GLASS – The interplay of movement and spatiotemporal variation in transmission degrades pandemic control
Nicholas Kortessis, Margaret W. Simon, Michael Barfield, Gregory E. Glass, Burton H. Singer, and Robert D. Holt
Article first published online: 5 OCT 2020 Proceedings of the National Academy of Sciences of the United States of America
ABSTRACT:
Successful public health regimes for COVID-19 push below unity long-term regional Rt —the average number of secondary cases caused by an infectious individual. We use a susceptible-infectious-recovered (SIR) model for two coupled populations to make the conceptual point that asynchronous, variable local control, together with movement between populations, elevates long-term regional Rt, and cumulative cases, and may even prevent disease eradication that is otherwise possible. For effective pandemic mitigation strategies, it is critical that models encompass both spatiotemporal heterogeneity in transmission and movement.
To control COVID-19, public policy must drive average effective net reproduction number (Rt) below unity, globally. Yet local governments craft policies based on local trends. In the United States, local controls wax and wane over time, often poorly coordinated across polities (e.g., states). New York may surge while Florida does not, but, later, this flips, generating repeated outbreaks varying among locations. Mathematical models are essential tools to monitor and control epidemics such as COVID-19 (2???–6), but they can also sharpen intuition about emergent epidemiological phenomena. While spatial processes are increasingly incorporated into epidemiological theory (7), as is temporal variation in disease transmission (4, 5, 8), their combined effect is underappreciated. Yet spatiotemporal variation is pervasive in epidemics; COVID-19 is no exception. Data for the United States (e.g., https://rt.live/) suggest Rt has fluctuated in wave-like fashions, with peaks at different times in different states. We show that infectious individuals moving among populations with asynchronous temporal dynamics in transmission can permit disease persistence when extirpation would otherwise occur, based on local estimates of transmission: Global average Rt over time may exceed 1, despite time-averaged Rt < 1 locally, everywhere. Moreover, even when extirpation is unlikely, spatiotemporally heterogeneous transmission, coupled with movement, can accelerate epidemic spread.
We illustrate these generic features of pandemics using a susceptible-infectious-recovered (SIR) model (see Materials and Methods) that captures essential elements of more realistic models, and allows us to clarify the essential features responsible for such effects. We consider 1) effective local control, where local transmission dynamics imply eradication, were locations isolated; and 2) ineffective local control, where local transmission dynamics generate varying but sustained spread.
Read the full publication at Proceedings of the National Academy of Sciences of the United States of America