Student Bio

Erick is a Statistician with a keen interest survival analysis, linear mixed effects models and joint modelling of longitudinal and time to event data. It was while pursuing his undergraduate degree at Maseno University-Bsc Applied Statistics that he developed an interest in statistics. This, coupled with the market need for individuals who were skilled in statistical techniques for analysing data, motivated him to pursue his M.Sc. in Biometry at the University of Nairobi. Through this learning experience, he gained valuable skills in advanced data analysis methods. Currently, Erick is a Statistical Programmer at Phastar, a global CRO that provides statistical consulting and clinical trial data collection and reporting services to pharmaceutical and biotech companies. Previously, Erick was a Data Management Officer with NRHS providing end to end technical skills in HIV projects funded by multiple donors like CDC, UIC, PEPFAR. Erick is a firm believer in utilizing quality, timely and accurate data for decision making and policy development.

Project Summary

Project Title: Joint Modelling of CD4 Count and Time To Wound Healing in HIV-Positive Men Following Circumcision


Background: Modelling longitudinal information and event time outcomes simultaneously helps in describing the progression of the disease over time. Past studies have mostly applied standard Cox proportional hazards model to establish the association between baseline CD4 count and time to wound healing following circumcision. However, Cox proportional hazards model does not take into account the special features of biomarkers besides not utilizing the entire longitudinal history of measurements. Consequently, results reported from Cox proportional hazards model could be biased or inefficient. To optimally investigate the association between CD4 count and time to wound healing, we used a joint modelling framework. In this framework, we utilized patients’ entire longitudinal history of CD4 count, while also properly accounting for measurement error caused by biological variation and missing measurements. Methods: In the first step, we fitted a linear mixed effects model to describe the evolution of square root CD4 count over time for each patient while adjusting for the priori selected baseline covariates. In the second step, we used the estimated evolution (square root CD4 count) in the Cox proportional hazards model to determine its relationship with time to wound healing. Some CD4 count values were missing for some patients at follow-up visits. This is a missing data problem synonymous with longitudinal studies and we assumed that the mechanism of missingness was missing at random (MAR), and thus, the results reported from the joint models, are still valid under MAR. Results: 115 out 119 patients completed their follow-up visits and their wounds were certified fully healed. Median time to wound healing was 49 days (IQR:49-63 ). There was no association between the current true value of square root CD4 count and wound healing time (p-value=0.536). However, for patients with the same current true value of square root CD4 count at a given time point t, the log hazard ratio for a unit increase in the rate of change in square root CD4 count trajectory was 1.514 (95% CI: 1.121; 1.908). Conclusion: Circumcising HIV-positive patients with any level of square root CD4 count is not harmful to their post-circumcision wound healing. However, patients with the same current true level of square root CD4 count could exhibit different slopes of the square root CD4 count trajectory at the same time point t, leading to different progression of wound healing between them.