The unintended consequences of inconsistent pandemic control policies

Controlling the spread of COVID-19 — even after a licensed vaccine is available — requires the effective use of nonpharmaceutical interventions, e.g., physical distancing, limits on group sizes, mask wearing, etc.. To date, such interventionshave neither been uniformly nor systematically implemented in most countries. For example, even when under strict stayat-home orders, numerous jurisdictions granted exceptions and/or were in close proximity to locations with entirely differentregulations in place. Here, we investigate the impact of such geographic inconsistencies in epidemic control policies bycoupling search and mobility data to a simple mathematical model of SARS-COV2 transmission. Our results show that whilestay-at-home orders decrease contacts in most areas of the United States of America (US), some specific activities and venuesoften see an increase in attendance. Indeed, over the month of March 2020, between 10 and 30% of churches in the US sawincreases in attendance; even as the total number of visits to churches declined nationally. This heterogeneity, where certainvenues see substantial increases in attendance while others close, suggests that closure can cause individuals to find an openvenue, even if that requires longer-distance travel. And, indeed, the average distance travelled to churches in the US rose by13% over the same period. Strikingly, our mathematical model reveals that, across a broad range of model parameters, partialmeasures can often be worse than no measures at all. In the most severe cases, individuals not complying with policies bytraveling to neighboring jurisdictions can create epidemics when the outbreak would otherwise have been controlled. Takentogether, our data analysis and modelling results highlight the potential unintended consequences of inconsistent epidemiccontrol policies and stress the importance of balancing the societal needs of a population with the risk of an outbreak growinginto a large epidemic.