Impacts of social distancing on the spread of infectious diseases with asymptomatic infection: A mathematical model

Huang, He; Chen, Yahong; Yan, Zhijun

doi:10.1016/j.amc.2021.125983

Cited by 20 publications

(13 citation statements)

References 56 publications

(62 reference statements)

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“…The diffusion impact on the disease spread was investigated for different initial population distributions and interventions effect was analyzed. Authors in 27 modeled the interaction between the epidemic spreading and information diffusion by developing a two-layer network. The study showed that the knowledge diffusion has a significant impact on controlling not only rumor but also epidemic.…”

Section: Literature Reviewmentioning

confidence: 99%

A particle swarm optimization approach for predicting the number of COVID-19 deaths

Haouari

Mhiri

2021

Sci Rep

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The rapid spread of the COVID-19 pandemic has raised huge concerns about the prospect of a major health disaster that would result in a huge number of deaths. This anxiety was largely fueled by the fact that the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), responsible for the disease, was so far unknown, and therefore an accurate prediction of the number of deaths was particularly difficult. However, this prediction is of the utmost importance for public health authorities to make the most reliable decisions and establish the necessary precautions to protect people’s lives. In this paper, we present an approach for predicting the number of deaths from COVID-19. This approach requires modeling the number of infected cases using a generalized logistic function and using this function for inferring the number of deaths. An estimate of the parameters of the proposed model is obtained using a Particle Swarm Optimization algorithm (PSO) that requires iteratively solving a quadratic programming problem. In addition to the total number of deaths and number of infected cases, the model enables the estimation of the infection fatality rate (IFR). Furthermore, using some mild assumptions, we derive estimates of the number of active cases. The proposed approach was empirically assessed on official data provided by the State of Qatar. The results of our computational study show a good accuracy of the predicted number of deaths.

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Section: Literature Reviewmentioning

confidence: 99%

A particle swarm optimization approach for predicting the number of COVID-19 deaths

Haouari

Mhiri

2021

Sci Rep

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“…Throughout history, the outbreak of epidemics has been a major disaster threatening human survival. For example, from 2019 to now, the sudden outbreak of COVID-19 [1][2][3][4] has deeply affected the lifestyle of people all over the world and has an indelible negative impact on the world economy. During the outbreak of COVID-19, epidemiological information is transmitted by word of mouth or social media, etc [5][6][7][8][9].…”

Section: Introductionmentioning

confidence: 99%

The Impact of the Global and Local Awareness Diffusion on Epidemic Transmission Considering the Heterogeneity of Individual Influences

Zhao

Han

2022

Preprint

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In this paper, we propose a coupled awareness - epidemic spreading model considering the heterogeneity of individual influences, which aims to explore the interaction between awareness diffusion and epidemic transmission. The considered heterogeneity of individual influences are threefold: the heterogeneity of individual influences in the information layer, the heterogeneity of individual influences in the epidemic layer and the heterogeneity of individual behavioral responses to epidemics. In addition, the individuals' receptive preference for information and the impacts of individuals' perceived local awareness ratio and individuals' perceived epidemic severity on self-protective behavior are included. The epidemic threshold is theoretically established according to the microscopic Markov chain approach and mean-field approach. Results indicate that the critical local and global awareness ratios have two-stage effects on the epidemic threshold. Besides, either the heterogeneity of individual influences in the information layer or the strength of individuals' responses to epidemics can influence the epidemic threshold with a nonlinear way. However, the heterogeneity of individual influences in the epidemic layer has few effect on the epidemic threshold, but can affects the magnitude of the final infected density.

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“…[41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51] on the effects of mandated social distancing on SARS-CoV-2 spread. In a recent paper [52] the authors considered the combination of both mandated and self-regulated types of social distancing, and studied their effect on the outbreak threshold of an (asymptomatic) infectious disease.…”

Section: Introductionmentioning

confidence: 99%

Effect of human behavior on the evolution of viral strains during an epidemic

Azizi

Komarova

Wodarz

2021

Preprint

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It is well known in the literature that human behavior can change as a reaction to disease observed in others, and that such behavioral changes can be an important factor in the spread of an epidemic. It has been noted that human behavioral traits in disease avoidance are under selection in the presence of infectious diseases. Here we explore a complimentary trend: the pathogen itself might experience a force of selection to become less "visible", or less "symptomatic", in the presence of such human behavioral trends. Using a stochastic SIR agent-based model, we investigated the co-evolution of two viral strains with cross-immunity, where the resident strain is symptomatic while the mutant strain is asymptomatic. We assumed that individuals exercised self-regulated social distancing (SD) behavior if one of their neighbors was infected with a symptomatic strain. We observed that the proportion of asymptomatic carriers increased over time with a stronger effect corresponding to higher levels of self-regulated SD. Adding mandated SD made the effect more significant, while the existence of a time-delay between the onset of infection and the change of behavior reduced the advantage of the asymptomatic strain. These results were consistent under random geometric networks, scale-free networks, and a synthetic network that represented the social behavior of the residents of New Orleans.

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Impacts of social distancing on the spread of infectious diseases with asymptomatic infection: A mathematical model

Cited by 20 publications

References 56 publications

A particle swarm optimization approach for predicting the number of COVID-19 deaths

A particle swarm optimization approach for predicting the number of COVID-19 deaths

The Impact of the Global and Local Awareness Diffusion on Epidemic Transmission Considering the Heterogeneity of Individual Influences

Effect of human behavior on the evolution of viral strains during an epidemic

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