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Towards Near Real Time Public Health Surveillance (A Decision Support System for Public Health Surveillance)

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International Journal of Computer Applications
© 2013 by IJCA Journal
Volume 61 - Number 21
Year of Publication: 2013
Authors:
Muhammad Asif
Nitin K. Tripathi
Shahbaz Ahmed
10.5120/10216-5083

Muhammad Asif, Nitin K Tripathi and Shahbaz Ahmed. Article: Towards Near Real Time Public Health Surveillance (A Decision Support System for Public Health Surveillance). International Journal of Computer Applications 61(21):45-50, January 2013. Full text available. BibTeX

@article{key:article,
	author = {Muhammad Asif and Nitin K. Tripathi and Shahbaz Ahmed},
	title = {Article: Towards Near Real Time Public Health Surveillance (A Decision Support System for Public Health Surveillance)},
	journal = {International Journal of Computer Applications},
	year = {2013},
	volume = {61},
	number = {21},
	pages = {45-50},
	month = {January},
	note = {Full text available}
}

Abstract

In recent years with increasing population and changing climatic conditions over the globe gave room to outbreak of different diseases, proper and timely handling of disease cases can result in saving many important human lives. Public health surveillance is the ongoing, systematic collection, analysis, interpretation and dissemination of data regarding a health-related event for use in public health action to reduce morbidity and mortality and to improve public health. Data disseminated by a PHS system can be used for immediate public health action, program planning and evaluation, and formulating research hypotheses. Timely access to disease related data and geographical location is very necessary for public health officials and decision makers in order to avoid mortality and morbidity rate in a particular area of interest (AOI). In this paper we propose and developed a web-GIS based system for public health surveillance about data collection and dissemination through internet. A database of disease cases has been created with six years of historical data from Chiang Mai province Thailand. This system efficiently provides the maps and charts in real time through internet-GIS concept for decision makers and public health officials for analysis and taking preventive actions.

References

  • Asif, M., & Tripathi, N. (2012). Evaluation of OpenID-Based Double-Factor Authentication for Preventing Session Hijacking in Web Applications. Journal of Computers, 7(11), 2623-2628.
  • Chaikaew, N., Tripathi, N. K., and Souris, M. (2009). Exploring spatial patterns and hotspots of diarrhea in Chiang Mai, Thailand. International Journal of Health Geographic 8(36).
  • Chretien, J.-P., and Lewis, S. H. (2008). Electronic public health surveillance in developing settings. BMC Proceedings Retrieved from http://www.biomedcentral.com/1753-6561/2/S3/S1.
  • Djibuti, M., Rukhadze, N., and Hotchkiss, D. (2007). Health system barriers to effective use of infectious disease surveillance data in the context of decentralization in Georgia: a qualitative study. Health Policy, 83, 323-331.
  • Epidemiology, B. o. (2001-2006). Situation of diarrheal diseases. Bangkok. Bangkok: Department of Disease Control, Ministry of Public Health.
  • Kho, A., Johnston, K., Wilson, J., and Wilson, S. J. (2006). Implementing an animated geographic information system to investigate factors associated with nosocomial infections: a novel approach. AmJ Infect Control, 34, 578-582.
  • M.Wagner, M., Moore, A. W., and Aryel, R. M. (2006). Handbook of Biosurveillance: Elsevier.
  • Nigel, C., and Son, D. (2012). GENI-DB: a database of global events for epidemic intelligence. Bioinformatics, 28(8), 1186-1188. Retrieved from http://bioinformatics.oxfordjournals.org/content/early/2012/03/01/bioinformatics.bts099.full.pdf+html doi:10.1093/bioinformatics/bts099.
  • Reinhardt, M., Elias, J., Albert, J., Matthias Frosch, Harmsen, D., and Vogel, U. (2008). EpiScanGIS: an online geographic surveillance system for meningococcal disease. International Journal of Health Geographics. Retrieved from http://www.ij-healthgeographics.com/content/7/1/33.
  • Tan, H., Chang, C., and Tseng, H. (2007). Evaluation of the national notifiable disease surveillance system in Taiwan: an example of varicella reporting. Vaccine 25, 2630-2633.
  • Teutsch SM, C. (2006). Principles and Practice of Public Health Surveillance. New York: Oxford University Press.
  • Thaewnongiew, K., Promthet, S., Nilvarangkul, K., Rangsin, Phitak, R. P., and Sarakarn, P. (2009). The surveillance system in health centers in northeastern Thailand. Japanese Journal of Infectious Disease 62(6), 444-449.
  • Wagner, M. M., Tsui, F. C., Espino, J. U., Dato, V. M., Sittig, D. F., Caruana, R. A., McGinnis, L. F., Deerfield, D. W., Druzdzel, M. J., and Fridsma, D. B. (2001). The emerging science of very early detection of disease outbreaks. [Research Support, U.S. Gov't, P.H.S.]. J Public Health Manag Pract, 7(6), 51-59.
  • WHO. (2010). Disease outbreaks Retrieved January 13, 2010, from http://www.who.int/topics/disease_outbreaks/en/
  • Wikipedia. (2012). 2011 dengue outbreak in Pakistan Retrieved April 15, 2012, from http://en.wikipedia.org/wiki/2011_dengue_outbreak_in_Pakistan
  • Wuthikun, W. (2001). Management Information Quality of Public Health Centers in Chian Mai Province. (Graduate School), Mahidol University, Thailand.
  • Zenilman, J. M., Ellish, N., Fresia, A., and Glass, G. (1999). The geography of sexual partnerships in Baltimore: applications of core theory dynamics using a geographic information system. Sexually Transmitted disease, 26, 75-81.