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Modeling serological testing to inform relaxation of social distancing for COVID-19 control.

ABSTRACT: Serological testing remains a passive component of the public health response to the COVID-19 pandemic. Using a transmission model, we examine how serological testing could have enabled seropositive individuals to increase their relative levels of social interaction while offsetting transmission risks. We simulate widespread serological testing in New York City, South Florida, and Washington Puget Sound and assume seropositive individuals partially restore their social contacts. Compared to no intervention, our model suggests that widespread serological testing starting in late 2020 would have averted approximately 3300 deaths in New York City, 1400 deaths in South Florida and 11,000 deaths in Washington State by June 2021. In all sites, serological testing blunted subsequent waves of transmission. Findings demonstrate the potential benefit of widespread serological testing, had it been implemented in the pre-vaccine era, and remain relevant now amid the potential for emergence of new variants.

SUBMITTER: Kraay ANM

PROVIDER: S-EPMC8642547 | biostudies-literature | 2021 Dec

REPOSITORIES: biostudies-literature

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Modeling serological testing to inform relaxation of social distancing for COVID-19 control.

Kraay Alicia N M ANM Nelson Kristin N KN Zhao Conan Y CY Demory David D Weitz Joshua S JS Lopman Benjamin A BA

Nature communications 20211203 1

Serological testing remains a passive component of the public health response to the COVID-19 pandemic. Using a transmission model, we examine how serological testing could have enabled seropositive individuals to increase their relative levels of social interaction while offsetting transmission risks. We simulate widespread serological testing in New York City, South Florida, and Washington Puget Sound and assume seropositive individuals partially restore their social contacts. Compared to no i ...[more]

PMID: 34862373

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Project description:Stay-at-home orders and shutdowns of non-essential businesses are powerful, but socially costly, tools to control the pandemic spread of SARS-CoV-2. Mass testing strategies, which rely on widely administered frequent and rapid diagnostics to identify and isolate infected individuals, could be a potentially less disruptive management strategy, particularly where vaccine access is limited. In this paper, we assess the extent to which mass testing and isolation strategies can reduce reliance on socially costly non-pharmaceutical interventions, such as distancing and shutdowns. We develop a multi-compartmental model of SARS-CoV-2 transmission incorporating both preventative non-pharmaceutical interventions (NPIs) and testing and isolation to evaluate their combined effect on public health outcomes. Our model is designed to be a policy-guiding tool that captures important realities of the testing system, including constraints on test administration and non-random testing allocation. We show how strategic changes in the characteristics of the testing system, including test administration, test delays, and test sensitivity, can reduce reliance on preventative NPIs without compromising public health outcomes in the future. The lowest NPI levels are possible only when many tests are administered and test delays are short, given limited immunity in the population. Reducing reliance on NPIs is highly dependent on the ability of a testing program to identify and isolate unreported, asymptomatic infections. Changes in NPIs, including the intensity of lockdowns and stay at home orders, should be coordinated with increases in testing to ensure epidemic control; otherwise small additional lifting of these NPIs can lead to dramatic increases in infections, hospitalizations and deaths. Importantly, our results can be used to guide ramp-up of testing capacity in outbreak settings, allow for the flexible design of combined interventions based on social context, and inform future cost-benefit analyses to identify efficient pandemic management strategies.

Project description:BackgroundSince March 2020, when coronavirus disease 2019 (COVID-19) was declared a pandemic, many countries have applied unprecedented restrictive measures to contain the spread of the virus. This study aimed to explore the optimal social distancing policy for COVID-19 control in South Korea to safely reopen the society.MethodsWe developed an age-specific, deterministic compartment epidemic model to examine the COVID-19 control decision-making process, including the epidemiology of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) between 1 July 2021 and 30 December 2022. The model consists of the natural history of COVID-19, testing performance, vaccinations, and social distancing enforcement measures to detect and control SARS-CoV-2. We modelled potential intervention scenarios with three distinct components: 1) social distancing duration and level; 2) testing intensity; and 3) vaccination uptake rate. The primary and secondary outcomes were COVID-19 incidence and prevalence of severe patients requiring intensive care unit (ICU) care.ResultsFour (or more) months of social distancing (that can reduce 40-60% transmission) may mitigate epidemic resurgence and ICU demand in the future and keep the cases below the capacity limit if the testing intensity and vaccination rate remain constant or increase by 20% (with respect to the current level). In contrast, two months of strict social distancing enforcement may also successfully mitigate future epidemic surge and ICU demand as long as testing intensity and vaccination rates are increased by 20%.ConclusionIn South Korea, given the relatively high vaccination coverage and low incidence, four or more months of social distancing enforcement can effectively mitigate epidemic resurgence after lifting the social distancing measures. In addition, increasing the testing intensity and vaccination rate may help reduce necessary social distancing levels and duration to prevent a future epidemic resurgence and mitigate social and economic damage.

Dataset Information

Modeling serological testing to inform relaxation of social distancing for COVID-19 control.

Publications

Modeling serological testing to inform relaxation of social distancing for COVID-19 control.

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