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 COVID-19 pandemic to decrease spread of 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 (e.g. acute bronchitis, acute sinusitis) formed distinct clusters from diagnoses that often originate from pathogens derived from the patient’s own flora (e.g. 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% CI = 0.30-0.40, p < 0.001) after the introduction of public health interventions in April 2020 through 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 = 0.90-1.01, p = 0.085) 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.