Disease modeling – An alert system for informing environmental risk factor for TB infection

Authors

  • K. Ram Mohan Rao Indian Space Research Organisation
  • Yogesh Kant Scientist
  • Satya Chandra NRSC

DOI:

https://doi.org/10.14738/jbemi.11.81

Keywords:

Mycobacterium tuberculosis, Regression, Vulnerability, GIS,

Abstract

Tuberculosis (TB) is an infectious disease caused by the bacillus Mycobacterium tuberculosis and spreads through air by a person suffering from TB. A risk map is derived based on socio-economic, environmental, health facilities, and Biological characteristics for quantifying the infection risk of the locality. The inter relation between the environmental variables, meteorological parameters, and socio economic variables such as rainfall, temperature, family income and population density with respect to number of past cases have been studied using regression model. Risk is calculated by mean of the probability of occurrence of tuberculosis and vulnerability to the infection. The risk map is computed by using statistical techniques to form spatial maps. An alert system is developed by using GIS from the background of geospatial data and later published to the web using open source internet GIS technologies.

Author Biographies

K. Ram Mohan Rao, Indian Space Research Organisation

NRSC

Yogesh Kant, Scientist

IIRS

References

. Murray CJL, and Lopez AD: The global burden of disease: a comprehensive assessment of mortality and disability from diseases, injuries and risk factors in 1990 and projected to 2020. World Health Organization Document 1996, W 74 96GL-1/1996.

. Narain JP (ed.): Tuberculosis-epidemiology and control. World Health Organization, Regional Office for South East Asia, New Delhi, India 2002, SEA/TB/2002. 248:15-18.

. India 2005. RNTC Status Report. Central TB Division, Directorate General of Health Services, New Delhi. [http://www.tbcindia.org].

. Cauthen GM, Pio A, and ten Dam HG. Annual risk of infection. World Health Organization Document 1988, WHO/TB/88.154: 1-34.

. Dye C, Scheele S, Dolin P, Pathania V and Raviglione MC.1999. Global burden of disease: estimated incidence, prevalence, and mortality by country. J Am Med Assoc 1999, 282: 677-686.

. Mayer JD. 1986.The role of spatial analysis and geographic data in detection of disease casusation.soc sci med.17:1213-1221.doi:10.1016/0277-9563 (83090014-X.

. Hay SI, Randolph SE, and Rogers DJ. 2000. An overview of remote sensing and Geodesy for Epidemiology and Public Health application..oxford: academic press: .pp 1-35

. Telzak EE. 1997.Tuberculosis and Human Immunodeficiency Virus infection. Med Clin North Am, 81: 345-360.

. Gunawardena,D.M.,wickeremasinghe,A.R.;Muthuwatte, L.; Weerasingha,.1998.Malaria risk factors in an academic region of Srilanka, impact and cost implications of risk-factors based interventions. American Journal of Tropical Medicine and Hygiene 58:533-542

. Smith JM, Miron M, Tremblay T, Ellis E.2008 Burden of Latent Tuberculosis Infection Among Federal Inmates 1998 to 2005. 6th Tuberculosis Conference 2008—Tuberculosis: It’s a Small World, Edmonton, Alberta, March, 2008.

. Mandy Tang and Cheong wai Tsoi. 2007. GIS intitiatives in improving the Dengue Vector Control. Eds. Poh. C and Ann S.H. GIS for health and management. Development in the Asia and pacific region. Springer publication.

. Peng ZR, Tsou MH, 2003, Internet GIS: Distributed Geographic Information Services for the internet and wireless networks. ISBN 0-471-35923-8m.

. Mohemmad Zouiten, Mostafa Harti, Chakib Nejjari, 2010. An architecture and an ontology-based context model for GIS health monitoring and alerting: Case of tuberculosis in Morocco. International Journal of Computer Science and Network Security VOL 10. No.11 November 2010

Downloads

Published

2014-02-15

How to Cite

Mohan Rao, K. R., Kant, Y., & Chandra, S. (2014). Disease modeling – An alert system for informing environmental risk factor for TB infection. British Journal of Healthcare and Medical Research, 1(1), 01–13. https://doi.org/10.14738/jbemi.11.81