Effectiveness of non-pharmaceutical interventions to reduce SARS-CoV-2 transmission in Canada and their association with COVID-19 hospitalization rates

Abstract

Background: Non-pharmaceutical interventions (NPIs) aim to reduce the incidence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infections mostly by limiting contacts between people where virus transmission can occur. However, NPIs limit social interactions and have negative impacts on economic, physical, mental and social well-being. It is, therefore, important to assess the impact of NPIs on reducing the number of coronavirus disease 2019 (COVID-19) cases and hospitalizations to justify their use.

Methods: Dynamic regression models accounting for autocorrelation in time series data were used with data from six Canadian provinces (British Columbia, Alberta, Saskatchewan, Manitoba, Ontario, Québec) to assess 1) the effect of NPIs (measured using a stringency index) on SARS-CoV-2 transmission (measured by the effective reproduction number), and 2) the effect of the number of hospitalized COVID-19 patients on the stringency index.

Results: Increasing stringency index was associated with a statistically significant decrease in the transmission of SARS-CoV-2 in Alberta, Saskatchewan, Manitoba, Ontario and Québec. The effect of stringency on transmission was time-lagged in all of these provinces except for Ontario. In all provinces except for Saskatchewan, increasing hospitalization rates were associated with a statistically significant increase in the stringency index. The effect of hospitalization on stringency was time-lagged.

Conclusion: These results suggest that NPIs have been effective in Canadian provinces, and that their implementation has been, in part, a response to increasing hospitalization rates of COVID-19 patients.

Keywords: COVID-19 hospitalization rates; SARS-CoV-2 transmission; dynamic regression; non-pharmaceutical interventions.

Figure 1

Summary of the model building and model selection approaches run separately for each province and objective Abbreviations: C, period of time with combined effects of vaccination, Alpha variant and winter; H, number of hospitalized COVID-19 patients; lag7, time lags at seven days; lag14, time lags at 14 days; obj, objective; R_t, transmission rate; sidx, stringency index

Figure 2

Study period time series at provincial level^a Abbreviations: AB, Alberta; BC, British Columbia; H, number of hospitalized COVID-19 patients; MB, Manitoba; ON, Ontario; QC, Québec; R_t, transmission rate; SK, Saskatchewan ^a Study period time series at provincial level for a) transmission rate, R_t, b) stringency of NPIs, sidx, and c) number of hospitalized COVID-19 patients, H, per capita, for visual comparison. Data are averaged per week

Figure 3

Scatter plot of stringency of non-pharmaceutical interventions against the transmission rate for six provinces in Canada^a Abbreviations: AB, Alberta; BC, British Columbia; MB, Manitoba; ON, Ontario; QC, Québec; R_t, transmission rate; sidx, stringency index; SK, Saskatchewan ^a Data are averaged per week. A linear fitted line between sidx and R_t with standard errors are included to highlight the trend between the two variables

Figure 4

Scatter plot of stringency of non-pharmaceutical interventions against the number of hospitalized COVID-19 patients for six provinces in Canada^a Abbreviations: AB, Alberta; BC, British Columbia; H, number of hospitalized COVID-19 patients; MB, Manitoba; ON, Ontario; QC, Québec; sidx, stringency index; SK, Saskatchewan ^a Data are averaged per week. A linear fitted line between sidx and H with standard errors are included to highlight the trend between the two variables