The role of inter-regional mobility in forecasting SARS-CoV-2 transmission

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 nationwide level. To model transmissions,
we use a simple mobility-enhanced SEIR compartmental model with sub-populations 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. By contrast, the improvement becomes larger when municipalities have a relatively large amount of incoming mobility compared with the number of inhabitants.