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Hepatitis C virus (HCV) is a single strained RNA virus. It
is one of the leading cause of liver-related mortality worldwide. Globally, 115 million people are infected with HCV. This study aims to find
the maximum possibility of occurrence of HCV causes, genotypes and
variables gender wise using TOPSIS (Technique for Order Preference by
Similarity to Ideal Solution). Our findings shows that, if a nation controls
on intravenous drug users then they would be able to save the male community and in case of blood transfusion and other causes women would
be saved by implementing hygienic policies in clinics. Whereas, in case
of genotype 1 women are on the top and in all other genotypes men are on
top. In case of HAI, by applying TOPSIS we figure out that, the severity
of the disease is present in women as relative closeness coefficient was
higher for women in case of HAI (greater than equal to 7) as compared
to men. Fibrosis score (1-2) are reported in case of infected women and
(3-4) are reported in case of infected men. We proposed that, in order to
decrease rate of HCV infections, results of different mathematical model
like TOPSIS should be utilized to suggest precautions to an infected individual.
Rabia Nasar, Adina Asim, Tabasam Rashid. (2020) Mathematical study to demonstrate the utilization of TOPSIS to find the maximum possibility of HCV causes, Punjab University Journal of Mathematics, Volume 52 , Issue No.4.
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