How to cite this paper
Jainsankar, R & Ranjani, M. (2024). Spatial disease mapping using the Poisson-Gamma model.Journal of Future Sustainability, 4(2), 101-106.
Refrences
Bernardinelli, L., Clayton, D., Pascutto, C., Montomoli, C., Ghislandi, M., & Songini, M. (1995). Bayesian analysis of space—time variation in disease risk. Statistics in Medicine, 14(21‐22), 2433-2443
Besag, J., & Newell, J. (1991). The detection of clusters in rare diseases. Journal of the Royal Statistical Society: Series A (Statistics in Society), 154(1), 143-155.
Besag, J., York, J., & Mollié, A. (1991). Bayesian image restoration, with two applications in spatial statistics. Annals of the institute of statistical mathematics, 43(1), 1-20.
Clayton, D., & Kaldor, J. (1987). Empirical Bayes estimates of age-standardized relative risks for use in disease map-ping. Biometrics, 671-681.
Cressie N. (1993). Statistics for spatial data. John Wiley & Sons ; New York.
Eckert, N., Parent, E., Bélanger, L., & Garcia, S. (2007). Hierarchical Bayesian modelling for spatial analysis of the number of avalanche occurrences at the scale of the township. Cold Regions Science and Technology, 50(1-3), 97-112.
Inskip, H., Beral, V., Fraser, P., & Haskey, J. (1983). Methods for age‐adjustment of rates. Statistics in medicine, 2(4), 455-466.
Jaisankar, R., & Kesavan, J. (2019). A study on spatial variations in temporal trends of dengue incidences in Tamil Na-du, India. International Journal of Scientific & Technology Research, 8(9), 788-92.
Jaisankar, R., Kesavan, J., & Ranjani M. (2019). A Spatial Analysis on Dengue Outbreaks in Tamil Nadu, 2013-2018. International Journal of Current Research, Vol. 11, Issue, 11, pp.8116-8120.
Knorr-Held, L., & Becker, N. (1999). Bayesian modelling of spatial heterogeneity in disease maps with application to German cancer mortality data.
Lawson, A. B., Biggeri, A. B., Boehning, D., Lesaffre, E., Viel, J. F., Clark, A., & Divino, F. (2000). Disease mapping models: an empirical evaluation. Disease Mapping Collaborative Group. Statistics in Medicine, 19(17), 2217-41.
Millar, R. B. (2009). Comparison of hierarchical Bayesian models for over dispersed count data using DIC and Bayes' factors. Biometrics, 65(3), 962-969.
Richardson, S., Thomson, A., Best, N., & Elliott, P. (2004). Interpreting posterior relative risk estimates in disease-mapping studies. Environmental health perspectives, 112(9), 1016-1025.
Ripley, B. D. (1988). Statistical inference for spatial processes. Cambridge university press.
Snow, J. (1854). On the communication of cholera by impure Thames water. Medical Times and Gazette, 9, 365-366
Srinivasan, R., & Venkatesan, P. (2014). Bayesian random effects model for disease mapping of relative risks. Ann Biol Res, 5(1), 23-31.
Venkatesan P, & Srinivasan R. (2010). Bayesian model of HIV/AIDS in India: A spatial analysis. Applied Bayesian Sta-tistical Analysis, 51-56.
WHO, Dengue in World Health Organization in India. (Accessed July 2019). [http://www.searo.who.int/india/topics/dengue/en/]
Besag, J., & Newell, J. (1991). The detection of clusters in rare diseases. Journal of the Royal Statistical Society: Series A (Statistics in Society), 154(1), 143-155.
Besag, J., York, J., & Mollié, A. (1991). Bayesian image restoration, with two applications in spatial statistics. Annals of the institute of statistical mathematics, 43(1), 1-20.
Clayton, D., & Kaldor, J. (1987). Empirical Bayes estimates of age-standardized relative risks for use in disease map-ping. Biometrics, 671-681.
Cressie N. (1993). Statistics for spatial data. John Wiley & Sons ; New York.
Eckert, N., Parent, E., Bélanger, L., & Garcia, S. (2007). Hierarchical Bayesian modelling for spatial analysis of the number of avalanche occurrences at the scale of the township. Cold Regions Science and Technology, 50(1-3), 97-112.
Inskip, H., Beral, V., Fraser, P., & Haskey, J. (1983). Methods for age‐adjustment of rates. Statistics in medicine, 2(4), 455-466.
Jaisankar, R., & Kesavan, J. (2019). A study on spatial variations in temporal trends of dengue incidences in Tamil Na-du, India. International Journal of Scientific & Technology Research, 8(9), 788-92.
Jaisankar, R., Kesavan, J., & Ranjani M. (2019). A Spatial Analysis on Dengue Outbreaks in Tamil Nadu, 2013-2018. International Journal of Current Research, Vol. 11, Issue, 11, pp.8116-8120.
Knorr-Held, L., & Becker, N. (1999). Bayesian modelling of spatial heterogeneity in disease maps with application to German cancer mortality data.
Lawson, A. B., Biggeri, A. B., Boehning, D., Lesaffre, E., Viel, J. F., Clark, A., & Divino, F. (2000). Disease mapping models: an empirical evaluation. Disease Mapping Collaborative Group. Statistics in Medicine, 19(17), 2217-41.
Millar, R. B. (2009). Comparison of hierarchical Bayesian models for over dispersed count data using DIC and Bayes' factors. Biometrics, 65(3), 962-969.
Richardson, S., Thomson, A., Best, N., & Elliott, P. (2004). Interpreting posterior relative risk estimates in disease-mapping studies. Environmental health perspectives, 112(9), 1016-1025.
Ripley, B. D. (1988). Statistical inference for spatial processes. Cambridge university press.
Snow, J. (1854). On the communication of cholera by impure Thames water. Medical Times and Gazette, 9, 365-366
Srinivasan, R., & Venkatesan, P. (2014). Bayesian random effects model for disease mapping of relative risks. Ann Biol Res, 5(1), 23-31.
Venkatesan P, & Srinivasan R. (2010). Bayesian model of HIV/AIDS in India: A spatial analysis. Applied Bayesian Sta-tistical Analysis, 51-56.
WHO, Dengue in World Health Organization in India. (Accessed July 2019). [http://www.searo.who.int/india/topics/dengue/en/]