Post-lockdown infection rates of COVID-19 following the reopening of public businesses

Abstract

Background The Coronavirus Disease 2019 (COVID-19) pandemic warranted a myriad of government-ordered business closures across the USA in efforts to mitigate the spread of the virus. This study aims to discover the implications of government-enforced health policies of reopening public businesses amidst the pandemic and its effect on county-level infection rates. Methods Eighty-three US counties (n = 83) that reported at least 20 000 cases as of 4 November 2020 were selected for this study. The dates when businesses (restaurants, bars, retail, gyms, salons/barbers and public schools) partially and fully reopened, as well as infection rates on the 1st and 14th days following each businesses’ reopening, were recorded. Regression analysis was conducted to deduce potential associations between the 14-day change in infection rate and mask usage frequency, median household income, population density and social distancing. Results On average, infection rates rose significantly as businesses reopened. The average 14-day change in infection rate was higher for fully reopened businesses (infection rate = +0.100) compared to partially reopened businesses (infection rate = +0.0454). The P-value of the two distributions was 0.001692, indicating statistical significance (P < 0.01). Conclusion This research provides insight into the transmission of COVID-19 and promotes evidence-driven policymaking for disease prevention and community health.

SIR model with social gatherings

“…This fact may provide a new insight on the way that NPIs such as social distancing and lockdowns affect the spread of the disease. For instance, it may be a tool to determine how restriction policies on social gatherings should be defined; or it may be helpful to better understand why infection rates can rise significantly after lockdowns are lifted [3]. 1.5 Finite population stochastic dynamics and mean-field limit.…”

“…More generally, for our proposed model (3), one can also study the finite population case. Let us thus consider the jump Markov process X N t = (S N t , I N t , R N t ) on {0, .…”

“…In this section we study the analytical behaviour of our proposed model (3). The following proposition summarizes the main properties of the function B(i) that we will use throughout this article.…”

“…, N } 3 described in Section 1.5, and also in Example 9. Denote Z N t = 1 N X N t , and let z t = (s t , i t , r t ) be the solution to (3). Assume that lim N Z N 0 = z 0 .…”

Impact of local mask mandates upon COVID-19 case rates in Oklahoma

“…Efforts for reducing community transmission of severe acute respiratory syndrome Coronavirus 2 (SARS-CoV-2), the causative agent for Coronavirus disease 2019 (COVID-19), initially focused on dramatic measures including federally-endorsed and state-mandated “shut-downs.” These included closure of schools (primary, secondary, and higher education), businesses, churches, and events, as well as restrictions on travel and nearly all commercial and non-commercial activities outside the home. These restrictions were effective in slowing the emergence of the pandemic in the US [ 1 ], but inflicted great costs, economic and otherwise [ 2 , 3 ]. With the recognition that these measures could not be permanent, and as understanding of transmission increased, more targeted policy recommendations became common, including reduction of large gatherings, encouragement of social distancing, utilization of face coverings [ 4 ], and eventually vaccination.…”