Interplay between mobility, multi-seeding and lockdowns shapes COVID-19 local impact

Area of Science:

• Epidemiology
• Mathematical Modeling
• Public Health

Background:

• Understanding mobility's role in epidemic spreading is vital for effective control policies.
• The impact of multi-seeding (multiple independent introductions of infection) on epidemic dynamics is often underestimated.
• Spatial heterogeneity in disease incidence is a key challenge in epidemic management.

Purpose of the Study:

• To investigate the non-linear effects of multi-seeding and mobility on epidemic incidence and peak timing.
• To explore how local demography and social mixing patterns modulate the impact of imported infections.
• To explain observed spatial heterogeneities in COVID-19 incidence and mortality using multi-seeding and mobility restrictions.

Main Methods:

• A modeling approach was employed to simulate epidemic dynamics.
• Analysis included model simulations and data from five European countries during the first COVID-19 wave.
• The study identified 'epidemic epicenters' based on their influence on national incidence and mortality peaks.

Main Results:

• The number of initial infections (seeds) has a non-linear effect on the incidence peak and its timing.
• The impact of each infection seed is amplified in smaller populations due to local demography and mixing patterns.
• A combination of multi-seeding and mobility restrictions effectively explains spatial variations in COVID-19 outcomes.

Conclusions:

• Mobility-driven multi-seeding plays a critical role in epidemic evolution and can significantly boost incidence.
• Local factors amplify the effect of imported cases, with smaller populations being more susceptible.
• Identifying epidemic epicenters is crucial for targeted control strategies and understanding national epidemic trajectories.