Chasing up and locking down the virus: Optimal pandemic interventions within a network

Abstract

During the COVID-19 pandemic countries invested significant amounts of resources into its containment. In early stages of the pandemic most of the (nonpharmaceutical) interventions can be classified into two groups: (i) testing and identification of infected individuals, (ii) social distancing measures to reduce the transmission probabilities. Furthermore, both groups of measures may, in principle, be targeted at certain subgroups of a networked population. To study such a problem, we propose an extension of the SIR model with additional compartments for quarantine and different courses of the disease across several network nodes. We develop the structure of the optimal allocation and study a numerical example of three symmetric regions that are subject to an asymmetric progression of the disease (starting from an initial hotspot). Key findings include that (i) for our calibrations policies are chosen in a "flattening-the-curve," avoiding hospital congestion; (ii) policies shift from containing spillovers from the hotspot initially to establishing a symmetric pattern of the disease; and (iii) testing that can be effectively targeted allows to reduce substantially the duration of the disease, hospital congestion and the total cost, both in terms of lives lost and economic costs.

Should the COVID-19 lockdown be relaxed or intensified in case a vaccine becomes available?

“…important. The government has the responsibility for the epidemic situation when elections take place (see e.g., [12,14], or [30]).…”

“…And indeed, the adaptation could straightforwardly be done by adding additional compartments (for identified people) and a parameter or a control variable (for testing efforts). This route has been followed in [30] again without vaccination. The analysis shows that testing has a strong effect on the pandemic if tracing is efficient.…”

Introduction to the special issue on new insights into economic epidemiology: Theory and policy

“…This section brings two additional original contributions in this respect. The first one (Freiberger et al, 2022) is a network-based epi-econ model. Network modeling in mathematical and applied epidemiology is not new (see a recent contribution due to Karaivanov, 2020), and typically captures the fact that infections are first of all spreading in individuals' social networks.…”

“…The second paper by Hritonenko et al (2021) introduces transmission delays into a SIR epi-econ model and derives theoretical and policy implications. Freiberger et al (2022) start from the premise that, for the COVID-19 pandemic, the two groups of interventions (testing/identification of infected individuals and social-distancing measures to reduce contagion) could be targeted at certain subgroups of a networked population (e.g., groups in different geographical regions). To study such a problem, they propose an extension of the SIR model with additional compartments for quarantine and different courses of the disease across several network nodes.…”

Path integral control of a stochastic multi-risk SIR pandemic model

“…In addition, targeted policies such as changing in norms and laws segregating the young population from the older are imposed, fatalities and economic damages because of COVID-19 can be substantially low (Acemoglu et al 2020). At the stages of the pandemic, most of the (non-pharmaceutical) interventions are classified into two groups such as testing and identification of infected individuals, and social distancing measures to reduce the transmission probabilities (Freiberger et al 2022). Moreover, these groups of measures target certain subgroups of a networked population.…”