{"id":"https://openalex.org/W2090048619","doi":"https://doi.org/10.1186/s12911-014-0108-4","title":"A Bayesian spatio\u2013temporal approach for real\u2013time detection of disease outbreaks: a case study","display_name":"A Bayesian spatio\u2013temporal approach for real\u2013time detection of disease outbreaks: a case study","publication_year":2014,"publication_date":"2014-12-01","ids":{"openalex":"https://openalex.org/W2090048619","doi":"https://doi.org/10.1186/s12911-014-0108-4","mag":"2090048619","pmid":"https://pubmed.ncbi.nlm.nih.gov/25476843"},"language":"en","primary_location":{"id":"doi:10.1186/s12911-014-0108-4","is_oa":true,"landing_page_url":"https://doi.org/10.1186/s12911-014-0108-4","pdf_url":"https://bmcmedinformdecismak.biomedcentral.com/counter/pdf/10.1186/s12911-014-0108-4","source":{"id":"https://openalex.org/S107516304","display_name":"BMC Medical Informatics and Decision Making","issn_l":"1472-6947","issn":["1472-6947"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310320256","host_organization_name":"BioMed Central","host_organization_lineage":["https://openalex.org/P4310320256","https://openalex.org/P4310319965"],"host_organization_lineage_names":["BioMed Central","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"BMC Medical Informatics and Decision Making","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj","pubmed"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://bmcmedinformdecismak.biomedcentral.com/counter/pdf/10.1186/s12911-014-0108-4","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5025574128","display_name":"Jian Zou","orcid":"https://orcid.org/0000-0002-7023-7949"},"institutions":[{"id":"https://openalex.org/I107077323","display_name":"Worcester Polytechnic Institute","ror":"https://ror.org/05ejpqr48","country_code":"US","type":"education","lineage":["https://openalex.org/I107077323"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Jian Zou","raw_affiliation_strings":["Worcester Polytechnic Institute, Worcester, USA. jzou@wpi.edu","Worcester Polytechnic Institute, Worcester, USA#TAB#"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Worcester Polytechnic Institute, Worcester, USA. jzou@wpi.edu","institution_ids":["https://openalex.org/I107077323"]},{"raw_affiliation_string":"Worcester Polytechnic Institute, Worcester, USA#TAB#","institution_ids":["https://openalex.org/I107077323"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5052821984","display_name":"Alan F. Karr","orcid":"https://orcid.org/0000-0002-7253-0129"},"institutions":[{"id":"https://openalex.org/I180297670","display_name":"RTI International","ror":"https://ror.org/052tfza37","country_code":"US","type":"funder","lineage":["https://openalex.org/I180297670"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Alan F Karr","raw_affiliation_strings":["RTI International, Research Triangle Park, USA. karr@rti.org","RTI International, Research Triangle Park , USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"RTI International, Research Triangle Park, USA. karr@rti.org","institution_ids":["https://openalex.org/I180297670"]},{"raw_affiliation_string":"RTI International, Research Triangle Park , USA","institution_ids":["https://openalex.org/I180297670"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5053927473","display_name":"Gauri Sankar Datta","orcid":"https://orcid.org/0009-0006-6340-8865"},"institutions":[{"id":"https://openalex.org/I165733156","display_name":"University of Georgia","ror":"https://ror.org/00te3t702","country_code":"US","type":"education","lineage":["https://openalex.org/I165733156"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Gauri Datta","raw_affiliation_strings":["University of Georgia, Athens, USA. gauri@stat.uga.edu","UNIVERSITY OF GEORGIA ATHENS USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Georgia, Athens, USA. gauri@stat.uga.edu","institution_ids":["https://openalex.org/I165733156"]},{"raw_affiliation_string":"UNIVERSITY OF GEORGIA ATHENS USA","institution_ids":["https://openalex.org/I165733156"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5034239230","display_name":"James Lynch","orcid":null},"institutions":[{"id":"https://openalex.org/I155781252","display_name":"University of South Carolina","ror":"https://ror.org/02b6qw903","country_code":"US","type":"education","lineage":["https://openalex.org/I155781252"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"James Lynch","raw_affiliation_strings":["University of South Carolina, Columbia, USA. lynch@stat.sc.edu","University of South Carolina-Columbia, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of South Carolina, Columbia, USA. lynch@stat.sc.edu","institution_ids":["https://openalex.org/I155781252"]},{"raw_affiliation_string":"University of South Carolina-Columbia, USA","institution_ids":["https://openalex.org/I155781252"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5053301712","display_name":"Shaun J. Grannis","orcid":"https://orcid.org/0000-0002-8093-6639"},"institutions":[{"id":"https://openalex.org/I1324682000","display_name":"Regenstrief Institute","ror":"https://ror.org/05f2ywb48","country_code":"US","type":"nonprofit","lineage":["https://openalex.org/I1324682000"]},{"id":"https://openalex.org/I55769427","display_name":"Indiana University \u2013 Purdue University Indianapolis","ror":"https://ror.org/05gxnyn08","country_code":"US","type":"education","lineage":["https://openalex.org/I55769427","https://openalex.org/I592451"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Shaun Grannis","raw_affiliation_strings":["Indiana University, Indianapolis, USA. sgrannis@regenstrief.org","Indiana University - Indianapolis, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Indiana University, Indianapolis, USA. sgrannis@regenstrief.org","institution_ids":["https://openalex.org/I1324682000","https://openalex.org/I55769427"]},{"raw_affiliation_string":"Indiana University - Indianapolis, USA","institution_ids":["https://openalex.org/I55769427"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5025574128"],"corresponding_institution_ids":["https://openalex.org/I107077323"],"apc_list":{"value":1570,"currency":"GBP","value_usd":2690},"apc_paid":{"value":1570,"currency":"GBP","value_usd":2690},"fwci":0.4065,"has_fulltext":true,"cited_by_count":12,"citation_normalized_percentile":{"value":0.65023673,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":97},"biblio":{"volume":"14","issue":"1","first_page":"108","last_page":"108"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11819","display_name":"Data-Driven Disease Surveillance","score":0.987500011920929,"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"}},"topics":[{"id":"https://openalex.org/T11819","display_name":"Data-Driven Disease Surveillance","score":0.987500011920929,"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/T10410","display_name":"COVID-19 epidemiological studies","score":0.004699999932199717,"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/T10243","display_name":"Statistical Methods and Bayesian Inference","score":0.0007999999797903001,"subfield":{"id":"https://openalex.org/subfields/2613","display_name":"Statistics and Probability"},"field":{"id":"https://openalex.org/fields/26","display_name":"Mathematics"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.700085461139679},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.5958108901977539},{"id":"https://openalex.org/keywords/context","display_name":"Context (archaeology)","score":0.5379176139831543},{"id":"https://openalex.org/keywords/public-health","display_name":"Public health","score":0.5327380299568176},{"id":"https://openalex.org/keywords/health-informatics","display_name":"Health informatics","score":0.5310573577880859},{"id":"https://openalex.org/keywords/disease-surveillance","display_name":"Disease surveillance","score":0.5095019936561584},{"id":"https://openalex.org/keywords/data-science","display_name":"Data science","score":0.4916735291481018},{"id":"https://openalex.org/keywords/public-health-surveillance","display_name":"Public health surveillance","score":0.4821140766143799},{"id":"https://openalex.org/keywords/bayesian-probability","display_name":"Bayesian probability","score":0.44863101840019226},{"id":"https://openalex.org/keywords/situation-awareness","display_name":"Situation awareness","score":0.4471040368080139},{"id":"https://openalex.org/keywords/false-positive-paradox","display_name":"False positive paradox","score":0.4285949170589447},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.34118473529815674},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.332768052816391},{"id":"https://openalex.org/keywords/medicine","display_name":"Medicine","score":0.1954367458820343},{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.1435421109199524}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.700085461139679},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.5958108901977539},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.5379176139831543},{"id":"https://openalex.org/C138816342","wikidata":"https://www.wikidata.org/wiki/Q189603","display_name":"Public health","level":2,"score":0.5327380299568176},{"id":"https://openalex.org/C145642194","wikidata":"https://www.wikidata.org/wiki/Q870895","display_name":"Health informatics","level":3,"score":0.5310573577880859},{"id":"https://openalex.org/C2776480101","wikidata":"https://www.wikidata.org/wiki/Q3555250","display_name":"Disease surveillance","level":3,"score":0.5095019936561584},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.4916735291481018},{"id":"https://openalex.org/C2776361769","wikidata":"https://www.wikidata.org/wiki/Q821775","display_name":"Public health surveillance","level":3,"score":0.4821140766143799},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.44863101840019226},{"id":"https://openalex.org/C145804949","wikidata":"https://www.wikidata.org/wiki/Q478123","display_name":"Situation awareness","level":2,"score":0.4471040368080139},{"id":"https://openalex.org/C64869954","wikidata":"https://www.wikidata.org/wiki/Q1859747","display_name":"False positive paradox","level":2,"score":0.4285949170589447},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.34118473529815674},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.332768052816391},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.1954367458820343},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.1435421109199524},{"id":"https://openalex.org/C146978453","wikidata":"https://www.wikidata.org/wiki/Q3798668","display_name":"Aerospace engineering","level":1,"score":0.0},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.0},{"id":"https://openalex.org/C166957645","wikidata":"https://www.wikidata.org/wiki/Q23498","display_name":"Archaeology","level":1,"score":0.0},{"id":"https://openalex.org/C159110408","wikidata":"https://www.wikidata.org/wiki/Q121176","display_name":"Nursing","level":1,"score":0.0}],"mesh":[{"descriptor_ui":"D001499","descriptor_name":"Bayes Theorem","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D001499","descriptor_name":"Bayes Theorem","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D001499","descriptor_name":"Bayes Theorem","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D004196","descriptor_name":"Disease Outbreaks","qualifier_ui":"Q000706","qualifier_name":"statistics & numerical data","is_major_topic":false},{"descriptor_ui":"D004196","descriptor_name":"Disease Outbreaks","qualifier_ui":"Q000706","qualifier_name":"statistics & numerical data","is_major_topic":false},{"descriptor_ui":"D004196","descriptor_name":"Disease Outbreaks","qualifier_ui":"Q000706","qualifier_name":"statistics & numerical data","is_major_topic":false},{"descriptor_ui":"D004636","descriptor_name":"Emergency Service, Hospital","qualifier_ui":"Q000706","qualifier_name":"statistics & numerical data","is_major_topic":false},{"descriptor_ui":"D004636","descriptor_name":"Emergency Service, Hospital","qualifier_ui":"Q000706","qualifier_name":"statistics & numerical data","is_major_topic":false},{"descriptor_ui":"D004636","descriptor_name":"Emergency Service, Hospital","qualifier_ui":"Q000706","qualifier_name":"statistics & numerical data","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":"D007196","descriptor_name":"Indiana","qualifier_ui":"Q000453","qualifier_name":"epidemiology","is_major_topic":false},{"descriptor_ui":"D007196","descriptor_name":"Indiana","qualifier_ui":"Q000453","qualifier_name":"epidemiology","is_major_topic":false},{"descriptor_ui":"D007196","descriptor_name":"Indiana","qualifier_ui":"Q000453","qualifier_name":"epidemiology","is_major_topic":false},{"descriptor_ui":"D007251","descriptor_name":"Influenza, Human","qualifier_ui":"Q000453","qualifier_name":"epidemiology","is_major_topic":false},{"descriptor_ui":"D007251","descriptor_name":"Influenza, Human","qualifier_ui":"Q000453","qualifier_name":"epidemiology","is_major_topic":false},{"descriptor_ui":"D007251","descriptor_name":"Influenza, Human","qualifier_ui":"Q000453","qualifier_name":"epidemiology","is_major_topic":false},{"descriptor_ui":"D008390","descriptor_name":"Markov Chains","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D008390","descriptor_name":"Markov Chains","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D008390","descriptor_name":"Markov Chains","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D008954","descriptor_name":"Models, Biological","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D008954","descriptor_name":"Models, Biological","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D008954","descriptor_name":"Models, Biological","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D011159","descriptor_name":"Population Surveillance","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":false},{"descriptor_ui":"D011159","descriptor_name":"Population Surveillance","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":false},{"descriptor_ui":"D011159","descriptor_name":"Population Surveillance","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":false},{"descriptor_ui":"D012140","descriptor_name":"Respiratory Tract Diseases","qualifier_ui":"Q000453","qualifier_name":"epidemiology","is_major_topic":false},{"descriptor_ui":"D012140","descriptor_name":"Respiratory Tract Diseases","qualifier_ui":"Q000453","qualifier_name":"epidemiology","is_major_topic":false},{"descriptor_ui":"D012140","descriptor_name":"Respiratory Tract Diseases","qualifier_ui":"Q000453","qualifier_name":"epidemiology","is_major_topic":false},{"descriptor_ui":"D016011","descriptor_name":"Normal Distribution","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D016011","descriptor_name":"Normal Distribution","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D016011","descriptor_name":"Normal Distribution","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D019982","descriptor_name":"Organizational Case Studies","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D019982","descriptor_name":"Organizational Case Studies","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D019982","descriptor_name":"Organizational Case Studies","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":true},{"descriptor_ui":"D062211","descriptor_name":"Spatio-Temporal Analysis","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D062211","descriptor_name":"Spatio-Temporal Analysis","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true}],"locations_count":3,"locations":[{"id":"doi:10.1186/s12911-014-0108-4","is_oa":true,"landing_page_url":"https://doi.org/10.1186/s12911-014-0108-4","pdf_url":"https://bmcmedinformdecismak.biomedcentral.com/counter/pdf/10.1186/s12911-014-0108-4","source":{"id":"https://openalex.org/S107516304","display_name":"BMC Medical Informatics and Decision Making","issn_l":"1472-6947","issn":["1472-6947"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310320256","host_organization_name":"BioMed Central","host_organization_lineage":["https://openalex.org/P4310320256","https://openalex.org/P4310319965"],"host_organization_lineage_names":["BioMed Central","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"BMC Medical Informatics and Decision Making","raw_type":"journal-article"},{"id":"pmid:25476843","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/25476843","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":"BMC medical informatics and decision making","raw_type":null},{"id":"pmh:oai:europepmc.org:3236870","is_oa":true,"landing_page_url":"https://www.ncbi.nlm.nih.gov/pmc/articles/4267748","pdf_url":null,"source":{"id":"https://openalex.org/S4306400806","display_name":"Europe PMC (PubMed Central)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1303153112","host_organization_name":"European Bioinformatics Institute","host_organization_lineage":["https://openalex.org/I1303153112"],"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":null,"raw_type":"Text"}],"best_oa_location":{"id":"doi:10.1186/s12911-014-0108-4","is_oa":true,"landing_page_url":"https://doi.org/10.1186/s12911-014-0108-4","pdf_url":"https://bmcmedinformdecismak.biomedcentral.com/counter/pdf/10.1186/s12911-014-0108-4","source":{"id":"https://openalex.org/S107516304","display_name":"BMC Medical Informatics and Decision Making","issn_l":"1472-6947","issn":["1472-6947"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310320256","host_organization_name":"BioMed Central","host_organization_lineage":["https://openalex.org/P4310320256","https://openalex.org/P4310319965"],"host_organization_lineage_names":["BioMed Central","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"BMC Medical Informatics and Decision Making","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G1309536167","display_name":"Collaborative Research for Developing ATD: Bayesian Methods in Syndromic Surveillance: CAR Models and Computational Implementation","funder_award_id":"0914603","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G1658258532","display_name":"Recurrent Events, Dynamic Reliability Systems, and Multiple Decision-Making with High-Dimensional Data","funder_award_id":"1106435","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G4737663369","display_name":"Statistical and Applied Mathematical Sciences Institute","funder_award_id":"0112069","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G5854856288","display_name":"Collaborative Research for Developing ATD: Bayesian Methods in Syndromic Surveillance: CAR Models and Computational Implementation","funder_award_id":"0914921","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G7845798442","display_name":null,"funder_award_id":"H98230","funder_id":"https://openalex.org/F4320311089","funder_display_name":"National Security Agency"}],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"},{"id":"https://openalex.org/F4320310010","display_name":"University of Georgia","ror":"https://ror.org/00te3t702"},{"id":"https://openalex.org/F4320310846","display_name":"University of South Carolina","ror":"https://ror.org/02b6qw903"},{"id":"https://openalex.org/F4320311089","display_name":"National Security Agency","ror":"https://ror.org/0047bvr32"},{"id":"https://openalex.org/F4320332468","display_name":"South Carolina Research Foundation, University of South Carolina","ror":"https://ror.org/02b6qw903"},{"id":"https://openalex.org/F4320333321","display_name":"University of Georgia Research Foundation","ror":null},{"id":"https://openalex.org/F4320337380","display_name":"Division of Mathematical Sciences","ror":"https://ror.org/051fftw81"}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2090048619.pdf","grobid_xml":"https://content.openalex.org/works/W2090048619.grobid-xml"},"referenced_works_count":24,"referenced_works":["https://openalex.org/W98698602","https://openalex.org/W118288330","https://openalex.org/W2002151188","https://openalex.org/W2028500805","https://openalex.org/W2031913033","https://openalex.org/W2035258045","https://openalex.org/W2039307858","https://openalex.org/W2051903196","https://openalex.org/W2077750777","https://openalex.org/W2077754282","https://openalex.org/W2087913418","https://openalex.org/W2118754020","https://openalex.org/W2138199368","https://openalex.org/W2146071514","https://openalex.org/W2146226171","https://openalex.org/W2150963718","https://openalex.org/W2152614795","https://openalex.org/W2166022262","https://openalex.org/W2166931027","https://openalex.org/W2477834368","https://openalex.org/W2798058877","https://openalex.org/W4241956284","https://openalex.org/W4256264211","https://openalex.org/W4302331569"],"related_works":["https://openalex.org/W57672338","https://openalex.org/W1536524154","https://openalex.org/W4297265718","https://openalex.org/W2947258557","https://openalex.org/W1680731157","https://openalex.org/W2125523620","https://openalex.org/W4285217346","https://openalex.org/W2619149464","https://openalex.org/W2085827856","https://openalex.org/W2104923010"],"abstract_inverted_index":{"BACKGROUND:":[0],"For":[1],"researchers":[2],"and":[3,28,31,95,123,141,168,176,193,249,286,300],"public":[4,163,196,293],"health":[5,164,197,290,305],"agencies,":[6],"the":[7,32,39,42,77,105,130,143,146,153,212,231,253,289,292],"complexity":[8],"of":[9,44,88,104,138,145,204,226,234,291],"high-dimensional":[10],"spatio-temporal":[11,157,250],"data":[12,74,131,166,238],"in":[13,41,129,162,179,252],"surveillance":[14,165,237,302],"for":[15,57,92,229,304],"large":[16],"reporting":[17],"networks":[18],"presents":[19],"numerous":[20],"challenges,":[21],"which":[22],"include":[23],"low":[24],"signal-to-noise":[25],"ratios,":[26],"spatial":[27],"temporal":[29],"dependencies,":[30],"need":[33,283],"to":[34,38,72,120,172,195,207,217,261,272,284],"characterize":[35],"uncertainties.":[36],"Central":[37],"problem":[40],"context":[43],"disease":[45],"outbreaks":[46,178],"is":[47],"a":[48,66,73,180,258,278,297],"decision":[49,205],"structure":[50],"that":[51,126,152,159,169,187],"requires":[52],"trading":[53],"off":[54],"false":[55,219],"positives":[56],"delayed":[58],"detections.":[59],"METHODS:":[60],"In":[61],"this":[62],"paper":[63],"we":[64,256,269],"apply":[65],"previously":[67],"developed":[68],"Bayesian":[69,279],"hierarchical":[70],"model":[71,154,190,213],"set":[75],"from":[76,211],"Indiana":[78],"Public":[79],"Health":[80],"Emergency":[81],"Surveillance":[82],"System":[83],"(PHESS)":[84],"containing":[85],"three":[86],"years":[87],"emergency":[89],"department":[90],"visits":[91],"influenza-like":[93],"illness":[94],"respiratory":[96],"illness.":[97],"Among":[98],"issues":[99,233,275],"requiring":[100],"attention":[101],"were":[102],"selection":[103],"underlying":[106],"network":[107],"(Too":[108],"few":[109],"nodes":[110,117],"attenuate":[111],"important":[112,135],"structure,":[113],"while":[114],"too":[115],"many":[116],"impose":[118],"barriers":[119],"both":[121,174],"modeling":[122,136],"computation.);":[124],"ensuring":[125],"confidentiality":[127],"protections":[128],"do":[132],"not":[133],"impede":[134],"day":[137],"week":[139],"effects;":[140],"evaluating":[142],"performance":[144],"model.":[147],"RESULTS:":[148],"Our":[149],"results":[150],"show":[151,208],"captures":[155],"salient":[156],"dynamics":[158,251],"are":[160,240,270],"present":[161,185],"sets,":[167],"it":[170],"appears":[171],"detect":[173],"\"annual\"":[175],"\"atypical\"":[177],"timely,":[181],"accurate":[182],"manner.":[183],"We":[184,199,242],"maps":[186],"help":[188],"make":[189],"output":[191,210],"accessible":[192],"comprehensible":[194],"authorities.":[198],"use":[200],"an":[201],"illustrative":[202],"family":[203],"rules":[206],"how":[209],"can":[214,243],"be":[215],"used":[216],"inform":[218],"positive-delayed":[220],"detection":[221],"tradeoffs.":[222],"CONCLUSIONS:":[223],"The":[224,281],"advantages":[225],"our":[227,295],"methodology":[228,296],"addressing":[230],"complicated":[232],"real":[235],"world":[236],"applications":[239],"three-fold.":[241],"easily":[244],"incorporate":[245],"additional":[246],"covariate":[247],"information":[248],"data.":[254],"Second,":[255],"furnish":[257],"unified":[259],"framework":[260],"provide":[262],"uncertainties":[263],"associated":[264],"with":[265],"each":[266],"parameter.":[267],"Third,":[268],"able":[271],"handle":[273],"multiplicity":[274],"by":[276],"using":[277],"approach.":[280],"urgent":[282],"quickly":[285],"effectively":[287],"monitor":[288],"makes":[294],"potentially":[298],"plausible":[299],"useful":[301],"approach":[303],"professionals.":[306]},"counts_by_year":[{"year":2025,"cited_by_count":3},{"year":2022,"cited_by_count":1},{"year":2020,"cited_by_count":2},{"year":2019,"cited_by_count":2},{"year":2018,"cited_by_count":2},{"year":2016,"cited_by_count":2}],"updated_date":"2026-07-22T07:51:19.307946","created_date":"2025-10-10T00:00:00"}