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Mathematical Analysis of Transmission and Control of Hiv/Aids in Different Regions of Pakistan

Thesis Info

Access Option

External Link

Author

Tirmizi, Syed Rizwan Ul Haq

Program

PhD

Institute

University of Karachi

City

Karachi

Province

Sindh

Country

Pakistan

Thesis Completing Year

2016

Thesis Completion Status

Completed

Subject

Mathemaics

Language

English

Link

http://prr.hec.gov.pk/jspui/bitstream/123456789/12955/1/Syed%20Rizwan%20Ul%20Haq%20Tirmizi%20soft%20copy%20for%20upload.pdf

Added

2021-02-17 19:49:13

Modified

2024-03-24 20:25:49

ARI ID

1676726617060

Similar


Acquired Immunodeficiency Syndrome (AIDS) was first acknowledged in the world in 1981. Highly Immunodeficiency Virus (HIV) was recognized as a cause of AIDS in 1983. By that time, nearly 96,000 people were living with HIV in Pakistan. The epidemic is of great public health concern because HIV is infectious and causes severe morbidity and death at last. However, successful treatment of HIV/AIDS requires high levels of adherence to prescribed medications. Epidemiologically, there are two approaches to control widespread disease—prevention and treatment. Although there is no cure, treatment exists that has transformed this disease from an acutely lethal infection into a manageable chronic illness. Therefore, the vision of this thesis, to build up mathematical models that can explain the spatial division of HIV/AIDS in Pakistan and gives assurance of treatment adherence within the country. For this purpose, we will study spatial cluster and autocorrelation analysis including trend surface analysis, semivariogram and different types of kriging etc. with the help of ArcGIS 10. We are also interested to study the HIV infection rate in Pakistan using mathematical statistics techniques that will be very helpful to produce maps of risk areas. Multilevel models will be performed using WinBUGS(c) for the significant spatial effects and relative risk factors in explaining the variation of HIV/AIDS. Thus, the areas with high risk can indicate typically and it is to be helpful for health policy makers, manage quick risk assessment and resource allocation. We will also try to make a model to express some major drug with their side effects and high levels of adherence to prescribed medications by using fuzzy matrix theory which is one of the best tools to analyze raw data involving elusiveness. Lastly, examines the biological consequences and public health implication of poor adherence in order to highlight the severity of this problem. We are also interested to make a comparative study model to improve the understanding level of the people about intervention of the disease and motivate them to change their risk behavior and social norms. Awareness to disease can help people to adopt suitable preventive procedures to keep themselves away from the risk.
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