Bio
I am a statistical/epidemiologist working mainly on the epidemiology and control of infectious diseases in low and middle income countries (LMICs). Since 2019, I have been affiliated with the London school of hygiene and tropical medicines (LSHTM).
I have a Bachelors of science degree in Applied Statistics from Maseno University in Kenya (2013). I was awarded the ISEG postgraduate training fellowship in Medical Statistics at LSHTM (2018) followed by a one-year placement at Zambart (Zambia). My work at Zambart was primarily centred around the analysis of TB and HIV data from cluster randomized trials. I was also heavily involved in the TB reduction through expanded ART and screening (TREATS) prevalence survey within the TREATS project.
Before commencing my masters, I was involved in the use of spatial and spatiotemporal methodology in habitat suitability mapping and disease prevalence mapping projects.
Affiliations
Teaching
Tutor in the Distance Learning Advanced Statistical Methods in Epidemiology Module (EPM304)
Research
My research interests are on the use of causal inference methods to generate real world evidence from real world data. I am particularly, but not exclusively, interested in methods bridging the worlds of causal inference and machine learning, and the worlds of causal inference and spatial statistics.
Currently, I am undertaking an NIHR funded pre-doctoral fellowship where I am focusing on the use of causal inference and machine learning to investigate the causal effect of being HIV-positive and on antiretroviral therapy (ART), compared with being HIV-negative, on the risk of having prevalent TB-disease.
Beyond my research endeavors, I am deeply committed to enhancing the biostatistics capacity of both individuals and institutions in LMICs. To advance this goal, I hold the role of the Zambian research co-investigator in the MRC International Statistics and Epidemiology Partnership (ISEP). Across 6 institutions in Sub-Saharan Africa (SSA), ISEP’s primary mission is to define and implement a sustainable strategy aimed at expanding capacity for applied medical statistics.
Selected Publications
