Smart testing and selective quarantine for the control of epidemics

Abstract

This paper is based on the observation that, during Covid-19 epidemic, the choice of which individuals should be tested has an important impact on the effectiveness of selective confinement measures. This decision problem is closely related to the problem of optimal sensor selection, which is a very active research subject in control engineering. The goal of this paper is to propose a policy to smartly select the individuals to be tested. The main idea is to model the epidemics as a stochastic dynamic system and to select the individual to be tested accordingly to some optimality criteria, e.g. to minimize the probability of undetected asymptomatic cases. Every day, the probability of infection of the different individuals is updated making use of the stochastic model of the phenomenon and of the information collected in the previous days. Simulations for a closed community of 10’000 individuals show that the proposed technique, coupled with a selective confinement policy, can reduce the spread of the disease while limiting the number of individuals confined if compared to the simple contact tracing of positive and to an off-line test selection strategy based on the number of contacts.

Effects of environmental parameters and their interactions on the spreading of SARS-CoV-2 in North Italy under different social restrictions. A new approach based on multivariate analysis

“…In Italy, epidemiological data are available on daily basis since the 24th February 2020, from national authorities ( https://github.com/pcm-dpc/COVID-19 ), in particular, the daily number of new cases should represent a possible measure of the pandemic spread, but unfortunately, it is not completely reliable ( Sartor et al, 2020 ), as the number of daily tests changes strongly according to the administrative territory, day of the week (lower number of tests on Saturday and Sunday) and time since the beginning of the pandemic. So, the interpretation of the results available presents some problems and data are not comparable considering different administrative areas; moreover, it strongly depends on the efficacy of the contact-tracing survey, that during the strongest pandemic rate was not sufficient in identifying all the contagious persons ( Pezzutto et al, 2021 ). It must also be considered that the contact-tracing cannot be done for asymptomatic individuals, who are not intercepted by screening tests.…”

Game-Theoretic Frameworks for Epidemic Spreading and Human Decision-Making: A Review

“…Decision making consists of the choices of individuals and the strategies of stakeholders at different hierarchical levels. Decision models considered in the existing literature mainly consider two types of decision-makers: a central planner [12,13,25,27,28,54,57,66,73,75,81,82,87,97,98,103,107,108,112,122,136,[139][140][141][142]144,146,148], which works for social benefits by conducting mechanism design and/or applying enforceable measures directly to the general public, and a collection of individuals with various types Fig. 1 Schematic illustration of the human-in-the-loop epidemic framework consisting of epidemic processes and decision models Fig.…”

“…For example, if individual i is quarantined, then a i j = 0 for all j ∈ N . To capture the effect of measures do not require complete isolation such as social distancing, several papers have considered weighted networks to describe the intensity of interactions [66,108]. For example, [66] uses a weight coefficient w i j ∈ [0, 1] to describe the intensity of the interaction between individual i and j.…”

Empirical evidence on the efficiency of bidirectional contact tracing in COVID-19

“…Therefore, whilst there is evidence from modelling studies pointing at the bene ts of backward contact tracing, no study has evaluated the e ciency in practice. The positivity rate of screened contacts has been proposed as an indicator for e cient allocation of testing and quarantine 29,30 .…”