Structure

Members of the NTD Modelling consortium have been awarded a grant from the Bill and Melinda Gates Foundation which invites it to become a part of the global effort to reduce the burden of infectious diseases amongst the poorest billion in the world

The focus of the grant will be neglected tropical diseases (NTDs), a diverse group of infections which thrive mainly among the poorest populations of the world. These NTDs perpetuate the cycle of poverty and cause long-term suffering to millions. In recent years there has been a huge international investment to prevent additional morbidity through the control and elimination of many of these diseases and the World Health Organization has set ambitious targets for eliminating much of the burden of these diseases by 2020.  

Mathematical modelling plays an increasing role in public health planning and decision making (such as determining cost-effectiveness of drugs and vaccines), but for NTDs the use of such quantitative predictions has been sparse. With 2020 rapidly approaching, the treatment and control programs need epidemiological models to help evaluate the impact of current programmes and potentially suggest more optimally targeted designs for the future. Identifying regions where the controls could work more effectively and providing refinements to control strategies could have a major impact on achieving the World Health Organization’s 2020 targets and could help reduce the length of time and cost of interventions

This is a large international effort, with teams from around the UK (Imperial College London, Liverpool School of Tropical Medicine, London School of Tropical Medicine and University of Warwick), Europe (Erasmus Medical Centre), the USA (Case Western Reserve University, Johns Hopkins University, Notre Dame University, Princeton University, University of California San Francisco and Yale University) and  Australia (Monash University). The gathering of this global team is a unique effort, brought together by the goal of improving the health of the poorest populations in the world.

Good quality modelling depends on good quality data and expert input through close collaboration with field epidemiologists, clinicians, country program managers and international bodies. Through a close relationship with the Task Force for Global Health in Atlanta, USA, the researchers will be linked into a network of leading experts in this field.

Dr Deirdre Hollingsworth, who is leading the consortium from the School of Life Sciences and the Mathematics Institute at the University of Warwick, thinks that “It is fantastic to be involved with such an exciting and worthwhile project that gives the international modelling community the opportunity to demonstrate its expertise and commitment to NTDs. There are significant scientific challenges to producing quantitative frameworks that can support the effort to control NTDs but through this unique partnership we will be ready for them.”

The consortium has been commissioned to review all current data within various models to compare and evaluate the most effective changes that can be made to the global program to encourage greater likelihood for success by 2020. By using multiple modelling approaches the consortium will ensure that the advice given is based on the best quality science, and has been robustly tested.

Dr Sake de Vlas of Erasmus MC, Rotterdam, who is involved in five projects within the consortium, said “this unprecedented effort will strengthen the collaboration between NTD modellers, field scientists, control programs and policy makers, thereby contributing greatly to the evidence base of the control and elimination of these important poverty related diseases.”

Professor Sir Roy Anderson from Imperial College London, who will be involved in three projects within the consortium, said “this is a wonderful opportunity to put public health policy formulation for the control of NTDs on a much firmer quantitative footing – with robust parameter estimation underpinning mathematical model predictions of the impact of different control strategies”