We are a collection of biostatisticians, research fellows, and students working on various topics in the Division of Epidemiology & Biostatistics, School of Public Health & Family Medicine at the University of Cape Town. Current research themes are looking at biomarker monitoring in chronic disease (eg viral load monitoring during pregnancy and postpartum) and a number of investigations into longitudinal modelling of exposures related to lung health in Africa.
We work with the Cape-R Users Group to promote R programming around the Cape and wider afield, please join if you are local to Cape Town (twitter @CapeRUser).
See the contact page for visiting and mailing address as well as other contact details. Email preferred.
Hosted by the Division of Epidemiology & Biostatistics, School of Public Health & Family Medicine, University of Cape Town.
This project is part of the European and Developing Countries Clinical Trials Partnership (EDCTP2) programme supported by the European Union (TMA2017SF-1959)
The abstract and a few summary figures of the MPH mini-dissertation submitted by Eke Arua for his degree. Abstract Introduction: Data from routine viral load monitoring is important for assessing the programmatic effectiveness of antiretroviral treatment (ART) in South Africa, but this is usually analysed in a cross-sectional manner and there are few analyses of …
This has been up in various guises before, it remains incomplete but I’ve had requests recently to post. Use this document in conjunction with the Research data planning checklist and the research data guidelines above to help with the research data planning process. 1. Describing your dataConsider:– How will this research be generated and used in …
We have a few positions available Modeller – we need a great R programmer to work on statistical simulation. This can either be as a postdoc (tax free) or we can appoint as a research fellow (not tax free), either way post PhD as research experience will help. This is really contract programming, but a …
Click on caption for details of individual projects and outputs. If you are unable to access publications or other outputs, please just email for a copy, we will be very happy to send and are working on getting all our papers open access/preprint available.
Biostatistician & Associate Professor Head, Division of Epidemiology & Biostatistics, School of Public Health & Family Medicine, University of Cape Town, South Africa
Academy of Medical Sciences Newton Advanced Fellow, Liverpool School of Tropical Medicine EDCTP2 Senior Fellow, BiostatsLAB-Africa Contributing investigator, Wellcome Centre for Infectious Diseases Research in Africa (CIDRI-Africa)
Maia is an applied biostatistician with more than a decade of experience in heath sciences research, the last six of which have been spent working with clinical researchers in Africa. Maia currently works with clinicians and epidemiologists in TB, HIV and respiratory disease related research as well as having a program of NIH, EDCTP and Academy of Medical Sciences funded research for biostatistical methods work. She teaches biostatistics anywhere she can, but mainly as part of the University of Cape Town Masters of Public Health programme & PATS MECOR.
Elton Mukonda (Research Fellow, PhD candidate, UCT) ORCID: 0000-0002-3930-3389 Elton is a trained demographer with considerable experience working as a statistician. He completed his MPhil in Demography in 2015 at the Centre for Actuarial Research(CARe), University of Cape Town, with a research on estimating mortality for metropolitan populations in developing countries. He is currently working on his PhD in the area of chronic disease monitoring in LMIC using simulation and economic evaluation approaches. Elton runs most of our R training program. Current interests include R programming, statistical learning, longitudinal data analysis, actuarial modelling and Bayesian Statistics.
Tracy Glass (Statistical Analyst, PhD candidate, UCT) Tracy currently works as a statistical analyst at the Division of Epidemiology and Biostatistics, UCT. She completed her Master of Public Health in 2016, specialising in epidemiology and biostatistics. She has previously worked as a research intern at the Burden of Disease Research Unit (BODRU), at the South African Medical Research Council. Her current interests include disease modelling and her PhD is looking at the impact of alternate monitoring and intervention in pregnant and postpartum women living with HIV.
Frissiano Honwana (Statistician & Assistant Lecturer, PhD student, UCT) ORCID: 0000-0001-6662-1027 Frissiano Honwana is a statistician in the Division of Epidemiology & Biostatistics. His areas of interest are longitudinal models, infectious disease modelling and predictive models for biomarkers in clinical trials. Frissiano is a member of South African Statistical Association (SASA).
Raymond T Nhapi (Statistical Analyst, PhD student, UCT) ORCID: 0000-0003-1144-7038 Raymond Nhapi is a Data Analyst and PhD student in the Division of Epidemiology and Biostatistics. He holds a MSc degree in Advanced Analytics from the University of Cape Town’s Department of Statistical Sciences. Research interests include designing clinical trials, statistical analysis of complex data structures and teaching & learning.
Luke Hannan (Statistical Analyst, PhD student, UCT) ORCID: 0000-0002-8217-843X Luke works as a statistical analyst in the Division of Epidemiology and Biostatistics, UCT. Luke has a background in Molecular Biology and Evolutionary Development, his current research interests include computational and statistical methods for the analysis of recurrent events and compositional data. His PhD is looking at developing novel methods for the analysis of longitudinal microbiome sequencing data, with applications to respiratory health in children.
Nicola Marozva (Data Analyst, UCT). Nicola holds an MPhil degree in Demography from the Centre for Actuarial Research (CARe), University of Cape Town. Her research interest includes statistical methods for epidemiology particularly for infectious diseases, longitudinal data analysis, machine learning and statistical prediction.
Eke Arua (MPH 2020, Epi & Biostats, UCT) Latent class models for HIV viral load trajectories.
Brian Rambau (MPH 2020, Epi & Biostats, UCT) Identifying and quantifying organism interactions in longitudinal child health studies.
Attie Stadler (MPH 2019, Epi & Biostats, UCT) Evaluation of the diagnostic performance of lung ultrasound compared to chest X-rays for the diagnosis of pneumonia in children.
Luke Hannan (MPH 2019, Epi & Biostats, UCT) Multi-state models for the analysis of wheezing in a cohort of Western Cape children.
Lee Sarkin (MSc 2019, Medicine, UCT) Survival of adults with HIV-1 infection or Type 2 diabetes in the South African private sector
Dumsile Maduna (MPH 2019, Epi & Biostats, UCT) The quality and variation of spirometry reads for testing lung function in children in sub-Saharan Africa.
Vester Gunsaru (MPH 2019, Epi & Biostats, UCT) Prediction of post-tuberculosis lung damage using CT lung imaging measures among adults in Malawi.
Justine Nasejje (PhD 2018, Statistics, UKZN) Random survival forests an alternative method to the Cox Regression model in analyzing survival data with application. Justine is now working as a lecturer at Wits. See a nice write up here.
Karryn Brown (MPH 2018, Epi & Biostats, UCT) HIV-related knowledge and antiretroviral therapy (ART) outcomes in HIV-infected women initiating ART during pregnancy. Currently working as a statistical analyst at UCT.
Jenna Oosthuizen (MPH 2018, Epi & Biostatis, UCT) Family planning behaviours among South African HIV-infected and HIV-uninfected women during the postpartum period.
Kathryn Manning (MPH 2018, Epi & Biostats, UCT) Descriptive epidemiology and risk factors for wheeze in early childhood: The Drakenstein Child Health Study
Rae MacGinty (MPH 2017, UCT) Associations between maternal mental health and child wheeze through two years of age in a South African birth cohort. You can find the associated published manuscript here: https://doi.org/10.1002/ppul.24008