{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,11,5]],"date-time":"2026-11-05T19:30:19Z","timestamp":1793907019663,"version":"4.8.0"},"reference-count":37,"publisher":"National Academy of Sciences","issue":"33","license":[{"start":{"date-parts":[[2022,8,8]],"date-time":"2022-08-08T00:00:00Z","timestamp":1659916800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc-nd\/4.0\/"}],"funder":[{"DOI":"10.13039\/100000001","name":"National Science Foundation","doi-asserted-by":"publisher","award":["2047488"],"award-info":[{"award-number":["2047488"]}],"id":[{"id":"10.13039\/100000001","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000001","name":"National Science Foundation","doi-asserted-by":"publisher","award":["2027744"],"award-info":[{"award-number":["2027744"]}],"id":[{"id":"10.13039\/100000001","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000001","name":"National Science Foundation","doi-asserted-by":"publisher","award":["2125326"],"award-info":[{"award-number":["2125326"]}],"id":[{"id":"10.13039\/100000001","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["www.pnas.org"],"crossmark-restriction":true},"short-container-title":["Proc. Natl. Acad. Sci. U.S.A."],"published-print":{"date-parts":[[2022,8,16]]},"abstract":"<jats:p>A common feature of large-scale extreme events, such as pandemics, wildfires, and major storms is that, despite their differences in etiology and duration, they significantly change routine human movement patterns. Such changes, which can be major or minor in size and duration and which differ across contexts, affect both the consequences of the events and the ability of governments to mount effective responses. Based on naturally tracked, anonymized mobility behavior from over 90 million people in the United States, we document these mobility differences in space and over time in six large-scale crises, including wildfires, major tropical storms, winter freeze and pandemics. We introduce a model that effectively captures the high-dimensional heterogeneity in human mobility changes following large-scale extreme events. Across five different metrics and regardless of spatial resolution, the changes in human mobility behavior exhibit a consistent hyperbolic decline, a pattern we characterize as \u201cspatiotemporal decay.\u201d When applied to the case of COVID-19, our model also uncovers significant disparities in mobility changes\u2014individuals from wealthy areas not only reduce their mobility at higher rates at the start of the pandemic but also maintain the change longer. Residents from lower-income regions show a faster and greater hyperbolic decay, which we suggest may help account for different COVID-19 rates. Our model represents a powerful tool to understand and forecast mobility patterns post emergency, and thus to help produce more effective responses.<\/jats:p>","DOI":"10.1073\/pnas.2203042119","type":"journal-article","created":{"date-parts":[[2022,8,8]],"date-time":"2022-08-08T15:16:07Z","timestamp":1659971767000},"update-policy":"https:\/\/doi.org\/10.1073\/pnas.cm10313","source":"Crossref","is-referenced-by-count":67,"title":["A spatiotemporal decay model of human mobility when facing large-scale crises"],"prefix":"10.1073","volume":"119","author":[{"given":"Weiyu","family":"Li","sequence":"first","affiliation":[{"name":"School of Mathematical Sciences, Suzhou University of Science and Technology, Suzhou 215009, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Qi","family":"Wang","sequence":"additional","affiliation":[{"name":"Department of Civil and Environmental Engineering, Northeastern University, Boston, MA 02115"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0756-5496","authenticated-orcid":false,"given":"Yuanyuan","family":"Liu","sequence":"additional","affiliation":[{"name":"Lally School of Management, Rensselaer Polytechnic Institute, Troy, NY 12180"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0601-1045","authenticated-orcid":false,"given":"Mario L.","family":"Small","sequence":"additional","affiliation":[{"name":"Department of Sociology, Columbia University, New York, NY 10027"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3952-208X","authenticated-orcid":false,"given":"Jianxi","family":"Gao","sequence":"additional","affiliation":[{"name":"Department of Computer Science and NEST Center, Rensselaer Polytechnic Institute, Troy, NY 12180"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"341","published-online":{"date-parts":[[2022,8,8]]},"reference":[{"key":"e_1_3_4_1_2","doi-asserted-by":"publisher","DOI":"10.1371\/journal.pone.0131469"},{"key":"e_1_3_4_2_2","doi-asserted-by":"publisher","DOI":"10.1038\/nature04292"},{"key":"e_1_3_4_3_2","doi-asserted-by":"publisher","DOI":"10.1098\/rsif.2014.1128"},{"key":"e_1_3_4_4_2","doi-asserted-by":"publisher","DOI":"10.1126\/science.1177170"},{"key":"e_1_3_4_5_2","doi-asserted-by":"publisher","DOI":"10.1038\/nphys1760"},{"key":"e_1_3_4_6_2","doi-asserted-by":"publisher","DOI":"10.1371\/journal.pone.0037027"},{"key":"e_1_3_4_7_2","doi-asserted-by":"publisher","DOI":"10.1140\/epjds\/s13688-017-0129-1"},{"key":"e_1_3_4_8_2","doi-asserted-by":"publisher","DOI":"10.1098\/rsif.2014.0834"},{"key":"e_1_3_4_9_2","doi-asserted-by":"crossref","unstructured":"E. Cho S. A. Myers J. Leskovec \u201cFriendship and mobility: User movement in location-based social networks\u201d in Proceedings of the 17th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (ACM 2011) pp. 1082\u20131090. 10.1145\/2020408.2020579.","DOI":"10.1145\/2020408.2020579"},{"key":"e_1_3_4_10_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.physa.2011.11.035"},{"key":"e_1_3_4_11_2","doi-asserted-by":"publisher","DOI":"10.1098\/rsif.2013.0246"},{"key":"e_1_3_4_12_2","doi-asserted-by":"publisher","DOI":"10.1371\/journal.pone.0017680"},{"key":"e_1_3_4_13_2","doi-asserted-by":"crossref","unstructured":"C. M. Schneider C. Rudloff D. Bauer M. C. Gonz\u00e1lez \u201cDaily travel behavior: Lessons from a week-long survey for the extraction of human mobility motifs related information\u201d in Proceedings of the 2nd ACM SIGKDD International Workshop on Urban Computing (ACM 2013) pp. 1\u20137.","DOI":"10.1145\/2505821.2505829"},{"key":"e_1_3_4_14_2","doi-asserted-by":"publisher","DOI":"10.1088\/1751-8113\/41\/22\/224015"},{"key":"e_1_3_4_15_2","doi-asserted-by":"publisher","DOI":"10.1371\/journal.pone.0081153"},{"key":"e_1_3_4_16_2","doi-asserted-by":"publisher","DOI":"10.1371\/journal.pmed.1001083"},{"key":"e_1_3_4_17_2","doi-asserted-by":"publisher","DOI":"10.1371\/journal.pcbi.1009865"},{"key":"e_1_3_4_18_2","doi-asserted-by":"publisher","DOI":"10.1038\/s41467-019-10063-w"},{"key":"e_1_3_4_19_2","doi-asserted-by":"publisher","DOI":"10.1057\/s41599-021-00824-8"},{"key":"e_1_3_4_20_2","doi-asserted-by":"publisher","DOI":"10.1016\/S0140-6736(20)30460-8"},{"key":"e_1_3_4_21_2","doi-asserted-by":"publisher","DOI":"10.1126\/science.abb7885"},{"key":"e_1_3_4_22_2","doi-asserted-by":"publisher","DOI":"10.1136\/bmj.m1379"},{"key":"e_1_3_4_23_2","doi-asserted-by":"publisher","DOI":"10.1177\/0020764020927047"},{"key":"e_1_3_4_24_2","doi-asserted-by":"publisher","DOI":"10.1038\/s41586-020-2923-3"},{"key":"e_1_3_4_25_2","doi-asserted-by":"publisher","DOI":"10.1002\/oby.22940"},{"key":"e_1_3_4_26_2","doi-asserted-by":"publisher","DOI":"10.1038\/s41597-020-00734-5"},{"key":"e_1_3_4_27_2","doi-asserted-by":"publisher","DOI":"10.1073\/pnas.2009412117"},{"key":"e_1_3_4_28_2","doi-asserted-by":"publisher","DOI":"10.1038\/nature06958"},{"key":"e_1_3_4_29_2","doi-asserted-by":"publisher","DOI":"10.1038\/s41586-020-2909-1"},{"key":"e_1_3_4_30_2","doi-asserted-by":"publisher","DOI":"10.1038\/s41586-021-03480-9"},{"key":"e_1_3_4_31_2","doi-asserted-by":"crossref","unstructured":"D. Wang \u201cHuman mobility social ties and link prediction\u201d in Proceedings of the 17th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (ACM 2011) pp. 1100\u20131108.","DOI":"10.1145\/2020408.2020581"},{"key":"e_1_3_4_32_2","first-page":"004912411985238","article-title":"The social integration of American cities: Network measures of connectedness based on everyday mobility across neighborhoods","volume":"50","author":"Phillips N. E.","year":"2019","unstructured":"N. E. Phillips, B. L. Levy, R. J. Sampson, M. L. Small, R. Q. Wang, The social integration of American cities: Network measures of connectedness based on everyday mobility across neighborhoods. Sociol. Methods Res. 50, 004912411985238 (2019).","journal-title":"Sociol. Methods Res."},{"key":"e_1_3_4_33_2","doi-asserted-by":"crossref","unstructured":"J. Gao Y. Yin B. F. Jones D. Wang Quantifying policy responses to a global emergency: Insights from the COVID-19 pandemic (2020). https:\/\/papers.ssrn.com\/abstract=3634820. 10.2139\/ssrn.3634820.","DOI":"10.2139\/ssrn.3634820"},{"key":"e_1_3_4_34_2","doi-asserted-by":"publisher","DOI":"10.1073\/pnas.1802537115"},{"key":"e_1_3_4_35_2","doi-asserted-by":"publisher","DOI":"10.1901\/jeab.2006.85-05"},{"key":"e_1_3_4_36_2","doi-asserted-by":"publisher","DOI":"10.1037\/0033-2909.130.5.769"},{"key":"e_1_3_4_37_2","doi-asserted-by":"publisher","DOI":"10.1901\/jeab.1999.71-27"}],"container-title":["Proceedings of the National Academy of Sciences"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/pnas.org\/doi\/pdf\/10.1073\/pnas.2203042119","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,8,8]],"date-time":"2022-08-08T15:18:00Z","timestamp":1659971880000},"score":1,"resource":{"primary":{"URL":"https:\/\/pnas.org\/doi\/full\/10.1073\/pnas.2203042119"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,8,8]]},"references-count":37,"journal-issue":{"issue":"33","published-print":{"date-parts":[[2022,8,16]]}},"alternative-id":["10.1073\/pnas.2203042119"],"URL":"https:\/\/doi.org\/10.1073\/pnas.2203042119","relation":{},"ISSN":["0027-8424","1091-6490"],"issn-type":[{"value":"0027-8424","type":"print"},{"value":"1091-6490","type":"electronic"}],"subject":[],"published":{"date-parts":[[2022,8,8]]},"assertion":[{"value":"2022-02-18","order":0,"name":"received","label":"Received","group":{"name":"publication_history","label":"Publication History"}},{"value":"2022-06-15","order":1,"name":"accepted","label":"Accepted","group":{"name":"publication_history","label":"Publication History"}},{"value":"2022-08-08","order":2,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}],"article-number":"e2203042119"}}