A Modified Epidemiological Model to Understand the Uneven Impact of COVID-19 on Vulnerable Individuals and the Approaches Required to Help them Emerge from Lockdown

Abstract: COVID-19 has shown a relatively low mortality rate in young healthy individuals, with the majority of this group being asymptomatic or having mild symptoms, while the severity of the disease among individuals with underlying health conditions has caused signiffcant mortality rates worldwide. Understanding these differences in mortality amongst different sectors of society and modelling this will enable the different levels of risk and vulnerabilities to be determined to enable strategies exit the lockdown. However, epidemiological models do not account for the variability encountered in the severity of the SARS-CoV-2 disease across different population groups. To overcome this limitation, it is proposed that a modiffed SEIR model, namely SEIR-v, through which the population is separated into two groups regarding their vulnerability to SARS-CoV-2 is applied. This enables the analysis of the spread of the epidemic when different contention measures are applied to different groups in society regarding their vulnerability to the disease. A Monte Carlo simulation indicates a large number of deaths could be avoided by slightly decreasing the exposure of vulnerable groups to the disease. From this modelling a number of mechanisms can be proposed to limit the exposure of vulnerable individuals to the disease in order to reduce the mortality rate among this group. One option could be the provision of a wristband to vulnerable people and those without a contact-tracing app. By combining very dense contact tracing data from smartphone apps and wristband signals with information about infection status and symptoms, vulnerable people can be protected and kept safer. Widespread utilisation would extend the protection further beyond these high risk groups.