Application of healthcare big data in active case finding of COVID-19 in Yinzhou district of Ningbo
During the prevention and control of the COVID-19 epidemic, identifying and controlling the source of infection has become one of the most important prevention and control measures to curb the epidemic in the absence of vaccines and specific therapeutic drugs. While actively taking traditional and comprehensive "early detection" measures, Yinzhou district implemented inter-departmental data sharing through the joint prevention and control mechanism. Relying on a healthcare big data platform that integrates the data from medical, disease control and non-health sectors, Yinzhou district innovatively explored the big data-driven COVID-19 case finding pattern with online suspected case screening and offline verification and disposal. Such effort has laid a solid foundation and gathered experience to conduct the dynamic and continuous surveillance and early warning for infectious disease outbreaks more effectively and efficiently in the future. This article introduces the exploration of this pattern in Yinzhou district and discusses the role of big data-driven disease surveillance in the prevention and control of infectious diseases.
| Medienart: |
E-Artikel |
|---|
| Erscheinungsjahr: |
2020 |
|---|---|
| Erschienen: |
2020 |
| Enthalten in: |
Zur Gesamtaufnahme - volume:41 |
|---|---|
| Enthalten in: |
Zhonghua liu xing bing xue za zhi = Zhonghua liuxingbingxue zazhi - 41(2020), 10 vom: 10. Okt., Seite 1611-1615 |
| Sprache: |
Chinesisch |
|---|
| Beteiligte Personen: |
Sun, Y X [VerfasserIn] |
|---|
| Links: |
|---|
| Themen: |
|---|
| Anmerkungen: |
Date Completed 17.12.2020 Date Revised 17.12.2020 published: Print Citation Status MEDLINE |
|---|
| doi: |
10.3760/cma.j.cn112338-20200608-00818 |
|---|
| funding: |
|
|---|---|
| Förderinstitution / Projekttitel: |
|
| PPN (Katalog-ID): |
NLM312311362 |
|---|
| LEADER | 01000naa a22002652 4500 | ||
|---|---|---|---|
| 001 | NLM312311362 | ||
| 003 | DE-627 | ||
| 005 | 20231225144138.0 | ||
| 007 | cr uuu---uuuuu | ||
| 008 | 231225s2020 xx |||||o 00| ||chi c | ||
| 024 | 7 | |a 10.3760/cma.j.cn112338-20200608-00818 |2 doi | |
| 028 | 5 | 2 | |a pubmed24n1041.xml |
| 035 | |a (DE-627)NLM312311362 | ||
| 035 | |a (NLM)32654429 | ||
| 040 | |a DE-627 |b ger |c DE-627 |e rakwb | ||
| 041 | |a chi | ||
| 100 | 1 | |a Sun, Y X |e verfasserin |4 aut | |
| 245 | 1 | 0 | |a Application of healthcare big data in active case finding of COVID-19 in Yinzhou district of Ningbo |
| 264 | 1 | |c 2020 | |
| 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 17.12.2020 | ||
| 500 | |a Date Revised 17.12.2020 | ||
| 500 | |a published: Print | ||
| 500 | |a Citation Status MEDLINE | ||
| 520 | |a During the prevention and control of the COVID-19 epidemic, identifying and controlling the source of infection has become one of the most important prevention and control measures to curb the epidemic in the absence of vaccines and specific therapeutic drugs. While actively taking traditional and comprehensive "early detection" measures, Yinzhou district implemented inter-departmental data sharing through the joint prevention and control mechanism. Relying on a healthcare big data platform that integrates the data from medical, disease control and non-health sectors, Yinzhou district innovatively explored the big data-driven COVID-19 case finding pattern with online suspected case screening and offline verification and disposal. Such effort has laid a solid foundation and gathered experience to conduct the dynamic and continuous surveillance and early warning for infectious disease outbreaks more effectively and efficiently in the future. This article introduces the exploration of this pattern in Yinzhou district and discusses the role of big data-driven disease surveillance in the prevention and control of infectious diseases | ||
| 650 | 4 | |a Journal Article | |
| 650 | 4 | |a Active case finding | |
| 650 | 4 | |a Big data | |
| 650 | 4 | |a COVID-19 | |
| 650 | 4 | |a Paradigm | |
| 700 | 1 | |a Lyu, J |e verfasserin |4 aut | |
| 700 | 1 | |a Shen, P |e verfasserin |4 aut | |
| 700 | 1 | |a Zhang, J Y |e verfasserin |4 aut | |
| 700 | 1 | |a Lu, P |e verfasserin |4 aut | |
| 700 | 1 | |a Huang, W Z |e verfasserin |4 aut | |
| 700 | 1 | |a Lin, H B |e verfasserin |4 aut | |
| 700 | 1 | |a Shui, L M |e verfasserin |4 aut | |
| 700 | 1 | |a Li, L M |e verfasserin |4 aut | |
| 773 | 0 | 8 | |i Enthalten in |t Zhonghua liu xing bing xue za zhi = Zhonghua liuxingbingxue zazhi |d 1993 |g 41(2020), 10 vom: 10. Okt., Seite 1611-1615 |w (DE-627)NLM012811793 |x 0254-6450 |7 nnns |
| 773 | 1 | 8 | |g volume:41 |g year:2020 |g number:10 |g day:10 |g month:10 |g pages:1611-1615 |
| 856 | 4 | 0 | |u http://dx.doi.org/10.3760/cma.j.cn112338-20200608-00818 |3 Volltext |
| 912 | |a GBV_USEFLAG_A | ||
| 912 | |a GBV_NLM | ||
| 951 | |a AR | ||
| 952 | |d 41 |j 2020 |e 10 |b 10 |c 10 |h 1611-1615 | ||