It is only possible to describe,understand and predict the transmission of an infection if sufficient data are available.The incidence (the number of new infections per time unit) is a pivotal epidemiological measure to study infectious disease occurrence.However,the efforts required to frequently sample a large subset of a population can be too demanding to obtain reliable incidence data.For instance,for infections in rodent populations,time and logistics efforts of capture-mark-recapture fieldwork often result in a lower than optimal sample size and sampling frequency,and a low-resolution longitudinal dataset.Serological data may provide opportunities to improve this.When per-host antibody or infectious agent quantities vary over time in a predictable manner,the quantity at a given time can be used to back-calculate the time since infection,thereby strongly increasing the temporal resolution of the data.Using Morogoro virus infection in Mastomys natalensis in a standard monthly capture-mark-recapture setting as a case study,we show how this method can significantly improve the quality of incidence data without additional sampling.