Improving prediction of future Mycoplasma pneumoniae epidemics using data-driven transmission models

Following the global re-emergence of Mycoplasma pneumoniae infections in 2023–24 after the COVID-19 pandemic,1 a key question is when, and to what extent, these infections will surge in the near future. This question is particularly relevant because the most recent epidemic placed a considerable burden on health-care systems worldwide.2 By extending our transmission modelling,2 we aimed to enable such epidemic predictions and advance recent modelling approaches.3 This advancement was based on the premise that short-term to medium-term forecasts can be improved by integrating data-driven transmission models, realistic reporting processes, and validation with contemporary surveillance data.