Health-seeking behavior and transmission dynamics in the control of influenza infection among different age groups
Received 11 October 2017
Accepted for publication 23 January 2018
Published 6 March 2018 Volume 2018:11 Pages 331—343
Checked for plagiarism Yes
Review by Single-blind
Peer reviewers approved by Dr Amy Norman
Peer reviewer comments 2
Editor who approved publication: Dr Sahil Khanna
Shu-Han You,1 Szu-Chieh Chen,2,3 Chung-Min Liao4
1Institute of Food Safety and Risk Management, National Taiwan Ocean University, Taiwan, Republic of China; 2Department of Public Health, Chung Shan Medical University, Taichung, Taiwan, Republic of China; 3Department of Family and Community Medicine, Chung Shan Medical University Hospital, Taichung, Taiwan, Republic of China; 4Department of Bioenvironmental Systems Engineering, National Taiwan University, Taipei, Taiwan, Republic of China
Background: It has been found that health-seeking behavior has a certain impact on influenza infection. However, behaviors with/without risk perception on the control of influenza transmission among age groups have not been well quantified.
Objectives: The purpose of this study was to assess to what extent, under scenarios of with/without control and preventive/protective behaviors, the age-specific network-driven risk perception influences influenza infection.
Materials and methods: A behavior-influenza model was used to estimate the spread rate of age-specific risk perception in response to an influenza outbreak. A network-based information model was used to assess the effect of network-driven risk perception information transmission on influenza infection. A probabilistic risk model was used to assess the infection risk effect of risk perception with a health behavior change.
Results: The age-specific overlapping percentage was estimated to be 40%–43%, 55%–60%, and 19%–35% for child, teenage and adult, and elderly age groups, respectively. Individuals perceive the preventive behavior to improve risk perception information transmission among teenage and adult and elderly age groups, but not in the child age group. The population with perceived health behaviors could not effectively decrease the percentage of infection risk in the child age group, whereas for the elderly age group, the percentage of decrease in infection risk was more significant, with a 97.5th percentile estimate of 97%.
Conclusion: The present integrated behavior-infection model can help health authorities in communicating health messages for an intertwined belief network in which health-seeking behavior plays a key role in controlling influenza infection.
Keywords: health-seeking behavior, influenza, infection, network-based information model, probabilistic risk model
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