  In this paper, we present a method to forecast the spread of SARS-CoV-2
across regions with a focus on the role of mobility. Mobility has previously
been shown to play a significant role in the spread of the virus, particularly
between regions. Here, we investigate under which epidemiological circumstances
incorporating mobility into transmission models yields improvements in the
accuracy of forecasting, where we take the situation in the Netherlands during
and after the first wave of transmission in 2020 as a case study. We assess the
quality of forecasting on the detailed level of municipalities, instead of on a
nation-wide level. To model transmissions, we use a simple mobility-enhanced
SEIR compartmental model with subpopulations corresponding to the Dutch
municipalities. We use commuter information to quantify mobility, and develop a
method based on maximum likelihood estimation to determine the other relevant
parameters. We show that taking inter-regional mobility into account generally
leads to an improvement in forecast quality. However, at times when policies
are in place that aim to reduce contacts or travel, this improvement is very
small.
