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 (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.
Medienart: |
E-Artikel |
---|
Erscheinungsjahr: |
2024 |
---|---|
Erschienen: |
2024 |
Enthalten in: |
Zur Gesamtaufnahme - volume:30 |
---|---|
Enthalten in: |
Emerging infectious diseases - 30(2024), 13 vom: 01. Apr., Seite S28-S35 |
Sprache: |
Englisch |
---|
Beteiligte Personen: |
Porter, Leah J [VerfasserIn] |
---|
Links: |
---|
Anmerkungen: |
Date Completed 03.04.2024 Date Revised 04.04.2024 published: Print Citation Status MEDLINE |
---|
doi: |
10.3201/eid3013.230719 |
---|
funding: |
|
---|---|
Förderinstitution / Projekttitel: |
|
PPN (Katalog-ID): |
NLM370511409 |
---|
LEADER | 01000caa a22002652 4500 | ||
---|---|---|---|
001 | NLM370511409 | ||
003 | DE-627 | ||
005 | 20240404235305.0 | ||
007 | cr uuu---uuuuu | ||
008 | 240403s2024 xx |||||o 00| ||eng c | ||
024 | 7 | |a 10.3201/eid3013.230719 |2 doi | |
028 | 5 | 2 | |a pubmed24n1364.xml |
035 | |a (DE-627)NLM370511409 | ||
035 | |a (NLM)38561640 | ||
040 | |a DE-627 |b ger |c DE-627 |e rakwb | ||
041 | |a eng | ||
100 | 1 | |a Porter, Leah J |e verfasserin |4 aut | |
245 | 1 | 0 | |a Development and Evaluation of Surveillance System for Identifying Jail-Associated COVID-19 Cases in Minnesota, USA, 2022 |
264 | 1 | |c 2024 | |
336 | |a Text |b txt |2 rdacontent | ||
337 | |a ƒaComputermedien |b c |2 rdamedia | ||
338 | |a ƒa Online-Ressource |b cr |2 rdacarrier | ||
500 | |a Date Completed 03.04.2024 | ||
500 | |a Date Revised 04.04.2024 | ||
500 | |a published: Print | ||
500 | |a Citation Status MEDLINE | ||
520 | |a 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 | ||
650 | 4 | |a Journal Article | |
650 | 4 | |a 2019 novel coronavirus disease | |
650 | 4 | |a COVID-19 | |
650 | 4 | |a Minnesota | |
650 | 4 | |a SARS-CoV-2 | |
650 | 4 | |a United States | |
650 | 4 | |a coronavirus disease | |
650 | 4 | |a correctional facilities | |
650 | 4 | |a electronic health records | |
650 | 4 | |a electronic laboratory reports | |
650 | 4 | |a jails | |
650 | 4 | |a public health surveillance | |
650 | 4 | |a residential facilities | |
650 | 4 | |a respiratory infections | |
650 | 4 | |a severe acute respiratory syndrome coronavirus 2 | |
650 | 4 | |a viruses | |
650 | 4 | |a zoonoses | |
700 | 1 | |a Rapheal, Erica |e verfasserin |4 aut | |
700 | 1 | |a Huebsch, Rebecca |e verfasserin |4 aut | |
700 | 1 | |a Bastian, Tiana |e verfasserin |4 aut | |
700 | 1 | |a Robinson, Trisha J |e verfasserin |4 aut | |
700 | 1 | |a Chakoian, Hanna |e verfasserin |4 aut | |
700 | 1 | |a Martin, Karen G |e verfasserin |4 aut | |
700 | 1 | |a Zipprich, Jennifer |e verfasserin |4 aut | |
773 | 0 | 8 | |i Enthalten in |t Emerging infectious diseases |d 1995 |g 30(2024), 13 vom: 01. Apr., Seite S28-S35 |w (DE-627)NLM088704254 |x 1080-6059 |7 nnns |
773 | 1 | 8 | |g volume:30 |g year:2024 |g number:13 |g day:01 |g month:04 |g pages:S28-S35 |
856 | 4 | 0 | |u http://dx.doi.org/10.3201/eid3013.230719 |3 Volltext |
912 | |a GBV_USEFLAG_A | ||
912 | |a GBV_NLM | ||
951 | |a AR | ||
952 | |d 30 |j 2024 |e 13 |b 01 |c 04 |h S28-S35 |