Dr Nick Scott and his team use maths to outsmart deadly infectious diseases and save vulnerable lives.
Tuberculosis (TB) is a global public health crisis, with an estimated 10.4million new infections in 2015 alone, with a significant proportion of the global burden affecting the Asia-Pacific region.
Halting the TB epidemic is further hampered by the continuing rise of multidrug resistant TB (MDR-TB) and extensively drug resistant TB (XDR-TB). Both the WHO and UN recognise the severity of TB, and have established targets for reductions in both the number of new cases and deaths caused by TB. Identifying how to best allocate effort and resources is key in reaching these targets, and is the primary purpose for what Optima TB sets out to achieve.
Optima TB combines an epidemiological model of TB transmission and disease progression integrated within a flexible economic and financial analysis framework. Combining these tools allows us to identify the most cost-effective intervention mix to achieve the greatest health impact against TB.
The tool aims to answer questions such as:
To date, Optima TB has been applied in countries in Southeast Asia, Eastern Europe, Africa and South America, and can be easily adapted to fit a country’s specific requirements. This can include different high risk groups, as well as co-infections that are known to interact with TB, such as HIV and diabetes.
The Optima approach has already been used extensively to inform policy makers in the search for allocative efficiency in HIV, nutrition and malaria, and is now being applied to tuberculosis control.
Developed in partnership between the Burnet Institute and University College of London (UCL), Optima TB combines Optima’s formal mathematical optimisation algorithm around the UCL TB epidemiological model.
For any general enquiries relating to this project, please contact:
PhD student and Research Associate