The understanding of data and disease processes around HIV and TB has been the main focus in the early life of Sacema.
The understanding of data and disease processes around HIV and tuberculosis (TB) has been the main focus in the early life of the DST/NRF Centre of Excellence in Epidemiological Modelling and Analysis (Sacema).
Sacema is based at Stellenbosch University's historical Mosterdsdrift site and, since 2006, has been home to about a dozen researchers. Recently it was awarded a SARChI South African Research Chair.
Epidemiological modelling and analysis are easier said than done and potentially cover a broad field.
The researchers and students who are funded and mentored by Sacema study the mathematical and statistical dynamics of everything from molecules in reaction vessels in laboratory processes and cells and virus particles in infected individuals to cohorts and whole populations in which epidemics play out.
Two dominant, and deceptively subtle, concrete activities dominate the Sacema agenda. First, Sacema studies the state of epidemics (that is, epidemiological surveillance) and, second, it performs scenario modelling and evaluation to understand the impact of specific intervention measures. This research blurs the distinction between science and policy. It is technically challenging (beyond the reach of routine methodologies) and fundamental to the health of our society, both clinically and more broadly as an indicator of the viability of rational planning.
Within surveillance, it is relatively easy to estimate how many or, more specifically, what proportion of, people have HIV (this is known as the "prevalence" of HIV).
It is much harder to figure out how rapidly new cases are occurring, for example, a year, (this is known as "incidence"). Sacema's work on incidence provides a stable theoretical foundation to analyses that had been based on simple heuristics and were beset by substantial theoretical dispute. Emphasis is now shifting towards support for ongoing studies and surveillance systems, training and the dissemination of computational tools.
For scenario modellers, the most talked about intervention in recent years is increased access to treatment. It exploits the proven point that a well-treated individual has dramatically reduced potential for transmitting the virus.
Sacema has been at the centre of wide-ranging debates on this issue, from forcing it back to centre stage to identifying the real issues in the heated ensuing arguments about cost, feasibility, time scales of expected impact and fundamental indicators of success or failure.
For more information visit www.sacema.com or www.incidence-stimation.com/page/cephia-sacema or contact Lynnmore Scheepers email@example.com