Mapping spatial colleague connectivity patterns from individual-level registry data to inform regional pandemic interventions

Abstract

Human mobility and social contact patterns are key drivers of infectious disease transmission, yet quantifying geographical connectivity at a fine spatial scale remains a challenge. We quantified geographical connectivity through the workplace using employment registry data covering more than 8 million workers in the Netherlands, producing colleague-connectedness metrics indexed by municipality triplets (two residential municipalities and one workplace municipality). Using the spread of SARS-CoV-2 Omicron as a test case, we found that a two-fold increase in within-province colleague connections was associated with a 3.7-day earlier onset, and between-province connectivity with a 2.5-day earlier onset. Regional lockdown scenarios showed heterogeneous impacts: locking down Zeeland would remove 2.6% of national colleague links, whereas Amsterdam alone would remove 10.0%. These fine-grained spatial connectivity data can serve as spatial mixing matrices in future transmission models, enabling more regionally targeted pandemic policy.