Understanding the Role of Environmental Transmission on COVID-19 Herd Immunity and Invasion Potential

Authors
Masud, M. A.Islam, Md HamidulKim, Byul Nim
Issue Date
2022-09
Publisher
Academic Press
Citation
Bulletin of Mathematical Biology, v.84, no.10
Abstract
COVID-19 is caused by the SARS-CoV-2 virus, which is mainly transmitted directly between humans. However, it is observed that this disease can also be transmitted through an indirect route via environmental fomites. The development of appropriate and effective vaccines has allowed us to target and anticipate herd immunity. Understanding of the transmission dynamics and the persistence of the virus on environmental fomites and their resistive role on indirect transmission of the virus is an important scientific and public health challenge because it is essential to consider all possible transmission routes and route specific transmission strength to accurately quantify the herd immunity threshold. In this paper, we present a mathematical model that considers both direct and indirect transmission modes. Our analysis focuses on establishing the disease invasion threshold, investigating its sensitivity to both transmission routes and isolate route-specific transmission rate. Using the tau-leap algorithm, we perform a stochastic model simulation to address the invasion potential of both transmission routes. Our analysis shows that direct transmission has a higher invasion potential than that of the indirect transmission. As a proof of this concept, we fitted our model with early epidemic data from several countries to uniquely estimate the reproduction numbers associated with direct and indirect transmission upon confirming the identifiability of the parameters. As the indirect transmission possess lower invasion potential than direct transmission, proper estimation and necessary steps toward mitigating it would help reduce vaccination requirement.
Keywords
REPRODUCTION NUMBERS; MODELS; INFECTIONS; VIRUSES; SARS; COVID-19; Vaccination; Indirect transmission; Mathematical modeling; Identifiability
ISSN
0092-8240
URI
https://pubs.kist.re.kr/handle/201004/114587
DOI
10.1007/s11538-022-01070-y
Appears in Collections:
KIST Article > 2022
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