The Collapse of Infectious Disease Diagnoses Commonly Due to Communicable Respiratory Pathogens During the Coronavirus Disease 2019 Pandemic: A Time Series and Hierarchical Clustering Analysis.

Background: Nonpharmaceutical interventions such as physical distancing and mandatory masking were adopted in many jurisdictions during the coronavirus disease 2019 pandemic to decrease spread of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). We determined the effects of these interventions on incidence of healthcare utilization for other infectious diseases. Methods: Using a healthcare administrative dataset, we employed an interrupted time series analysis to measure changes in healthcare visits for various infectious diseases across the province of Ontario, Canada, from January 2017 to December 2020. We used a hierarchical clustering algorithm to group diagnoses that demonstrated similar patterns of change through the pandemic months. Results: We found that visits for infectious diseases commonly caused by communicable respiratory pathogens (eg, acute bronchitis, acute sinusitis) formed distinct clusters from diagnoses that often originate from pathogens derived from the patient's own flora (eg, urinary tract infection, cellulitis). Moreover, infectious diagnoses commonly arising from communicable respiratory pathogens (hierarchical cluster 1: highly impacted diagnoses) were significantly decreased, with a rate ratio (RR) of 0.35 (95% confidence interval [CI], .30-.40; P < .001) after the introduction of public health interventions in April-December 2020, whereas infections typically arising from the patient's own flora (hierarchical cluster 3: minimally impacted diagnoses) did not demonstrate a sustained change in incidence (RR, 0.95 [95% CI, .90-1.01]; P = .085). Conclusions: Public health measures to curtail the incidence of SARS-CoV-2 were widely effective against other communicable respiratory infectious diseases with similar modes of transmission but had little effect on infectious diseases not strongly dependent on person-to-person transmission.

A wastewater-based epidemic model for SARS-CoV-2 with application to three Canadian cities.

The COVID-19 pandemic has stimulated wastewater-based surveillance, allowing public health to track the epidemic by monitoring the concentration of the genetic fingerprints of SARS-CoV-2 shed in wastewater by infected individuals. Wastewater-based surveillance for COVID-19 is still in its infancy. In particular, the quantitative link between clinical cases observed through traditional surveillance and the signals from viral concentrations in wastewater is still developing and hampers interpretation of the data and actionable public-health decisions. We present a modelling framework that includes both SARS-CoV-2 transmission at the population level and the fate of SARS-CoV-2 RNA particles in the sewage system after faecal shedding by infected persons in the population. Using our mechanistic representation of the combined clinical/wastewater system, we perform exploratory simulations to quantify the effect of surveillance effectiveness, public-health interventions and vaccination on the discordance between clinical and wastewater signals. We also apply our model to surveillance data from three Canadian cities to provide wastewater-informed estimates for the actual prevalence, the effective reproduction number and incidence forecasts. We find that wastewater-based surveillance, paired with this model, can complement clinical surveillance by supporting the estimation of key epidemiological metrics and hence better triangulate the state of an epidemic using this alternative data source.

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.