Stringency of containment and closures on the growth of SARS-CoV-2 in Canada prior to accelerated vaccine roll-out

Abstract

Background: Many studies have examined the effectiveness of non-pharmaceutical interventions (NPIs) on SARS-CoV-2 transmission worldwide. However, less attention has been devoted to understanding the limits of NPIs across the course of the pandemic and along a continuum of their stringency. In this study, we explore the relationship between the growth of SARS-CoV-2 cases and an NPI stringency index across Canada before the accelerated vaccine roll-out.

Methods: We conducted an ecological time-series study of daily SARS-CoV-2 case growth in Canada from February 2020 to February 2021. Our outcome was a back-projected version of the daily growth ratio in a stringency period (i.e., a 10-point range of the stringency index) relative to the last day of the previous period. We examined the trends in case growth using a linear mixed-effects model accounting for stringency period, province, and mobility in public domains.

Results: Case growth declined rapidly by 20-60% and plateaued within the first month of the first wave, irrespective of the starting values of the stringency index. When stringency periods increased, changes in case growth were not immediate and were faster in the first wave than in the second. In the first wave, the largest decreasing trends from our mixed effects model occurred in both early and late stringency periods, depending on the province, at a geometric mean index value of 30⋅1 out of 100. When compared with the first wave, the stringency periods in the second wave possessed little association with case growth.

Conclusions: The minimal association in the first wave, and the lack thereof in the second, is compatible with the hypothesis that NPIs do not, per se, lead to a decline in case growth. Instead, the correlations we observed might be better explained by a combination of underlying behaviors of the populations in each province and the natural dynamics of SARS-CoV-2. Although there exist alternative explanations for the equivocal relationship between NPIs and case growth, the onus of providing evidence shifts to demonstrating how NPIs can consistently have flat association, despite incrementally high stringency.

Keywords: Epidemiology; Non-pharmaceutical Interventions; SARS-CoV-2; Stringency Index.

Figure 1

Schematic diagrams of: (A) Back-projected cases by their estimated date of infection (blue ribbon) versus their date of report (gray bars). Because of delays between being infected and confirmed as a case, the back-projected cases occur earlier in time. The light and dark blue ribbons are the 90% and 50% credible intervals, respectively; and (B) our calculation of the relative growth ratio. Day t is defined as the t-th day of a stringency period (i.e., since O.S.I changed deciles). Day n represents the last day of the period. Note that different stringency periods could have different numbers of days; O.S.I = Oxford Stringency Index; g(t) = growth rate on day t. Panel (A) is modified from Abbott et al., 2020Figure 1. Panel (B) is a modified version of Figure 1 in Li et al., 2020.

Figure 2

Epidemic curves of observed cases (gray bars) and the mean back-projected cases (blue line) in 5 Canadian provinces. Because of delays between being infected and being confirmed as a case, the back-projected cases occur earlier in time.

Figure 3

Growth ratios in cases for the study provinces. The panels below show the daily growth ratio in cases and demonstrate a shared decline in case growth across all provinces. The y-axis re-scales the growth ratios against that on the first day after study inclusion. The dashed line represents the average cumulative reduction in growth ratio across all provinces in the second wave (20%); Str. Period = Stringency Period.

Figure 4

Temporal changes in the relative growth ratio following 10-point changes in the stringency index, in each wave, for all provinces combined. For each stringency period, the reference point is the day before entering a that period. It is important to note that different stringency periods can have different numbers of days. Because of limited data availability, particularly in the first wave, we did not plot timelines longer than 30 days. A locally weighted smoothing function (black line) plots the trend (i.e., the average) across each wave. Shaded regions are 95% confidence intervals. Str. Period = Stringency Period.

Figure 5

Steepness (slope) of relative growth ratio across different stringency periods (i.e., deciles of the Oxford Stringency Index) for each province (colored dots) as estimated by the mixed effects regression analysis. Values > 0 (dashed line) indicate increased case growth, and values < 0 indicate decreased growth. Here, the greatest decline in growth rate in each province happened with the least stringent measures, at the earliest stages of the pandemic. A locally weighted smoothing function (black dotted line) is plotted to visualize trends in the estimated slopes across all provinces. Shaded regions are 95% confidence intervals.