We establish identifying assumptions and estimation procedures for the ATT in a Difference-in-Differences setting with staggered treatment adoption in the presence of spillovers. We show that the ATT can be estimated by a simple TWFE method that extends the approach of Wooldridge [2022]'s fully interacted regression model. We broaden our framework to the non-linear case of count data, offering estimation of the ATT by a simple TWFE Poisson model, and we revisit a corresponding application from the crime literature. Monte Carlo simulations show that our estimator performs competitively.