Estimating Survival Probability of Drug Users with Application to Drug and Substance Abuse in Kenya
American Journal of Theoretical and Applied Statistics
Volume 6, Issue 6, November 2017, Pages: 284-289
Received: Jun. 28, 2017; Accepted: Jul. 17, 2017; Published: Nov. 27, 2017
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Authors
Robert Kasisi, Department of Mathematics and Computer Science Moi University, Eldoret, Kenya
Joseph Koske, Department of Mathematics and Computer Science Moi University, Eldoret, Kenya
Mathew Kosgei, Department of Mathematics and Computer Science Moi University, Eldoret, Kenya
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Abstract
The contemporary studies on drug abuse have blamed the increasing menace of drug abuse on failure of governments to enact adequate laws prohibiting drug abuse and failure to place strict border controls to prevent entry of drugs. Others have blamed social media and modernization as key players towards the current trends of drug abuse. As a result studies have shifted from studying factors leading to drug abuse as these seem to be obvious to studying covariates that leading to improved probabilities of recovery upon treatment. Female substance users are said to be proportionately more likely to recover from drug use than male substance abusers. However studies have showed that female drug users experience low turnout for treatment from drug abuse. With the increasing trend of women drug users seeking treatment there is an urgent need to estimate survival probability of drug use subjects based on marital status, age, gender and job status. This study sought to determine the survival probability of drug users in Kenya for the period between July 2013 and June 2015. Kaplan Meier analysis was used to determine the survival probability of a subject entering into drug use at different stages of life based on predictive covariates. Survival probability of drug users based on age, gender, marital status and employment status was determined. The study recommended that there significant differences in survival probability based on gender, age, marital status and employment status. Therefore the study recommended that treatment services be tailored on treating subjects based on these predictive covariates.
Keywords
Survival Probability, Kaplan Meier Analysis, Intervention Programs, Hazard Rate, Drug Abuse
To cite this article
Robert Kasisi, Joseph Koske, Mathew Kosgei, Estimating Survival Probability of Drug Users with Application to Drug and Substance Abuse in Kenya, American Journal of Theoretical and Applied Statistics. Vol. 6, No. 6, 2017, pp. 284-289. doi: 10.11648/j.ajtas.20170606.14
Copyright
Copyright © 2017 Authors retain the copyright of this article.
This article is an open access article distributed under the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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