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.
Citation
M.Sc. (Biometric) Thesis 2004Sponsorhip
University of NairobiPublisher
Depatment of Mathematics, University of Nairobi
Description
Master of Science Thesis