Early detection of respiratory disease outbreaks through primary healthcare data.
Journal
Journal of global health
ISSN: 2047-2986
Titre abrégé: J Glob Health
Pays: Scotland
ID NLM: 101578780
Informations de publication
Date de publication:
03 Nov 2023
03 Nov 2023
Historique:
medline:
6
11
2023
pubmed:
2
11
2023
entrez:
2
11
2023
Statut:
epublish
Résumé
The emergence of coronavirus disease 2019 (COVID-19) in 2020 highlighted the relevance of surveillance systems in detecting early signs of potential outbreaks, thus enabling public health authorities to act before the pathogen becomes widespread. Syndromic digital surveillance through web applications has played a crucial role in monitoring the spread of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) virus. However, this approach requires expensive infrastructure, which is not available in developing countries. Pre-existing sources of information, such as encounters in primary health care (PHC), can provide valuable data for a syndromic surveillance system. Here we evaluated the utility of PHC data to identify early warning signals of the first COVID-19 outbreak in Bahia-Brazil in 2020. We compared the weekly counts of PHC encounters due to respiratory complaints and the number of COVID-19 cases in 2020 in Bahia State - Brazil. We used the data from December 2016 to December 2019 to predict the expected number of encounters in 2020. We analysed data aggregated by geographic regions (n = 34) and included those where historical PHC data was available for at least 70% of the population. Twenty-one out of 34 regions met the inclusion criteria. We observed that notification of COVID-19 cases was preceded by at least two weeks with an excess of encounters of respiratory complaints in 18/21 (86%) of the regions analysed and four weeks or more in 10/21 (48%) regions. Digital syndromic surveillance systems based on already established PHC databases may add time to preparedness and response to emerging epidemics.
Sections du résumé
Background
UNASSIGNED
The emergence of coronavirus disease 2019 (COVID-19) in 2020 highlighted the relevance of surveillance systems in detecting early signs of potential outbreaks, thus enabling public health authorities to act before the pathogen becomes widespread. Syndromic digital surveillance through web applications has played a crucial role in monitoring the spread of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) virus. However, this approach requires expensive infrastructure, which is not available in developing countries. Pre-existing sources of information, such as encounters in primary health care (PHC), can provide valuable data for a syndromic surveillance system. Here we evaluated the utility of PHC data to identify early warning signals of the first COVID-19 outbreak in Bahia-Brazil in 2020.
Methods
UNASSIGNED
We compared the weekly counts of PHC encounters due to respiratory complaints and the number of COVID-19 cases in 2020 in Bahia State - Brazil. We used the data from December 2016 to December 2019 to predict the expected number of encounters in 2020. We analysed data aggregated by geographic regions (n = 34) and included those where historical PHC data was available for at least 70% of the population.
Results
UNASSIGNED
Twenty-one out of 34 regions met the inclusion criteria. We observed that notification of COVID-19 cases was preceded by at least two weeks with an excess of encounters of respiratory complaints in 18/21 (86%) of the regions analysed and four weeks or more in 10/21 (48%) regions.
Conclusions
UNASSIGNED
Digital syndromic surveillance systems based on already established PHC databases may add time to preparedness and response to emerging epidemics.
Identifiants
pubmed: 37917874
doi: 10.7189/jogh.13.04124
pmc: PMC10623377
doi:
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
04124Informations de copyright
Copyright © 2023 by the Journal of Global Health. All rights reserved.
Déclaration de conflit d'intérêts
Disclosure of interest: The authors completed the ICMJE Disclosure of Interest Form (available upon request from the corresponding author) and disclose no relevant interests.
Références
Nat Med. 2020 May;26(5):634-638
pubmed: 32273611
Emerg Infect Dis. 2021 Feb;27(2):612-615
pubmed: 33496228
Lancet. 2020 Nov 21;396(10263):1636
pubmed: 33096042
J Gen Virol. 2021 Jun;102(6):
pubmed: 34130773
Int J Equity Health. 2012 Jun 21;11:33
pubmed: 22720869
Stat Med. 2013 Mar 30;32(7):1206-22
pubmed: 22941770
BMJ Glob Health. 2018 Jul 3;3(4):e000829
pubmed: 29997906
Nat Commun. 2021 Jan 19;12(1):434
pubmed: 33469026
Lancet Reg Health West Pac. 2020 Nov;4:100024
pubmed: 34013214
Lancet Respir Med. 2021 Apr;9(4):407-418
pubmed: 33460571
Epidemics. 2021 Dec;37:100528
pubmed: 34814093
Euro Surveill. 2017 Jul 13;22(28):
pubmed: 28749331