Estimating the impact of COVID-19 control measures using a Bayesian model of physical distancing

Abstract

Extensive physical distancing measures are currently the primary intervention against coronavirus disease (COVID-) worldwide. It is therefore urgent to estimate the impact such measures are having. We introduce a Bayesian epidemiological model in which a proportion of individuals are willing and able to participate in distancing measures, with the timing of these measures informed by survey data on a itudes to distancing and COVID-. We t our model to reported COVID-cases in British Columbia, Canada, using an observation model that accounts for both underestimation and the delay between symptom onset and reporting. We estimate the impact that physical distancing (also known as social distancing) has had on the contact rate and examine the projected impact of relaxing distancing measures. We nd that distancing has had a strong impact, consistent with declines in reported cases and in hospitalization and intensive care unit numbers. We estimate that approximately . ( . -. % CI) of contacts have been removed for individuals in British Columbia practising physical distancing and that this fraction is above the threshold of . at which prevalence is expected to grow. However, relaxing distancing measures beyond this threshold re-starts rapid exponential growth. Because the extent of underestimation is unknown, the data are consistent with a wide range in the prevalence of COVID-in the population; changes to testing criteria over time introduce additional uncertainty. Our projections indicate that intermi ent distancing measures-if su ciently strong and robustly followedcould control COVID-transmission, but that if distancing measures are relaxed too much, the epidemic curve would grow to high prevalence.

Conditions for a Second Wave of COVID-19 Due to Interactions Between Disease Dynamics and Social Processes

“…The timeseries show that the epidemic curve is flattened and delayed as closure becomes more efficacious, which reduces peak demand for intensive care beds and buys time for developing pharmaceutical interventions like vaccines and antiviral drugs, improving testing capacity, and establishing novel approaches to patient care. For the remainder of our analysis, to determine C 0 it was assumed that C 0 should be large enough to bring the effective reproduction number R eff below 1, reflecting the observed success in multiple jurisdictions where physical distancing and closure have maintained R eff < 1 [6][7][8]. Hence we chose C 0 = 1 − 1/R 0 based on the elimination threshold for the SEIR model [30].…”

“…Mathematical models of SARS-CoV-2 transmission and control show that physical distancing can mitigate the pandemic [2][3][4][5] and this has subsequently been backed up by empirical analyses of case notification data. These analyses show how mitigation measures have reduced the effective reproduction number of SARS-CoV-2 below one, meaning that each infected case infects less than one person on average [6][7][8]. However, the population's willingness to support school and workplace closures could wane over time, as the economic costs of closure accumulate [9].…”

Ranking the effectiveness of worldwide COVID-19 government interventions

“…To date, studies of the country-specific progression of the COVID-19 pandemic 7 have mostly explored the independent effects of a single category of interventions. These categories include travel restrictions 2,8 , social distancing [9][10][11][12] , or personal protective measures 13 . Some studies focused on a single country or even a town [14][15][16][17][18] .…”

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

“…These measures have flattened the epidemic curve: They have reduced the effective reproduction number of SARS-CoV-2 below one, meaning that each infected case is infecting less than one person on average (5). The epidemic curve is a common way to visualize the spread of an infectious disease and has become ubiquitous during the COVID-19 pandemic.…”