A Dual Index Machine Learning Framework Integrating Structural Vulnerability and Human Mobility for Dynamic Pandemic Risk Assessment

A Dual Index Machine Learning Framework Integrating Structural Vulnerability and Human Mobility for Dynamic Pandemic Risk Assessment | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article A Dual Index Machine Learning Framework Integrating Structural Vulnerability and Human Mobility for Dynamic Pandemic Risk Assessment Jian Xu, Ming-Hsiang Tsou, Atsushi Nara, Trisalyn Nelson, Susan Cassels This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8267220/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 10 You are reading this latest preprint version Abstract The COVID-19 pandemic has highlighted the urgent need for spatially and temporally precise tools to assess community vulnerability and inform equitable public health responses. This study proposes a dual-index framework that integrates structural and mobility risk factors to support dynamic pandemic modeling. We first construct the Pandemic Responsive Vulnerability Index (PRVI) using 53 sociodemographic variables from the American Community Survey (ACS), weighted by their empirical correlation with COVID-19 case rates in San Diego County. Building on this static foundation, we develop the Dynamic Pandemic-Responsive Index of Spatio-temporal Mobility and Vulnerability (D-PRISM) by incorporating lagged mobility metrics derived from SafeGraph data into a Random Forest predictive model. The model can accurately capture spatial patterns and localized outbreaks across dynamic temporal windows that static index alone fails to detect. The PRVI and D-PRISM serve complementary functions: PRVI profiles long-term structural vulnerability, while D-PRISM enables real-time risk detection. Together, they offer a scalable and transferable approach to modeling pandemic risk. The framework can be applied beyond COVID-19 to other infectious diseases or pandemics that show spatio-temporal dynamics. By using divergent high-resolution data, machine learning, this work advances the field of precision public health and provides insights for targeted interventions. pandemic vulnerability COVID-19 human mobility dynamic index machine learning precision public health Full Text Additional Declarations No competing interests reported. Cite Share Download PDF Status: Under Review Version 1 posted Editorial decision: Revision requested 24 Feb, 2026 Reviews received at journal 24 Feb, 2026 Reviews received at journal 05 Feb, 2026 Reviewers agreed at journal 03 Feb, 2026 Reviewers agreed at journal 21 Jan, 2026 Reviewers invited by journal 16 Jan, 2026 Editor invited by journal 16 Jan, 2026 Editor assigned by journal 02 Jan, 2026 Submission checks completed at journal 31 Dec, 2025 First submitted to journal 31 Dec, 2025 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-8267220","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":577064186,"identity":"15e2111d-1c21-438b-9002-c43934c23607","order_by":0,"name":"Jian Xu","email":"","orcid":"","institution":"San Diego State University","correspondingAuthor":false,"prefix":"","firstName":"Jian","middleName":"","lastName":"Xu","suffix":""},{"id":577064187,"identity":"fe55e7e8-b1c6-4fbe-bb68-5dacd4031f83","order_by":1,"name":"Ming-Hsiang Tsou","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAoklEQVRIiWNgGAWjYNCCCgbGBhDNQ5RqNhBxhmQtjG2kaNGd3/7wMe+8Otn5MxIYH7xtI0KL2TEeY2PebYeNN9xIYDacS6QWNmnebQcSN0gkABnEaWF/Js07py4R6DD230RqYTCT5m1gTmy4kcDGTKSWHGPDOceAfjnzsFlyzjlitBw+/vDBmxpgiLUnH/zwpowILUgAEjWjYBSMglEwCqgBANMgNYjpMDtfAAAAAElFTkSuQmCC","orcid":"","institution":"San Diego State University","correspondingAuthor":true,"prefix":"","firstName":"Ming-Hsiang","middleName":"","lastName":"Tsou","suffix":""},{"id":577064188,"identity":"d9d67b23-8362-47ed-99fd-aec977415e59","order_by":2,"name":"Atsushi Nara","email":"","orcid":"","institution":"San Diego State University","correspondingAuthor":false,"prefix":"","firstName":"Atsushi","middleName":"","lastName":"Nara","suffix":""},{"id":577064189,"identity":"89fd95b6-169a-4d6c-8450-ce6dfd3d61c8","order_by":3,"name":"Trisalyn Nelson","email":"","orcid":"","institution":"University of California, Santa Barbara","correspondingAuthor":false,"prefix":"","firstName":"Trisalyn","middleName":"","lastName":"Nelson","suffix":""},{"id":577064190,"identity":"73f0e4d0-bc23-4b82-8a53-3d0b3789f1fd","order_by":4,"name":"Susan Cassels","email":"","orcid":"","institution":"University of California, Santa Barbara","correspondingAuthor":false,"prefix":"","firstName":"Susan","middleName":"","lastName":"Cassels","suffix":""}],"badges":[],"createdAt":"2025-12-03 07:38:17","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-8267220/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-8267220/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":100732072,"identity":"705e5188-733a-4a89-b47e-8ac3cf785c33","added_by":"auto","created_at":"2026-01-20 21:41:23","extension":"docx","order_by":0,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":2405317,"visible":true,"origin":"","legend":"","description":"","filename":"dualindexmanuscriptrevise2.docx","url":"https://assets-eu.researchsquare.com/files/rs-8267220/v1/589ea02a323c08a1c3318e10.docx"},{"id":100732586,"identity":"bddb3b2f-6496-45a4-8955-780233228f9f","added_by":"auto","created_at":"2026-01-20 21:48:39","extension":"json","order_by":1,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":6954,"visible":true,"origin":"","legend":"","description":"","filename":"09baf5bd350b4dd28c2b2b6bf3a0524d.json","url":"https://assets-eu.researchsquare.com/files/rs-8267220/v1/9887b81df05995423951a1ba.json"},{"id":100732233,"identity":"45d350d2-fb0a-4c86-9bc1-64ebcb5c1f66","added_by":"auto","created_at":"2026-01-20 21:44:43","extension":"xml","order_by":2,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":121651,"visible":true,"origin":"","legend":"","description":"","filename":"09baf5bd350b4dd28c2b2b6bf3a0524d1enriched.xml","url":"https://assets-eu.researchsquare.com/files/rs-8267220/v1/03f6f30b7c51b39d0eaa3b90.xml"},{"id":100732590,"identity":"c4750c3b-993d-4843-aef3-43537dc139f1","added_by":"auto","created_at":"2026-01-20 21:48:41","extension":"png","order_by":3,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":51305,"visible":true,"origin":"","legend":"","description":"","filename":"floatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-8267220/v1/fbde57281990d34e984ca5dd.png"},{"id":100732229,"identity":"0e1bf12f-2d4b-42d3-a0cd-482509fe8b3a","added_by":"auto","created_at":"2026-01-20 21:44:42","extension":"png","order_by":4,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":384912,"visible":true,"origin":"","legend":"","description":"","filename":"floatimage2.png","url":"https://assets-eu.researchsquare.com/files/rs-8267220/v1/b8415009b4e6f275940f516c.png"},{"id":100732246,"identity":"c1f54f39-2ba3-4cbf-add6-7be67b0aebae","added_by":"auto","created_at":"2026-01-20 21:45:01","extension":"png","order_by":5,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":61744,"visible":true,"origin":"","legend":"","description":"","filename":"floatimage3.png","url":"https://assets-eu.researchsquare.com/files/rs-8267220/v1/c9a661f843d9647ea5ebe4d2.png"},{"id":100732294,"identity":"35ead578-4284-4a8e-860e-a83f038800b6","added_by":"auto","created_at":"2026-01-20 21:45:36","extension":"jpeg","order_by":6,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":344518,"visible":true,"origin":"","legend":"","description":"","filename":"floatimage4.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-8267220/v1/b8ca45b62681d98a5791fe9f.jpeg"},{"id":100732625,"identity":"21287f92-c2e1-4be2-9bef-b596326435b3","added_by":"auto","created_at":"2026-01-20 21:49:29","extension":"png","order_by":7,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":143593,"visible":true,"origin":"","legend":"","description":"","filename":"floatimage5.png","url":"https://assets-eu.researchsquare.com/files/rs-8267220/v1/746648337990e96a295cf58e.png"},{"id":100732589,"identity":"610ddd41-2567-4747-897e-2251197730e1","added_by":"auto","created_at":"2026-01-20 21:48:40","extension":"png","order_by":8,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":62738,"visible":true,"origin":"","legend":"","description":"","filename":"floatimage6.png","url":"https://assets-eu.researchsquare.com/files/rs-8267220/v1/80558bd8507b1e21ebfbb6ea.png"},{"id":100732301,"identity":"08977672-23c6-48af-9854-793671be4bec","added_by":"auto","created_at":"2026-01-20 21:45:39","extension":"png","order_by":9,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":63048,"visible":true,"origin":"","legend":"","description":"","filename":"floatimage7.png","url":"https://assets-eu.researchsquare.com/files/rs-8267220/v1/1a95b8e69a01f9580af7d33f.png"},{"id":100732232,"identity":"6fdb1738-9f12-4658-a20d-183365a068cb","added_by":"auto","created_at":"2026-01-20 21:44:43","extension":"png","order_by":10,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":1025472,"visible":true,"origin":"","legend":"","description":"","filename":"floatimage8.png","url":"https://assets-eu.researchsquare.com/files/rs-8267220/v1/5f477f370d96409ebbabe724.png"},{"id":100732228,"identity":"b44d54f2-4229-46d9-8e2d-a4ef92569710","added_by":"auto","created_at":"2026-01-20 21:44:36","extension":"jpeg","order_by":11,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":1027277,"visible":true,"origin":"","legend":"","description":"","filename":"floatimage9.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-8267220/v1/72cce4593afe4e2ebe673eb1.jpeg"},{"id":100732305,"identity":"fc531979-081a-4582-a8d8-238afefa6fa1","added_by":"auto","created_at":"2026-01-20 21:45:42","extension":"png","order_by":12,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":13342,"visible":true,"origin":"","legend":"","description":"","filename":"Onlinefloatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-8267220/v1/12d50c5a98a3a0fa8e5f68f6.png"},{"id":100732375,"identity":"7a43d917-e240-4461-a8cf-45f790954855","added_by":"auto","created_at":"2026-01-20 21:46:56","extension":"png","order_by":13,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":70590,"visible":true,"origin":"","legend":"","description":"","filename":"Onlinefloatimage2.png","url":"https://assets-eu.researchsquare.com/files/rs-8267220/v1/5f17249e3b1a32ff0502c947.png"},{"id":100732094,"identity":"f39ea15e-0d23-4bb8-af74-dd0f41f385ce","added_by":"auto","created_at":"2026-01-20 21:42:06","extension":"png","order_by":14,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":13282,"visible":true,"origin":"","legend":"","description":"","filename":"Onlinefloatimage3.png","url":"https://assets-eu.researchsquare.com/files/rs-8267220/v1/91d56d2c05db758447d02513.png"},{"id":100732241,"identity":"e3e172a0-4b61-4b17-b278-f958c83817e3","added_by":"auto","created_at":"2026-01-20 21:44:56","extension":"png","order_by":15,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":68704,"visible":true,"origin":"","legend":"","description":"","filename":"Onlinefloatimage4.png","url":"https://assets-eu.researchsquare.com/files/rs-8267220/v1/62e8fc8b5d5bdfd306becd79.png"},{"id":100732287,"identity":"6d2515a4-1203-49eb-9d25-0fe275f82e37","added_by":"auto","created_at":"2026-01-20 21:45:23","extension":"png","order_by":16,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":34342,"visible":true,"origin":"","legend":"","description":"","filename":"Onlinefloatimage5.png","url":"https://assets-eu.researchsquare.com/files/rs-8267220/v1/afec3750504592ee53f71a7e.png"},{"id":100732388,"identity":"c983142c-a153-4704-a46e-0d4b44069472","added_by":"auto","created_at":"2026-01-20 21:47:20","extension":"png","order_by":17,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":17559,"visible":true,"origin":"","legend":"","description":"","filename":"Onlinefloatimage6.png","url":"https://assets-eu.researchsquare.com/files/rs-8267220/v1/83becb39d7e2812c65f8cae2.png"},{"id":100732376,"identity":"958bbd23-518b-4e8c-93ed-69ccc112fc40","added_by":"auto","created_at":"2026-01-20 21:46:57","extension":"png","order_by":18,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":18170,"visible":true,"origin":"","legend":"","description":"","filename":"Onlinefloatimage7.png","url":"https://assets-eu.researchsquare.com/files/rs-8267220/v1/255f0554b207a02e37438a58.png"},{"id":100732288,"identity":"59e0d54b-0545-4a5e-a326-b8b71fe1238b","added_by":"auto","created_at":"2026-01-20 21:45:25","extension":"png","order_by":19,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":169631,"visible":true,"origin":"","legend":"","description":"","filename":"Onlinefloatimage8.png","url":"https://assets-eu.researchsquare.com/files/rs-8267220/v1/7dac8e6066ed1a149a6ddb56.png"},{"id":100732074,"identity":"bc4c966c-5a4f-44b4-a921-b43b73608d06","added_by":"auto","created_at":"2026-01-20 21:41:27","extension":"png","order_by":20,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":266981,"visible":true,"origin":"","legend":"","description":"","filename":"Onlinefloatimage9.png","url":"https://assets-eu.researchsquare.com/files/rs-8267220/v1/ec3f6e81faff35e83b56b0b0.png"},{"id":100732550,"identity":"cc1a4a1d-925a-4fe0-8dff-56ec579a0192","added_by":"auto","created_at":"2026-01-20 21:48:12","extension":"xml","order_by":21,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":118929,"visible":true,"origin":"","legend":"","description":"","filename":"09baf5bd350b4dd28c2b2b6bf3a0524d1structuring.xml","url":"https://assets-eu.researchsquare.com/files/rs-8267220/v1/68420182b410321b6a87672e.xml"},{"id":100732585,"identity":"7083e535-5daa-44ff-8920-d49509b3a574","added_by":"auto","created_at":"2026-01-20 21:48:39","extension":"html","order_by":22,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":133522,"visible":true,"origin":"","legend":"","description":"","filename":"earlyproof.html","url":"https://assets-eu.researchsquare.com/files/rs-8267220/v1/4a46481a32198c615b001933.html"},{"id":100734506,"identity":"974862f1-2177-48a1-b923-b575421f75da","added_by":"auto","created_at":"2026-01-20 22:13:29","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1287088,"visible":true,"origin":"","legend":"","description":"","filename":"dualindexmanuscriptrevise2.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8267220/v1_covered_03650bcb-2d9a-4a50-993b-e8d9264bd41b.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"A Dual Index Machine Learning Framework Integrating Structural Vulnerability and Human Mobility for Dynamic Pandemic Risk Assessment","fulltext":[],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":false,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":true,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":true,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"discover-artificial-intelligence","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"diai","sideBox":"Learn more about [Discover Artificial Intelligence](https://www.springer.com/44163)","snPcode":"","submissionUrl":"","title":"Discover Artificial Intelligence","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Discover Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"pandemic vulnerability, COVID-19; human mobility, dynamic index, machine learning, precision public health","lastPublishedDoi":"10.21203/rs.3.rs-8267220/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8267220/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eThe COVID-19 pandemic has highlighted the urgent need for spatially and temporally precise tools to assess community vulnerability and inform equitable public health responses. This study proposes a dual-index framework that integrates structural and mobility risk factors to support dynamic pandemic modeling. We first construct the Pandemic Responsive Vulnerability Index (PRVI) using 53 sociodemographic variables from the American Community Survey (ACS), weighted by their empirical correlation with COVID-19 case rates in San Diego County. Building on this static foundation, we develop the Dynamic Pandemic-Responsive Index of Spatio-temporal Mobility and Vulnerability (D-PRISM) by incorporating lagged mobility metrics derived from SafeGraph data into a Random Forest predictive model. The model can accurately capture spatial patterns and localized outbreaks across dynamic temporal windows that static index alone fails to detect. The PRVI and D-PRISM serve complementary functions: PRVI profiles long-term structural vulnerability, while D-PRISM enables real-time risk detection. Together, they offer a scalable and transferable approach to modeling pandemic risk. The framework can be applied beyond COVID-19 to other infectious diseases or pandemics that show spatio-temporal dynamics. By using divergent high-resolution data, machine learning, this work advances the field of precision public health and provides insights for targeted interventions.\u003c/p\u003e","manuscriptTitle":"A Dual Index Machine Learning Framework Integrating Structural Vulnerability and Human Mobility for Dynamic Pandemic Risk Assessment","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-01-20 19:49:34","doi":"10.21203/rs.3.rs-8267220/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2026-02-25T04:34:31+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-02-24T19:40:14+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-02-06T00:02:32+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"130741640978359846978081484407174701886","date":"2026-02-04T01:53:03+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"167170981909133620721618845774053377214","date":"2026-01-21T23:10:24+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2026-01-16T09:48:12+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2026-01-16T06:28:58+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2026-01-02T07:09:35+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-12-31T06:59:07+00:00","index":"","fulltext":""},{"type":"submitted","content":"Discover Artificial Intelligence","date":"2025-12-31T06:48:53+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"discover-artificial-intelligence","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"diai","sideBox":"Learn more about [Discover Artificial Intelligence](https://www.springer.com/44163)","snPcode":"","submissionUrl":"","title":"Discover Artificial Intelligence","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Discover Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"a8e1f7b8-263c-4921-85a9-c59d885ff06d","owner":[],"postedDate":"January 20th, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2026-03-11T09:09:39+00:00","versionOfRecord":[],"versionCreatedAt":"2026-01-20 19:49:34","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8267220","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8267220","identity":"rs-8267220","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}