Simulating influenza pandemic dynamics with public risk communication and individual responsive behavior

Abstract

Individual responsive behavior to an influenza pandemic has significant impacts on the spread dynamics of this epidemic. Current influenza modeling efforts considering responsive behavior either oversimplify the process and may underestimate pandemic impacts, or make other problematic assumptions and are therefore constrained in utility. This study develops an agent-based model for pandemic simulation, and incorporates individual responsive behavior in the model based on public risk communication literature. The resultant model captures the stochastic nature of epidemic spread process, and constructs a realistic picture of individual reaction process and responsive behavior to pandemic situations. The model is then applied to simulate the spread dynamics of 2009 H1N1 influenza in a medium-size community in Arizona. Simulation results illustrate and compare the spread timeline and scale of this pandemic influenza, without and with the presence of pubic risk communication and individual responsive behavior. Sensitivity analysis sheds some lights on the influence of different communication strategies on pandemic impacts. Those findings contribute to effective pandemic planning and containment, particularly at the beginning of an outbreak.

Knowledge and Practice of Health Protective Measures of Early Childhood Learners in Benin City, Nigeria

“…In this way, they are preparing the learners to manage future occurrence of any pandemic. This is because when protective behaviours are learned in school and become part of life it can slow down the spread of disease and reduce morbidity (Tooher et al, 2009;Zhong et al, 2017).…”

“…COVID-19 is transmitted from person to person mainly through close contact and larger respiratory droplets. Strong evidence supported the fact that individuals' behaviour is the key to slowing down the disease spread and reducing morbidity (Tooher et al, 2009;Zhong et al, 2017).…”

Reflecting on the safety zoo: Developing an integrated pandemics barrier model using early lessons from the Covid-19 pandemic

“…At first statistical data about the different health stages which persons with a diagnosed pathogen infection go through (Zhong, 2017) are highly uncertain, most so immediately after the onset. As pandemic spread grows, such data can provide useful records.…”

How reported outbreak data can shape individual behavior in a social world

“…Public-facing health media outlets should tailor communicated information for risk reporting [ 6 ], as risk assessment is influenced by individual perception [ 7 ] and different forms of information can vary in evoking perceived risk [ 6 , 8 ]. The importance of the information (and misinformation) available to people regarding their own personal risk of infection has been demonstrated to have the potential, at the very least, of influencing epidemic outcomes [ 3 , 4 , 9 ]. For reporting agencies, priority should be given to the data most likely to promote responsible and appropriate concern as well as the subsequent adoption of protective behaviors, rather than either incite panic or inadvertently encourage complacency [ 3 , 4 , 10 ].…”