The Signature Features of COVID‐19 Pandemic in a Hybrid Mathematical Model—Implications for Optimal Work–School Lockdown Policy. Issue 5 (25th March 2021)

• Record Type: Journal Article
• Authors: Lazebnik, Teddy; Bunimovich‐Mendrazitsky, Svetlana
• Is Part Of: Advanced theory and simulations. Volume 4:Issue 5(2021)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2021-03-25
• Subjects: COVID‐19 spread dynamics -- hybrid models -- spatio‐temporal models -- two‐age group SIR; Science -- Simulation methods -- Periodicals; Science -- Methodology -- Periodicals; Engineering -- Simulation methods -- Periodicals; Engineering -- Methodology -- Periodicals; 507.21
• DOI: 10.1002/adts.202000298
• Languages: English
• ISSNs: 2513-0390

Abstract

Abstract: The new COVID‐19 pandemic has challenged policymakers on key issues. Most countries have adopted "lockdown" policies to reduce the spatial spread of COVID‐19, but they have damaged the economic and moral fabric of society. Mathematical modeling in non‐pharmaceutical intervention policy management has proven to be a major weapon in this fight due to the lack of an effective COVID‐19 vaccine. A new hybrid model for COVID‐19 dynamics using both an age‐structured mathematical model based on the SIRD model and spatio‐temporal model in silico is presented, analyzing the data of COVID‐19 in Israel. Using the hybrid model, a method for estimating the reproduction number of an epidemic in real‐time from the data of daily notification of cases is introduced. The results of the proposed model are confirmed by the Israeli Lockdown experience with a mean square error of 0.205 over 2 weeks. The use of mathematical models promises to reduce the uncertainty in the choice of "Lockdown" policies. The unique use of contact details from 2 classes (children and adults), the interaction of populations depending on the time of day, and several physical locations, allow a new look at the differential dynamics of the spread and control of infection. Abstract : This paper presents a new spatio‐temporal model for COVID‐19 spread that divides the population into two age groups (children and adults). In silico simulation allowing to predict the influence of non‐pharmaceutical intervention lockdown and time both schooling and working hours is shown.