A framework for the study of zoonotic disease emergence and its drivers: spillover of bat pathogens as a case study

Wood, James L. N.; Leach, Melissa; Waldman, Linda; MacGregor, Hayley; Fooks, Anthony R.; Jones, Kate E.; Restif, Olivier; Dechmann, Dina; Hayman, David T. S.; Baker, Kate S.; Peel, Alison J.; Kamins, Alexandra O.; Fahr, Jakob; Ntiamoa-Baidu, Yaa; Suu-Ire, Richard; Breiman, Robert F.; Epstein, Jonathan H.; Field, Hume E.; Cunningham, Andrew A.

The development of mathematical models that integrate information from all the empirical research components is a critical foundation of this theme [44, 45, 47, 49] . These models should investigate the potential roles of different mechanisms that can influence infection dynamics, including host-pathogen interactions at the individual level, virus circulation within and among bat colonies (which requires detailed understanding of host ecology) and inter-species transmission (impacted by viral tropisms and human-bat interactions). Beyond their traditional use for post hoc analysis of data, mathematical models are critical, primary elements in this research framework on disease spillover that can provide: -rational guidance for field data collection, particularly for wildlife disease [44] . This can maximize the utility of quantitative information and its use in models; and -a quantitative framework to connect the different research themes and disciplines and to analyse their impact on virus dynamics.