19 outbreaks in ACFs after the introduction of COVID-19 vaccine were far lower when compared with the prevaccine period. Facilities with higher crowding indexes should be prioritised for vaccination and should advocate for higher vaccination coverage among staff and residents. Overall, ensuring optimal vaccination coverage in the ACF setting is critical to minimising disease burden in this vulnerable population.

Data availability statement

Data are available on reasonable request. The authors declare that the data collected were gathered from publicly available databases and are available on reasonable request.

Ethics statements

Patient consent for publication

Not applicable.

Footnote

Twitter @M_R_Hashan

Contributors MRH and GK designed the study. MRH, CK and GK designed the literature search. GK supervised the literature search and review process. MRH and GC reviewed the citations and reports and extracted the data. MRH and NS analysed the data and visualisation. MRH, NS and GK interpreted the results. MRH, GC, NS and GK wrote the first draft of the manuscript. GK is the gurantor of the study. All authors revised successive drafts of the paper and have approved the final version for publication.

Funding This work was supported by a Queensland Advancing Clinical Research Fellowship awarded to GK by Queensland Health’s Health Innovation, Investment and Research Office (HIRO), Office of the Director-General.

Disclaimer The funders had no role in study design, data collection or analysis, writing of the article, or the decision to publish. The corresponding author had access to all the data in the study and the final responsibility for the decision to submit the article for publication.

Competing interests None declared.

Patient and public involvement Patients and/or the public were not involved in the design, or conduct, or reporting, or dissemination plans of this research.

Provenance and peer review Not commissioned; externally peer reviewed.

Supplemental material This content has been supplied by the author(s). It has not been vetted by BMJ Publishing Group Limited (BMJ) and may not have been peer-reviewed. Any opinions or recommendations discussed are solely those of the author(s) and are not endorsed by BMJ. BMJ disclaims all liability and responsibility arising from any reliance placed on the content. Where the content includes any translated material, BMJ does not warrant the accuracy and reliability of the translations (including but not limited to local regulations, clinical guidelines, terminology, drug names and drug dosages), and is not responsible for any error and/or omissions arising from translation and adaptation or otherwise.

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