Mathematical modelling for infectious diseases and public health works best through collaborations with epidemiologists, policy makers and field experts.Multiple modelling groups working on the same question allows us to investigate model structure uncertainty – the importance of particular underlying assumptions of each model type. The need for structures that connect modellers and users. Designing and parameterising models raises questions about underlying biology, data availability and implementation policy structures. Conversations between these different sectors will help identify the need for studies to address key uncertainties. NTD modelling lags behind modelling for other infectious diseases and it needs to be able to access the huge advances in the broader modelling field. With the right funding framework and the right relationship between modellers and users, new insight into NTDs will be possible. A recruitment problem: many modellers work on NTDs for a short amount of time due to lack of funding and limited impact of publications, again as a result of the small modelling community. We need mechanisms to attract and keep infectious disease modellers in this area.