Assessment of an enhanced COVID-19 case and contact management protocol in controlling a SARS-CoV-2 Alpha (B.1.1.7) variant outbreak on a construction site.

BACKGROUND: To control the spread of SARS-CoV-2 variants of concern (VOCs), Kingston, Frontenac, and Lennox & Addington (KFL&A) Public Health implemented a more stringent COVID-19 case and contact management (CCM) protocol than what was used across Ontario at the time. We describe epidemiological data and public health measures employed during one of the largest COVID-19 outbreaks in the KFL&A region at the time, caused by the SARS-CoV-2 Alpha (B.1.1.7) VOC, to assess this enhanced protocol. METHODS: We obtained line lists of workers associated with the construction site outbreak, and subsequent cases and contacts from case investigators. Case testing, mutation status, and whole genome sequencing were conducted by Public Health Ontario Laboratories. RESULTS: From 409 high-risk contacts of the outbreak, 109 (27%) developed COVID-19. Three generations of spread were associated with the outbreak, affecting seven public health regions across three provinces. Using an enhanced approach to the CCM, KFL&A Public Health caught 15 cases that could have been missed by standard provincial protocols. CONCLUSIONS: Rapid initial spread within the construction site produced a relatively high attack rate among workers (26%) and their immediate contacts (34%). KFL&A Public Health's implementation of stringent CCM protocols and fast testing turn-around time effectively curbed the spread of the disease in subsequent generations - illustrated by the large reduction in attack rate (34%-14%) and cases (50-10) between the second and third generations. Lessons learned from this analysis may inform guidance on the CCM for future SARS-CoV-2 VOCs as well as other highly transmissible communicable diseases.

HISTORIQUE: Pour contrôler la propagation des variants inquiétants (VOC) du SRAS-CoV-2, la région sociosanitaire de Kingston, Frontenac, Lennox et Addington (KFL&A) a adopté un protocole plus rigoureux de gestion des cas et des contacts (GCC) qui était utilisé partout en Ontario à l'époque. Les auteurs décrivent les données épidémiologiques et les mesures sanitaires employées pendant l'une des plus grosses éclosions de COVID-19 de la région sociosanitaire de KFL&A, causée par le VOC Alpha (B.1.1.7) du SRAS-CoV-2, afin d'évaluer ce protocole amélioré. MÉTHODOLOGIE: Les auteurs ont obtenu les listes des lignes des travailleurs associés à l'éclosion sur le chantier de construction, ainsi que des cas et des contacts subséquents des enquêteurs de cas. Les Laboratoires de Santé publique Ontario ont procédé au dépistage des cas et ont vérifié l'état mutationnel et le séquençage du génome entier. RÉSULTATS: Des 409 contacts à haut risque de l'éclosion, 109 (27%) ont contracté la COVID-19. Trois générations de propagation étaient associées à l'éclosion et touchaient sept régions sociosanitaires réparties dans trois provinces. Au moyen d'une approche améliorée de la GCC, la région sociosanitaire de KFL&A a dépisté 15 cas qui auraient pu être omis par les protocoles provinciaux standards. CONCLUSIONS: Une propagation initiale rapide sur le chantier de construction a produit un taux d'attaque relativement élevé chez les travailleurs (26%) et leurs contacts immédiats (34%). Ladoption de protocoles rigoureux de GCC dans la région sociosanitaire de KFL&A et l'obtention rapide des résultats du dépistage ont enrayé la propagation de la maladie avec efficacité dans les générations suivantes, ce qui est démontré par une forte réduction du taux d'attaque (de 34% à 14%) et de cas (de 50 à 10) entre la deuxiéme génération et la troisiéme. Les leçons tirées de cette analyse pourraient éclairer les conseils sur la GCC des futurs VOC du SRAS-COV-2 et des autres maladies contagieuses hautement transmissibles.

The Association between the Fibrosis-4 Index and COVID-19: A Systematic Review and Meta-Analysis.

OBJECTIVE: The prognosis value of fibrosis-4 score (FIB-4) in COVID-19 is controversial. Hence, we conducted a systematic review and meta-analysis to investigate the association between the FIB-4 index and COVID-19 disease progression. METHODS: We performed meta-analysis using the PubMed, Embase, and Cochrane databases. A fixed- or random-effects model was used for evaluating heterogeneity. RESULTS: Thirteen studies were included. The meta-analysis of unadjusted results showed that compared to lower FIB-4 index, patients with higher FIB-4 index had increased odds of mortality (OR=5.1, 95%CI 3.67-7.09; P<0.001), ICU admission (OR=2.32, 95%CI: 1.65-3.25, P<0.00001) and need for mechanical ventilator support (OR=3.51, 95%CI: 2.1-5.85, P<0.001). In addition, the meta-analysis of adjusted results showed patients with higher FIB-4 index was associated with increased risk of mortality (OR=3.01, 95%CI: 2.21-4.09, P<0.001) and need for mechanical ventilator support (OR=3.76, 95%CI: 2.08-6.82, P<0.001) compared to patients with lower FIB-4 index. CONCLUSIONS: This meta-analysis indicated that high FIB-4 index score was associated with the severity and mortality in COVID-19 infected patients.

Opioid usage and COVID-19 prognosis: A systematic review and meta-analysis.

The COVID-19 pandemic continues to have profound health, social, psychological, and economic ramifications. Infection by COVID-19 has been of concern in people who use opioids, as opioid use has been known to mediate immunosuppression and is associated with respiratory depression and end-organ damage. With differing modalities of opioid usage, the association between opioids and COVID-19 outcomes is not well understood. We performed a comprehensive systematic search of seven health science databases, including PubMed, Embase, Cochrane Library, Web of Science, China National Knowledge Infrastructure (CNKI), and Wanfang Data, up to December 15, 2021. We identified a total of five related articles, which were included in this study. The meta-analysis showed that opioids have a significant association with ICU admission for COVID-19 patients (OR = 5.41, 95%CI: 1.85 to 15.79, P = 0.002). Use of opioids was also associated with higher mortality among patients with COVID-19 compared to non-users (OR = 2.74, 95%CI: 1.34 to 5.62, P = 0.034), while use of opioids was not significantly associated with need for mechanical ventilation (OR = 3.68, 95%CI: 0.85 to 15.90, P = 0.081). Furthermore, the adjusted analysis indicated that COVID-19 patients with a history of opioid use were more likely to be admitted to the ICU (OR = 3.57, 95%CI: 3.05 to 4.17, P<0.001) and have higher mortality rates (OR = 1.72, 95%CI: 1.09 to 2.72, P = 0.02), while there was no significant association with need for mechanical ventilation (OR = 2.09, 95%CI: 0.77 to 5.64, P = 0.146). Significant heterogeneity existed across the included studies. Patients using opioids with COVID-19 were at higher risk of ICU admission and mortality. Prospective studies are required to confirm these findings.

Fending off Delta - Hospital measures to reduce nosocomial transmission of COVID-19.

OBJECTIVES: Following the emergence of the Delta variant of SARS-CoV-2 in Singapore, our hospital experienced a Delta-linked ward cluster. In this study, we review the enhanced strategies in preventing nosocomial transmission of COVID-19 following widespread community transmission of the Delta variant. METHODS: We conducted a cohort study on exposures to unexpected COVID-19 cases for which contact tracing was initiated from June 2021 to October 2021. Strategies evaluated included upgraded personal protective equipment (PPE) and rostered routine testing (RRT) for staff and patients, surveillance of staff with acute respiratory illness (ARI), and expanded quarantining and testing for contacts of identified cases. RESULTS: From 193 unexpected COVID-19 exposures, 2,573 staff, 542 patients, and 128 visitor contacts were traced. Four staff contacts subsequently had SARS-CoV-2 infection. Two were likely from exposure in community settings, whereas 2 had exposure to the same COVID-19 positive staff in the hospital, forming the only hospital cluster. One inpatient had a nosocomial infection, possibly from visitors. The SARS-CoV-2 detection rate among staff was 0.3% (of 11,200 staff) from biweekly RRT and 2.5% (of 3,675 staff) from ARI surveillance. CONCLUSION: Enhanced hospital measures, including upgraded PPE and RRT for staff and patients, staff sickness surveillance, and more rigorous management of contacts of COVID-19 cases, were likely to have reduced nosocomial transmission amid the Delta variant.

Limited Propagation of SARS-CoV-2 among Children in a Childcare Center, Canada, 2021.

An outbreak of severe acute respiratory syndrome coronavirus 2 with no definitive source and potential exposure to variants of concern was declared at a childcare center in Ontario, Canada, in March 2021. We developed a robust outbreak management approach to detect, contain, and interrupt this outbreak and limit propagation among children.

COVID-19 outbreak in a personal service setting in Kingston, Ontario, 2020.

BACKGROUND: During the coronavirus disease 2019 (COVID-19) pandemic, Ontario created a three-phase reopening framework for the economy. Outbreaks were expected at each phase. One week after Phase Two of reopening in the provincial public health administration region of Kingston, Frontenac, Lennox and Addington (KFL&A), a positive case was reported after three weeks of zero new COVID-19 cases. The objective of this report is to describe this COVID-19 outbreak, linked to a personal service setting (PSS), and the public health response to contain the outbreak. METHODS: The outbreak investigation included all COVID-19 cases in KFL&A between June 20, 2020 and July 3, 2020. Public health inspectors and nurses were rapidly deployed to inspect the PSS. A multimodal approach to high-volume testing involved fixed assessment centres, drive-through testing capacity and targeted testing at the outbreak site. Testing was conducted through a real-time polymerase chain reaction assay at the local Public Health Ontario laboratory. RESULTS: Thirty-seven cases were associated with the outbreak: 38% through direct PSS exposure; 32% through household contact; and 30% through social and workplace contact. A superspreading event contributed to 38% of total cases. The majority of cases were in the low to mid-quintiles when analyzed for material deprivation. Testing rates increased four-fold compared to the prior baseline weeks in response to media attention and public health messaging, resulting in a low percent positivity. CONCLUSION: The interplay of aggressive accessible testing, quick lab turnaround time, contact tracing within 24 hours of positive laboratory results as per provincial standards, frequent public communication, rapid inspections, mandatory self-isolation and face coverings were measures successful in halting the outbreak. Inspections or self-audits should be required at all PSSs prior to reopening and outbreak management must work with PSSs to reduce the possibility of superspreading events.

Validation of an internationally derived patient severity phenotype to support COVID-19 analytics from electronic health record data.

OBJECTIVE: The Consortium for Clinical Characterization of COVID-19 by EHR (4CE) is an international collaboration addressing coronavirus disease 2019 (COVID-19) with federated analyses of electronic health record (EHR) data. We sought to develop and validate a computable phenotype for COVID-19 severity. MATERIALS AND METHODS: Twelve 4CE sites participated. First, we developed an EHR-based severity phenotype consisting of 6 code classes, and we validated it on patient hospitalization data from the 12 4CE clinical sites against the outcomes of intensive care unit (ICU) admission and/or death. We also piloted an alternative machine learning approach and compared selected predictors of severity with the 4CE phenotype at 1 site. RESULTS: The full 4CE severity phenotype had pooled sensitivity of 0.73 and specificity 0.83 for the combined outcome of ICU admission and/or death. The sensitivity of individual code categories for acuity had high variability-up to 0.65 across sites. At one pilot site, the expert-derived phenotype had mean area under the curve of 0.903 (95% confidence interval, 0.886-0.921), compared with an area under the curve of 0.956 (95% confidence interval, 0.952-0.959) for the machine learning approach. Billing codes were poor proxies of ICU admission, with as low as 49% precision and recall compared with chart review. DISCUSSION: We developed a severity phenotype using 6 code classes that proved resilient to coding variability across international institutions. In contrast, machine learning approaches may overfit hospital-specific orders. Manual chart review revealed discrepancies even in the gold-standard outcomes, possibly owing to heterogeneous pandemic conditions. CONCLUSIONS: We developed an EHR-based severity phenotype for COVID-19 in hospitalized patients and validated it at 12 international sites.