The Potential of Digital Symptom-based Screening to Reduce the Transmission of SARS-CoV-2: a Modelling Study (Preprint)

Abstract

BACKGROUND Early efforts to control the COVID-19 pandemic have been focused on Non-Pharmaceutical Interventions (NPIs) in the absence of effective treatments or sufficient vaccine supply. While retrospective analyses and modeling studies confirmed that severe restrictions of social contacts, i.e., lockdowns, are most effective in reducing transmission of SARS-CoV-2, they incur large economic costs and mental health risks. Earlier detection of cases has also been proposed as an effective method of control, but studies have so far only considered enhanced laboratory testing. Digital applications have been developed which aim to identify possible cases of COVID-19 based on reported symptoms and risk factors. OBJECTIVE The aim of this study is to explore the effects of digital screening applications for COVID-19 on the transmission of SARS-CoV-2. METHODS Using an established epidemiological Susceptible-Exposed-Infectious-Recovered (SEIR) model for infectious disease transmission, we simulate the transmission of SARS-CoV-2 in Germany, the UK, and the USA for 366 days after the virus was introduced in the population. We study 4 scenarios: 1) no interventions (base case), 2) symptom-based self-isolation after consulting healthcare providers, 3) self-isolation using digital screening applications, and 4) severe social contact limitations (lockdown). We included sensitivity analyses for different ratios of infectiousness of pre-symptomatic cases compared to symptomatic cases, and different rates of adoption of digital screening tools. RESULTS Without any intervention, 74% of the German population would be infected with SARS-CoV-2 within the simulation period (UK: 76%, USA: 77%). Self-isolation of symptomatic cases would already slow the spread of the virus significantly and lead to only 18% of the German population being infected (UK: 17%, USA: 17%). Using a digital application could further reduce the infected population to 10% (UK: 9%, USA: 9%), compared to 3% under lockdown conditions. While the effectiveness of digital screening applications varies with the adoption rate, even a low adoption rate could significantly reduce transmission. In the case that pre-symptomatic cases are less infectious than symptomatic cases, the overall proportion of infected individuals in the population decreases, and the effectiveness of different interventions converges. CONCLUSIONS Digital symptom-based screening tools can substantially impact the transmission of SARS-CoV-2 and might be a viable element in strategies to control COVID-19 through NPIs.