CoCoDyMo · Co-morbidity and co-infection dynamicCo-morbidity and co-infection dynamic modelling to optimize the control of neglected tropical diseases, tuberculosis, malaria and HIV across vulnerable populations

Infections are a leading cause of mortality and morbidity. Among these, tuberculosis (TB), malaria, HIV/AIDS and Neglected Tropical Diseases (NTDs) are the main contributors to the global burden of disease, particularly in Sub-Saharan Africa, where these chronic infections predominantly affect impoverished communities. Despite increasing evidence that these diseases affect the same populations and that interactions between them impact disease transmission and control, the complex, non-linear dynamics of co-infections with multiple NTDs, TB, malaria or HIV/AIDS, and the implications of these dynamics for disease control remain unknown. Therefore, in CoCoDyMo, we propose to integrate my deep expertise in data sciences, mathematical modelling of infectious diseases and health economics to gain novel insights into co-infections between NTDs, TB, malaria and HIV/AIDS and optimize the integrated control of these diseases. First, we will map, at a fine geographical scale across Sub-Saharan Africa, where NTDs, TB, malaria, and HIV/AIDS are likely to be co-infectious. Then, we will develop new methods to dynamically model relevant co-infections, to understand the life course history of co-infections, elucidate some of the biological questions surrounding the interactions between different pathogens, and how these influence disease progression and control. Finally, we will forecast future trends in disease transmission and evaluate the likely synergistic impact of different interventions (drug administration, vaccines, and surveys) across multiple diseases, both in terms of health and economic benefits. These efforts, at the frontier of infectious disease research, will provide novel insights into the fundamental biology of co-infections with NTDs, TB, malaria and HIV/AIDS and pave the way for exploring relevant policy questions around the integration of disease-specific programs into unified efforts that can maximize the benefits to vulnerable populations.