{"id":"https://openalex.org/W4309651455","doi":"https://doi.org/10.1145/3557915.3560993","title":"Reviving the economy while saving lives","display_name":"Reviving the economy while saving lives","publication_year":2022,"publication_date":"2022-11-01","ids":{"openalex":"https://openalex.org/W4309651455","doi":"https://doi.org/10.1145/3557915.3560993"},"language":"en","primary_location":{"id":"doi:10.1145/3557915.3560993","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3557915.3560993","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3557915.3560993","source":{"id":"https://openalex.org/S4363608995","display_name":"Proceedings of the 30th International Conference on Advances in Geographic Information Systems","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 30th International Conference on Advances in Geographic Information Systems","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"hybrid","oa_url":"https://dl.acm.org/doi/pdf/10.1145/3557915.3560993","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5101472243","display_name":"Tao Feng","orcid":"https://orcid.org/0000-0002-7341-0225"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Tao Feng","raw_affiliation_strings":["Tsinghua University, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5034129532","display_name":"Huandong Wang","orcid":"https://orcid.org/0000-0002-6382-0861"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Huandong Wang","raw_affiliation_strings":["Tsinghua University, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5103169022","display_name":"Xiaochen Fan","orcid":"https://orcid.org/0000-0001-8945-3046"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiaochen Fan","raw_affiliation_strings":["Tsinghua University, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5040747504","display_name":"Xia Tong","orcid":"https://orcid.org/0000-0002-6994-6318"},"institutions":[{"id":"https://openalex.org/I241749","display_name":"University of Cambridge","ror":"https://ror.org/013meh722","country_code":"GB","type":"education","lineage":["https://openalex.org/I241749"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Tong Xia","raw_affiliation_strings":["University of Cambridge, Cambridge, United Kingdom"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Cambridge, Cambridge, United Kingdom","institution_ids":["https://openalex.org/I241749"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100355277","display_name":"Yong Li","orcid":"https://orcid.org/0000-0001-5617-1659"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yong Li","raw_affiliation_strings":["Tsinghua University, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":true,"cited_by_count":1,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"12"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10410","display_name":"COVID-19 epidemiological studies","score":0.9991000294685364,"subfield":{"id":"https://openalex.org/subfields/2611","display_name":"Modeling and Simulation"},"field":{"id":"https://openalex.org/fields/26","display_name":"Mathematics"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10410","display_name":"COVID-19 epidemiological studies","score":0.9991000294685364,"subfield":{"id":"https://openalex.org/subfields/2611","display_name":"Modeling and Simulation"},"field":{"id":"https://openalex.org/fields/26","display_name":"Mathematics"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11519","display_name":"Digital Mental Health Interventions","score":0.9355999827384949,"subfield":{"id":"https://openalex.org/subfields/3202","display_name":"Applied Psychology"},"field":{"id":"https://openalex.org/fields/32","display_name":"Psychology"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T10168","display_name":"COVID-19 and Mental Health","score":0.9240999817848206,"subfield":{"id":"https://openalex.org/subfields/3203","display_name":"Clinical Psychology"},"field":{"id":"https://openalex.org/fields/32","display_name":"Psychology"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5782788395881653},{"id":"https://openalex.org/keywords/scalability","display_name":"Scalability","score":0.4184889495372772},{"id":"https://openalex.org/keywords/business","display_name":"Business","score":0.36085695028305054},{"id":"https://openalex.org/keywords/risk-analysis","display_name":"Risk analysis (engineering)","score":0.3566271662712097}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5782788395881653},{"id":"https://openalex.org/C48044578","wikidata":"https://www.wikidata.org/wiki/Q727490","display_name":"Scalability","level":2,"score":0.4184889495372772},{"id":"https://openalex.org/C144133560","wikidata":"https://www.wikidata.org/wiki/Q4830453","display_name":"Business","level":0,"score":0.36085695028305054},{"id":"https://openalex.org/C112930515","wikidata":"https://www.wikidata.org/wiki/Q4389547","display_name":"Risk analysis (engineering)","level":1,"score":0.3566271662712097},{"id":"https://openalex.org/C77088390","wikidata":"https://www.wikidata.org/wiki/Q8513","display_name":"Database","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3557915.3560993","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3557915.3560993","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3557915.3560993","source":{"id":"https://openalex.org/S4363608995","display_name":"Proceedings of the 30th International Conference on Advances in Geographic Information Systems","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 30th International Conference on Advances in Geographic Information Systems","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.1145/3557915.3560993","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3557915.3560993","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3557915.3560993","source":{"id":"https://openalex.org/S4363608995","display_name":"Proceedings of the 30th International Conference on Advances in Geographic Information Systems","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 30th International Conference on Advances in Geographic Information Systems","raw_type":"proceedings-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G3710896277","display_name":"\u79fb\u52a8\u7528\u6237\u65f6\u7a7a\u884c\u4e3a\u5efa\u6a21\u4e0e\u9884\u6d4b\u65b9\u6cd5\u7814\u7a76","funder_award_id":"61971267","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G3734416573","display_name":"\u79fb\u52a8\u7528\u6237App\u4f7f\u7528\u884c\u4e3a\u5efa\u6a21\u4e0e\u9884\u6d4b\u7814\u7a76","funder_award_id":"61972223","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G4872662616","display_name":null,"funder_award_id":"U1936217","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G7024251178","display_name":null,"funder_award_id":"2020AAA0106000","funder_id":"https://openalex.org/F4320335777","funder_display_name":"National Key Research and Development Program of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320335777","display_name":"National Key Research and Development Program of China","ror":null}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4309651455.pdf","grobid_xml":"https://content.openalex.org/works/W4309651455.grobid-xml"},"referenced_works_count":8,"referenced_works":["https://openalex.org/W2911286998","https://openalex.org/W2963963616","https://openalex.org/W3015740662","https://openalex.org/W3090021658","https://openalex.org/W3171599858","https://openalex.org/W4205242797","https://openalex.org/W4212816027","https://openalex.org/W4214563805"],"related_works":["https://openalex.org/W4391375266","https://openalex.org/W2748952813","https://openalex.org/W2390279801","https://openalex.org/W2358668433","https://openalex.org/W4396701345","https://openalex.org/W2376932109","https://openalex.org/W2001405890","https://openalex.org/W2389214306","https://openalex.org/W4396696052","https://openalex.org/W2382290278"],"abstract_inverted_index":{"With":[0],"the":[1,8,14,22,55,71,89,99,116,140,164,197,222,235,266],"gradual":[2],"improvements":[3],"in":[4,79,110,216,293],"COVID-19":[5],"metrics":[6],"and":[7,48,67,108,125,138,146,159,200,246,279],"accelerated":[9],"immunization":[10],"progress,":[11],"countries":[12],"around":[13],"world":[15],"have":[16],"began":[17],"to":[18,44,54,105,133,155,188,212,233,238],"focus":[19],"on":[20,121,218],"reviving":[21],"economy":[23],"while":[24],"continuously":[25],"strengthening":[26],"epidemic":[27,65,100,126,198],"control.":[28],"POInt-of-Interest":[29],"(POI)":[30],"reopening,":[31],"as":[32,85],"a":[33,41,61,111,157,170,183,207,229,281],"necessity":[34],"for":[35,176,290],"restoring":[36],"human":[37],"mobilities,":[38],"has":[39],"become":[40],"crucial":[42],"step":[43],"recouple":[45],"economic":[46,68,123,268,295],"recovery":[47,124],"public":[49],"health":[50],"management.":[51],"In":[52,70],"contrast":[53],"lock-down":[56],"policy,":[57],"POI":[58,82,90,119,178,201,283],"reopening":[59,83,91,113,120,284],"demands":[60],"dynamic":[62],"trade-off":[63],"between":[64],"interventions":[66],"costs.":[69],"urban":[72,96,192],"scenario,":[73],"there":[74,93],"exist":[75],"three":[76],"key":[77],"challenges":[78],"developing":[80],"effective":[81],"strategies":[84],"follows.":[86],"(1)":[87],"During":[88],"process,":[92,285],"are":[94,103,128,131,150],"multiple":[95],"factors":[97,193],"affecting":[98],"transmission,":[101],"which":[102,130,286],"difficult":[104,154],"simultaneously":[106],"incorporate":[107],"balance":[109],"single":[112],"strategy;":[114],"(2)":[115],"effects":[117],"of":[118,143,224,249],"both":[122],"control":[127],"long-term,":[129],"hard":[132],"capture":[134],"by":[135,264,270],"static":[136],"models;":[137],"(3)":[139],"dual":[141],"objectives":[142],"minimizing":[144],"infections":[145,245,278],"maintaining":[147],"POIs'":[148],"visits":[149],"conflicting,":[151],"making":[152],"it":[153],"achieve":[156],"flexible":[158,214],"scalable":[160],"trade-off.":[161],"To":[162],"tackle":[163],"above":[165],"challenges,":[166],"we":[167,181,205,227],"propose":[168],"Reopener,":[169],"deep":[171,209],"reinforcement":[172],"learning":[173],"(RL)":[174],"framework":[175],"smart":[177],"reopening.":[179],"First,":[180],"utilize":[182],"bipartite":[184],"graph":[185],"neural":[186],"network":[187,211],"automatically":[189],"encode":[190],"all":[191,258],"that":[194,255],"would":[195],"affect":[196],"prevention":[199],"visit":[202,247],"restriction.":[203],"Second,":[204],"employ":[206],"RL-based":[208],"policy":[210],"enable":[213],"updates":[215],"restrictions":[217],"POIs":[219],"along":[220],"with":[221,261],"trend":[223],"epidemic.":[225],"Third,":[226],"design":[228,292],"novel":[230],"reward":[231],"function":[232],"guide":[234],"RL":[236],"agent":[237],"learn":[239],"smartly,":[240],"thus":[241],"comprehensively":[242],"trading":[243],"off":[244],"sustainability":[248],"POIs.":[250],"Extensive":[251],"experimental":[252],"results":[253],"demonstrate":[254],"Reopener":[256,274],"outperforms":[257],"baseline":[259],"methods":[260],"remarkable":[262],"improvements,":[263],"reducing":[265],"overall":[267],"cost":[269],"at":[271],"least":[272],"6.42%.":[273],"can":[275],"effectively":[276],"suppress":[277],"support":[280],"phase-based":[282],"provides":[287],"valuable":[288],"insights":[289],"strategy":[291],"post-COVID-19":[294],"recovery.":[296]},"counts_by_year":[{"year":2024,"cited_by_count":1}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}
