Local lockdowns outperform global lockdown on the far side of the COVID-19 epidemic curve

Abstract

In the late stages of an epidemic, infections are often sporadic and geographically distributed. Spatially structured stochastic models can capture these important features of disease dynamics, thereby allowing a broader exploration of interventions. Here we develop a stochastic model of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) transmission among an interconnected group of population centers representing counties, municipalities, and districts (collectively, “counties”). The model is parameterized with demographic, epidemiological, testing, and travel data from Ontario, Canada. We explore the effects of different control strategies after the epidemic curve has been flattened. We compare a local strategy of reopening (and reclosing, as needed) schools and workplaces county by county, according to triggers for county-specific infection prevalence, to a global strategy of province-wide reopening and reclosing, according to triggers for province-wide infection prevalence. For trigger levels that result in the same number of COVID-19 cases between the two strategies, the local strategy causes significantly fewer person-days of closure, even under high intercounty travel scenarios. However, both cases and person-days lost to closure rise when county triggers are not coordinated and when testing rates vary among counties. Finally, we show that local strategies can also do better in the early epidemic stage, but only if testing rates are high and the trigger prevalence is low. Our results suggest that pandemic planning for the far side of the COVID-19 epidemic curve should consider local strategies for reopening and reclosing.

Non-pharmaceutical interventions during the COVID-19 pandemic: A review

“…The papers that used a metapopulation approach in the sample under investigation here cover several important angles such as the spatial heterogeneity of the pandemic due to local differences in the implementation of NPIs and/or features of population distributions [107] , [116] , [117] , the first pandemic wave and the efficacy of the measures put in place [108] , [109] , [110] , [111] , [112] , [113] , [121] , and reopening scenarios [106] , [114] , [115] , [118] . Let’s dive in some details.…”

“…Ref. [106] uses a metapopulation approach considering all counties of Ontario Canada. Mobility across subpopulation is estimated via a survey that mapped commuters in the region.…”

“…A subsets of papers use a metapopulation approach accounting also for the age-stratification and contact matrices within each subpopulation. In this group we find papers that evaluate the risks of importation of cases from China in the early phases of the pandemic [22] , model the first wave [119] , [121] , [122] , [123] , [147] and investigate reopening scenarios [106] , [120] .…”

The effect of COVID-19 on the economy: Evidence from an early adopter of localized lockdowns

“…As countries have begun to reopen and ease mobility restrictions, localized lockdowns are increasingly considered a critical element of a non-pharmaceutical toolkit to control COVID-19 resurgence [ 9 , 10 , 23 , 34 , 35 ]. In contrast to nation-wide lockdowns, localized lockdowns are implemented over a limited geographical area, ranging from a neighbourhood to a city, including suburbs, districts, or towns.…”

Estimating the COVID-19 R number: a bargain with the devil?

“…In a similar vein, transmission models that project COVID-19 cases and deaths under different NPI scenarios could be highly valuable for optimising a country's portfolio of NPIs. 8 , 9 , 10 Moreover, I think R provides a social utility that epidemiologists can easily overlook. The success of large-scale NPIs requires population adherence.…”