Brian Williams, PhD

Brian Williams, PhD

Faculty Member, MMED and DAIDD clinics

Research Fellow
South African Centre for Epidemiological Modelling and Analysis

About: Brian retired from the TB program in the World Health Organization (WHO). Having originally studied Physics, first at the University of Natal and then at Cambridge University, he has carried out research in solid-state physics, ecology, and epidemiology. Before joining the WHO in 2001 he was the Director of the Epidemiological Research Unit in Johannesburg where he led research into occupational diseases of mine-workers, especially TB and silicosis. In 1994, as the epidemic of HIV/AIDS became apparent in South Africa, he set up the Mothusimpilo Project in Carletonville, South Africa, the biggest gold-mining complex in the world. There he worked with mine-workers, sex-workers, and adolescents to understand and to find ways to manage the epidemic of HIV. More recently, he has been closely involved with developing and promoting the use of treatment-as-prevention to stop the epidemic of HIV. He conceived the idea of a center for the application of mathematics to biological systems in South Africa, which led to the founding of SACEMA in 2006. Dr. Williams has contributed to the MMED clinics and precursor programs since 2009, inspiring participants to tackle the challenge of learning to do meaningful modeling that will have real-world public health impacts.

Selected publications:

Williams, Gupta, Wollmers, Granich. (2017) Progress and prospects for the control of HIV and tuberculosis in South Africa - a dynamical modelling study. The Lancet Public Health

Williams, Gouws, Somse, Mmelesi, Lwamba, Chikoko, Fazito, Turay, Kiwango, Chikukwa, Damisoni, Gboun. (2015) Epidemiological trends for HIV in southern Africa - implications for reaching the elimination targets. Current HIV/AIDS Research

Granich, Gilks, Dye, de Cock, Williams. (2017) Universal voluntary HIV testing with immediate antiretroviral therapy as a strategy for elimination of HIV transmission - a mathematical model. Epidemics