Effectiveness of early warning systems in the detection of infectious diseases outbreaks: a systematic review.


Journal

BMC public health
ISSN: 1471-2458
Titre abrégé: BMC Public Health
Pays: England
ID NLM: 100968562

Informations de publication

Date de publication:
29 11 2022
Historique:
received: 22 09 2022
accepted: 14 11 2022
entrez: 29 11 2022
pubmed: 30 11 2022
medline: 2 12 2022
Statut: epublish

Résumé

Global pandemics have occurred with increasing frequency over the past decade reflecting the sub-optimum operationalization of surveillance systems handling human health data. Despite the wide array of current surveillance methods, their effectiveness varies with multiple factors. Here, we perform a systematic review of the effectiveness of alternative infectious diseases Early Warning Systems (EWSs) with a focus on the surveillance data collection methods, and taking into consideration feasibility in different settings. We searched PubMed and Scopus databases on 21 October 2022. Articles were included if they covered the implementation of an early warning system and evaluated infectious diseases outbreaks that had potential to become pandemics. Of 1669 studies screened, 68 were included in the final sample. We performed quality assessment using an adapted CASP Checklist. Of the 68 articles included, 42 articles found EWSs successfully functioned independently as surveillance systems for pandemic-wide infectious diseases outbreaks, and 16 studies reported EWSs to have contributing surveillance features through complementary roles. Chief complaints from emergency departments' data is an effective EWS but it requires standardized formats across hospitals. Centralized Public Health records-based EWSs facilitate information sharing; however, they rely on clinicians' reporting of cases. Facilitated reporting by remote health settings and rapid alarm transmission are key advantages of Web-based EWSs. Pharmaceutical sales and laboratory results did not prove solo effectiveness. The EWS design combining surveillance data from both health records and staff was very successful. Also, daily surveillance data notification was the most successful and accepted enhancement strategy especially during mass gathering events. Eventually, in Low Middle Income Countries, working to improve and enhance existing systems was more critical than implementing new Syndromic Surveillance approaches. Our study was able to evaluate the effectiveness of Early Warning Systems in different contexts and resource settings based on the EWSs' method of data collection. There is consistent evidence that EWSs compiling pre-diagnosis data are more proactive to detect outbreaks. However, the fact that Syndromic Surveillance Systems (SSS) are more proactive than diagnostic disease surveillance should not be taken as an effective clue for outbreaks detection.

Sections du résumé

BACKGROUND
Global pandemics have occurred with increasing frequency over the past decade reflecting the sub-optimum operationalization of surveillance systems handling human health data. Despite the wide array of current surveillance methods, their effectiveness varies with multiple factors. Here, we perform a systematic review of the effectiveness of alternative infectious diseases Early Warning Systems (EWSs) with a focus on the surveillance data collection methods, and taking into consideration feasibility in different settings.
METHODS
We searched PubMed and Scopus databases on 21 October 2022. Articles were included if they covered the implementation of an early warning system and evaluated infectious diseases outbreaks that had potential to become pandemics. Of 1669 studies screened, 68 were included in the final sample. We performed quality assessment using an adapted CASP Checklist.
RESULTS
Of the 68 articles included, 42 articles found EWSs successfully functioned independently as surveillance systems for pandemic-wide infectious diseases outbreaks, and 16 studies reported EWSs to have contributing surveillance features through complementary roles. Chief complaints from emergency departments' data is an effective EWS but it requires standardized formats across hospitals. Centralized Public Health records-based EWSs facilitate information sharing; however, they rely on clinicians' reporting of cases. Facilitated reporting by remote health settings and rapid alarm transmission are key advantages of Web-based EWSs. Pharmaceutical sales and laboratory results did not prove solo effectiveness. The EWS design combining surveillance data from both health records and staff was very successful. Also, daily surveillance data notification was the most successful and accepted enhancement strategy especially during mass gathering events. Eventually, in Low Middle Income Countries, working to improve and enhance existing systems was more critical than implementing new Syndromic Surveillance approaches.
CONCLUSIONS
Our study was able to evaluate the effectiveness of Early Warning Systems in different contexts and resource settings based on the EWSs' method of data collection. There is consistent evidence that EWSs compiling pre-diagnosis data are more proactive to detect outbreaks. However, the fact that Syndromic Surveillance Systems (SSS) are more proactive than diagnostic disease surveillance should not be taken as an effective clue for outbreaks detection.

Identifiants

pubmed: 36447171
doi: 10.1186/s12889-022-14625-4
pii: 10.1186/s12889-022-14625-4
pmc: PMC9707072
doi:

Types de publication

Systematic Review Journal Article Research Support, Non-U.S. Gov't

Langues

eng

Sous-ensembles de citation

IM

Pagination

2216

Informations de copyright

© 2022. The Author(s).

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Auteurs

Rehab Meckawy (R)

Public Health and Community Medicine Department, Alexandria Faculty of Medicine, Alexandria University, Champollion street, Al Attarin, Alexandria, Egypt. R_Mekawy2120396@alexmed.edu.eg.

David Stuckler (D)

Department of Social and Political Sciences and Dondena Research Center, Bocconi University, Via Roberto Sarfatti, 25, 20100, Milan, MI, Italy.

Adityavarman Mehta (A)

University of Leeds, Leeds, LS2 9JT, UK.

Tareq Al-Ahdal (T)

Institute of Global Health (HIGH), Heidelberg University, Neuenheimer feld 130/3, 69120, Heidelberg, Germany.

Bradley N Doebbeling (BN)

College of Health Solutions, Arizona State University, 975 S. Myrtle Ave, Tempe, AZ, USA.

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