The tier-system implemented by California to restrict mobility during the COVID-19 pandemic was associated with an overall decrease in mobility when counties shifted to a more restrictive tier, and increased mobility when they shifted to a less restrictive tier. We identified that shorter and medium range trips greatly decreased with changes to a more restrictive tier, whereas only medium trips increased noticeably when moving to a less restrictive tier. Surprisingly, we found that longer trips between 50 and 250 miles increased following a change to a more restrictive tier. Furthermore, important geographic differences across counties regarding mobility patterns were identified, where Northern California and the coastline had a greater decrease in mobility when moving to a more restrictive tier. These differences were in part explained by differences in economic activity and political opinions. At the county level, higher GDP, higher income, lower number of farms, and lower percentage of voting yes on the governor recall was associated with a greater impact on mobility. Overall, the tier system proved to be an effective policy in managing mobility, with counties generally changing their mobility patterns following a change in tier status.
We found that the tier system was effective in impacting mobility, reducing the population not staying at home by -4.45 [-5.44, -3.47] per 100 persons when counties moved to a more restrictive tier (Table S4). However, when counties moved to a less restrictive tier, the population staying at home increased by only 0.57 [-0.08, 1.22] per 100 persons, with imprecise results (Table S5). This indicates that even when restrictions loosen, counties may not revert back to original mobility patterns immediately.32,33 Risk perception may play an important role in the willingness of populations to continue to implement protective measures, even with easing of restrictions.34,35 This can also help explain the spatial variation in mobility changes throughout the state, as some counties may have the capacity and resources to maintain more conservative behaviors with regards to COVID-19 (Figure 3). The results of this study provide insight into the potential impacts of implementing a spatially derived policy, like the tier-system, in efforts to combat dynamic public health emergencies.
The effectiveness of the California tier system policy also varied by distance of the trips travelled. Overall, the daily number of trips decreased by -36.7 [-56.3, -17.0] per 100 persons when moving to a more restrictive tier, with strongest reductions in lower distance trips of 25 miles or less (Table S4). However, results also indicate unintended consequences of this policy as moving to a more restrictive tier increased trips from 50 to 250 miles (Figure 3). This reverse effect may be explained by residents travelling to neighboring counties when moving to a more restrictive tier to avoid restrictions. This differs from some of the existing research showing that lockdowns have a stronger reduction in long-range mobility than short-range trips.12,23 However, previous work on this topic has been limited and varied; Pullano and colleagues identified that lockdown was associated with decreases in shorter trips in France,23 whereas Schlosser and colleagues found that in Germany, longer distance trips decreased more strongly than shorter distance trips following the COVID-19 lockdown.36 This may be due to differences between the tier system and full lockdown measures evaluated in prior studies. The unintended consequences of the tier system may also be due to limited enforcement. The California tier system was enforced more strictly for businesses, but there was limited enforcement concerning individual adherence to the stay-at-home orders and recommendations to limit travel (Table S2). California did not enforce the law to the same degree other parts of the world did, such as France issuing fines for violations against the home confinement orders and lockdown restrictions.23 Taken together, this may explain the opposite observed effect of an increase in longer trips. These unintended effects are critical to understanding how the population responded to the policy and to better prepare for future measures to reduce mobility.
The variation in mobility reduction from the tier system between counties in California provides insight into how the policy could be adapted to the demographics of sub-populations to maximize effectiveness. We found that as the county GDP and median income increased, the tier system had a greater impact on mobility. Several studies have identified higher compliance with COVID-19 policies among regions with higher income and increased access to resources.16–18,21,22,37−39 It is important to note that many frontline workers lacked the ability to shelter in place, which in turn increased their risk of contracting, and spreading, the virus.40 Similar to our results, it has been shown in other studies that areas with lower income had less of a reduction in mobility during the pandemic.41 This could potentially be due to the percentages of frontline and essential workers in lower-income communities compared to jobs that can feasibly be done remotely by higher-income workers. These differences can be partially explained by a mobility adaptation disparity since higher-paying jobs have increased flexibility to work from home when compared to essential-positions that dominate the job sector in lower-income counties.37
Similarly, although the results were not precise, we did find that the number of farms was associated with less of a reduction in mobility when moving to a more restrictive tier (Table 2). Farmworkers were shown to be particularly affected by COVID-19.420 This may be due to the essential nature of agricultural work; even with tier system restrictions, farm workers were expected to continue working.43 This population is particularly vulnerable as they have low incomes, and many are ineligible for unemployment and other benefits. The lack of social protections and exploitative work conditions are important to consider when understanding differing responses to the tier system.43,44 Essential workers comprise 26% of the working age population, and nearly 50% are from minority racial and ethnic groups. Minority groups are also at greater risk of numerous chronic diseases that are also linked to worse COVID-19 outcomes. This is crucial to study as frontline workers and lower-income communities can have higher exposure rates to the virus, driving further health disparities and inequities. COVID-19 measures tailored and adapted to these vulnerable populations are necessary to effectively and equitably implement policies and limit viral spread.
We found the county-level recall election results were associated with tier system response—In other words, counties voting for the recall were less likely to decrease their mobility when moving to a more restrictive tier (Figure 4). Previous work has considered how county-level political preferences play a role in responsiveness to stay-at-home orders. Engle and colleagues identified that for every 15.6% increase in persons voting for the Republican Party in 2016, mobility has a smaller reduction from 7.87–5.05%.18 Our results are consistent with this research, indicating that political affiliation may be an important consideration in the efficacy of these policies. In California, the recall election emerged in direct opposition to the Governor’s COVID-19 policies, including the tier system. The consideration of politics is critical to understanding the effects of COVID-19 policies, as the social and political economy are key to shaping compliance to public health measures.45
There are limitations to this study that are important to acknowledge. First, as the mobility dataset started in 2019, we only had one year to draw comparisons. Ideally, we would have had more years to use as a baseline mobility measure, but we feel contrasting 2020/2021 to 2019 remains useful, as 2019 was not affected by the pandemic or related policies. Second, the mobility data used is experimental, and data quality standards may be lacking. By comparing mobility within each county using the same data source, we feel the data are sufficiently reliable for the purpose of this study. Also, any residents that do not own or go out with a mobile phone will be excluded from the sample; this could produce a bias as, for example, older persons may be less likely to own or travel with mobile phones; phone behaviors may have also changed because of the pandemic. Moreover, any trip that did not have a pause of 10 minutes or more away from home would not be captured. We also relied on measures of mobility at the county level, and effects may vary within counties; we hope to explore within county variability using more spatially resolved estimates in future work but are currently limited by county-level estimates. Lastly, effects of the pandemic coincided with wildfires and heat waves that affected the state during the summer and fall of 2020, which could also impact mobility; in future work, it would be interesting to disentangle the specific effect of these events.
In conclusion, we found strong evidence that the California tier system and associated restrictions were effective in decreasing population mobility. However, results also showed unintended effects of increased travel for longer trips when moving to a more restrictive tier, which is important to consider when developing and implementing future policies. It may indicate that greater coordination is required between neighboring counties. There was also spatial variation in the effectiveness of this policy, which can be partially explained by differences in economic activity and political opinions across the state. It is important to understand this heterogeneity in the response to the California tier system policy to adapt it to maximize equity and effectiveness. To our knowledge, this was the first study assessing the impact of the tier system policy in California on mobility patterns during its complete duration and how these mobility patterns differed by various county-level characteristics. Results provide evidence that the regional tier system classification was effective in limiting population mobility during a pandemic. Evaluating the strengths and weaknesses of COVID-19 response policies is informative for other states and countries to increase preparedness and to inform effective policies for future global health emergencies.