Socio-economic factors of misconception about HIV/AIDS among ever-married women in Punjab: A comparison of non-spatial and spatial hierarchical Bayesian Poisson model
Keywords:
Bayesian Hierarchical Model, Conditional Autoregressive Bayesian Hierarchical Model, Moran I, Geary’s c, Spatial autocorrelation.Abstract
Combating HIV/Aids is the sixth goal of Millennium Development Goals and has become an increasing health concern in Pakistan. Pakistan is among the 11 countries in the Asia-Pacific which houses a majority of people infected with HIV. The only way to battle HIV is to provide accurate knowledge about HIV / Aids transmission among general public especially women of child bearing age i.e. 15-49 years. Prevention of HIV and misconception about its transmission are associated to each other. Therefore, the present study aimed to identify the spatial distribution of the three types of misconception factors of HIV transmission (i.e. transmitted by mosquito bite, supernatural means and sharing food with HIV positive person). This study also provides the core socio-economic factors to stop the misconception about HIV/ Aids transmission and helped in reducing its epidemic in Pakistan. Spatial and Non-Spatial Bayesian Hierarchical model were applied to the data and results from them revealed that the Conditional Autoregressive Bayesian Hierarchical Models (Spatial Model) were more appropriate. The results showed that Conditional Autoregressive Bayesian Hierarchical models at level 2 are best fit to the data. The results identified that average size of household, mean age of ever-married women in each tehsil, ownership of assets, percentage of TB patients, adolescent birth rate and intrauterine device used as contraceptive measures were the negatively associated with the response variables. While, percentage of ever-married women who attended matric level school, percentage of household received benefits from government social protection schemes, percentage of Hepatitis patients, access to mass media by TV, Female sterilization and condom used as a contraceptive measure were the positively significant factors for misconception indicators about HIV/ Aids Transmission.
References
Carey, M. et al., 2000. Using information, motivational enhancement, and skills training to reduce the risk of HIV infection for low-income urban women: a second randomized clinical trial. Health Psychology, pp. 3-11.
Dirk Pfeiffer, T. R. M. S. K. S. D. R. A. C., 2008. Spatial Analysis in Epidemiology. s.l.:Ocford University Press.
Draper, D., 1996. Discussion of the Paper by Lee and Nelder. Journal of the Royal Statistical Society, Series B, pp. 662-663.
Duncan Lee, G. S., 2010. Spatial modeling of air pollution in studies of its short-term health effects. Biometrics, December, Volume 4, pp. 1238-46.
GBD, 2016. Global Burden of Disease Study 2016, s.l.: Institute for Health Metrics and Evaluation.
Hailu, T. G., 2016. A Multilevel Modeling Analysis of the Determinants and Cross-Regional Variation of the HIV Testing in Ethiopia: Ethiopian DHS 2011. Journal of Biometrics & Biostatistics.
Jay M. Ver Hoef, E. P. D. T., 2006. Spatial statistical models that use flow and stream distance. Environmental and Ecological Statistics, December, 13(4), pp. 449-464.
Jittimanee, S. X. et al., 2009. Social Stigma and Knowledge of Tuberculosis and HIV among Patients with Both Diseases in Thailand. PLoS One.
Lee, D., 2017. CARBayes version 5.0: An R Package for Spatial Areal Unit Modelling with Conditional Autoregressive Priors. June.
Leroux, B. G., Lei, X. & Breslow, N., 2000. Estimation of Disease
Rates in Small Areas: A new Mixed Model for Spatial Dependence. In: D. B. M. Elizabeth Halloran, ed. Statistical Models in Epidemiology, the Environment and Clinical Trials. New York: Springer-Verlag.
Letamo, G., 2007. Misconceptions about HIV prevention and transmission in Botswana. African Journal of AIDS Research, pp. 193-198.
M Mizanur Rahman, M. K. M. S., 2009. Adolescent Knowledge and Awareness about HIV/AIDS and Factors Affecting them in Bangladesh. Journal of Ayub Medical College Abbottabad, pp. 3-6.
Martin, A. D., 2003. Bayesian Inference for Heterogeneous Event Counts. Sociological Methods & Research, August.pp. 30-63.
Mondal. N.I., R. M. R. O. a. A. N., 2012. Level of Awareness about HIV/AIDS among Ever Married Women in Bangladesh. Food Public Health, pp. 73-78.
Mondal, N. I., Hoque, N., Chowdhury, R. K. & Hossain, S., 2016. Factors Associated with Misconceptions about HIV Transmission among Ever-Married Women in Bangladesh. Japanese Journal of Infectious Diseases, Volume 68, pp. 13-19.
Nicky Best, S. R. A. T., 2005. A Comparison of Bayesian Spatial Models for Disease Mapping. Statistical Methods in Medical Research, Volume 14, pp. 35-59.
Nicola G. Best, R. A. A. A. T. L. A. W. E. M. C., 1999. Bayesian Models for Spatially Correlated Disease and Exposure Data. In: J. O. B. A. P. D. A. F. M. S. J. M. Bernardo, ed. Bayesian Statistics 6. s.l.:Oxford University Press.
Ochako, R. U. D. N. P. K. S. a. O. A., 2011. Trends and Determinants of Comprehensive HIV and AIDS knowledge amoung Urban Young Women in Kenya. AIDS Research and Therapy, pp. 8-11.
Peter Zeilhofer, E. B. N. R. L. G. A. R. L., 2006. Spatial Patterns of Water Quality in the Cuiabá River Basin, Central Brazil. Environmental Monitoring and Assessment, December, 123(1-3), pp. 41-62.
Rashid, M. & Chand, S., 2016. Spatial Analysis and Modeling of Infant Mortality Rate Using Conditional Autoregressive Model - A Case Study of Punjab, Pakistan. Pakistan Journal of Medical Research, Volume 55.
Rauf, W. et al., 2010. Knowledge of and misconceptions about the spread and prevention of HIV infection among older urban women attending the Tshwane District Hospital, South Africa. South African Family Practice, pp. 142-148.
Rauf, W. H. S. R. A. a. B. P. J., 2010. Knowledge of and Misconceptions about the Spread and Prevention of HIV Infection among Older Urban Women Attending the Tshwane District Hospital, South Africa. South African Family Practice, 52(2), pp. 142-148.
Tenkorang, E., 2013. Myths and misconceptions about HIV transmission in Ghana: what are the drivers?. Culture, Health and Sexuality, pp. 296-310.
Tribune, T. E., 2011. HIV/AIDS: Pakistan has one of Asia’s highest HIV prevalence rates. [Online]
Available at: http://tribune.com.pk/story/240379/hivaids-pakistan-has-one-of-asias-highest-hiv-prevalence-rates/
UNAIDS, 2005. National Aids Programmes: A gude to indicators For Monitoring and Evaluating National Antiretroviral Programmes, s.l.: Joint United Nations Programme on HIV/AIDS (UNAIDS), World Health Organization.
W. Holmes Finch, J. E. B. K. K., 2014. Multilevel Modeling Using R. London: CRC Press.
Weiss, R., 1993. How does HIV cause AIDS?. Science, May.p. 260.
