Impacts of State Reopening Policy on Human Mobility

Nguyễn, Thủy; Gupta, Sumedha; Andersen, Martin; Bento, Ana I.; Simon, Kosali; Wing, Coady

doi:10.3386/w27235

Cited by 65 publications

(63 citation statements)

References 20 publications

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“…Although rates of recent unemployment and absence from work are still very high in the May CPS data, reopening policies have reduced the negative impact of the epidemic on the labor market. The improvements in labor market outcomes are consistent with cell signal data, which show a rise in physical mobility starting in mid-April and continuing through May (Nguyen et al 2020). Of course, it is unclear whether these returns to normalcy can be sustained in the face of more recent increases in COVID-19 cases and hospitalizations.…”

Section: Resultssupporting

confidence: 77%

Determinants of Disparities in Covid-19 Job Losses

Montenovo

Jiang

Rojas

et al. 2020

Self Cite

412

350

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We make several contributions to understanding the socio-demographic ramifications of the COVID-19 epidemic and policy responses on employment outcomes of subgroups in the U.S., benchmarked against two previous recessions. First, monthly Current Population Survey (CPS) data show greater declines in employment in April and May 2020 (relative to February) for Hispanics, younger workers, and those with high school degrees and some college. Between April and May, all the demographic subgroups considered regained some employment. While in most cases the re-employment in May was proportional to the employment drop occurred through April, we show that this was not the case for Blacks. Second, we show that job loss was larger in occupations that require more interpersonal contact and that cannot be performed remotely. Third, we see that consistent with theories of occupational segregation, the extent to which workers of certain demographic groups sort (pre-COVID-19) into occupations and industries can explain a sizeable portion of the gender, race, and ethnic gaps in recent unemployment. However, there remain substantial unexplained differences in employment losses across groups even in these detailed decompositions. We also demonstrate the importance of tracking workers who report having a job but are absent from work, in addition to tracking employed and unemployed workers. We conclude with a discussion of policy priorities and future research needs implied by the disparities in labor market losses from the COVID-19 crisis that we identify.

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Section: Resultssupporting

confidence: 77%

Determinants of Disparities in Covid-19 Job Losses

Montenovo

Jiang

Rojas

et al. 2020

Self Cite

412

350

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“…This may be possible due to the increased awareness of the population of the ongoing COVID-19 epidemic in Wuhan and other areas of China. In fact, it has become apparent that individual and collective human behavior has had subtle and recognizable effects on SARS-CoV-2 transmission [22][23][24][25]. After the declaration of the public health emergency on January 24 and the adoption of strict control measures, we estimated a quick reduction of daily reproduction number, similar to what observed in other provinces of China [10] and elsewhere [26][27][28][29].…”

Section: Discussionsupporting

confidence: 64%

The COVID-19 outbreak in Sichuan, China: epidemiology and impact of interventions

Liu

Bento

Yang

et al. 2020

Preprint

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In January 2020, a COVID19 outbreak was detected in Sichuan Province of China. The aim of this work is to characterize the epidemiology of the Sichuan outbreak and estimate the impact of the performed interventions. We analyzed patient records for all laboratory confirmed cases reported in the province for the period of January 21 to March 16, 2020. To estimate the basic and daily reproduction numbers, we used a Bayesian framework. In addition, we estimate the number of cases averted by the implemented control strategies. The outbreak resulted in 539 confirmed cases, lasted less than two months, and no further local transmission was detected after February 27. The median age of local cases was 8 years older than that of imported cases. Severity of symptoms increased with age. We estimated R0 at 2.4 (95% CI: 1.6-3.7). The epidemic was self sustained for about 3 weeks before going below the epidemic threshold 3 days after the declaration of a public health emergency by Sichuan authorities. Our findings indicate that, were the control measures be adopted four weeks later, the epidemic could have lasted 49 days longer (95%CI: 31-68 days), causing 9,216 (95%CI: 1,317-25,545) more cases and possibly overwhelming Sichuan healthcare system.

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“…30,32 Figure 3 shows a weakly positive correlation between temperature and park visitation but a lack of correlation between temperature and encounter rate. In other words, while people in most states change their behavior to visit parks more when temperatures are higher, in line with previous work, 13,33 their potential encounter rates do not significantly increase (with a few exceptions). (Similar trends are observed on the county level in Extended Data Figure 5.…”

Section: Effects Of Weather On Mobilitysupporting

confidence: 86%

“…Most of these states experienced a new surge in COVID-19 cases in July, 10 consistent with studies that argue that an early reopening led to the new wave. [11][12][13] Dates of reaching 30% of pre-pandemic potential encounter rate are not correlated with implementation dates of reopening plans (R 2 =0.062) or with expirations of stay-at-home orders (R 2 =0.049), which is further evidence that mobility behaviors are substantially independent of state policies. The consistency across mobility measures suggests the primacy of national awareness and national guidelines over state policies in determining human behavior.…”

Section: Mobility Changes and Policy Timingmentioning

confidence: 99%

Weather and Policy Influences on Mobility during the U.S. COVID-19 Pandemic

Mooring

Linz

2020

Preprint

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As the novel coronavirus SARS-CoV-2 continues to proliferate across the globe, it is a struggle to predict and prevent its spread. The successes of mobility interventions demonstrate how policies can help limit the person-to-person interactions that are essential to infection. With significant community spread, experts predict this virus will continue to be a threat until a safe and effective vaccine has been developed and widely deployed. We aim to understand mobility changes, measured via mobile device tracking, during the first major quarantine period in the United States by assessing how people changed their behavior in response to policies and to weather. Here we show that consistent national messaging was associated with consistent national behavioral change, regardless of local policy. Furthermore, while behavior changed with favorable weather conditions generally the changes did not increase encounters between people. The independence of encounters and temperatures suggests that behavioral changes will not impact any direct physical modulation of transmission by weather as the pandemic continues. Both of these results are encouraging for the potential of the country to be able to curb the virus with clear national messaging.

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Impacts of State Reopening Policy on Human Mobility

Cited by 65 publications

References 20 publications

Determinants of Disparities in Covid-19 Job Losses

Determinants of Disparities in Covid-19 Job Losses

The COVID-19 outbreak in Sichuan, China: epidemiology and impact of interventions

Weather and Policy Influences on Mobility during the U.S. COVID-19 Pandemic

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