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- Springer Journals
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- Copyright © The Author(s) 2023
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- 2047-2994
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- 10.1186/s13756-023-01215-1
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Abstract
Background Risk factors for nosocomial COVID‑19 outbreaks continue to evolve. The aim of this study was to investigate a multi‑ ward nosocomial outbreak of COVID‑19 between 1st September and 15th November 2020, occurring in a setting without vaccination for any healthcare workers or patients. Methods Outbreak report and retrospective, matched case–control study using incidence density sampling in three cardiac wards in an 1100‑bed tertiary teaching hospital in Calgary, Alberta, Canada. Patients were confirmed/probable COVID‑19 cases and contemporaneous control patients without COVID ‑19. COVID ‑19 outbreak definitions were based on Public Health guidelines. Clinical and environmental specimens were tested by RT‑PCR and as applicable quantitative viral cultures and whole genome sequencing were conducted. Controls were inpatients on the cardiac wards during the study period confirmed to be without COVID ‑19, matched to outbreak cases by time of symptom onset dates, age within ± 15 years and were admitted in hospital for at least 2 days. Demographics, Braden Score, baseline medications, laboratory measures, co‑morbidities, and hospitalization characteristics were collected on cases and controls. Univariate and multivariate conditional logistical regression was used to identify independent risk factors for nosocomial COVID‑19. Results The outbreak involved 42 healthcare workers and 39 patients. The strongest independent risk factor for nosocomial COVID‑19 (IRR 3.21, 95% CI 1.47–7.02) was exposure in a multi‑bedded room. Of 45 strains successfully sequenced, 44 (97.8%) were B.1.128 and differed from the most common circulating community lineages. SARS‑ CoV‑2 positive cultures were detected in 56.7% (34/60) of clinical and environmental specimens. The multidisciplinary outbreak team observed eleven contributing events to transmission during the outbreak. Conclusions Transmission routes of SARS‑ CoV‑2 in hospital outbreaks are complex; however multi‑bedded rooms play a significant role in the transmission of SARS‑ CoV‑2. *Correspondence: John M. Conly John.Conly@albertahealthservices.ca; jconly@ucalgary.ca Full list of author information is available at the end of the article © The Author(s) 2023. Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http:// creat iveco mmons. org/ licen ses/ by/4. 0/. The Creative Commons Public Domain Dedication waiver (http:// creat iveco mmons. org/ publi cdoma in/ zero/1. 0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data. Leal et al. Antimicrobial Resistance & Infection Control (2023) 12:21 Page 2 of 13 Keywords COVID‑19, Nosocomial, Outbreak, Risk factors, Case–control, Incidence density sampling, Rate ratio, Viral culture, Environment Background was conducted during the pandemic by our provincial The risks of nosocomial transmission of viral respiratory healthcare organization using the COVID-19 Symptom infections [1] have been known for many years and Monitoring Tool [9]. All patients were screened at the have been recognized in the SARS-CoV-2 pandemic time of initial presentation for respiratory symptoms, [2]. Nosocomial transmission of SARS-CoV-2 has been travel, and COVID-19 exposure to quickly identify those reported in acute care institutions from many countries, who required additional precautions. For all admitted including Canada [3–6] and highlight how rapidly patients, the COVID-19 Symptom Monitoring Tool [9] SARS‐CoV‐2 can spread across hospital wards. Previous was completed by nursing staff at least once daily for the outbreaks have revealed common themes, including duration of the patient’s hospitalization and recorded in (1) significant disruption of health care services, (2) the patient’s medical chart. The outbreak was first declared th the need to enhance infection prevention and control on 19 September 2020 on Wards A and C, 48 h after (IPC) measures (3) the promotion of a culture that IPC five epidemiologically linked patients tested positive from is everyone’s responsibility and (4) that all healthcare SARS-CoV-2 nasopharyngeal (NP) swabs sent on Sept workers (HCWs) need vigilance when assessing patients 17–18, 2020. The symptoms of these patients were thought for COVID-19, appropriate donning and doffing of initially to be due solely to their underlying cardiac disease. th personal protective equipment (PPE), and to ensure Then the outbreak was subsequently declared on 30 appropriate environmental cleaning [7, 8]. However, September 2020 on Ward B. There was limited community evidence continues to evolve on the risk factors for transmission during this time period (active cases, 30.7 per nosocomial SARS-CoV-2 infections among hospitalized 10,000 population) [10]. patients. We investigated a multi-ward nosocomial outbreak Outbreak investigation of SARS-CoV-2 beginning in September 2020 with the Case definition and contact tracing following objectives: (1) to describe a nosocomial SARS- Case definitions for confirmed or probable cases of CoV-2 infection outbreak investigation on three linked COVID-19, outbreak and close contact definitions were cardiac wards in our acute care tertiary hospital and (2) based on Public Health guidelines (Additional file 1). to conduct a matched-case control study to determine ward and patient-related risk factors for nosocomial Data collection for outbreak investigation and response transmission of SARS-CoV-2 among cardiac patients. Baseline pre-existing hospital and cardiac unit infection control measures along with details of the multidisciplinary outbreak response of investigations Methods and control measures that were initiated at the Setting description of hospital and cardiac wards declaration of the outbreak are outlined in Additional Our facility is an 1100-bed tertiary teaching hospital in file 1. The multidisciplinary outbreak team met Calgary, Alberta. The three cardiac wards included two regularly until the outbreak subsided and collated medical cardiac wards on the same floor separated by an investigation findings and general observations into elevator bank (Ward A and B) and one cardiac intensive tabular format. Index date for a case was either the care ward (Ward C) two floors above the medical cardiac date symptoms started or the date of a laboratory wards with frequent patient and HCW movement confirmation for SARS-CoV-2, whichever came first. between the wards. There were 294 admissions and 1,991 Isolation information was collected from the patient’s patient-days per month across the cardiac wards during medical record (electronic [EMR] and paper) and the fiscal 2020/2021 year. Wards A and B each had six through discussions with the unit manager. The room single-bed, six two-bed, and five four-bed rooms, while on the cardiac wards where a patient with COVID- Ward C had four single-bed, seven two-bed, and one four- 19 was deemed to have acquired the infection (room bed rooms. As per our provincial healthcare organization attribution) was the room where the patient stayed policy, universal admission RT-PCR laboratory testing in within five days prior to symptom onset (based on for SARS-CoV-2 was not employed at any time during a median incubation time of 5 days for the original the pandemic. Universal admission symptom screening Wuhan strain) [11]. Information on room movement L eal et al. Antimicrobial Resistance & Infection Control (2023) 12:21 Page 3 of 13 and shared bathrooms was collected from the EMR. wards was amplified by multiplex PCR according to HCWs linked to the outbreak were interviewed by the ARTIC V1 or V3 with clean up and no dilutions Workplace Health and Safety (WHS) using a detailed protocols [15–17] using the Resende oligos [18] as questionnaire similar to the COVID-19 Symptom 2000-bp amplicons with sequencing done using Oxford Monitoring tool [9] used for patients and included Nanopore. Lineages were assigned using pangolin [19]. additional questions for forward and backwards contact tracing. Visitors to the affected wards were notified and Case–control study encouraged to be tested in the community via Public Study design and population Health if symptomatic or exposed to a known case A retrospective matched case–control study analyzed the on the wards. Public Health interviewed all visitors medical records of patients implicated in the COVID-19 who tested positive for contact tracing purposes and outbreak and matched patient controls using incidence symptom ascertainment. density sampling of a dynamic population [20, 21] from our hospital between 1st September 2020 and 15th November 2020. Case patients were defined as admitted inpatients Ventilation assessments during the study period who were found to have a Ventilation, measured in air exchanges per hour (AEH) laboratory-confirmed COVID-19 infection during and percentage outside air were assessed on the three routine medical care and that were attributed to the wards by Facilities, Maintenance, and Engineering cardiac wards as per outbreak protocols (Additional and interpreted relative to the Canadian Safety file 1). Association standards for Heating, Ventilation, and Air Control patients were defined as inpatients present Conditioning (HVAC) Systems in Health Care Facilities on the cardiac wards during the study period who (CSA-Z317.2-15). either tested negative for SARS-CoV-2, regardless of signs or symptoms, after the outbreak was declared, or were presumed negative if they were identified prior Laboratory and virological methods to the outbreak declaration. Of the controls, 80% of the Serial nasopharyngeal swabs and occasionally throat individual control patients were discharged after the swabs were collected by experienced personnel and outbreak was initially declared and therefore had serial tested for SARS-CoV-2 using a validated real-time asymptomatic testing, all of which were negative. Of the RT-PCR assay targeting the E gene with internal controls remaining controls, 20% were discharged prior to the [12] to obtain cycle threshold (Ct) values. Clinical and start of the outbreak and would only have been tested environmental specimens obtained from consenting for SARS-CoV-2 if they presented with symptoms. patients from the affected wards were sent to the Li On clinical review, none of these patients had any Ka Shing Institute for Virology (University of Alberta) symptoms suggestive of COVID-19 during or after their for quantitative viral culture testing as per Lin et al. hospitalization, and in addition 71% of this group had [13] and PCR assays were performed according to RT-PCR tests done pre- and post-discharge which were methods previously described [12–14]. Environmental all negative. The remaining five control patients who samples were obtained from rooms with known positive were not tested for SARS-CoV-2 had multiple doctors’ patients with a focus on high-touch areas including visits with no documentation of symptoms. Control call bells, bedrails, telephones, cellphones, bathroom patients were matched to cases if the timing of their sites, commodes, and mobile medical equipment such stay on the outbreak wards overlapped symptom onset as pulse oximeters or other oxygen monitoring probes. dates of the cases, by age within + /− 15 years of the Symptomatic patients or HCWs were tested for SARS- case age and had a minimum hospital admission of at CoV-2 and serial asymptomatic SARS-CoV-2 RT-PCR least 2 days. Controls were initially matched in a n:1 prevalence testing was done on all inpatients (q2- 5 days) ratio with replacement, whereby each case could have a during the outbreak only and was arranged and strongly variable number of controls with some controls used as a recommended for HCWs (q5 days) who worked on the control for multiple cases [22]. Each case was matched to outbreak wards in the 14 days prior to and during the controls 1:5. Controls were randomly selected for cases outbreak [9]. that had more than five matched controls. For cases who had symptom onset during their hospital admission, exposures were examined 7-days prior to Whole genome sequencing their COVID-19 symptom onset date. For cases who had The full genome of SARS-CoV-2 strains obtained from symptom onset after discharge, hospital exposures were the NP swabs of HCWs and patients from the cardiac Leal et al. Antimicrobial Resistance & Infection Control (2023) 12:21 Page 4 of 13 examined in the 7-days prior to discharge. For controls, proportional to the number times they were matched to the dates when outbreaks were declared were considered a case, to account for the matching with replacement. the index date for controls. For controls admitted to Statistical significance was set at p < 0.05. All significant Ward A, 19 September was the index date, and for variables in the univariate analysis were considered controls on Ward B, 30 September was the index date. for inclusion in the multivariate conditional logistic Exposures for controls were examined in the 7-days prior regression analysis. Where appropriate, a sensitivity to the start of the outbreak on Ward A (19th September) analysis for the multivariate regression was performed or Ward B (30th September), depending on when the using different cut-offs depending on the variable. As control case was admitted. Controls admitted after the the cases and controls were matched on time based on 30th of September outbreak were excluded. symptom onset date, with exposures considered in a fixed time frame prior to index date, the parameters estimated Data collection from the logistic regression are interpreted and reported Data on case and control patients were collected using as incidence rate ratios [20, 21]. The analysis was retrospective chart review of medical records using a performed using R version 4.1.1 (IBM Corp, Armonk, standardized data collection instrument. Demographics NY, USA). data, the Braden Score, baseline medications and laboratory measures were collected from the EMR. Results Laboratory measures were categorized as abnormal if the Outbreak description results fell outside the normal ranges for each measure The cardiac wards had 685 admissions between 1st as defined by laboratory and clinical criteria (Additional September 2020 and 15th November 2020, with an file 1). Comorbidities were collected from admissions average length of stay of 4.6 days. During the outbreak in the two years prior to the index date for cases and period, there were 81 cases: 42 HCWs and 39 patients controls from the Discharge Abstract Database (DAD). with 10 recorded patient deaths (Fig. 1). Hospitalization characteristics were collected from the Over half of the patients with COVID-19 were males Admission, Discharge, Transfer database (Additional (56.4%), while HCWs with COVID-19 were mostly file 1). females (70.4%). The mean age of patients was 75 years (SD 12), and 38 years (SD 12) among HCWs. The attack Statistical analysis rate among patients was 5.7%, with a case fatality rate Outbreak attack rates among admitted patients and of 25.6%. All patients and visitors who were found to be case-fatality rates were calculated. Descriptive statistics SARS-CoV-2 RT-PCR positive were symptomatic, while and univariate conditional logistic regression were used 40/42 (95.2%) HCWs were found to have symptoms to compare variables, with controls weighted inversely [23]. Although all patients were tested serially while Fig. 1 Epidemic curve by index date* for patients across the cardiac wards. Case numbers ( Ward: Number): Patients ( Ward A:27, Ward C:1, Ward B:11); Healthcare workers, HCWs ( Ward A:33, Ward C:0, Ward B:9), and Visitors ( Ward A:5, Ward C:0, Ward B:0). *Index date was either the symptom onset date or the date of laboratory confirmation for SARS‑ CoV‑2, whichever came first L eal et al. Antimicrobial Resistance & Infection Control (2023) 12:21 Page 5 of 13 Fig. 2 Case Linkage by HCW and Patient Flow Map on Ward A. On 19 September 2020, a COVID‑19 outbreak was declared at our facility on Ward A following identification and confirmation of a nosocomial COVID ‑19 case on Ward A (Patient 28) admitted on 10 September 2020, followed by two patients (Patient 1 and 4) admitted on 11 and 12 September, respectively, that enabled additional transmission events via HCWs to Ward C. Patient 4 was considered to have an exposure from a person visiting the hospital from the community. The outbreak extended to Ward B on 30 September 2020. Black Circle—patient (red outline is a patient transferred to Ward B); Brown Diamond—HCW; Blue Pentagon—visitor. Arrows—transmission pathways (dotted line indicates less likely transmission pathway); Black arrows—patient to staff; Green arrows– patient to patient; Red arrows— HCW to HCW; Orange arrows—to another unit; Blue arrows—HCW to patient; Red dashed line square around patients 1 and 4 and the HCW labelled as R—major nodes of forward transmission in hospital after the outbreak was declared, testing was Laboratory, virologic, and ventilation results not mandatory for HCWs but a total of 1497 RT-PCR Of the 73 and 10 pre- and post-cleaning environmental tests were collected from 1,011 HCWs, of which 376 swab samples collected on Ward A 11 (15.1%) and HCWs were identified as core nursing and management one (10%) were RT-PCR positive for SARS-CoV-2 staff, excluding physicians, residents, allied health (p = 0.6674) (Additional file 2). On Ward B, 3/55 professionals, and lab services who were much smaller in (5.4%) randomly sampled and 9/13 (69.2%) targeted number and many of whom were transient on the affected environmental swabs (stethoscope, pulse oximeter, wards. HCW compliance for SARS-CoV-2 prevalence gown, bedside tables/flooring, urine catheter bag, testing was very high during this outbreak given that this bedrail, inhaler) were RT-PCR positive for SARS- was the first major outbreak in our hospital during the CoV-2, respectively. There were 64 specimens collected pandemic and was in an unvaccinated population. Details directly from 8 consenting patients, including clinical of the symptoms in the patients, HCWs and visitors are specimens and their immediate environment from reported elsewhere [9] and were found in 97.7% of cases, Wards A and B, all of whom had NP Ct values < 20 (N with influenza-like–illness (ILI) symptoms and signs gene; range 11.4–19.2). SARS-CoV-2 was cultured from being found in 84.9% of all RT-PCR positive cases. The 34/60 (56.7%) clinical and environmental specimens outbreak network map is provided in Fig. 2. Leal et al. Antimicrobial Resistance & Infection Control (2023) 12:21 Page 6 of 13 Table 1 Potential sources and contributing events to transmission of SARS‑ CoV‑2 contributing to the outbreak on the cardiac wards Lapses in routine practices and Failure to isolate symptomatic patients at symptom onset (10 symptomatic patients in hospital were not additional precautions isolated for a total of 38 days (range 1–10 days) before outbreak were declared) Failure to recognize initial cases with illness symptoms compatible with COVID‑19 due to crossover with symptoms common to cardiac patients with heart failure (symptomatic patients were not isolated for a total of 15 days (range 1–3) after the outbreaks were declared) Inappropriate discontinuation of contact/droplet precautions in five patients identified as close contacts of known cases, who initially tested negative (only to test positive later) Premature (prior to 14‑ day incubation period) discontinuation of contact/droplet precautions Suboptimal donning/doffing and hand hygiene by healthcare workers Uncertainty around performance of a point‑ of‑ care risk assessment Increased patient‑to ‑patient exposures Shared rooms and bathrooms among 34 (89.5%) patients leading to close contact between patients and potential transmission events through either respiratory droplets/particles across a continuum of sizes and/or contact (direct or indirect) Transfer of seven patients, identified as close contact to other wards resulting in two forward transmission events Lapses in environmental cleaning Potential lapses in environmental cleaning leading to fomite transmission HCW and visitor exposures Healthcare worker‑related transmission events (e.g., shared breakrooms, carpooling, socializing outside of work) and transmission events related to HCWs interacting with patients between wards up until the outbreak was declared and for several days thereafter before cohorting was strictly enforced Potential visitor‑to ‑patient transmission with observed visitor non‑ compliance with masking and distancing recommendations 0 5 with titres of ranging between 5.0 × 10 and 5.2 × 10 Four controls were excluded based on admission dates pfu/ml (Additional file 2 : Table A3). resulting in 70 different individual control patients Of the 78 NP specimens collected from both patients weighted by the number of times they were matched and HCWs who were confirmed to be related to to a case. Table 2 shows demographic data, underlying the cardiac wards and were successfully sequenced diseases, laboratory findings and mobility findings (n = 45), 44 (97.7%) were SARS-CoV-2 lineage B.1.128. seven days prior to the index date for cases and controls. Community samples sequenced for SARS-CoV-2 Within the seven days prior to the index date, cases during the same period differed substantially from the were in hospital longer than controls (median 7 days vs. outbreak strain with B.1.128 representing only 8.9% of 4.4 days). The overall median and mean length of stay the circulating lineages at the time in our local setting on the cardiac wards prior to the index date was similar and less than 1% across almost 2000 typed strains between cases and controls (mean 12.3 vs 13.1 days, across the province at the time. median 7.8 vs 6.0 days, respectively). Of the cases, 75.9% Ventilation, on Wards A, B, and C ranged from 4.3– (31/39) had underlying chronic diseases (Additional 10.7, 6.9–14.3, and 10.5–13 AEH, respectively, all with file 3). Compared with the controls, the cases had a 100% outside air, meeting or exceeding the Canadian higher prevalence of fluid/electrolyte disorders (35.9% Standards Association (CSA) standards of a minimum vs. 14.3%, p = 0.001) and neurological disorders (10.3% outdoor AEH of 4 for 100% outside air. vs. 2.9%, p = 0.020). Prior to symptom onset, cases were also more likely to have lymphopenia (46.1% vs. Sources and contributing events of transmission 28.6%, p = 0.016), were on a diuretic longer (3.03 days The multidisciplinary outbreak team, through its vs. 2.41 days, p = 0.031) and immunosuppressive agents investigations, identified eleven potential sources and longer (0.52 days vs. 0.05 days, p = 0.003) than controls. contributing events to transmission during this cardiac Prior to symptom onset, cases were less likely than ward outbreak which are summarized in Table 1. controls to walk occasionally or frequently (69.2% vs. 85.7%, p = 0.0001). Case control study Characteristics of hospital stay Clinical characteristics of patients Patients who spent more than 50% of their hospital The case control study included all 39 case patients stay in a single-bed room, had a 63% (IRR 0.37, 95% CI matched to 183 controls, of which 74 were different 0.15–0.92) lower rate of acquiring COVID-19 in hospital individuals acting as control patients (Additional file 3). during this outbreak (Table 3), whereas patients who L eal et al. Antimicrobial Resistance & Infection Control (2023) 12:21 Page 7 of 13 Table 2 Patient characteristics prior to index date during COVID‑19 outbreak Variables Nosocomial COVID‑19 Matched control IRR P value b b N = 39 (%) N = 70 (%) (95%CI) Age, years, median (IQR) 76 (15.5) 73 (13) 1.04 (1.00–1.07) 0.024 Sex Male 23 (59.0%) 49 (70.0%) 0.62 (0.36–1.04) 0.070 Underlying disease Other Neurological Disorders 4 (10.3%) 2 (2.9%) 2.04 (1.12–3.74) 0.020 Fluid/Electrolyte Disorders 14 (35.9%) 10 (14.3%) 3.16 (1.57–6.37) 0.001 Elixhauser score (AHRQ) Median (IQR) 6 (19.5) 7 (14) 1.03 (‑1.05) 0.039 Mean (± SD) 9.87 (11.72) 8.38 (9.44) Laboratory findings Abnormal WBC count 5 (12.8%) 13 (18.6%) 0.63 (0.31–1.30) 0.212 Abnormal Lymphocyte 18 (46.1%) 20 (28.6%) 1.82 (1.12–2.94) 0.016 Abnormal Creatinine 18 (46.1%) 24 (34.3%) 1.49 (0.94–2.35) 0.087 Abnormal Platelet 5 (12.8%) 7 (10.0%) 1.00 (0.57–1.78) 0.992 Abnormal Hemoglobin 18 (46.1%) 34 (48.6%) 0.86 (0.56–1.32) 0.492 Abnormal Neutrophil 9 (23.1%) 15 (21.4%) 1.01 (0.58–1.74) 0.984 Mobility‑slightly limited or no limitations 34 (87.2%) 61 (87.1%) 1.14 (0.54–2.44) 0.726 Activity‑ walks occasionally or frequently 27 (69.2%) 60 (85.7%) 0.38 (0.23–0.62) 0.0001 Braden score, median (IQR) 20 (18–21) 20 (19–21) 0.97 (0.90–1.05) 0.482 Medications Days on ACE inhibitors, mean (SD) 0.82 (1.98) 0.82 (1.85) 0.99 (0.85–1.16) 0.920 Days on angiotensin II inhibitors, mean (SD) 1.05 (2.22) 0.99 (2.20) 1.03 (0.93–1.13) 0.604 Days on angiotensin receptor blockers and neprilysin 0.11 (0.71) 0.06 (0.33) 1.29 (0.78–2.14) 0.321 inhibitors, mean (SD) Days on diuretic, mean (SD) 3.03 (3.16) 2.41 (2.83) 1.09 (1.01–1.18) 0.031 Days on immunosuppressive agents, mean (SD) 0.52 (1.84) 0.05 (0.51) 1.33 (1.10–1.60) 0.003 ACE angiotensin-converting enzyme, AHRQ Agency for Healthcare Research and Quality, CI confidence interval, IQR interquartile range, IRR incidence rate ratio, SD standard deviation Index date for cases was either the symptom onset date or first laboratory confirmation for SARS-CoV-2, whichever came first. Index date for controls was when the outbreak was declared, either 19 September 2020 or 30 September 2020 Number and percentages displayed, unless otherwise indicated for continuous variables Only those comorbidities that were significantly different between cases and controls are displayed. Additional file 3 lists results for all comorbidities Abnormal values based on laboratory measure values falling outside normal ranges as defined by laboratory and clinical criteria multivariate regression was performed using different spent more than 50% of their hospital stay in a multi- cut-offs (25%, 75%) for percentage of exposure time in bedded room had nearly twice the rate of acquiring multi-bedded rooms. The rate ratio of a nosocomial COVID-19 in hospital (IRR 1.86, 95% CI 1.17–2.94). COVID-19 case increased from 1.89 (95% CI 1.04–3.43) Specifically, patients that were in multi-bedded rooms between four and seven days were significantly more at the > 25% cut-off to 3.32 (95% CI 1.47–7.02) at the likely to acquire COVID-19 (IRR 3.89, 95% CI 2.28–6.65) > 75% cut-off for percentage of time spent in a multi- compared to patients who spent less than or equal to two bedded room (Additional file 3). days in a multi-bedded room. Control measures and interventions Patient risk factors for nosocomial COVID‑19 outbreak Control measures included but were not limited to: active The multivariate analysis (Table 4) revealed that versus passive fit-for-work screening among HCWs fluid/electrolyte or neurological disorders, days on with staff symptom screening and temperature checks immunosuppressive agents, and percent of exposure in a multi-bedded room were independent risk factors for nosocomial COVID-19. A sensitivity analysis for the Leal et al. Antimicrobial Resistance & Infection Control (2023) 12:21 Page 8 of 13 Table 3 Characteristics of the hospital stay for cases and Table 4 Independent risk factors for nosocomial COVID‑19 from controls of the COVID‑19 outbreak multivariate analysis Variables Nosocomial Matched IRR (95%CI) P value Variables aIRR 95%CI P value COVID‑19 No. control No. (%) (%) Age 1.04 1.00–1.08 0.073 Underlying disease Percent of exposure on single room Fluid/electrolyte disorders 3.82 1.62–9.02 0.002 0–50% of 36 (92.3%) 55 (78.6%) Reference Other neurological disorders 2.66 1.32–5.38 0.006 time Medications > 50% of 3 (7.7%) 15 (21.43%) 0.37 0.031 time (0.15–0.92) Days on diuretic 1.05 0.95–1.15 0.331 Percent of exposure on double room Days on immunosuppressive 1.39 1.06–1.83 0.018 agents 0–50% of 26 (66.7%) 46 (65.7%) Reference time Elixhauser score (AHRQ) 0.97 0.93–1.01 0.132 > 50% of 12 (33.3%) 24 (34.3%) 0.76 0.310 Abnormal lymphocyte 1.38 0.75–2.55 0.302 time (0.44–1.30) Percent of exposure on multi‑bedded room Percent of exposure on multi‑bedded room 0–50% of time Reference Reference Reference 0–50% of 20 (51.2%) 45 (64.3%) Reference > 50% of time 3.21 1.47–7.02 0.003 time AHRQ agency for healthcare research and quality, CI confidence interval, aIRR > 50% of 19 (48.7%) 25 (35.7%) 1.86 0.008 adjusted incidence rate ratio time (1.17–2.94) *Age, neurological disorders, fluid/electrolyte disorders, Elixhauser Days in single room (two‑ day intervals) score, lymphocyte levels, activity, days spent on diuretics, days spent on ≥ 0, ≤ 2 35 (89.7%) 57 (81.4%) Reference immunosuppressive agents, and time spent on single bed and/or multi-bed rooms from univariate analysis were included in multivariate analysis. Activity > 2, ≤ 4 2 (5.1%) 9 (12.9%) 0.44 0.140 was removed due to missing data, and of the variables capturing room use, (0.15–1.31) only the percent of exposure in a multi-bed room was included due to heavy > 4, ≤ 7 2 (5.1%) 4 (5.7%) 0.82 0.709 multicollinearity between these variables (0.29–2.31) Days in double room (two‑ day intervals) ≥ 0, ≤ 2 28 (71.8%) 46 (65.7%) Reference the most responsible healthcare practitioners, with IPC > 2, ≤ 4 1 (2.6%) 11 (15.7%) 0.17 0.069 approval, use of dedicated bedside commodes in two-bed (0.02–1.15) and multi-bedded rooms with shared toilets and blocking > 4, ≤ 7 10 (25.6%) 13 (18.6%) 0.74 0.300 beds to reduce the number of multi-bedded rooms being (0.41–1.31) used. Days in multi‑bedded room (two ‑ day intervals) ≥ 0, ≤ 2 18 (46.2%) 50 (71.4%) Reference Discussion > 2, ≤ 4 5 (12.8%) 11 (15.7%) 1.15 0.686 (0.58–2.30) Our study is one of several observational studies > 4, ≤ 7 16 (41.0%) 9 (12.9%) 3.89 0.000 exploring risk factors for patient COVID-19 acquisition (2.28–6.65) in hospitals [25–32]. There were several factors which CI confidence interval, IQR interquartile range, IRR incidence rate ratio, SD were identified during this outbreak in a setting without standard deviation vaccination for any HCWs or patients which may have facilitated the transmission events to occur. Failure to isolate symptomatic patients on symptom onset likely twice per shift; continuous masking and eye protection led to transmission via close contact [33] through by HCWs; enhanced education on PPE including a either respiratory droplets/particles across a continuum PPE Safety Coach Program [24]; ward logs for tracking of sizes, and/or contact (direct and indirect) routes staff and physicians entering the wards, continuation of transmission within shared rooms/bathrooms. A of asymptomatic testing every five days for as long as retrospective cohort study found in a crude analysis the HCW worked on any impacted ward, exclusion of of 122 patients across three outbreak wards that being non-essential HCWs (e.g. students, volunteers) on the exposed to a symptomatic COVID-19 patient within affected wards; and HCW cohorting on all outbreak the same 4-bed bay regardless of proximity in the room wards, aided by a single-site order restricting HCWs to was associated with doubling the risk of becoming only work on a specific ward without moving between a case (crude RR, 2.3, 95% CI 1.42–3.65) [27]. In a wards. Other control measures included, visitation matched case–control by Aghdassi et al. [28], the restrictions, enhanced cleaning of high touch or shared multivariate analysis revealed that presence on a ward equipment, symptom screening twice daily for patients that experienced a COVID-19 outbreak (aOR 15.9, 95% on all outbreak wards, discontinuation of precautions by L eal et al. Antimicrobial Resistance & Infection Control (2023) 12:21 Page 9 of 13 infection can alter levels and/or activities of hormones CI 2.5–100.8) and documented contact with a COVID- that depend on cell volume (e.g. insulin) and/or balances 19 case (aOR 23.4, 95% CI 4.6–117.7) to be the primary total body water (e.g. aldosterone), which increases ACE2 factors for nosocomial COVID-19 infections in patients receptors potentially making individuals more susceptible [28]. This latter study and the results of our outbreak to infection [41]. It is also possible that by virtue of their investigation supports the need to preemptively isolate underlying cardiac conditions, these patients may have patients known to be exposed to cases. had a higher degree of pre-existing fluid and electrolyte Based on our findings, patients who spent > 50% of disorders. their admission in a multi-bedded room had 3.2 times Many studies have reported on the identification of the rate of acquiring COVID-19. Other observational SARS-CoV-2 RNA on inanimate surfaces; however, some studies have demonstrated that multi-bedded rooms authors have suggested that the risk of transmission of versus one-to-two bedded rooms and the use of shared SARS-CoV-2 through fomites is low [42]. A recently toilets were more common among nosocomial COVID- published systematic review identified that infectious 19 cases compared to controls [29, 31, 34, 35]. The SARS-CoV-2 is indeed present on fomites in multiple duration of time in a multi-bedded room was a major risk settings, especially high frequency touched surfaces. factor and the finding of a dose–response relationship Infectious SARS-CoV-2 on fomites was significantly adds epidemiologic strength of association to this more likely when the RT-PCR Ct values for clinical finding. Another study from Singapore in a large cohort specimens and fomite samples was < 30 and most of nosocomial SARS-CoV-2 infections in patients housed frequently detected within the first week of symptom in 5–6-bed cubicles, during time periods encompassing onset in immunocompetent individuals [43, 44]. Other both SARS-CoV-2 Delta and Omicron variants found studies have corroborated the finding of infectious that sharing a common toilet with ≥ 1 cohorted cubicle virus being very strongly correlated with low Ct values, was an independent risk factor for a transmission event irrespective of the variant [45, 46]. (aOR, 1.92; 95% CI, 1.02–3.62) along with performance Data presented from our viral cultures showing very of aerosol-generating procedures and a cycle-threshold high quantitative burdens of infectious virus both value of < 20 on RT-PCR testing [36]. This latter finding from patients and their immediate surroundings in corroborates our finding of a 3.2-fold increased rate conjunction with very low Ct values lends support that of acquiring SARS-CoV-2 with exposure to a multi- direct and indirect (fomite) transmission played a role as bedded room with a shared toilet and adds additional a route of transmission. For this outbreak, the culturable support given that it is irrespective of variant strain of virologic and RT-PCR patient and environmental data SARS-CoV-2. would lend support to contact transmission occurring Another outbreak factor was the delayed recognition within multi-bedded rooms and/or shared bathrooms, of initial cases with illness symptoms compatible with especially in the setting of continuous surgical mask COVID-19 due to crossover with symptoms common to wearing by all HCWs, and ventilation parameters cardiac patients with heart failure (shortness of breath, exceeding standards and with 100% outside air. We cough, chest pain, dyspnea). It was difficult to know cannot exclude mixed modes of transmission, but the if clinical judgement, situational factors (e.g. staffing relative protection provided for nosocomial acquisition shortages, workarounds), or compromised HCW psychological and physical safety (e.g. stress, fatigue, by patients within single rooms argues against long burnout) resulted in suboptimal point-of-care risk range airborne transmission. We cannot exclude poor assessment resulting in missed, delayed, or incorrect hand hygiene and suboptimal PPE practices by HCWs diagnosis of COVID-19 among these patients leading which have been implicated previously as associated with to preventable exposures and increased transmission nosocomial transmission of SARS-CoV-2 by HCWs, even [37]. Precise case identification is essential to isolate with the use of full PPE [44, 47]. vulnerable individuals and hence contain transmission Our outbreak investigation identified multiple [38, 39]. exposures among HCWs from symptomatic patients A surprising finding was that individuals with before they were diagnosed with COVID-19, despite underlying fluid and electrolyte disorders had nearly the use of continuous masking by all HCWs but without four times the rate of acquiring COVID-19. It has other components of PPE, which may have contributed been hypothesized that the renin–angiotensin– to acquisition of COVID-19 among HCWs. Doffing of aldosterone system and its core factor ACE2 which PPE in the appropriate manner and sequence is critical to regulates electrolyte homeostasis may play a role in the prevent self-contamination [48–50]. acquisition of COVID-19 [40, 41]. Dehydration, chronic Our study is not without limitations. The retrospective hypertonicity, and/or hypovolemia before COVID-19 nature of our case–control study precludes conclusions Leal et al. Antimicrobial Resistance & Infection Control (2023) 12:21 Page 10 of 13 of causation for acquisition of COVID-19. Nosocomial of HCWs in the principles of infection prevention and cases were investigated more thoroughly during the control including vigilance in donning and doffing of outbreak, whereas data on controls were collected PPE. retrospectively. Selection bias is a common limitation of case–control studies; however, we believe this bias was Abbreviations mitigated by selecting controls matching by age with ACE2 Angiotensin converting enzyme 2 similar clinical health statuses and ensuring controls AEH Air exchanges per hour ARECCI A Project Ethics Community Consensus Initiative overlapped their time in hospital with the case patients. CHREB C onjoint Health Research Ethics Board Both cases and controls would have been exposed to COVID‑19 Coronavirus disease 2019 similar outbreak control measures. Confounding bias CSA Canadian Standards Association Ct Cycle threshold may exist. Information on HCWs was insufficient DAD Discharge Abstract Database to include in the study. Although we did not employ EMR Electronic medical record universal admission RT-PCR testing for SARS-CoV-2 as HCWs Healthcare workers HVAC Heating, ventilation, and air conditioning per local policy, recent recommendations argue against IPC Infection prevention and control its routine use for asymptomatic persons in healthcare IRR Incidence rate ratio facilities [51].NP Nasopharyngeal OR Odds ratio There have been many reports on hospital-based ORION Outbr eak Reports and Intervention studies of Nosocomial outbreaks of COVID-19 [4, 25, 27–29, 31, 39, 52–56], infection however a strength of our report is that it incorporated PPE Personal protective equipment RNA Ribonucleic acid a case–control study to explore contributing ward and RT‑PCR Reverse‑transcription polymerase chain reaction patient-related factors to the acquisition of COVID- SARS‑ CoV‑2 Severe acute respiratory syndrome Coronavirus‑2 19, occurring in a setting without vaccination for any SD Standard deviation WHS Workplace Health and Safety HCWs or patients. Our outbreak has similarities with other COVID-19 nosocomial outbreaks including Supplementary Information unidentified cases on a ward [39, 56], positive HCWs The online version contains supplementary material available at https:// doi. who may have sub-optimal adherence to IPC measures org/ 10. 1186/ s13756‑ 023‑ 01215‑1. [52, 54], and the role of multi-bedded rooms in SARS- CoV-2 transmission [27, 29, 31, 34, 35] Further, our Additional file 1. Definitions: Lists full definitions for outbreak, case report included patient symptoms, environmental definition, and data sources. It also provides additional details about data collection. sampling, whole genome sequencing, viral culture and Additional file 2. Environmental sampling results: Includes three tables has identified the novel finding of fluid and electrolyte of the environmental sampling results before and after cleaning, and disorders increasing the likelihood of COVID-19 cultivatable virus detected from clinical and environmental specimens. acquisition. Additional file 3. Additional case ‑ control details and results: Includes case‑ control matching details, breakdown of comorbidities between cases and matched controls, and independent risk factors for nosocomial COVID‑19 using different cut ‑ off points for the percent exposure on multi‑ Conclusion bedded rooms. In conclusion, conducting outbreak investigations and evaluating hypotheses epidemiologically is critical Acknowledgements in identifying sources of and measures to mitigate We thank Paul Dieu, Christina Ferrato, Kara Gill, Raymond Ma, and Johanna transmission of SARS-CoV-2. Key learnings for Thayer from the Genomics and Bioinformatics or Research Department, Alberta Public Health Laboratory – South, Calgary, AB, Canada and the future outbreaks include but are not limited to (1) Canadian COVID‑19 Genomics Network (CanCOGeN) for their support. We also recognizing structural and organizational elements wish to thank the Calgary Zone Workplace Health and Safety Occupational in hospitals i.e. multi-bedded rooms, frequent patient Health Nursing team, with special thanks to Durwin Luc, the Public Health Communicable Disease team, the Foothills Medical Centre Site Command movements, routes of patient movement that may Post and the cardiology medical team for their assistance with queries contribute to potential spread and include them in related to healthcare worker and visitor data acquisition. We would also like pandemic responses; (2) recognizing the contribution to acknowledge the work done by Dr. Uma Chandran and Winnie Winter in creating the initial draft and updates of the COVID‑19 symptom identification of contaminated surfaces and especially mobile and monitoring tool (COVID‑19SIMT ). The HCW component of this study medical equipment; the need for careful cleaning was presented in abstract form as a poster at AMMI Canada‑ CACMID and disinfection; and the need for hand hygiene with Annual Meeting in 2021. (https:// jammi. utpjo urnals. press/ doi/ pdf/ 10. 3138/ jammi.6. issue‑ s1). We acknowledge the Infection Prevention and Control compliance monitoring, (3) prompt identification of and Public Health team members who facilitated rapid contact tracing and COVID-19 patients; (4) using consistent approaches epidemiological investigations related to the outbreak. The site leadership to ending contact/droplet precautions; (5) minimizing teams were also instrumental in facilitating the coordinated and effective outbreak response. patient transfers; and (6) maintaining adequate training L eal et al. Antimicrobial Resistance & Infection Control (2023) 12:21 Page 11 of 13 Author contributions AGW5 ‑ Special Services Bldg, 1403 29Th Street Nw, Calgary, AB T2N 2T9, Conceptualization: J.L., J.M.C., H.M.O., J.El.; Methodology: J.L., J.M.C., H.M.O., J.E.; Canada. Department of Laboratory Medicine and Pathology, University Data Curation: J.L., J.M.C., H.M.O., D.D., Z.K., K.S., J.El., J.Er., D.S., K.R., K.W., M.C., of Alberta, Edmonton, AB, Canada. Women and Children’s Health Research B.B., K.P., Y.L., D.E., Formal Analysis: J.L., J.M.C., H.M.O., L.A., D.D., Supervision: J.L., Institute, University of Alberta, Edmonton, AB, Canada. Alberta Public Health J.M.C., Investigation: H.M.O., Z.K., K.S., J.Er., M.C., B.B., K.P., Y.L., D.E. Validation: D.D., Laboratory, Alberta Precision Laboratories, Edmonton, AB, Canada. I nfec tion Z.K., K.S., M.C., B.B. Writing original draft: J.L., J.M.C., H.M.O. Writing‑review and Prevention and Control, Alberta Health Services, Lethbridge, AB, Canada. editing: J.L., J.M.C., H.M.O., L.A., D.D., Z.K., K.S., J.El., J.Er., P.J., A.W., D.S., K.R., K.W., Infection Prevention and Control, Alberta Health Services, Edmonton, AB, M.C., B.B., K.P., Y.L., D.E.; Resources: H.M.O., P.J., A.W., D.S., K.R., K.W., D.E.; Funding Canada. acquisition: J.M.C. All authors read and approved the final manuscript. Received: 5 October 2022 Accepted: 10 February 2023 Funding This study was funded in part by the University of Calgary Infectious Diseases Research and Innovation Fund for COVID‑19 and the Canadian COVID ‑19 Genomics Network (CanCOGeN). References Availability of data and materials 1. Paphitis K, Achonu C, Callery S, Gubbay J, Katz K, Muller M, et al. Beyond The datasets generated and/or analyzed during the current study are not flu: Trends in respiratory infection outbreaks in Ontario healthcare publicly available so as to not compromise patient identity. settings from 2007 to 2017, and implications for non‑influenza outbreak management. Can Commun Dis Rep. 2021;47(56):269–75. https:// doi. org/ 10. 14745/ ccdr. v47i5 6a04. Declarations 2. Wang D, Hu B, Hu C, Zhu F, Liu X, Zhang J, et al. Clinical characteristics of 138 hospitalized patients with 2019 Novel Coronavirus‑infected Ethics approval and consent to participate pneumonia in Wuhan, China. JAMA. 2020;323(11):1061–9. https:// doi. org/ The outbreak investigations were conducted in the setting of a formal 10. 1001/ jama. 2020. 1585. Epidemiologic Investigation under Public Health in the Province of Alberta. 3. Abbas M, Robalo Nunes T, Martischang R, Zingg W, Iten A, Pittet D, et al. The ARECCI (A Project Ethics Community Consensus Initiative) assessment Nosocomial transmission and outbreaks of coronavirus disease 2019: the scored this project as fitting with a quality improvement project for which need to protect both patients and healthcare workers. Antimicrob Resist Institutional Review Board approval was not required. The case control Infect Control. 2021;10(1):7. https:// doi. org/ 10. 1186/ s13756‑ 020‑ 00875‑7. component and collection and culturing of patients was approved by 4. Kanji JN, Chan YLE, Boychuk LR, Boyington C, Turay S, Kobelsky M, the University of Calgary’s Conjoint Health Research Ethics Board (CHREB et al. SARS‑ CoV‑2 outbreak in a Canadian suburban tertiary hospital ID: REB21‑0666 and REB20‑0444, respectively). The ORION framework for necessitating full facility closure: a descriptive observational study. CMAJ reporting an outbreak or intervention study of a nosocomial organism was Open. 2022;10(1):E137–45. https:// doi. org/ 10. 9778/ cmajo. 20210 064. followed in this report. 5. Susky EK, Hota S, Armstrong IE, Mazzulli T, Kestenberg S, Casaubon LK, et al. Hospital outbreak of the severe acute respiratory coronavirus virus Consent for publication 2 (SARS‑ CoV‑2) delta variant in partially and fully vaccinated patients and Not applicable. healthcare workers in Toronto, Canada. Infect Control Hosp Epidemiol. 2021:1–4. doi:https:// doi. org/ 10. 1017/ ice. 2021. 471. Competing interests 6. Lessells R, Moosa Y, de Oliveira T. Report into a nosocomial outbreak of All authors will have filled out an ICMJE Disclosure form. JL reports Program coronavirus disease 2019 (COVID‑19) at Netcare St. Augustine’s Hospital. funds from the Centre of Health Informatics at the University of Calgary used KwaZulu‑Natal, South Africa: University of KwaZulu‑Natal and the to provide in‑Kind analytical support for her COVID ‑19 research, not related KwaZulu‑Natal Research Innovation and Sequencing Platform; 2020 15 to this manuscript and funds paid to the University of Calgary to support May 2020. professional development, specifically IPAC Canada 2022 Virtual conference 7. Wilson J. Infection prevention and control in the COVID‑19 pandemic: fees were reimbursed by the Public Health Agency of Canada’s Canadian what have we learnt? J Infect Prev. 2021;22(1):5–6. https:// doi. org/ 10. Nosocomial Infection Surveillance Program. All other authors do not have 1177/ 17571 77420 984914. relevant conflicts of interest to declare related to any aspect of the submitted 8. Moynihan R, Sanders S, Michaleff ZA, Scott AM, Clark J, To EJ, et al. Impact manuscript. All authors have reviewed the version of the manuscript which of COVID‑19 pandemic on utilisation of healthcare services: a systematic has been submitted. review. BMJ Open. 2021;11(3):e045343. doi:https:// doi. org/ 10. 1136/ bmjop en‑ 2020‑ 045343. Author details 9. O’Grady HM, Dixit D, Khawaja Z, Snedeker K, Ellison J, Erebor J, et al. Infection Prevention and Control, Alberta Health Services, Calgary, AB, Asymptomatic Severe Acute Respiratory Syndrome Coronavirus‑2 Canada. Department of Pediatrics, Division of Infectious Diseases, University (SARS‑ CoV‑2) infection in adults is uncommon using rigorous symptom of Calgary and Alberta Health Services, Calgary, AB, Canada. Depar tment characterization and follow‑up in an acute care adult hospital outbreak. of Medicine, Cumming School of Medicine, University of Calgary and Alberta Infect Control Hosp Epidemiol. 2022(Online ahead of print):1–25. Health Services, Calgary, AB, Canada. Provincial Population and Public Health, doi:https:// doi. org/ 10. 1017/ ice. 2022. 168. Alberta Health Services, Calgary, AB, Canada. Department of Family Medicine, 10. Williamson T, Eastwood C, Quan H, Southern D. The COVID‑19 response: University of Calgary and Alberta Health Services, Calgary, AB, Canada. Alberta’s pandemic response Calgary, Canada: Centre for Health Cardiac Sciences, Foothills Medical Centre, Alberta Health Services, Calgary, Informatics; 2020. Available from: https:// covid‑ track er. chi‑ csm. ca/. AB, Canada. Department of Community Health Sciences, Cumming School 11. Elias C, Sekri A, Leblanc P, Cucherat M, Vanhems P. The incubation period of Medicine, University of Calgary, Calgary, AB, Canada. O ’Brien I nstitute of COVID‑19: a meta‑analysis. Int J Infect Dis. 2021;104:708–10. https:// for Public Health, University of Calgary and Alberta Health Services, Calgary, doi. org/ 10. 1016/j. ijid. 2021. 01. 069. AB, Canada. Department of Microbiology, Immunology and Infectious 12. Pabbaraju K, Wong AA, Douesnard M, Ma R, Gill K, Dieu P, et al. Diseases, University of Calgary, Calgary, AB, Canada. Depar tment Development and validation of RT‑PCR assays for testing for SARS‑ CoV‑2. of Pathology and Laboratory Medicine, University of Calgary and Alberta J Assoc Med Microbiol Infec Dis Can. 2021;6(1):16–22. https:// doi. org/ 10. Health Services, Calgary, AB, Canada. Synder Institute for Chronic Diseases, 3138/ jammi‑ 2020‑ 0026. University of Calgary and Alberta Health Services, Calgary, AB, Canada. 13. Lin Y‑ C, Malott RJ, Ward L, Kiplagat L, Pabbaraju K, Gill K, et al. Detection W21C, Department of Medicine, University of Calgary, Calgary, AB, Canada. and quantification of infectious severe acute respiratory coronavirus‑2 Alberta Public Health Laboratory, Alberta Precision Laboratories, Calgary, AB, in diverse clinical and environmental samples. Sci Rep. 2022;12(1):5418. Canada. Li Ka Shing Institute of Virology, University of Alberta, Edmonton, https:// doi. org/ 10. 1038/ s41598‑ 022‑ 09218‑5. AB, Canada. Department of Medical Microbiology and Immunology, University of Alberta, Edmonton, AB, Canada. Foothills Medical Centre, Leal et al. Antimicrobial Resistance & Infection Control (2023) 12:21 Page 12 of 13 14. Rajakumar I, Isaac DL, Fine NM, Clarke B, Ward LP, Malott RJ, et al. Extensive 32. Lakhani K, Minguell J, GuerraF ‑ arfan E, Lara Y, Jambrina U, Pijoan J, et al. environmental contamination and prolonged severe acute respiratory Nosocomial infection with SARS‑ CoV2 and main out ‑ comes after surgery coronavirus2 (SARS C ‑ oV 2) viabilit ‑ y in immunosuppressed recent heart within an orthopaedic surgery department in a tertiary trauma centre transplant recipients with clinical and virologic benefit with remdesivir. Infect in Spain. Int Orthop. 2020;44(12):2505–13. https:// doi. org/ 10. 1007/ Control Hosp Epidemiol. 2021:1–3. doi:https:// doi. org/ 10. 1017/ ice. 2021. 89.s00264020‑ 04798‑ 1‑ . 15. nCoV‑2019 sequencing protocol V.1. protocols.io. 2020. Available from: 33. Onakpoya IJ, Heneghan CJ, Spencer EA, Brassey J, Pluddemann A, Evans DH, https:// www. proto cols. io/ view/ ncov‑ 2019‑ seque ncing‑ proto col‑ bp2l6 et al. SARS‑ CoV2 and the r ‑ ole of close contact in transmission: a systematic n26rg qe/ v1? versi on_ warni ng= no. review. F1000Res. 2021;10:280. doi:https:// doi. org/ 10. 12688/ f1000 resea rch. 16. Tyson JR, James P, Stoddart D, Sparks N, Wickenhagen A, Hall G, et al. 52439.3. Improvements to the ARTIC multiplex PCR method for SARS‑ CoV‑2 34. Martin A, Kampouri E, Senn L, Sartori C. Epidemiology and risk factors of genome sequencing using nanopore. bioRxiv. 2020. doi:https:// doi. org/ nosocomial COVID infections in the Service of internal medicine at CHUV. 10. 1101/ 2020. 09. 04. 283077. Rev Med Suisse. 2021;17(760):2049–54. 17. nCoV‑2019 sequencing protocol v3 (LoCost) V.3. 2020. Available from: 35. Karan A, Klompas M, Tucker R, Baker M, Vaidya V, Rhee C. The risk of severe https:// www. proto cols. io/ view/ ncov‑ 2019‑ seque ncing‑ proto col v3‑‑ acute respiratory syndrome coronavirus 2 (SARS‑ CoV2) transmission ‑ locost‑ bp2l6 n26rg qe/ v3. from patients with undiagnosed Coronavirus Disease 2019 (COVID‑ 18. Long reads nanopore sequencing to recover SARS‑ CoV‑2 whole genome 19) to roommates in a large academic medical center. Clin Infect Dis. v.3. University College London. 2020. Available from: https:// www. proto 2022;74(6):1097–100. https:// doi. org/ 10. 1093/ cid/ ciab5 64. cols. io/ view/ long‑ reads‑ nanop ore‑ seque ncing‑ to‑ recov er‑ sars‑ cov‑ 5jyl8 36. Wee LE, Ko KKK, Conceicao EP, Aung MK, Aung MO, Yang Y, et al. Enhanced mkw9g 2w/ v3. infection prevention measures including universal N95 usage and daily 19. Rambaut A, Holmes EC, O’Toole A, Hill V, McCrone JT, Ruis C, et al. A testing: the impact on SARS‑ CoV2 transmission in cohor ‑ ted hospital dynamic nomenclature proposal for SARS‑ CoV‑2 lineages to assist cubicles through successive Delta and Omicron waves. Clin Infect Dis. genomic epidemiology. Nat Microbiol. 2020;5(11):1403–7. https:// doi. 2022;75(5):917–9. https:// doi. org/ 10. 1093/ cid/ ciac3 20. org/ 10. 1038/ s41564‑ 020‑ 0770‑5. 37. Gandhi TK, Singh H. Reducing the risk of diagnostic error in the COVID19 ‑ 20. Labrecque JA, Hunink MMG, Ikram MA, Ikram MK. Do case‑ control studies era. J Hosp Med. 2020;15(6):363–6. https:// doi. org/ 10. 12788/ jhm. 3461. always estimate odds ratios? Am J Epidemiol. 2021;190(2):318–21. https:// 38. Chen T, Hanna J, Walsh EE, Falsey AR, Laguio‑ Vila M, Lesho E. Syncope, Near doi. org/ 10. 1093/ aje/ kwaa1 67. syncope, or nonmechanical falls as a presenting feature of COVID19. Ann ‑ 21. Knol MJ, Vandenbroucke JP, Scott P, Egger M. What do case‑ control Emerg Med. 2020;76(1):115–7. https:// doi. org/ 10. 1016/j. annem ergmed. studies estimate? Survey of methods and assumptions in published case‑2020. 04. 037. control research. Am J Epidemiol. 2008;168(9):1073–81. https:// doi. org/ 39. Roberts SC, Foppiano Palacios C, Grubaugh ND, Alpert T, Ott IM, Breban 10. 1093/ aje/ kwn217. MI, et al. An outbreak of SARS‑ CoV2 on a transplant unit in the ear ‑ ly 22. Dehejia RH, Wahba S. Propensity score‑matching methods for vaccination era. Transpl Infect Dis. 2022;24(2):e13782. doi:https:// doi. org/ 10. nonexperimental causal studies. Rev Econ Stat. 2002;84(1):151–61. 1111/ tid. 13782. https:// doi. org/ 10. 1162/ 00346 53023 17331 982. 40. Nahkuri S, Becker T, Schueller V, Massberg S, BauerM ‑ ehren A. Prior fluid and 23. Dixit D, Conly J, Snedeker K, Etches N, Weiss A, Suddes M, et al. electrolyte imbalance is associated with COVID19 mor ‑ tality. Commun Med. Nosocomial SARS‑ CoV‑2 infection in health care workers: descriptive 2021;1(1):51. https:// doi. org/ 10. 1038/ s43856021‑ 00051‑ x‑ . analysis of a large acute care hospital COVID‑19 outbreak on cardiac 41. Stookey JD, Allu PKR, Chabas D, Pearce D, Lang F. Hypotheses about sub‑ units. . J Assoc Med Microbiol Infect Dis Can. 2021;6(Suppl):Abstract P17. optimal hydration in the weeks before coronavirus disease (COVID19) as ‑ doi:https:// doi. org/ 10. 3138/ jammi.6. s1. abst. a risk factor for dying from COVID19. M ‑ ed Hypotheses. 2020;144:110237. 24. Alberta Health Services. Provincial PPE Safety Coach Program Edmonton, doi:https:// doi. org/ 10. 1016/j. mehy. 2020. 110237. Alberta: Alberta Health Services; 2020 [Available from: https:// www. alber 42. Goldman E. Exaggerated risk of transmission of COVID19 b ‑ y fomites. tahea lthse rvices. ca/ ipc/ Page1 7279. aspx. Lancet Infect Dis. 2020;20(8):892–3. https:// doi. org/ 10. 1016/ S14733099(20)‑ 25. Biernat MM, Zinczuk A, Biernat P, BoguckaF ‑ edorczuk A, Kwiatkowski 305612 ‑ . J, Kalicinska E, et al. Nosocomial outbreak of SARS‑ CoV2 inf ‑ ection in 43. Onakpoya IJ, Heneghan CJ, Spencer EA, Brassey J, Pluddemann A, Evans DH, a haematological unit H ‑ igh mortality rate in infected patients with et al. SARS‑ CoV2 and the r ‑ ole of fomite transmission: a systematic review. haematologic malignancies. J Clin Virol. 2020;130:104574. doi:https:// doi. F1000Res. 2021;10:233. doi:https:// doi. org/ 10. 12688/ f1000 resea rch. 51590.3. org/ 10. 1016/j. jcv. 2020. 104574. 44. O’Grady HM, Harrison R, Snedeker K, Trufen L, Yue P, Ward L, et al. A two‑ 26. Iio R, Kaneko T, Mizuno H, Isaka Y. Clinical characteristics of COVID19 ‑ ward acute care hospital outbreak of SARS‑ CoV2 delta var ‑ iant including a infection in a dialysis center during a nosocomial outbreak. Clin Exp pointsour ‑ ce outbreak associated with the use of a mobile vital signs cart Nephrol. 2021;25(6):652–9. https:// doi. org/ 10. 1007/ s10157021‑ 02025‑ 8‑ . and sub‑ optimal doffing of personal protective equipment. J Hosp Infect. 27. Leeman DS, Ma TS, Pathiraja MM, Taylor JA, Adnan TZ, Baltas I, et al. Severe 2022;131:1–11. https:// doi. org/ 10. 1016/j. jhin. 2022. 09. 019. acute respiratory coronavirus virus 2 (SARS‑ CoV2) nosocomial transmission ‑ 45. Bouton TC, Atarere J, Turcinovic J, Seitz S, Sher‑ Jan C, Gilbert M, et al. Viral dynamics, a retrospective cohort study of two healthcareassociat ‑ ed dynamics of Omicron and Delta SARS‑ CoV2 var ‑ iants with implications for coronavirus disease 2019 (COVID19) clust ‑ ers in a district hospital in England timing of release from isolation: a longitudinal cohort study. Clin Infect Dis. during March and April 2020. Infect Control Hosp Epidemiol. 2021:17. ‑ 2022. https:// doi. org/ 10. 1093/ cid/ ciac5 10. doi:https:// doi. org/ 10. 1017/ ice. 2021. 483. 46. Young BE, Ong SWX, Ng LFP, Anderson DE, Chia WN, Chia PY, et al. Viral 28. Aghdassi SJS, Schwab F, Pena Diaz LA, Brodzinski A, Fucini GB, Hansen S, dynamics and immune correlates of Coronavirus Disease 2019 (COVID19) ‑ et al. Risk factors for nosocomial SARS‑ CoV2 inf ‑ ections in patients: results severity. Clin Infect Dis. 2021;73(9):e2932–42. https:// doi. org/ 10. 1093/ cid/ from a retrospective matched case‑ control study in a tertiary care university ciaa1 280. center. Antimicrob Resist Infect Control. 2022;11(1):9. https:// doi. org/ 10. 47. Ran L, Chen X, Wang Y, Wu W, Zhang L, Tan X. Risk factors of healthcare 1186/ s13756022‑ 01056‑ 4‑ . workers with Coronavirus Disease 2019: a retrospective cohort study in a 29. Thoma R, Kohler P, Haller S, Schlegal M, Flury D. Wardle ‑ vel risk factors designated hospital of Wuhan in China. Clin Infect Dis. 2020;71(16):2218–21. associated with nosocomial coronavirus disease 2019 (COVID19) outbr ‑ eaks: https:// doi. org/ 10. 1093/ cid/ ciaa2 87. a matched case‑ control study. Antimicrobial Stewardship Healthcare 48. Chughtai AA, Chen X, Macintyre CR. Risk of self‑ contamination during Epidemiol. 2022;2(e49):1–3. https:// doi. org/ 10. 1017/ ash. 2022. 11. doffing of personal protective equipment. Am J Infect Control. 30. Abbas M, Robalo Nunes T, Cori A, Cordey S, Laubscher F, Baggio S, et al. 2018;46(12):1329–34. https:// doi. org/ 10. 1016/j. ajic. 2018. 06. 003. Explosive nosocomial outbreak of SARS‑ CoV2 in a r ‑ ehabilitation clinic: the 49. Saran S, Gurjar M, Garg A. Identifying and implementing strategies to reduce limits of genomics for outbreak reconstruction. J Hosp Infect. 2021;117:124– the risk of self‑ contamination of health care workers caused by doffing of 34. https:// doi. org/ 10. 1016/j. jhin. 2021. 07. 013. personal protective equipment during the COVID19 pandemic ‑ . Disaster 31. Dinh C, Gallouche M, Terrisse H, Gam K, Giner C, Nemoz B, et al. Risk factors Med Public Health Prep. 2020:1–4. doi:https:// doi. org/ 10. 1017/ dmp. 2020. of nosocomial Covid19 in a F ‑ rench university hospital: a case ‑ control study. 396. Preprint: Research Square; 2022. L eal et al. Antimicrobial Resistance & Infection Control (2023) 12:21 Page 13 of 13 50. Verbeek JH, Rajamaki B, Ijaz S, Sauni R, Toomey E, Blackwood B, et al. Personal protective equipment for preventing highly infectious diseases due to exposure to contaminated body fluids in healthcare staff. Cochrane Database of Systematic Reviews. 2020(4). doi:https:// doi. org/ 10. 1002/ 14651 858. CD011 621. pub4. 51. Talbot TR, Hayden MK, Yokoe DS, Malani AN, Amer HA, Kalu IC, et al. Asymptomatic screening for severe acute respiratory coronavirus virus 2 (SARS‑ CoV2) as an inf ‑ ection prevention measure in healthcare facilities: Challenges and considerations. Infect Control Hosp Epidemiol. 2022:1–6. doi:https:// doi. org/ 10. 1017/ ice. 2022. 295. 52. Rana K, Sharma B, Lakshmi PVM, Kaur M, Singh MP, Singh R, et al. Nosocomial outbreak of SARS‑ CoV2 in a non ‑ ‑ COVID zone of a tertiary care hospital of North India: Need to upgrade infection control practices. J Prim Care Community Health. 2021;12:21501327211050750. https:// doi. org/ 10. 1177/ 21501 32721 10507 53. 53. Harada S, Uno S, Ando T, Iida M, Takano Y, Ishibashi Y, et al. Control of a nosocomial outbreak of COVID19 in a univ ‑ ersity hospital. Open Forum Infect Dis. 2020;7(12):ofaa512. doi:https:// doi. org/ 10. 1093/ ofid/ ofaa5 12. 54. Lee U, Kim SE, Lee SY, Wi HN, Choi O, Park JW, et al. Source analysis and effective control of a COVID 19 outbr ‑ eak in a university teaching hospital during a period of increasing community prevalence of COVID19. J K ‑ orean Med Sci. 2021;36(24):e179. doi:https:// doi. org/ 10. 3346/ jkms. 2021. 36. e179. 55. Moore G, Rickard H, Stevenson D, AranegaBou P ‑ , Pitman J, Crook A, et al. Detection of SARS‑ CoV2 within the healthcar ‑ e environment: a multi‑ centre study conducted during the first wave of the COVID 19 outbr ‑ eak in England. J Hosp Infect. 2021;108:189–96. https:// doi. org/ 10. 1016/j. jhin. 2020. 11. 024. 56. Lesho EP, Walsh EE, Gutowski J, Reno L, Newhart D, Yu S, et al. A cluster‑ control approach to a coronavirus disease 2019 (COVID19) outbr ‑ eak on a stroke ward with infection control considerations for dementia and vascular units. Infect Control Hosp Epidemiol. 2021;42(11):1333–9. https:// doi. org/ 10. 1017/ ice. 2020. 1437. 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Journal
Antimicrobial Resistance and Infection Control – Springer Journals
Published: Mar 22, 2023
Keywords: COVID-19; Nosocomial; Outbreak; Risk factors; Case–control; Incidence density sampling; Rate ratio; Viral culture; Environment