Development and Evaluation of Surveillance System for Identifying Jail-Associated COVID-19 Cases in Minnesota, USA, 2022
Confinement facilities are high-risk settings for the spread of infectious disease, necessitating timely surveillance to inform public health action. To identify jail-associated COVID-19 cases from electronic laboratory reports maintained in the Minnesota Electronic Disease Surveillance System (MED...
| Main Authors: | , , , , , , , |
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| Format: | Article |
| Language: | English |
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Centers for Disease Control and Prevention
2024-04-01
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| Series: | Emerging Infectious Diseases |
| Subjects: | |
| Online Access: | https://wwwnc.cdc.gov/eid/article/30/13/23-0719_article |
| _version_ | 1797224490335207424 |
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| author | Leah J. Porter Erica Rapheal Rebecca Huebsch Tiana Bastian Trisha J. Robinson Hanna Chakoian Karen G. Martin Jennifer Zipprich |
| author_facet | Leah J. Porter Erica Rapheal Rebecca Huebsch Tiana Bastian Trisha J. Robinson Hanna Chakoian Karen G. Martin Jennifer Zipprich |
| author_sort | Leah J. Porter |
| collection | DOAJ |
| description |
Confinement facilities are high-risk settings for the spread of infectious disease, necessitating timely surveillance to inform public health action. To identify jail-associated COVID-19 cases from electronic laboratory reports maintained in the Minnesota Electronic Disease Surveillance System (MEDSS), Minnesota, USA, the Minnesota Department of Health developed a surveillance system that used keyword and address matching (KAM). The KAM system used a SAS program (SAS Institute Inc., https://www.sas.com) and an automated program within MEDSS to identify confinement keywords and addresses. To evaluate KAM, we matched jail booking data from the Minnesota Statewide Supervision System by full name and birthdate to the MEDSS records of adults with COVID-19 for 2022. The KAM system identified 2,212 cases in persons detained in jail; sensitivity was 92.40% and specificity was 99.95%. The success of KAM demonstrates its potential to be applied to other diseases and congregate-living settings for real-time surveillance without added reporting burden.
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| first_indexed | 2024-04-24T13:53:57Z |
| format | Article |
| id | doaj.art-b2c5fefb44354aa1a656156107f0e8fa |
| institution | Directory Open Access Journal |
| issn | 1080-6040 1080-6059 |
| language | English |
| last_indexed | 2024-04-24T13:53:57Z |
| publishDate | 2024-04-01 |
| publisher | Centers for Disease Control and Prevention |
| record_format | Article |
| series | Emerging Infectious Diseases |
| spelling | doaj.art-b2c5fefb44354aa1a656156107f0e8fa2024-04-04T00:34:35ZengCenters for Disease Control and PreventionEmerging Infectious Diseases1080-60401080-60592024-04-013013283510.3201/eid3013.230719Development and Evaluation of Surveillance System for Identifying Jail-Associated COVID-19 Cases in Minnesota, USA, 2022Leah J. PorterErica RaphealRebecca HuebschTiana BastianTrisha J. RobinsonHanna ChakoianKaren G. MartinJennifer Zipprich Confinement facilities are high-risk settings for the spread of infectious disease, necessitating timely surveillance to inform public health action. To identify jail-associated COVID-19 cases from electronic laboratory reports maintained in the Minnesota Electronic Disease Surveillance System (MEDSS), Minnesota, USA, the Minnesota Department of Health developed a surveillance system that used keyword and address matching (KAM). The KAM system used a SAS program (SAS Institute Inc., https://www.sas.com) and an automated program within MEDSS to identify confinement keywords and addresses. To evaluate KAM, we matched jail booking data from the Minnesota Statewide Supervision System by full name and birthdate to the MEDSS records of adults with COVID-19 for 2022. The KAM system identified 2,212 cases in persons detained in jail; sensitivity was 92.40% and specificity was 99.95%. The success of KAM demonstrates its potential to be applied to other diseases and congregate-living settings for real-time surveillance without added reporting burden. https://wwwnc.cdc.gov/eid/article/30/13/23-0719_articleCOVID-192019 novel coronavirus diseasecoronavirus diseasesevere acute respiratory syndrome coronavirus 2SARS-CoV-2viruses |
| spellingShingle | Leah J. Porter Erica Rapheal Rebecca Huebsch Tiana Bastian Trisha J. Robinson Hanna Chakoian Karen G. Martin Jennifer Zipprich Development and Evaluation of Surveillance System for Identifying Jail-Associated COVID-19 Cases in Minnesota, USA, 2022 Emerging Infectious Diseases COVID-19 2019 novel coronavirus disease coronavirus disease severe acute respiratory syndrome coronavirus 2 SARS-CoV-2 viruses |
| title | Development and Evaluation of Surveillance System for Identifying Jail-Associated COVID-19 Cases in Minnesota, USA, 2022 |
| title_full | Development and Evaluation of Surveillance System for Identifying Jail-Associated COVID-19 Cases in Minnesota, USA, 2022 |
| title_fullStr | Development and Evaluation of Surveillance System for Identifying Jail-Associated COVID-19 Cases in Minnesota, USA, 2022 |
| title_full_unstemmed | Development and Evaluation of Surveillance System for Identifying Jail-Associated COVID-19 Cases in Minnesota, USA, 2022 |
| title_short | Development and Evaluation of Surveillance System for Identifying Jail-Associated COVID-19 Cases in Minnesota, USA, 2022 |
| title_sort | development and evaluation of surveillance system for identifying jail associated covid 19 cases in minnesota usa 2022 |
| topic | COVID-19 2019 novel coronavirus disease coronavirus disease severe acute respiratory syndrome coronavirus 2 SARS-CoV-2 viruses |
| url | https://wwwnc.cdc.gov/eid/article/30/13/23-0719_article |
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