Effective epidemic model for COVID-19 using accumulated deaths

TL;DR

This paper introduces a simple, robust model based on accumulated deaths to estimate key COVID-19 epidemiological parameters, including mortality rate and reproduction number, aiding assessment of intervention effectiveness.

Contribution

It presents a novel approach linking a simple death-based model to the SIR model for better parameter estimation and intervention analysis.

Findings

Crude mortality rate estimated between 10^-4 and 10^-3.

Model provides estimates of basic reproduction number.

Assesses impact of social distancing and lockdowns.

Abstract

The severe acute respiratory syndrome COVID-19 has been in the center of the ongoing global health crisis in 2020. The high prevalence of mild cases facilitates sub-notification outside hospital environments and the number of those who are or have been infected remains largely unknown, leading to poor estimates of the crude mortality rate of the disease. Here we use a simple model to describe the number of accumulated deaths caused by COVID-19. The close connection between the proposed model and an approximate solution of the SIR model provides a system of equations whose solutions are robust estimates of epidemiological parameters. We find that the crude mortality varies between $10^{-4}$ and $10^{-3}$ depending on the severity of the outbreak which is lower than previous estimates obtained from laboratory confirmed patients. We also estimate quantities of practical interest such as the basic reproduction number and the expected number of deaths in the asymptotic limit with and without social distancing measures and lockdowns, which allow us to measure the efficiency of these interventions.