Importance of untested infectious individuals for the suppression of COVID-19 epidemics

Francisco Perez-Reche; Norval Strachan

The main aim of our models is to contribute to the understanding of the epidemiological patterns of SARS-Cov-2 rather than to provide exact predictions. Hence the models should be viewed as a general guide of how the outbreak and interventions may play out rather than as an exact representation of COVID-19 epidemics 17 . We made several simplifying assumptions in the models. In particular, spatial and age heterogeneities were ignored. However, it is known that there is both spatial heterogeneity within the populations 36 (e.g. cities and rural areas) as well as differences in both susceptibility and mortality across different age and vulnerability groups 29, 37 . Another limitation of our approach is that it assumes that the transition times between compartments are exponentially distributed. This memory-less assumption is usual for classical compartmental models 17 . For COVID-19, however, transitions between compartments are better described in terms of gamma distributions 3,29 and using models with memory would provide a more precise description of the dynamics 3, 17, 38 . In addition, our model is limited in terms of the specific ways to make interventions operational. For instance, reductions in transmission are treated at a generic level without specifying if they could be achieved by enhanced social distancing, school closure, etc. Accounting for such details would require using individual-based simulations 15 .