13. Spatial and Spatiotemporal Patterns

Spatial and spatiotemporal data analysis is of great importance in disease dynamics for a number of reasons such as looking for space-time clustering, hotspot detection, characterizing invasion waves, and quantifying spatial synchrony. Spatial synchrony—the level of correlation in outbreak dynamics at different locations—is of particular significance to acute immunizing infections, because asynchrony may permit regional persistence of infections despite local chains-of-transmission breaking during post-epidemic troughs (Keeling et al., 2004, see Sect. 15.7). Conversely, spatial synchrony can exacerbate the economic and public health burden because the resulting regionalized outbreaks can overwhelm logistical capabilities as was evident in the early part of the 2013–2014 West African Ebola outbreak and the 2020–2021 SARS-CoV-2 pandemic.