Modeling and Analysis of an SIRS Epidemic Model with Effect of Awareness Programs by Media
This paper proposes and analyzes an SIRS epidemic model incorporating the effects of the awareness programs driven by the media. Media and media driven awareness programs play a promising role in disseminating the information about outbreak of any disease across the globe. This motivates people to take precautionary measures and guides the infected individuals to get hospitalized. Timely hospitalization helps to reduce diagnostic delays and hence results in fast recovery of infected individuals. The aim of this study is to investigate the impact of the media on the spread and control of infectious diseases. This model is analyzed using stability theory of differential equations. The sensitivity of parameters has been discussed and it has been found that the awareness programs driven by the media have positive impact in reducing the infection prevalence of the infective population in the region under consideration.
[1] World Health Organization, Philadelphia: World Health Organization;
2005. WHO checklist for influenza pandemic preparedness planning.
Available from: http://www.who.int/csr/resources/publications/influenza/
WHO CDS CSR GIP 2005 4/en/.
[2] World Health Organization, Global Burden of
disease: 2004 update, 2008. Available from:
http://www.who.int/healthinfo/global burden disease/2004
report update/en/index.html.
[3] World Health Organization, Global Influenza Program.
Philadelphia: World Health Organization; 2009. Pandemic
Influenza Preparedness and Response. Available from:
http://www.who.int/influenza/resources/documents/pandemic
guidance 04 2009/en/index.html.
[4] C.R. Simpson, Nature as News: Science Reporting in The New York
Times 1898 to 1983, The Int. J. Polit., Cult. Soc., 1 218-241, 1987.
[5] M.D. Slater, K.A. Rasinski, Media Exposure and Attention as Mediating
Variables Influencing Social Risk Judgments, J. Commun. 55 810-827,
2005.
[6] R. Liu, J. Wu, H. Zhu, Media/psychological impact on multiple outbreaks
of emerging infectious diseases, Comput. Math. Methods Med., 8
153-164, 2007.
[7] J. Gholami, S.H. Hosseini, M. Ashoorkhani, R. Majdzadeh, Lessons
Learned from H1N1 Epidemic: The Role of Mass Media in Informing
Physicians, Int. J. Prev. Med., 2 32-37, 2011.
[8] R.J. Blendon, J.M. Benson, C.M. DesRoches, E. Raleigh, K. Taylor-Clark,
The public’s response to severe acute respiratory syndrome in Toronto and
the United States, Clin. Infect. Dis., 38 925, 2004.
[9] A. Coulter, J. Ellins, Patient-focused interventions: a review of the
evidence, The Health Foundation, London, 2006.
[10] J. T. Shattuck, Lecture medicine and the media, N Engl J Med., 339
87-92, 1998.
[11] A. Mensua, S. Mounier-Jack, R. Coker, Pandemic influenza
preparedness in Latin America: analysis of national strategic plans,
Health Policy Plan., 24 253-60, 2009.
[12] J. Cui, Y. Sun, H. Zhu, The Impact of Media on the Control of Infectious
Diseases, J. Dyn. Differ. Eqn., 20 31-53, 2007.
[13] Y. Liu, J. Cui, The Impact of Media Coverage on the Dynamics of
Infectious disease, Int. J. Biomath., 1 65-74, 2008.
[14] Y. Li, J. Cui, The effect of constant and pulse vaccination on SIS
epidemic models incorporating media coverage, Commun. Nonlinear Sci.
Numer. Simul., 14 2353-2365, 2009.
[15] Z. Mukandavire, W. Garira and J.M. Tchuenche, Modelling effects
of public health educational campaigns on HIV/AIDS transmission
dynamics, Appl. Math. Model., 33 2084-2095, 2009.
[16] C. Sun, W. Yang, J. Arino, K. Khan, Effect of meida-induced social
distancing on disease transmission in a two patch setting, Math. Biosci.,
Article in press, 2011.
[17] J. M. Tchuenche, N Dube, C P Bhunu, R. J. Smith, C. T. Bauch,
The impact of media coverage on the transmission dynamics of human
influenza, BMC Public Health, 11(Suppl. 1)S5, 2011.
[18] A. K. Misra, A. Sharma, J. B. Shukla, Modeling and Analysis of effects
of awareness programs by media on the spread of diseases, Math. Comp.
Model., 53 1221-1228, 2011.
[19] P. Driessche, W. James, Reproduction numbers and sub-threshold
endemic equilibria for compartmental models of disease transmission,
Math. Biosci., 180 29–48, 2002.
[20] V. Lakshmikantham, S. Leela, A.A. Martynyuk, Stability Analysis of
Nonlinear Systems, Marcel Dekker Inc., New York, 1989.
[21] B. Ermentrout, Simulating, Analyzing, and Animating Dynamical
Systems: A Guide to XPPAUT for Researchers and Students (Sofeare,
Environments, Tools), 1st edition. SIAM, Philadelphia, PA, 2002.
[1] World Health Organization, Philadelphia: World Health Organization;
2005. WHO checklist for influenza pandemic preparedness planning.
Available from: http://www.who.int/csr/resources/publications/influenza/
WHO CDS CSR GIP 2005 4/en/.
[2] World Health Organization, Global Burden of
disease: 2004 update, 2008. Available from:
http://www.who.int/healthinfo/global burden disease/2004
report update/en/index.html.
[3] World Health Organization, Global Influenza Program.
Philadelphia: World Health Organization; 2009. Pandemic
Influenza Preparedness and Response. Available from:
http://www.who.int/influenza/resources/documents/pandemic
guidance 04 2009/en/index.html.
[4] C.R. Simpson, Nature as News: Science Reporting in The New York
Times 1898 to 1983, The Int. J. Polit., Cult. Soc., 1 218-241, 1987.
[5] M.D. Slater, K.A. Rasinski, Media Exposure and Attention as Mediating
Variables Influencing Social Risk Judgments, J. Commun. 55 810-827,
2005.
[6] R. Liu, J. Wu, H. Zhu, Media/psychological impact on multiple outbreaks
of emerging infectious diseases, Comput. Math. Methods Med., 8
153-164, 2007.
[7] J. Gholami, S.H. Hosseini, M. Ashoorkhani, R. Majdzadeh, Lessons
Learned from H1N1 Epidemic: The Role of Mass Media in Informing
Physicians, Int. J. Prev. Med., 2 32-37, 2011.
[8] R.J. Blendon, J.M. Benson, C.M. DesRoches, E. Raleigh, K. Taylor-Clark,
The public’s response to severe acute respiratory syndrome in Toronto and
the United States, Clin. Infect. Dis., 38 925, 2004.
[9] A. Coulter, J. Ellins, Patient-focused interventions: a review of the
evidence, The Health Foundation, London, 2006.
[10] J. T. Shattuck, Lecture medicine and the media, N Engl J Med., 339
87-92, 1998.
[11] A. Mensua, S. Mounier-Jack, R. Coker, Pandemic influenza
preparedness in Latin America: analysis of national strategic plans,
Health Policy Plan., 24 253-60, 2009.
[12] J. Cui, Y. Sun, H. Zhu, The Impact of Media on the Control of Infectious
Diseases, J. Dyn. Differ. Eqn., 20 31-53, 2007.
[13] Y. Liu, J. Cui, The Impact of Media Coverage on the Dynamics of
Infectious disease, Int. J. Biomath., 1 65-74, 2008.
[14] Y. Li, J. Cui, The effect of constant and pulse vaccination on SIS
epidemic models incorporating media coverage, Commun. Nonlinear Sci.
Numer. Simul., 14 2353-2365, 2009.
[15] Z. Mukandavire, W. Garira and J.M. Tchuenche, Modelling effects
of public health educational campaigns on HIV/AIDS transmission
dynamics, Appl. Math. Model., 33 2084-2095, 2009.
[16] C. Sun, W. Yang, J. Arino, K. Khan, Effect of meida-induced social
distancing on disease transmission in a two patch setting, Math. Biosci.,
Article in press, 2011.
[17] J. M. Tchuenche, N Dube, C P Bhunu, R. J. Smith, C. T. Bauch,
The impact of media coverage on the transmission dynamics of human
influenza, BMC Public Health, 11(Suppl. 1)S5, 2011.
[18] A. K. Misra, A. Sharma, J. B. Shukla, Modeling and Analysis of effects
of awareness programs by media on the spread of diseases, Math. Comp.
Model., 53 1221-1228, 2011.
[19] P. Driessche, W. James, Reproduction numbers and sub-threshold
endemic equilibria for compartmental models of disease transmission,
Math. Biosci., 180 29–48, 2002.
[20] V. Lakshmikantham, S. Leela, A.A. Martynyuk, Stability Analysis of
Nonlinear Systems, Marcel Dekker Inc., New York, 1989.
[21] B. Ermentrout, Simulating, Analyzing, and Animating Dynamical
Systems: A Guide to XPPAUT for Researchers and Students (Sofeare,
Environments, Tools), 1st edition. SIAM, Philadelphia, PA, 2002.
@article{"International Journal of Engineering, Mathematical and Physical Sciences:66852", author = "Navjot Kaur and Mini Ghosh and S.S. Bhatia", title = "Modeling and Analysis of an SIRS Epidemic Model with Effect of Awareness Programs by Media", abstract = "This paper proposes and analyzes an SIRS epidemic model incorporating the effects of the awareness programs driven by the media. Media and media driven awareness programs play a promising role in disseminating the information about outbreak of any disease across the globe. This motivates people to take precautionary measures and guides the infected individuals to get hospitalized. Timely hospitalization helps to reduce diagnostic delays and hence results in fast recovery of infected individuals. The aim of this study is to investigate the impact of the media on the spread and control of infectious diseases. This model is analyzed using stability theory of differential equations. The sensitivity of parameters has been discussed and it has been found that the awareness programs driven by the media have positive impact in reducing the infection prevalence of the infective population in the region under consideration.
", keywords = "Infectious diseases, SIRS model, Media, Stability
theory, Simulation.", volume = "8", number = "1", pages = "240-7", }
