Cascading effects of COVID-19 on population mobility and air quality: An exploration including place characteristics using geovisualization

Submitted: 19 November 2021
Accepted: 22 January 2022
Published: 17 February 2022
Abstract Views: 1753
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This study hypothesizes that public health responses to coronavirus disease 2019 (COVID-19), including a mandated restriction of activity (commonly called a €˜lockdown') resulted in reduced transportation activities and changes in air quality in Texas, USA. This presented a natural experiment where population mobility and air quality before and after the lockdown could be compared. Changes in mobility were measured by SafeGraph mobility data (from opt-in smart phone applications that transmit location data) and air quality changes were based on NO2 concentrations measured by the European Space Agency's Sentinel-5 Precursor satellite (from the TROPOspheric Monitoring Instrument). The changes in population mobility and NO2 concentration between mid-March 2020 (lockdown initiated) and the end of 2020, as compared to the same time window in 2019, were the basis of exploring the lockdown hypothesis. Additionally, numerous socio-economic (place based) indicators were hypothesized to follow public health vulnerability assumptions based on COVID- 19 incidence patterns. This hypothesis was subjected to geovisualization techniques in order to find potential patterns and insights into the complex combinations of these place-based data. Our results suggest that simultaneously visualizing COVID-19, mobility, air quality and socio-economic data yields insights in underlying spatial processes related to public health policy decisions. The hypothesis that the lockdown resulted in reduced mobility and NO2 concentrations was found partially correct - this trend was observed in highly urbanized areas, but not in less populated areas. Data related public health vulnerability assumptions (e.g. a region's age, poverty, education, etc.) were agreed with in part, but disagreed with in part.

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Abbott G, 2020a. Executive Order GA 08 Relating to COVID-19 preparedness and mitigation. Office of the Texas Governor March 19. Available from: https://gov.texas.gov/uploads/files/press/EO-GA_08_COVID-19_preparedness_and_mitigation_FINAL_03-19-2020_1.pdf
Abbott G, 2020b. Executive Order GA-15 Relating to hospital capacity during the COVID-19 disaster. Office of the Texas Governor April 17. Available from: https://gov.texas.gov/uploads/files/press/EO-GA-15_hospital_capacity_COVID-19_TRANS_04-17-2020.pdf
Abbott G, 2020c. Executive Order GA-16 Relating to the safe, strategic reopening of select services as the first step to Open Texas in response to the COVID-19 disaster. Office of the Governor April 17. Available from: https://gov.texas.gov/uploads/files/press/EO-GA-16_Opening_Texas_COVID-19_FINAL_04-17-2020.pdf
Abbott G, 2020d. Executive Order GA 26 Relating to the expanded opening of Texas in response to the COVID-19 disaster. Office of the Texas Governor June 3. Available from: https://gov.texas.gov/uploads/files/press/EO-GA-26_expanded_opening_COVID-19.pdf
Abbott G, 2020e. Executive Order GA 29 Relating to the use of face coverings during the COVID-19 disaster. Office of the Texaas Governor July 2. Available from: https://gov.texas.gov/uploads/files/press/EO-GA-29-use-of-face-coverings-during-COVID-19-IMAGE-07-02-2020.pdf
Abbott G, 2020f. Executive Order GA 30 Relating to the continued response to the COVID-19 disaster as Texas reopens. Office of the Texas Governor 5 pgs. Available from: https://gov.texas.gov/uploads/files/press/EO-GA-30_expanded_openings_COVID-19.pdf
Abbott G, 2020g. Executive Order GA 32 Relating to the continued response to the COVID-19 disaster as Texas reopens. Office of the Texas Governor October 7. Available from: https://gov.texas.gov/uploads/files/press/EO-GA-32_continued_response_to_COVID-19_IMAGE_10-07-2020.pdf
Agency for Toxic Substance and Disease Registry, 2020. CDC SVI 2018 Documentation. U.S. Department of Health and Human Services. Available from: https://www.atsdr.cdc.gov/placeandhealth/svi/documentation/SVI_documentation_2018.html
Castellanos P, Boersma KF, 2012. Reductions in nitrogen oxides over Europe driven by environmental policy and economic recession. Sci Rep 2:1-7. DOI: https://doi.org/10.1038/srep00265
Chan JF-W, Yuan S, Kok K-H, To KK-W, Chu H, Yang J, Xing F, Liu J, Yip CC-Y, Poon RW-S, 2020. A familial cluster of pneumonia associated with the 2019 novel coronavirus indicating person-to-person transmission: a study of a family cluster. Lancet 395:514-23. DOI: https://doi.org/10.1016/S0140-6736(20)30154-9
Crippa M, Guizzardi D, Muntean M, Schaaf E, Dentener F, Van Aardenne JA, Monni S, Doering U, Olivier JG, Pagliari V, 2018. Gridded emissions of air pollutants for the period 1970-2012 within EDGAR v4. 3.2. Earth Sys Sci Data 10:1987-2013. DOI: https://doi.org/10.5194/essd-10-1987-2018
Curier R, Kranenburg R, Segers A, Timmermans R, and Schaap M, 2014. Synergistic use of OMI NO2 tropospheric columns and LOTOS-EUROS to evaluate the NOx emission trends across Europe. Remote Sens Env 149:58-69. DOI: https://doi.org/10.1016/j.rse.2014.03.032
Gao S, Rao J, Kang Y, Liang Y, Kruse J, 2020. Mapping county-level mobility pattern changes in the United States in response to COVID-19. SIGSpatial Sp 12:16-26. DOI: https://doi.org/10.1145/3404820.3404824
Ghude SD, Pfister GG, Jena C, Van Der A R, Emmons LK, Kumar R, 2013. Satellite constraints of nitrogen oxide (NOx) emissions from India based on OMI observations and WRFâ€Chem simulations. Geophys Res Lett 40:423-8. DOI: https://doi.org/10.1002/grl.50065
Gorelick N, Hancher M, Dixon M, Ilyushchenko S, Thau D, Moore R, 2017. Google Earth Engine: planetary-scale geospatial analysis for everyone. Remote Sens Env 202:18-27. DOI: https://doi.org/10.1016/j.rse.2017.06.031
Hellerstedt JW, 2020. Declaration of a Public Health Disaster in the State of Texas, Department of State Health Services. Secretary of State March 19. Available from: https://www.dshs.state.tx.us/coronavirus/docs/DECLARATION-PublicHealthDisaster.pdf
Johns Hopkins Coronavirus Resource Center, 2021. Data Download. The COVID Tracking Project updated daily. Available from: https://covidtracking.com/data/download
Kala AK, Atkinson SF, Tiwari C, 2020. Exploring the socio-economic and environmental components of infectious diseases using multivariate geovisualization: West Nile Virus. PeerJ 8:e9577. DOI: https://doi.org/10.7717/peerj.9577
Kim SW, Heckel A, Mckeen S, Frost G, Hsie EY, Trainer M, Richter A, Burrows J, Peckham S, Grell G, 2006. Satelliteâ€observed US power plant NOx emission reductions and their impact on air quality, Geophys Res Lett 33. DOI: https://doi.org/10.1029/2006GL027749
Kraemer MU, Yang C-H, Gutierrez B, Wu C-H, Klein B, Pigott DM, Du Plessis L, Faria NR, Li R, Hanage WP, 2020. The effect of human mobility and control measures on the COVID-19 epidemic in China. Sci 368:493-7. DOI: https://doi.org/10.1126/science.abb4218
Lamsal LN, Duncan BN, Yoshida Y, Krotkov NA, Pickering KE, Streets DG, and Lu Z, 2015. US NO2 trends (2005-2013): EPA Air Quality System (AQS) data versus improved observations from the Ozone Monitoring Instrument (OMI). Atmos Env 110:130-43. DOI: https://doi.org/10.1016/j.atmosenv.2015.03.055
Lelieveld J, Evans JS, Fnais M, Giannadaki D, Pozzer A, 2015. The contribution of outdoor air pollution sources to premature mortality on a global scale. Nature 525:367-71. DOI: https://doi.org/10.1038/nature15371
Li Q, Guan X, Wu P, Wang X, Zhou L, Tong Y, Ren R, Leung KS, Lau EH, Wong JY, 2020. Early transmission dynamics in Wuhan, China, of novel coronavirus-infected pneumonia. N Engl J Med [Epub ahead of print]. DOI: https://doi.org/10.1056/NEJMoa2001316
Pishue B, 2020. COVID-19’s impact on freight: an analysis of long-haul freight movement during a pandemic. INRIX Res [Epub ahead of print].
Slotnick D, 2020. Coronavirus demolished air travel around the globe. Bus Insider 22 [Epub ahead of print].
Streets DG, Canty T, Carmichael GR, De Foy B, Dickerson RR, Duncan BN, Edwards DP, Haynes JA, Henze DK, Houyoux MR, 2013. Emissions estimation from satellite retrievals: A review of current capability. Atmos Env 77:1011-42. DOI: https://doi.org/10.1016/j.atmosenv.2013.05.051
Texas Department of State Health Services, 2020. DSHS Announces First Case of COVID-19 in Texas. Texas Health and Human Services March 4. Available from: https://www.dshs.texas.gov/news/releases/2020/20200304.aspx
Texas Department of State Health Services, 2021. Texas COVID-19 Data. Texas Health and Human Services updated daily. Available from: https://dshs.texas.gov/coronavirus/additionaldata.aspx
U.S. Environmental Protection Agency, 2018. 2014 National Emissions Inventory Report. Available from: https://www.epa.gov/air-emissions-inventories/2014-national-emissions-inventory-nei-data#doc
Wang S, Zhang Q, Streets D, He K, Martin R, Lamsal L, Chen D, Lei Y, Lu Z, 2012. Growth in NO x emissions from power plants in China: bottom-up estimates and satellite observations. Atmos Chem Phys 12:4429-47. DOI: https://doi.org/10.5194/acp-12-4429-2012

How to Cite

Atkinson, S. F., Kala, A. K., & Tiwari, C. (2022). Cascading effects of COVID-19 on population mobility and air quality: An exploration including place characteristics using geovisualization. Geospatial Health, 17(s1). https://doi.org/10.4081/gh.2022.1056

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