{"id":"https://openalex.org/W4402978002","doi":"https://doi.org/10.1371/journal.pcbi.1012497","title":"Managing spatio-temporal heterogeneity of susceptibles by embedding it into an homogeneous model: A mechanistic and deep learning study","display_name":"Managing spatio-temporal heterogeneity of susceptibles by embedding it into an homogeneous model: A mechanistic and deep learning study","publication_year":2024,"publication_date":"2024-09-30","ids":{"openalex":"https://openalex.org/W4402978002","doi":"https://doi.org/10.1371/journal.pcbi.1012497","pmid":"https://pubmed.ncbi.nlm.nih.gov/39348420"},"language":"en","primary_location":{"id":"doi:10.1371/journal.pcbi.1012497","is_oa":true,"landing_page_url":"https://doi.org/10.1371/journal.pcbi.1012497","pdf_url":null,"source":{"id":"https://openalex.org/S86033158","display_name":"PLoS Computational Biology","issn_l":"1553-734X","issn":["1553-734X","1553-7358"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310315706","host_organization_name":"Public Library of Science","host_organization_lineage":["https://openalex.org/P4310315706"],"host_organization_lineage_names":["Public Library of Science"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"PLOS Computational Biology","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj","pubmed"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://doi.org/10.1371/journal.pcbi.1012497","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5022759446","display_name":"Biao Tang","orcid":"https://orcid.org/0000-0002-0418-5773"},"institutions":[{"id":"https://openalex.org/I87445476","display_name":"Xi'an Jiaotong University","ror":"https://ror.org/017zhmm22","country_code":"CN","type":"education","lineage":["https://openalex.org/I87445476"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Biao Tang","raw_affiliation_strings":["School of Mathematics and Statistics, Xi'an Jiaotong University, Xi'an, People's Republic of China","The Interdisciplinary Research Center for Mathematics and Life Sciences, Xi'an Jiaotong University, Xi'an, People's Republic of China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Mathematics and Statistics, Xi'an Jiaotong University, Xi'an, People's Republic of China","institution_ids":["https://openalex.org/I87445476"]},{"raw_affiliation_string":"The Interdisciplinary Research Center for Mathematics and Life Sciences, Xi'an Jiaotong University, Xi'an, People's Republic of China","institution_ids":["https://openalex.org/I87445476"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5111346849","display_name":"Kexin Ma","orcid":"https://orcid.org/0009-0002-7091-6383"},"institutions":[{"id":"https://openalex.org/I87445476","display_name":"Xi'an Jiaotong University","ror":"https://ror.org/017zhmm22","country_code":"CN","type":"education","lineage":["https://openalex.org/I87445476"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Kexin Ma","raw_affiliation_strings":["School of Mathematics and Statistics, Xi'an Jiaotong University, Xi'an, People's Republic of China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Mathematics and Statistics, Xi'an Jiaotong University, Xi'an, People's Republic of China","institution_ids":["https://openalex.org/I87445476"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5113902674","display_name":"Yan Liu","orcid":"https://orcid.org/0009-0004-7669-6996"},"institutions":[{"id":"https://openalex.org/I87445476","display_name":"Xi'an Jiaotong University","ror":"https://ror.org/017zhmm22","country_code":"CN","type":"education","lineage":["https://openalex.org/I87445476"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yan Liu","raw_affiliation_strings":["School of Mathematics and Statistics, Xi'an Jiaotong University, Xi'an, People's Republic of China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Mathematics and Statistics, Xi'an Jiaotong University, Xi'an, People's Republic of China","institution_ids":["https://openalex.org/I87445476"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100725506","display_name":"Wang Xia","orcid":"https://orcid.org/0000-0001-9317-4824"},"institutions":[{"id":"https://openalex.org/I88830068","display_name":"Shaanxi Normal University","ror":"https://ror.org/0170z8493","country_code":"CN","type":"education","lineage":["https://openalex.org/I88830068"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xia Wang","raw_affiliation_strings":["School of Mathematics and Statistics, Shaanxi Normal University, Xi'an, People's Republic of China"],"raw_orcid":"https://orcid.org/0000-0001-9317-4824","affiliations":[{"raw_affiliation_string":"School of Mathematics and Statistics, Shaanxi Normal University, Xi'an, People's Republic of China","institution_ids":["https://openalex.org/I88830068"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5041520845","display_name":"Sanyi Tang","orcid":"https://orcid.org/0000-0002-3324-746X"},"institutions":[{"id":"https://openalex.org/I88830068","display_name":"Shaanxi Normal University","ror":"https://ror.org/0170z8493","country_code":"CN","type":"education","lineage":["https://openalex.org/I88830068"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Sanyi Tang","raw_affiliation_strings":["School of Mathematics and Statistics, Shaanxi Normal University, Xi'an, People's Republic of China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Mathematics and Statistics, Shaanxi Normal University, Xi'an, People's Republic of China","institution_ids":["https://openalex.org/I88830068"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5022540617","display_name":"Yanni Xiao","orcid":"https://orcid.org/0000-0003-0432-7628"},"institutions":[{"id":"https://openalex.org/I87445476","display_name":"Xi'an Jiaotong University","ror":"https://ror.org/017zhmm22","country_code":"CN","type":"education","lineage":["https://openalex.org/I87445476"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yanni Xiao","raw_affiliation_strings":["School of Mathematics and Statistics, Xi'an Jiaotong University, Xi'an, People's Republic of China","The Interdisciplinary Research Center for Mathematics and Life Sciences, Xi'an Jiaotong University, Xi'an, People's Republic of China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Mathematics and Statistics, Xi'an Jiaotong University, Xi'an, People's Republic of China","institution_ids":["https://openalex.org/I87445476"]},{"raw_affiliation_string":"The Interdisciplinary Research Center for Mathematics and Life Sciences, Xi'an Jiaotong University, Xi'an, People's Republic of China","institution_ids":["https://openalex.org/I87445476"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5051694242","display_name":"Robert Cheke","orcid":"https://orcid.org/0000-0002-7437-1934"},"institutions":[{"id":"https://openalex.org/I348769827","display_name":"Public Health England","ror":"https://ror.org/00vbvha87","country_code":"GB","type":"government","lineage":["https://openalex.org/I1311074006","https://openalex.org/I348769827"]},{"id":"https://openalex.org/I4210162782","display_name":"Natural Resources Institute","ror":"https://ror.org/05t3n1398","country_code":"GB","type":"other","lineage":["https://openalex.org/I4210162782"]},{"id":"https://openalex.org/I47508984","display_name":"Imperial College London","ror":"https://ror.org/041kmwe10","country_code":"GB","type":"education","lineage":["https://openalex.org/I47508984"]},{"id":"https://openalex.org/I55060895","display_name":"University of Greenwich","ror":"https://ror.org/00bmj0a71","country_code":"GB","type":"education","lineage":["https://openalex.org/I55060895"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Robert A. Cheke","raw_affiliation_strings":["Department of Infectious Disease Epidemiology, Imperial College London, School of Public Health, White City Campus, London, United Kingdom","Natural Resources Institute, University of Greenwich at Medway, Central Avenue, Chatham Maritime, Kent, United Kingdom"],"raw_orcid":"https://orcid.org/0000-0002-7437-1934","affiliations":[{"raw_affiliation_string":"Department of Infectious Disease Epidemiology, Imperial College London, School of Public Health, White City Campus, London, United Kingdom","institution_ids":["https://openalex.org/I47508984","https://openalex.org/I348769827"]},{"raw_affiliation_string":"Natural Resources Institute, University of Greenwich at Medway, Central Avenue, Chatham Maritime, Kent, United Kingdom","institution_ids":["https://openalex.org/I55060895","https://openalex.org/I4210162782"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":7,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":{"value":2655,"currency":"USD","value_usd":2655},"apc_paid":{"value":2655,"currency":"USD","value_usd":2655},"fwci":1.0475,"has_fulltext":true,"cited_by_count":3,"citation_normalized_percentile":{"value":0.75123109,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":98},"biblio":{"volume":"20","issue":"9","first_page":"e1012497","last_page":"e1012497"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10410","display_name":"COVID-19 epidemiological studies","score":1.0,"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":1.0,"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/T10167","display_name":"Influenza Virus Research Studies","score":0.998199999332428,"subfield":{"id":"https://openalex.org/subfields/2713","display_name":"Epidemiology"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}},{"id":"https://openalex.org/T11581","display_name":"Viral Infections and Outbreaks Research","score":0.992900013923645,"subfield":{"id":"https://openalex.org/subfields/2725","display_name":"Infectious Diseases"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/homogeneous","display_name":"Homogeneous","score":0.6654587388038635},{"id":"https://openalex.org/keywords/herd-immunity","display_name":"Herd immunity","score":0.5621450543403625},{"id":"https://openalex.org/keywords/population","display_name":"Population","score":0.5491037368774414},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5142116546630859},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4633086025714874},{"id":"https://openalex.org/keywords/epidemic-model","display_name":"Epidemic model","score":0.4602760970592499},{"id":"https://openalex.org/keywords/econometrics","display_name":"Econometrics","score":0.3538384437561035},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3514277935028076},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.20364117622375488},{"id":"https://openalex.org/keywords/medicine","display_name":"Medicine","score":0.09321865439414978}],"concepts":[{"id":"https://openalex.org/C66882249","wikidata":"https://www.wikidata.org/wiki/Q169336","display_name":"Homogeneous","level":2,"score":0.6654587388038635},{"id":"https://openalex.org/C106192422","wikidata":"https://www.wikidata.org/wiki/Q736798","display_name":"Herd immunity","level":3,"score":0.5621450543403625},{"id":"https://openalex.org/C2908647359","wikidata":"https://www.wikidata.org/wiki/Q2625603","display_name":"Population","level":2,"score":0.5491037368774414},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5142116546630859},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4633086025714874},{"id":"https://openalex.org/C1627819","wikidata":"https://www.wikidata.org/wiki/Q2572354","display_name":"Epidemic model","level":3,"score":0.4602760970592499},{"id":"https://openalex.org/C149782125","wikidata":"https://www.wikidata.org/wiki/Q160039","display_name":"Econometrics","level":1,"score":0.3538384437561035},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3514277935028076},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.20364117622375488},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.09321865439414978},{"id":"https://openalex.org/C99454951","wikidata":"https://www.wikidata.org/wiki/Q932068","display_name":"Environmental health","level":1,"score":0.0},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.0}],"mesh":[{"descriptor_ui":"D000077321","descriptor_name":"Deep Learning","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D000077321","descriptor_name":"Deep Learning","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D000077321","descriptor_name":"Deep Learning","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D000077321","descriptor_name":"Deep Learning","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D000077321","descriptor_name":"Deep Learning","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D000086382","descriptor_name":"COVID-19","qualifier_ui":"Q000453","qualifier_name":"epidemiology","is_major_topic":true},{"descriptor_ui":"D000086382","descriptor_name":"COVID-19","qualifier_ui":"Q000453","qualifier_name":"epidemiology","is_major_topic":true},{"descriptor_ui":"D000086382","descriptor_name":"COVID-19","qualifier_ui":"Q000453","qualifier_name":"epidemiology","is_major_topic":true},{"descriptor_ui":"D000086382","descriptor_name":"COVID-19","qualifier_ui":"Q000453","qualifier_name":"epidemiology","is_major_topic":true},{"descriptor_ui":"D000086382","descriptor_name":"COVID-19","qualifier_ui":"Q000453","qualifier_name":"epidemiology","is_major_topic":true},{"descriptor_ui":"D000086382","descriptor_name":"COVID-19","qualifier_ui":"Q000821","qualifier_name":"virology","is_major_topic":true},{"descriptor_ui":"D000086382","descriptor_name":"COVID-19","qualifier_ui":"Q000821","qualifier_name":"virology","is_major_topic":true},{"descriptor_ui":"D000086382","descriptor_name":"COVID-19","qualifier_ui":"Q000821","qualifier_name":"virology","is_major_topic":true},{"descriptor_ui":"D000086382","descriptor_name":"COVID-19","qualifier_ui":"Q000821","qualifier_name":"virology","is_major_topic":true},{"descriptor_ui":"D000086382","descriptor_name":"COVID-19","qualifier_ui":"Q000821","qualifier_name":"virology","is_major_topic":true},{"descriptor_ui":"D000086402","descriptor_name":"SARS-CoV-2","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D000086402","descriptor_name":"SARS-CoV-2","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D000086402","descriptor_name":"SARS-CoV-2","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D000086402","descriptor_name":"SARS-CoV-2","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D000086402","descriptor_name":"SARS-CoV-2","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D000090005","descriptor_name":"Epidemiological Models","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D000090005","descriptor_name":"Epidemiological Models","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D000090005","descriptor_name":"Epidemiological Models","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D000090005","descriptor_name":"Epidemiological Models","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D000090005","descriptor_name":"Epidemiological Models","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D002681","descriptor_name":"China","qualifier_ui":"Q000453","qualifier_name":"epidemiology","is_major_topic":false},{"descriptor_ui":"D002681","descriptor_name":"China","qualifier_ui":"Q000453","qualifier_name":"epidemiology","is_major_topic":false},{"descriptor_ui":"D002681","descriptor_name":"China","qualifier_ui":"Q000453","qualifier_name":"epidemiology","is_major_topic":false},{"descriptor_ui":"D002681","descriptor_name":"China","qualifier_ui":"Q000453","qualifier_name":"epidemiology","is_major_topic":false},{"descriptor_ui":"D002681","descriptor_name":"China","qualifier_ui":"Q000453","qualifier_name":"epidemiology","is_major_topic":false},{"descriptor_ui":"D004198","descriptor_name":"Disease Susceptibility","qualifier_ui":"Q000453","qualifier_name":"epidemiology","is_major_topic":false},{"descriptor_ui":"D004198","descriptor_name":"Disease Susceptibility","qualifier_ui":"Q000453","qualifier_name":"epidemiology","is_major_topic":false},{"descriptor_ui":"D004198","descriptor_name":"Disease Susceptibility","qualifier_ui":"Q000453","qualifier_name":"epidemiology","is_major_topic":false},{"descriptor_ui":"D004198","descriptor_name":"Disease Susceptibility","qualifier_ui":"Q000453","qualifier_name":"epidemiology","is_major_topic":false},{"descriptor_ui":"D004198","descriptor_name":"Disease Susceptibility","qualifier_ui":"Q000453","qualifier_name":"epidemiology","is_major_topic":false},{"descriptor_ui":"D006801","descriptor_name":"Humans","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D006801","descriptor_name":"Humans","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D006801","descriptor_name":"Humans","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D006801","descriptor_name":"Humans","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D006801","descriptor_name":"Humans","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D016571","descriptor_name":"Neural Networks, Computer","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D016571","descriptor_name":"Neural Networks, Computer","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D016571","descriptor_name":"Neural Networks, Computer","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D016571","descriptor_name":"Neural Networks, Computer","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D016571","descriptor_name":"Neural Networks, Computer","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D019295","descriptor_name":"Computational Biology","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":true},{"descriptor_ui":"D019295","descriptor_name":"Computational Biology","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":true},{"descriptor_ui":"D019295","descriptor_name":"Computational Biology","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":true},{"descriptor_ui":"D019295","descriptor_name":"Computational Biology","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":true},{"descriptor_ui":"D019295","descriptor_name":"Computational Biology","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":true},{"descriptor_ui":"D062211","descriptor_name":"Spatio-Temporal Analysis","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D062211","descriptor_name":"Spatio-Temporal Analysis","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D062211","descriptor_name":"Spatio-Temporal Analysis","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D062211","descriptor_name":"Spatio-Temporal Analysis","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D062211","descriptor_name":"Spatio-Temporal Analysis","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false}],"locations_count":4,"locations":[{"id":"doi:10.1371/journal.pcbi.1012497","is_oa":true,"landing_page_url":"https://doi.org/10.1371/journal.pcbi.1012497","pdf_url":null,"source":{"id":"https://openalex.org/S86033158","display_name":"PLoS Computational Biology","issn_l":"1553-734X","issn":["1553-734X","1553-7358"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310315706","host_organization_name":"Public Library of Science","host_organization_lineage":["https://openalex.org/P4310315706"],"host_organization_lineage_names":["Public Library of Science"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"PLOS Computational Biology","raw_type":"journal-article"},{"id":"pmid:39348420","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/39348420","pdf_url":null,"source":{"id":"https://openalex.org/S4306525036","display_name":"PubMed","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"PLoS computational biology","raw_type":null},{"id":"pmh:oai:gala.gre.ac.uk:48297","is_oa":true,"landing_page_url":null,"pdf_url":"http://gala.gre.ac.uk/id/eprint/48297/7/48297%20CHEKE_Managing_Spatio-temporal_Heterogeneity_of_Susceptibles_by_Embedding_it_into_an_Homogeneous_Model_A_Mechanistic_and_Deep_Learning_Study_%28OA%29_2024.pdf","source":{"id":"https://openalex.org/S4306401244","display_name":"Greenwich Academic Literature Archive (University of Greenwich)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I55060895","host_organization_name":"University of Greenwich","host_organization_lineage":["https://openalex.org/I55060895"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"Article"},{"id":"pmh:oai:pubmedcentral.nih.gov:11476686","is_oa":true,"landing_page_url":"https://www.ncbi.nlm.nih.gov/pmc/articles/11476686","pdf_url":"https://pmc.ncbi.nlm.nih.gov/articles/PMC11476686/pdf/pcbi.1012497.pdf","source":{"id":"https://openalex.org/S2764455111","display_name":"PubMed Central","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"PLoS Comput Biol","raw_type":"Text"}],"best_oa_location":{"id":"doi:10.1371/journal.pcbi.1012497","is_oa":true,"landing_page_url":"https://doi.org/10.1371/journal.pcbi.1012497","pdf_url":null,"source":{"id":"https://openalex.org/S86033158","display_name":"PLoS Computational Biology","issn_l":"1553-734X","issn":["1553-734X","1553-7358"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310315706","host_organization_name":"Public Library of Science","host_organization_lineage":["https://openalex.org/P4310315706"],"host_organization_lineage_names":["Public Library of Science"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"PLOS Computational Biology","raw_type":"journal-article"},"sustainable_development_goals":[{"score":0.8299999833106995,"display_name":"Good health and well-being","id":"https://metadata.un.org/sdg/3"}],"awards":[{"id":"https://openalex.org/G148668811","display_name":null,"funder_award_id":"12031010","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G2938791190","display_name":null,"funder_award_id":"2022YFA1003704","funder_id":"https://openalex.org/F4320335777","funder_display_name":"National Key Research and Development Program of China"},{"id":"https://openalex.org/G3444962800","display_name":null,"funder_award_id":"12371502","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G3829970902","display_name":null,"funder_award_id":"12101488","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G8441189814","display_name":null,"funder_award_id":"12220101001","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation 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":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":52,"referenced_works":["https://openalex.org/W1570529436","https://openalex.org/W1587799944","https://openalex.org/W2010365240","https://openalex.org/W2024844031","https://openalex.org/W2027443119","https://openalex.org/W2069629287","https://openalex.org/W2071544114","https://openalex.org/W2072086516","https://openalex.org/W2073017712","https://openalex.org/W2089450265","https://openalex.org/W2094882464","https://openalex.org/W2102216674","https://openalex.org/W2123252019","https://openalex.org/W2133587230","https://openalex.org/W2139495090","https://openalex.org/W2144301074","https://openalex.org/W2148301044","https://openalex.org/W2155951261","https://openalex.org/W2163930085","https://openalex.org/W2171580218","https://openalex.org/W2539167814","https://openalex.org/W2898861634","https://openalex.org/W2899283552","https://openalex.org/W2962855412","https://openalex.org/W2999026783","https://openalex.org/W3000586685","https://openalex.org/W3003668884","https://openalex.org/W3007580879","https://openalex.org/W3008294222","https://openalex.org/W3009468976","https://openalex.org/W3031533743","https://openalex.org/W3045154200","https://openalex.org/W3093610264","https://openalex.org/W3152577110","https://openalex.org/W3175859364","https://openalex.org/W3205480029","https://openalex.org/W4220678683","https://openalex.org/W4221082445","https://openalex.org/W4224231998","https://openalex.org/W4224273004","https://openalex.org/W4225712666","https://openalex.org/W4285142983","https://openalex.org/W4293247424","https://openalex.org/W4316014100","https://openalex.org/W4318381729","https://openalex.org/W4321188363","https://openalex.org/W4323533424","https://openalex.org/W4323925175","https://openalex.org/W4366768931","https://openalex.org/W4367334335","https://openalex.org/W4382682956","https://openalex.org/W4394989333"],"related_works":["https://openalex.org/W33346620","https://openalex.org/W4205973155","https://openalex.org/W3132824026","https://openalex.org/W3083820245","https://openalex.org/W4293861032","https://openalex.org/W3211261050","https://openalex.org/W3135082321","https://openalex.org/W3157327618","https://openalex.org/W4361194392","https://openalex.org/W4385094157"],"abstract_inverted_index":{"Accurate":[0],"prediction":[1,175],"of":[2,13,38,120,133,147,150,154,164,195,226,230],"epidemics":[3],"is":[4],"pivotal":[5],"for":[6,10,50,74,123,193,223,235],"making":[7],"well-informed":[8],"decisions":[9],"the":[11,20,35,51,57,75,96,106,115,124,131,134,155,160,174,179,188,196,200,212,221,224],"control":[12],"infectious":[14],"diseases,":[15],"but":[16],"addressing":[17],"heterogeneity":[18,37,186],"in":[19,90,128,173,187],"system":[21],"poses":[22],"a":[23,30,46,62,71,80,85,145,227],"challenge.":[24],"In":[25],"this":[26,218],"study,":[27],"we":[28,69,113],"propose":[29],"novel":[31],"modelling":[32,236],"framework":[33],"integrating":[34],"spatio-temporal":[36],"susceptible":[39],"individuals":[40],"into":[41],"homogeneous":[42,161],"models,":[43],"by":[44],"introducing":[45],"continuous":[47],"recruitment":[48,58,76],"process":[49],"susceptibles.":[52],"A":[53],"neural":[54],"network":[55],"approximates":[56],"rate":[59,77,117,143],"to":[60,94,104,206],"develop":[61,79],"Universal":[63],"Differential":[64],"Equations":[65],"(UDE)":[66],"model.":[67,82],"Simultaneously,":[68],"pre-set":[70],"specific":[72],"form":[73],"and":[78,103,118,144,152,166,198,232],"mechanistic":[81,107],"Data":[83],"from":[84,203],"COVID":[86],"Omicron":[87,126],"variant":[88],"outbreak":[89,201],"Shanghai":[91],"are":[92],"used":[93],"train":[95],"UDE":[97],"model":[98,108],"using":[99,109],"deep":[100],"learning":[101],"methods":[102],"calibrate":[105],"MCMC":[110],"methods.":[111],"Subsequently,":[112],"project":[114],"attack":[116,142],"peak":[119,146],"new":[121,148,228,233],"infections":[122,149],"first":[125],"wave":[127],"China":[129],"after":[130],"adjustment":[132],"dynamic":[135],"zero-COVID":[136],"policy.":[137],"Our":[138,182],"projections":[139,163],"indicate":[140],"an":[141,170],"80.06%":[151],"3.17%":[153],"population,":[156],"respectively,":[157],"compared":[158],"with":[159,211],"model's":[162],"99.97%":[165],"32.78%,":[167],"thus":[168],"providing":[169],"18.6%":[171],"improvement":[172],"accuracy":[176],"based":[177],"on":[178],"actual":[180],"data.":[181],"simulations":[183],"demonstrate":[184],"that":[185,217],"susceptibles":[189],"decreases":[190],"herd":[191],"immunity":[192],"~37.36%":[194],"population":[197],"prolongs":[199],"period":[202],"~30":[204],"days":[205],"~70":[207],"days,":[208],"also":[209],"aligning":[210],"real":[213],"case.":[214],"We":[215],"consider":[216],"study":[219],"lays":[220],"groundwork":[222],"development":[225],"class":[229],"models":[231],"insights":[234],"heterogeneity.":[237]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":1}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}