COVID-19 Vaccination is Associated with Reduced Outpatient Antibiotic Prescribing In Older Adults with Confirmed SARS-CoV-2: A Population Wide Cohort Study.

BACKGROUND: Antibiotics are frequently prescribed unnecessarily in outpatients with COVID-19. We sought to evaluate factors associated with antibiotic prescribing in those with SARS-CoV-2 infection. METHODS: We performed a population-wide cohort study of outpatients 66 years or older with PCR-confirmed SARS-CoV-2 from January 1st 2020 to December 31st 2021 in Ontario, Canada. We determined rates of antibiotic prescribing within 1-week before (pre-diagnosis) and 1-week after (post-diagnosis) reporting of the positive SARS-CoV-2 result, compared to a self-controlled period (baseline). We evaluated predictors of prescribing, including a primary series COVID-19 vaccination, in univariate and multivariable analyses. RESULTS: We identified 13,529 eligible nursing home residents and 50,885 eligible community dwelling adults with SARS-CoV-2 infection. Of the nursing home and community residents, 3,020 (22%) and 6,372 (13%) received at least one antibiotic prescription within 1 week of a SARS-CoV-2 positive result, respectively. Antibiotic prescribing in nursing home and community residents occurred at 15.0 and 10.5 prescriptions per 1000 person-days pre-diagnosis and 20.9 and 9.8 per 1000 person-days post-diagnosis, higher than the baseline rates of 4.3 and 2.5 prescriptions per 1000 person-days. COVID-19 vaccination was associated with reduced prescribing in nursing home and community residents, with adjusted post-diagnosis IRRs of 0.7 (95%CI 0.4-1) and 0.3 (95%CI 0.3-0.4) respectively. CONCLUSIONS: Antibiotic prescribing was high and with little or no decline following SARS-CoV-2 diagnosis, though was reduced in COVID-19 vaccinated individuals, highlighting the importance of vaccination and antibiotic stewardship in older adults with COVID-19.

Association Between Diabetes and Mortality Among Adult Patients Hospitalized With COVID-19: A Cohort Study of Hospitalized Adults in Ontario, Canada, and Copenhagen, Denmark.

OBJECTIVES: Diabetes has been reported to be associated with an increased risk of death among patients with COVID-19. However, the available studies lack detail on COVID-19 illness severity and measurement of relevant comorbidities. METHODS: We conducted a multicentre, retrospective cohort study of patients 18 years of age and older who were hospitalized with COVID-19 between January 1, 2020, and November 30, 2020, in Ontario, Canada, and Copenhagen, Denmark. Chart abstraction emphasizing comorbidities and disease severity was performed by trained research personnel. The association between diabetes and death was measured using Poisson regression. The main outcome measure was in-hospital 30-day risk of death. RESULTS: Our study included 1,133 hospitalized patients with COVID-19 in Ontario and 305 in Denmark, of whom 405 and 75 patients, respectively, had pre-existing diabetes. In both Ontario and Denmark, patients with diabetes were more likely to be older; have chronic kidney disease, cardiovascular disease, and higher troponin levels; and be receiving antibiotics, when compared with adults without diabetes. In Ontario, 24% (n=96) of adults with diabetes died compared with 15% (n=109) of adults without diabetes. In Denmark, 16% (n=12) of adults with diabetes died in hospital compared with 13% (n=29) of those without diabetes. In Ontario, the crude mortality ratio among patients with diabetes was 1.60 (95% confidence interval [CI], 1.24 to 2.07) and in the adjusted regression model it was 1.19 (95% CI, 0.86 to 1.66). In Denmark, the crude mortality ratio among patients with diabetes was 1.27 (95% CI, 0.68 to 2.36) and in the adjusted model it was 0.87 (95% CI, 0.49 to 1.54). Meta-analysis of the 2 rate ratios from each region resulted in a crude mortality ratio of 1.55 (95% CI, 1.22 to 1.96) and an adjusted mortality ratio of 1.11 (95% CI, 0.84 to 1.47). CONCLUSION: The presence of diabetes was not strongly associated with in-hospital COVID-19 mortality independent of illness severity and other comorbidities.

Detection of Covid-19 Outbreaks Using Built Environment Testing for SARS-CoV-2

Background: Environmental surveillance of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) through wastewater has become a useful tool for population-level surveillance. Built environment sampling may provide a more spatially refined approach for surveillance in congregate living settings. Methods: We conducted a prospective study in 10 long-term care homes (LTCHs) between September 2021 and November 2022. Floor surfaces were sampled weekly at multiple locations within each building and analyzed for the presence of SARS-CoV-2 using quantitative reverse transcriptase polymerase chain reaction. The primary outcome was the presence of a coronavirus disease 2019 (Covid-19) outbreak in the week that floor sampling was performed. Results: Over the 14-month study period, we collected 4895 swabs at 10 LTCHs. During the study period, 23 Covid-19 outbreaks occurred with 119 cumulative weeks under outbreak. During outbreak periods, the proportion of floor swabs that were positive for SARS-CoV-2 was 54.3% (95% confidence interval [CI], 52 to 56.6), and during non-outbreak periods it was 22.3% (95% CI, 20.9 to 23.8). Using the proportion of floor swabs positive for SARS-CoV-2 to predict Covid-19 outbreak status in a given week, the area under the receiver-operating characteristic curve was 0.84 (95% CI, 0.78 to 0.9). Among 10 LTCHs with an outbreak and swabs performed in the prior week, eight had positive floor swabs exceeding 10% at least 5 days before outbreak identification. For seven of these eight LTCHs, positivity of floor swabs exceeded 10% more than 10 days before the outbreak was identified. Conclusions: Detection of SARS-CoV-2 on floors is strongly associated with Covid-19 outbreaks in LTCHs. These data suggest a potential role for floor sampling in improving early outbreak identification. Wastewater testing has proven to be a valuable tool for forecasting Covid-19 outbreaks. Fralick et al. now report that swabbing of surfaces (i.e., floors) for SARS-CoV-2 may provide a similar benefit for predicting outbreaks in long-term care homes.

The association between diabetes and mortality among adult patients hospitalized with COVID-19: Cohort Study of Hospitalized Adults in Ontario, Canada and Copenhagen, Denmark

Importance Diabetes has been reported to be associated with an increased risk of death among patients with COVID-19. However, available studies lack detail on COVID illness severity and measurement of relevant comorbidities. Design, Setting, and Participants We conducted a multicenter, retrospective cohort study of patients over the age of 18 years who were hospitalized with COVID-19 between January 1, 2020 and November 30, 2020 in Ontario, Canada and Copenhagen, Denmark. Chart ion emphasizing co-morbidities and disease severity was performed by trained research personnel. The association between diabetes and death was measured using Poissson regression. Main Outcomes and Measures Within hospital 30-day risk of death. Results Our study included 1133 hospitalized patients with COVID-19 in Ontario and 305 in Denmark, of whom 405 and 75 patients respectively had pre-existing diabetes. In both Ontario and Denmark, patients with diabetes were more likely to be older, have chronic kidney disease, cardiovascular disease, higher troponin levels, and to receive antibiotics compared with adults who did not have diabetes. In Ontario, 24% (n=96) of adults with diabetes died compared with 15% (n=109) of adults without diabetes. In Denmark, 16% (n=12) of adults with diabetes died in hospital compared with 13% (n=29) among those without diabetes. In Ontario, the crude mortality rate ratio among patients with diabetes was 1.60 [1.24 – 2.07 95% CI] and in the adjusted regression model was 1.19 [0.86 – 1.66 95% CI]. In Denmark, the crude mortality rate ratio among patients with diabetes was 1.27 (0.68 – 2.36 95% CI) and in the adjusted model was 0.87 (0.49 – 1.54 95% CI)]. Meta-analysis of the two rate ratios from each region resulted in a crude mortality rate ratio of 1.55 (95% CI 1.22,1.96) and an adjusted mortality rate ratio of 1.11 (95% CI 0.84, 1.47). Conclusions Presence of diabetes was not strongly associated with in-hospital COVID mortality independent of illness severity and other comorbidities.

The spatial and temporal distribution of SARS-CoV-2 from the built environment of COVID-19 patient rooms: A multicentre prospective study.

BACKGROUND: SARS-CoV-2 can be detected from the built environment (e.g., floors), but it is unknown how the viral burden surrounding an infected patient changes over space and time. Characterizing these data can help advance our understanding and interpretation of surface swabs from the built environment. METHODS: We conducted a prospective study at two hospitals in Ontario, Canada between January 19, 2022 and February 11, 2022. We performed serial floor sampling for SARS-CoV-2 in rooms of patients newly hospitalized with COVID-19 in the past 48 hours. We sampled the floor twice daily until the occupant moved to another room, was discharged, or 96 hours had elapsed. Floor sampling locations included 1 metre (m) from the hospital bed, 2 m from the hospital bed, and at the room's threshold to the hallway (typically 3 to 5 m from the hospital bed). The samples were analyzed for the presence of SARS-CoV-2 using quantitative reverse transcriptase polymerase chain reaction (RT-qPCR). We calculated the sensitivity of detecting SARS-CoV-2 in a patient with COVID-19, and we evaluated how the percentage of positive swabs and the cycle threshold of the swabs changed over time. We also compared the cycle threshold between the two hospitals. RESULTS: Over the 6-week study period we collected 164 floor swabs from the rooms of 13 patients. The overall percentage of swabs positive for SARS-CoV-2 was 93% and the median cycle threshold was 33.4 (interquartile range [IQR]: 30.8, 37.2). On day 0 of swabbing the percentage of swabs positive for SARS-CoV-2 was 88% and the median cycle threshold was 33.6 (IQR: 31.8, 38.2) compared to swabs performed on day 2 or later where the percentage of swabs positive for SARS-CoV-2 was 98% and the cycle threshold was 33.2 (IQR: 30.6, 35.6). We found that viral detection did not change with increasing time (since the first sample collection) over the sampling period, Odds Ratio (OR) 1.65 per day (95% CI 0.68, 4.02; p = 0.27). Similarly, viral detection did not change with increasing distance from the patient's bed (1 m, 2 m, or 3 m), OR 0.85 per metre (95% CI 0.38, 1.88; p = 0.69). The cycle threshold was lower (i.e., more virus) in The Ottawa Hospital (median quantification cycle [Cq] 30.8) where floors were cleaned once daily compared to the Toronto hospital (median Cq 37.2) where floors were cleaned twice daily. CONCLUSIONS: We were able to detect SARS-CoV-2 on the floors in rooms of patients with COVID-19. The viral burden did not vary over time or by distance from the patient's bed. These results suggest floor swabbing for the detection of SARS-CoV-2 in a built environment such as a hospital room is both accurate and robust to variation in sampling location and duration of occupancy.

Antibiotic resistance associated with the COVID-19 pandemic: a systematic review and meta-analysis.

BACKGROUND: COVID-19 and antimicrobial resistance (AMR) are two intersecting global public health crises. OBJECTIVE: We aimed to describe the impact of the COVID-19 pandemic on AMR across health care settings. DATA SOURCE: A search was conducted in December 2021 in WHO COVID-19 Research Database with forward citation searching up to June 2022. STUDY ELIGIBILITY: Studies evaluating the impact of COVID-19 on AMR in any population were included and influencing factors were extracted. Reporting of enhanced infection prevention and control and/or antimicrobial stewardship programs was noted. METHODS: Pooling was done separately for Gram-negative and Gram-positive organisms. Random-effects meta-analysis was performed. RESULTS: Of 6036 studies screened, 28 were included and 23 provided sufficient data for meta-analysis. The majority of studies focused on hospital settings (n = 25, 89%). The COVID-19 pandemic was not associated with a change in the incidence density (incidence rate ratio 0.99, 95% CI: 0.67-1.47) or proportion (risk ratio 0.91, 95% CI: 0.55-1.49) of methicillin-resistant Staphylococcus aureus or vancomycin-resistant enterococci cases. A non-statistically significant increase was noted for resistant Gram-negative organisms (i.e. extended-spectrum beta-lactamase, carbapenem-resistant Enterobacterales, carbapenem or multi-drug resistant or carbapenem-resistant Pseudomonas aeruginosa or Acinetobacter baumannii, incidence rate ratio 1.64, 95% CI: 0.92-2.92; risk ratio 1.08, 95% CI: 0.91-1.29). The absence of reported enhanced infection prevention and control and/or antimicrobial stewardship programs initiatives was associated with an increase in gram-negative AMR (risk ratio 1.11, 95% CI: 1.03-1.20). However, a test for subgroup differences showed no statistically significant difference between the presence and absence of these initiatives (p 0.40). CONCLUSION: The COVID-19 pandemic may have hastened the emergence and transmission of AMR, particularly for Gram-negative organisms in hospital settings. But there is considerable heterogeneity in both the AMR metrics used and the rate of resistance reported across studies. These findings reinforce the need for strengthened infection prevention, antimicrobial stewardship, and AMR surveillance in the context of the COVID-19 pandemic.

Variation in the risk of death due to COVID-19: An international multicenter cohort study of hospitalized adults.

BACKGROUND: There is wide variation in mortality among patients hospitalized with COVID-19. Whether this is related to patient or hospital factors is unknown. OBJECTIVE: To compare the risk of mortality for patients hospitalized with COVID-19 and to determine whether the majority of that variation was explained by differences in patient characteristics across sites. DESIGN, SETTING, AND PARTICIPANTS: An international multicenter cohort study of hospitalized adults with laboratory-confirmed COVID-19 enrolled from 10 hospitals in Ontario, Canada and 8 hospitals in Copenhagen, Denmark between January 1, 2020 and November 11, 2020. MAIN OUTCOMES AND MEASURES: Inpatient mortality. We used a multivariable multilevel regression model to compare the in-hospital mortality risk across hospitals and quantify the variation attributable to patient-level factors. RESULTS: There were 1364 adults hospitalized with COVID-19 in Ontario (n = 1149) and in Denmark (n = 215). In Ontario, the absolute risk of in-hospital mortality ranged from 12.0% to 39.8% across hospitals. Ninety-eight percent of the variation in mortality in Ontario was explained by differences in the characteristics of the patients. In Denmark, the absolute risk of inpatients ranged from 13.8% to 20.6%. One hundred percent of the variation in mortality in Denmark was explained by differences in the characteristics of the inpatients. CONCLUSION: There was wide variation in inpatient COVID-19 mortality across hospitals, which was largely explained by patient-level factors, such as age and severity of presenting illness. However, hospital-level factors that could have affected care, including resource availability and capacity, were not taken into account. These findings highlight potential limitations in comparing crude mortality rates across hospitals for the purposes of reporting on the quality of care.

A Time Series Analysis Evaluating Antibiotic Prescription Rates in Long-Term Care during the COVID-19 Pandemic in Alberta and Ontario, Canada.

The COVID-19 pandemic affected access to care, and the associated public health measures influenced the transmission of other infectious diseases. The pandemic has dramatically changed antibiotic prescribing in the community. We aimed to determine the impact of the COVID-19 pandemic and the resulting control measures on oral antibiotic prescribing in long-term care facilities (LTCFs) in Alberta and Ontario, Canada using linked administrative data. Antibiotic prescription data were collected for LTCF residents 65 years and older in Alberta and Ontario from 1 January 2017 until 31 December 2020. Weekly prescription rates per 1000 residents, stratified by age, sex, antibiotic class, and selected individual agents, were calculated. Interrupted time series analyses using SARIMA models were performed to test for changes in antibiotic prescription rates after the start of the pandemic (1 March 2020). The average annual cohort size was 18,489 for Alberta and 96,614 for Ontario. A significant decrease in overall weekly prescription rates after the start of the pandemic compared to pre-pandemic was found in Alberta, but not in Ontario. Furthermore, a significant decrease in prescription rates was observed for antibiotics mainly used to treat respiratory tract infections: amoxicillin in both provinces (Alberta: -0.6 per 1000 LTCF residents decrease in weekly prescription rate, p = 0.006; Ontario: -0.8, p < 0.001); and doxycycline (-0.2, p = 0.005) and penicillin (-0.04, p = 0.014) in Ontario. In Ontario, azithromycin was prescribed at a significantly higher rate after the start of the pandemic (0.7 per 1000 LTCF residents increase in weekly prescription rate, p = 0.011). A decrease in prescription rates for antibiotics that are largely used to treat respiratory tract infections is in keeping with the lower observed rates for respiratory infections resulting from pandemic control measures. The results should be considered in the contexts of different LTCF systems and provincial public health responses to the pandemic.

Screening Large Population Health Databases for Potential Coronavirus Disease 2019 Therapeutics: A Pharmacopeia-Wide Association Study of Commonly Prescribed Medications.

Background: For both the current and future pandemics, there is a need for high-throughput drug screening methods to identify existing drugs with potential preventive and/or therapeutic activity. Epidemiologic studies could complement laboratory-focused efforts to identify possible therapeutic agents. Methods: We performed a pharmacopeia-wide association study (PWAS) to identify commonly prescribed medications and medication classes that are associated with the detection of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in older individuals (≥65 years) in long-term care homes (LTCHs) and the community, between 15 January 2020 and 31 December 2020, across the province of Ontario, Canada. Results: A total of 26 121 cases and 2 369 020 controls from LTCHs and the community were included in this analysis. Many of the drugs and drug classes evaluated did not yield significant associations with SARS-CoV-2 detection. However, some drugs and drug classes appeared to be significantly associated with reduced SARS-CoV-2 detection, including cardioprotective drug classes such as statins (weighted odds ratio [OR], 0.91; standard P < .01, adjusted P < .01) and ß-blockers (weighted OR, 0.87; standard P < .01, adjusted P = .01), along with individual agents ranging from levetiracetam (weighted OR, 0.70; standard P < .01, adjusted P < .01) to fluoxetine (weighted OR, 0.86; standard P = .013, adjusted P = .198) to digoxin (weighted OR, 0.89; standard P < .01, adjusted P = .02). Conclusions: Using this epidemiologic approach, which can be applied to current and future pandemics, we have identified a variety of target drugs and drug classes that could offer therapeutic benefit in coronavirus disease 2019 (COVID-19) and may warrant further validation. Some of these agents (eg, fluoxetine) have already been identified for their therapeutic potential.

Screening Large Population Health Databases for Potential COVID-19 Therapeutics: A Pharmacopeia-Wide Association Study (PWAS) of Commonly Prescribed Medications

Background For both the current and future pandemics, there is a need for high-throughput drug screening methods to identify existing drugs with potential preventative and/or therapeutic activity. Epidemiologic studies could complement lab-focused efforts to identify possible therapeutic agents. Methods We performed a pharmacopeia-wide association study (PWAS) to identify commonly prescribed medications and medication classes that are associated with the detection of SARS-CoV-2 in older individuals (>65 years) in long-term care homes (LTCH) and the community, between January 15 th, 2020 and December 31 st, 2020, across the province of Ontario, Canada. Results 26,121 cases and 2,369,020 controls from LTCH and the community were included in this analysis. Many of the drugs and drug classes evaluated did not yield significant associations with SARS-CoV-2 detection. However, some drugs and drug classes appeared significantly associated with reduced SARS-CoV-2 detection, including cardioprotective drug classes such as statins (weighted OR 0.91, standard p-value <0.01, adjusted p-value <0.01) and beta-blockers (weighted OR 0.87, standard p-value <0.01, adjusted p-value 0.01), along with individual agents ranging from levetiracetam (weighted OR 0.70, standard p-value <0.01, adjusted p-value <0.01) to fluoxetine (weighted OR 0.86, standard p-value 0.013, adjusted p-value 0.198) to digoxin (weighted OR 0.89, standard p-value <0.01, adjusted p-value 0.02). Conclusions Using this epidemiologic approach which can be applied to current and future pandemics we have identified a variety of target drugs and drug classes that could offer therapeutic benefit in COVID-19 and may warrant further validation. Some of these agents (e.g. fluoxetine) have already been identified for their therapeutic potential.

Écart de mobilité : estimation des seuils de mobilité requis pour maîtriser le SRAS-CoV-2 au Canada.

CONTEXTE: Les interventions non pharmacologiques demeurent le principal moyen de maîtriser le coronavirus du syndrome respiratoire aigu sévère 2 (SRAS-CoV-2) d'ici à ce que la couverture vaccinale soit suffisante pour donner lieu à une immunité collective. Nous avons utilisé des données de mobilité anonymisées de téléphones intelligents afin de quantifier le niveau de mobilité requis pour maîtriser le SRAS-CoV-2 (c.-à-d., seuil de mobilité), et la différence par rapport au niveau de mobilité observé (c.-à-d., écart de mobilité). MÉTHODES: Nous avons procédé à une analyse de séries chronologiques sur l'incidence hebdomadaire du SRAS-CoV-2 au Canada entre le 15 mars 2020 et le 6 mars 2021. Le paramètre mesuré était le taux de croissance hebdomadaire, défini comme le rapport entre les cas d'une semaine donnée et ceux de la semaine précédente. Nous avons mesuré les effets du temps moyen passé hors domicile au cours des 3 semaines précédentes à l'aide d'un modèle de régression log-normal, en tenant compte de la province, de la semaine et de la température moyenne. Nous avons calculé le seuil de mobilité et l'écart de mobilité pour le SRAS-CoV-2. RÉSULTATS: Au cours des 51 semaines de l'étude, en tout, 888 751 personnes ont contracté le SRAS-CoV-2. Chaque augmentation de 10 % de l'écart de mobilité a été associée à une augmentation de 25 % du taux de croissance des cas hebdomadaires de SRAS-CoV-2 (rapport 1,25, intervalle de confiance à 95 % 1,20­1,29). Comparativement à la mobilité prépandémique de référence de 100 %, le seuil de mobilité a été plus élevé au cours de l'été (69 %, écart interquartile [EI] 67 %­70 %), et a chuté à 54 % pendant l'hiver 2021 (EI 52 %­55 %); un écart de mobilité a été observé au Canada entre juillet 2020 et la dernière semaine de décembre 2020. INTERPRÉTATION: La mobilité permet de prédire avec fiabilité et constance la croissance des cas hebdomadaires et il faut maintenir des niveaux faibles de mobilité pour maîtriser le SRAS-CoV-2 jusqu'à la fin du printemps 2021. Les données de mobilité anonymisées des téléphones intelligents peuvent servir à guider le relâchement ou le resserrement des mesures de distanciation physique provinciales et régionales.

Predictors and microbiology of respiratory and bloodstream bacterial infection in patients with COVID-19: living rapid review update and meta-regression.

BACKGROUND: The prevalence of bacterial infection in patients with COVID-19 is low, however, empiric antibiotic use is high. Risk stratification may be needed to minimize unnecessary empiric antibiotic use. OBJECTIVE: To identify risk factors and microbiology associated with respiratory and bloodstream bacterial infection in patients with COVID-19. DATA SOURCES: We searched MEDLINE, OVID Epub and EMBASE for published literature up to 5 February 2021. STUDY ELIGIBILITY CRITERIA: Studies including at least 50 patients with COVID-19 in any healthcare setting. METHODS: We used a validated ten-item risk of bias tool for disease prevalence. The main outcome of interest was the proportion of COVID-19 patients with bloodstream and/or respiratory bacterial co-infection and secondary infection. We performed meta-regression to identify study population factors associated with bacterial infection including healthcare setting, age, comorbidities and COVID-19 medication. RESULTS: Out of 33 345 studies screened, 171 were included in the final analysis. Bacterial infection data were available from 171 262 patients. The prevalence of co-infection was 5.1% (95% CI 3.6-7.1%) and secondary infection was 13.1% (95% CI 9.8-17.2%). There was a higher odds of bacterial infection in studies with a higher proportion of patients in the intensive care unit (ICU) (adjusted OR 18.8, 95% CI 6.5-54.8). Female sex was associated with a lower odds of secondary infection (adjusted OR 0.73, 95% CI 0.55-0.97) but not co-infection (adjusted OR 1.05, 95% CI 0.80-1.37). The most common organisms isolated included Staphylococcus aureus, coagulase-negative staphylococci and Klebsiella species. CONCLUSIONS: While the odds of respiratory and bloodstream bacterial infection are low in patients with COVID-19, meta-regression revealed potential risk factors for infection, including ICU setting and mechanical ventilation. The risk for secondary infection is substantially greater than the risk for co-infection in patients with COVID-19. Understanding predictors of co-infection and secondary infection may help to support improved antibiotic stewardship in patients with COVID-19.

The Impact of COVID-19 on Outpatient Antibiotic Prescriptions in Ontario, Canada; An Interrupted Time Series Analysis.

BACKGROUND: The coronavirus disease 2019 (COVID-19) pandemic has potentially impacted outpatient antibiotic prescribing. Investigating this impact may identify stewardship opportunities in the ongoing COVID-19 period and beyond. METHODS: We conducted an interrupted time series analysis on outpatient antibiotic prescriptions and antibiotic prescriptions/patient visits in Ontario, Canada, between January 2017 and December 2020 to evaluate the impact of the COVID-19 pandemic on population-level antibiotic prescribing by prescriber specialty, patient demographics, and conditions. RESULTS: In the evaluated COVID-19 period (March-December 2020), there was a 31.2% (95% CI, 27.0% to 35.1%) relative reduction in total antibiotic prescriptions. Total outpatient antibiotic prescriptions decreased during the COVID-19 period by 37.1% (95% CI, 32.5% to 41.3%) among family physicians, 30.7% (95% CI, 25.8% to 35.2%) among subspecialist physicians, 12.1% (95% CI, 4.4% to 19.2%) among dentists, and 25.7% (95% CI, 21.4% to 29.8%) among other prescribers. Antibiotics indicated for respiratory infections decreased by 43.7% (95% CI, 38.4% to 48.6%). Total patient visits and visits for respiratory infections decreased by 10.7% (95% CI, 5.4% to 15.6%) and 49.9% (95% CI, 43.1% to 55.9%). Total antibiotic prescriptions/1000 visits decreased by 27.5% (95% CI, 21.5% to 33.0%), while antibiotics indicated for respiratory infections/1000 visits with respiratory infections only decreased by 6.8% (95% CI, 2.7% to 10.8%). CONCLUSIONS: The reduction in outpatient antibiotic prescribing during the COVID-19 pandemic was driven by less antibiotic prescribing for respiratory indications and largely explained by decreased visits for respiratory infections.

The impact of COVID-19 on community antibiotic use in Canada: an ecological study.

OBJECTIVES: The COVID-19 pandemic has had an effect on the incidence of infectious diseases and medical care. This study aimed to describe the impact of the COVID-19 pandemic on community-level antibiotic use. METHODS: Using national antibiotic dispensing data from IQVIA's CompuScript database, this ecological study investigated antibiotic dispensing through community retail pharmacies in Canada from November 2014 to October 2020. Analyses were stratified by age, sex, prescription origin and approximate indication. RESULTS: Adjusting for seasonality, the national rate of antibiotic dispensing in Canada decreased by 26.5% (50.4 to 37.0 average prescriptions per 1000 inhabitants) during the first 8 months of the Canadian COVID-19 period (March to October 2020), compared with the pre-COVID-19 period. Prescribing rates in children ≤18 years decreased from 43.7 to 12.2 prescriptions per 1000 inhabitants in males (-72%) and from 46.8 to 14.9 prescriptions per 1000 inhabitants in females (-68%) in April 2020. Rates in adults ≥65 decreased from 74.9 to 48.8 prescriptions per 1000 inhabitants in males (-35%) and from 91.7 to 61.3 prescriptions per 1000 inhabitants in females (-33%) in May 2020. Antibiotic prescriptions from family physicians experienced a greater decrease than from surgeons and infectious disease physicians. Prescribing rates for antibiotics for respiratory indications decreased by 56% in May 2020 (29.2 to 12.8 prescriptions per 1000 inhabitants), compared with prescribing rates for urinary tract infections (9.4 to 7.8 prescriptions per 1000 inhabitants; -17%) and skin and soft tissue infections (6.4 to 5.2 prescriptions per 1000 inhabitants; -19%). DISCUSSION: The first 8 months of the COVID-19 pandemic reduced community antibiotic dispensing by 26.5% in Canada, compared with the marginal decrease of 3% in antibiotic consumption between 2015 and 2019. Further research is needed to understand the implications and long-term effects of the observed reductions on antibiotic use on antibiotic resistance in Canada.

The mobility gap: estimating mobility thresholds required to control SARS-CoV-2 in Canada.

BACKGROUND: Nonpharmaceutical interventions remain the primary means of controlling severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) until vaccination coverage is sufficient to achieve herd immunity. We used anonymized smartphone mobility measures to quantify the mobility level needed to control SARS-CoV-2 (i.e., mobility threshold), and the difference relative to the observed mobility level (i.e., mobility gap). METHODS: We conducted a time-series study of the weekly incidence of SARS-CoV-2 in Canada from Mar. 15, 2020, to Mar. 6, 2021. The outcome was weekly growth rate, defined as the ratio of cases in a given week versus the previous week. We evaluated the effects of average time spent outside the home in the previous 3 weeks using a log-normal regression model, accounting for province, week and mean temperature. We calculated the SARS-CoV-2 mobility threshold and gap. RESULTS: Across the 51-week study period, a total of 888 751 people were infected with SARS-CoV-2. Each 10% increase in the mobility gap was associated with a 25% increase in the SARS-CoV-2 weekly case growth rate (ratio 1.25, 95% confidence interval 1.20-1.29). Compared to the prepandemic baseline mobility of 100%, the mobility threshold was highest in the summer (69%; interquartile range [IQR] 67%-70%), and dropped to 54% in winter 2021 (IQR 52%-55%); a mobility gap was present in Canada from July 2020 until the last week of December 2020. INTERPRETATION: Mobility strongly and consistently predicts weekly case growth, and low levels of mobility are needed to control SARS-CoV-2 through spring 2021. Mobility measures from anonymized smartphone data can be used to guide provincial and regional loosening and tightening of physical distancing measures.

Evaluating the contributions of strategies to prevent SARS-CoV-2 transmission in the healthcare setting: a modelling study.

INTRODUCTION: Since its onset, the COVID-19 pandemic has caused significant morbidity and mortality worldwide, with particularly severe outcomes in healthcare institutions and congregate settings. To mitigate spread, healthcare systems have been cohorting patients to limit contacts between uninfected patients and potentially infected patients or healthcare workers (HCWs). A major challenge in managing the pandemic is the presence of currently asymptomatic/presymptomatic individuals capable of transmitting the virus, who could introduce COVID-19 into uninfected cohorts. The optimal combination of personal protective equipment (PPE), testing and other approaches to prevent these events is unclear, especially in light of ongoing limited resources. METHODS: Using stochastic simulations with a susceptible-exposed-infected-recovered dynamic model, we quantified and compared the impacts of PPE use, patient and HCWs surveillance testing and subcohorting strategies. RESULTS: In the base case without testing or PPE, the healthcare system was rapidly overwhelmed, and became a net contributor to the force of infection. We found that effective use of PPE by both HCWs and patients could prevent this scenario, while random testing of apparently asymptomatic/presymptomatic individuals on a weekly basis was less effective. We also found that even imperfect use of PPE could provide substantial protection by decreasing the force of infection. Importantly, we found that creating smaller patient/HCW-interaction subcohorts can provide additional resilience to outbreak development with limited resources. CONCLUSION: These findings reinforce the importance of ensuring adequate PPE supplies even in the absence of testing and provide support for strict subcohorting regimens to reduce outbreak potential in healthcare institutions.

Antibiotic prescribing in patients with COVID-19: rapid review and meta-analysis.

BACKGROUND: The proportion of patients infected with SARS-CoV-2 that are prescribed antibiotics is uncertain, and may contribute to patient harm and global antibiotic resistance. OBJECTIVE: The aim was to estimate the prevalence and associated factors of antibiotic prescribing in patients with COVID-19. DATA SOURCES: We searched MEDLINE, OVID Epub and EMBASE for published literature on human subjects in English up to June 9 2020. STUDY ELIGIBILITY CRITERIA: We included randomized controlled trials; cohort studies; case series with ≥10 patients; and experimental or observational design that evaluated antibiotic prescribing. PARTICIPANTS: The study participants were patients with laboratory-confirmed SARS-CoV-2 infection, across all healthcare settings (hospital and community) and age groups (paediatric and adult). METHODS: The main outcome of interest was proportion of COVID-19 patients prescribed an antibiotic, stratified by geographical region, severity of illness and age. We pooled proportion data using random effects meta-analysis. RESULTS: We screened 7469 studies, from which 154 were included in the final analysis. Antibiotic data were available from 30 623 patients. The prevalence of antibiotic prescribing was 74.6% (95% CI 68.3-80.0%). On univariable meta-regression, antibiotic prescribing was lower in children (prescribing prevalence odds ratio (OR) 0.10, 95% CI 0.03-0.33) compared with adults. Antibiotic prescribing was higher with increasing patient age (OR 1.45 per 10 year increase, 95% CI 1.18-1.77) and higher with increasing proportion of patients requiring mechanical ventilation (OR 1.33 per 10% increase, 95% CI 1.15-1.54). Estimated bacterial co-infection was 8.6% (95% CI 4.7-15.2%) from 31 studies. CONCLUSIONS: Three-quarters of patients with COVID-19 receive antibiotics, prescribing is significantly higher than the estimated prevalence of bacterial co-infection. Unnecessary antibiotic use is likely to be high in patients with COVID-19.

Bacterial co-infection and secondary infection in patients with COVID-19: a living rapid review and meta-analysis.

BACKGROUND: Bacterial co-pathogens are commonly identified in viral respiratory infections and are important causes of morbidity and mortality. The prevalence of bacterial infection in patients infected with SARS-CoV-2 is not well understood. AIMS: To determine the prevalence of bacterial co-infection (at presentation) and secondary infection (after presentation) in patients with COVID-19. SOURCES: We performed a systematic search of MEDLINE, OVID Epub and EMBASE databases for English language literature from 2019 to April 16, 2020. Studies were included if they (a) evaluated patients with confirmed COVID-19 and (b) reported the prevalence of acute bacterial infection. CONTENT: Data were extracted by a single reviewer and cross-checked by a second reviewer. The main outcome was the proportion of COVID-19 patients with an acute bacterial infection. Any bacteria detected from non-respiratory-tract or non-bloodstream sources were excluded. Of 1308 studies screened, 24 were eligible and included in the rapid review representing 3338 patients with COVID-19 evaluated for acute bacterial infection. In the meta-analysis, bacterial co-infection (estimated on presentation) was identified in 3.5% of patients (95%CI 0.4-6.7%) and secondary bacterial infection in 14.3% of patients (95%CI 9.6-18.9%). The overall proportion of COVID-19 patients with bacterial infection was 6.9% (95%CI 4.3-9.5%). Bacterial infection was more common in critically ill patients (8.1%, 95%CI 2.3-13.8%). The majority of patients with COVID-19 received antibiotics (71.9%, 95%CI 56.1 to 87.7%). IMPLICATIONS: Bacterial co-infection is relatively infrequent in hospitalized patients with COVID-19. The majority of these patients may not require empirical antibacterial treatment.