Modeling time-to gonorrhea or chlamydia infections

Abstract

Chlamydia Trachomatis (CT) and Gonorrhea (GC) have been of great health concern for mankind for a long time despite their preventable nature. The interaction between biological, social and behavioural factors have sustained the spread of these infections. The study involved in this project was to assess how these factors are associated with these infections. HIV status is associated with these infections. Kaplan-Meier estimate curve was to compare the survival times between the HIV positive and the HIV negative. Logrank test statistic for assessing the infection rate with GC or CT. The Cox Proportional hazard model for assessing the factors affecting these infections regarding time-to-first infection. These factors included age, prostitution duration, average number of clients per week and condom use. Many extensions of the cox model have been proposed to handle the multiple event time data such as recurrent events. The recurrent event data have been analysed using standard survival techniques with an additional adjustment for the correlation between events within an individual leading to frailty models. The timescale most often used is the gap time, after an event, the subject starts again at 0 and the time to the next event corresponds to the duration it takes to experience the next event.