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1. On the Role of Asymptomatic Carriers in Epidemic Spread Processes

   https://doi.org/10.23919/ACC50511.2021.9483337  

   Bi, Xiaoqi; Beck, Carolyn L. (May 2021, American Control Conference)

   We present an epidemiological compartment model, SAIR(S), that explicitly captures the dynamics of asymptomatic infected individuals in an epidemic spread process. We first present a group model and then discuss networked versions. We provide an investigation of equilibria and stability properties for these models, and present simulation results illustrating the effects of asymptomatic-infected individuals on the spread of the disease. We also discuss local isolation effects on the epidemic dynamics in terms of the networked models. Finally, we provide initial parameter estimation results based on simple least-squares approaches and local test-site data 

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2. Computational Modeling Framework for the Study of Infectious Disease Spread through Commercial Air-Travel

   https://doi.org/10.1109/AERO47225.2020.9172285  

   P. Derjany, S Namilae (April 2020, IEEE Aerospace conference)

   This paper presents an integrated computational modelling framework combining pedestrian dynamics and infection spread models, to analyse the infectious disease spread during the different stages of air-travel. While, commercial air travel is central to the global mobility of goods and people, it has also been identified as a leading factor in the spread of several epidemic diseases including influenza, SARS and Ebola. The mixing of susceptible and infectious individuals in these high people density locations like airports involves pedestrian movement which needs to be taken into account in the modeling studies of disease dynamics. We develop a Molecular Dynamics based social force modeling approach for pedestrian dynamics and combine it with a stochastic infection dynamics model to evaluate the spread of viral infectious diseases in airplanes and airports. We apply the multiscale model for various key components of air travel and suggest strategies to reduce the number of contacts and the spread of infectious diseases. We simulate pedestrian movement during boarding and deplaning of some typical commercial airplane models and movement of people through security check areas. We found specific boarding strategies that reduce the number of contacts. Further, we find that smaller airplanes are more effective in reducing the number of contacts compared to larger airplanes. We propose certain queue configuration that reduces contacts between people and mitigate disease spread. 

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3. Control strategies for COVID-19 epidemic with vaccination, shield immunity and quarantine: A metric temporal logic approach

   https://doi.org/10.1371/journal.pone.0247660  

   Xu, Zhe; Wu, Bo; Topcu, Ufuk (March 2021, PLOS ONE)

   Borri, Alessandro (Ed.)

   Ever since the outbreak of the COVID-19 epidemic, various public health control strategies have been proposed and tested against the coronavirus SARS-CoV-2. We study three specific COVID-19 epidemic control models: the susceptible, exposed, infectious, recovered (SEIR) model with vaccination control; the SEIR model with shield immunity control; and the susceptible, un-quarantined infected, quarantined infected, confirmed infected (SUQC) model with quarantine control. We express the control requirement in metric temporal logic (MTL) formulas (a type of formal specification languages) which can specify the expected control outcomes such as “ the deaths from the infection should never exceed one thousand per day within the next three months ” or “ the population immune from the disease should eventually exceed 200 thousand within the next 100 to 120 days ”. We then develop methods for synthesizing control strategies with MTL specifications. To the best of our knowledge, this is the first paper to systematically synthesize control strategies based on the COVID-19 epidemic models with formal specifications. We provide simulation results in three different case studies: vaccination control for the COVID-19 epidemic with model parameters estimated from data in Lombardy, Italy; shield immunity control for the COVID-19 epidemic with model parameters estimated from data in Lombardy, Italy; and quarantine control for the COVID-19 epidemic with model parameters estimated from data in Wuhan, China. The results show that the proposed synthesis approach can generate control inputs such that the time-varying numbers of individuals in each category (e.g., infectious, immune) satisfy the MTL specifications. The results also show that early intervention is essential in mitigating the spread of COVID-19, and more control effort is needed for more stringent MTL specifications. For example, based on the model in Lombardy, Italy, achieving less than 100 deaths per day and 10000 total deaths within 100 days requires 441.7% more vaccination control effort than achieving less than 1000 deaths per day and 50000 total deaths within 100 days. 

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4. Importance of social inequalities to contact patterns, vaccine uptake, and epidemic dynamics

   https://doi.org/10.1038/s41467-024-48332-y  

   Manna, Adriana; Koltai, Júlia; Karsai, Márton (December 2024, Nature Communications)

   Abstract Individuals’ socio-demographic and economic characteristics crucially shape the spread of an epidemic by largely determining the exposure level to the virus and the severity of the disease for those who got infected. While the complex interplay between individual characteristics and epidemic dynamics is widely recognised, traditional mathematical models often overlook these factors. In this study, we examine two important aspects of human behaviour relevant to epidemics: contact patterns and vaccination uptake. Using data collected during the COVID-19 pandemic in Hungary, we first identify the dimensions along which individuals exhibit the greatest variation in their contact patterns and vaccination uptake. We find that generally higher socio-economic groups of the population have a higher number of contacts and a higher vaccination uptake with respect to disadvantaged groups. Subsequently, we propose a data-driven epidemiological model that incorporates these behavioural differences. Finally, we apply our model to analyse the fourth wave of COVID-19 in Hungary, providing valuable insights into real-world scenarios. By bridging the gap between individual characteristics and epidemic spread, our research contributes to a more comprehensive understanding of disease dynamics and informs effective public health strategies. 

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5. Epidemic Conditions with Temporary Link Deactivation on a Network SIR Disease Model

   https://doi.org/10.30707/SPORA7.1.1647885542.976088  

   Hannah Scanlon, Wake Forest (January 2021, SPORA: A Journal of Biomathematics)

   The spread of an infectious disease depends on intrinsic properties of the disease as well as the connectivity and actions of the population. This study investigates the dynamics of an SIR type model which accounts for human tendency to avoid infection while also maintaining preexisting, interpersonal relationships. Specifically, we use a network model in which individuals probabilistically deactivate connections to infected individuals and later reconnect to the same individuals upon recovery. To analyze this network model, a mean field approximation consisting of a system of fourteen ordinary differential equations for the number of nodes and edges is developed. This system of equations is closed using a moment closure approximation for the number of triple links. By analyzing the differential equations, it is shown that, in addition to force of infection and recovery rate, the probability of deactivating edges and the average node degree of the underlying network determine if an epidemic occurs. 

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