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Artikel ; Online: Health Sentinel: A mobile crowdsourcing platform for self-reported surveys provides early detection of COVID-19 clusters in San Luis Potosí, Mexico.

Ruiz-Correa, Salvador / López-Revilla, Rubén / Díaz-Barriga, Fernando / Marmolejo-Cossío, Francisco / Del Carmen Robledo-Valero, Viridiana / Hernández-Huérfano, Emilio Ernesto / Álvarez-Rivera, Leonardo / Rangel-Martínez, Mónica Liliana / Lutzow-Steiner, Miguel Ángel / Ortiz-Vázquez, Luis Alfredo / Mendoza-Lara, Andrea Rebeca / Olivo-Rodríguez, Montserrat / Galván-Ramírez, Marco Sebastián / Morales-Neri, Ángel Emanuel / Martínez-Donjuan, Víctor Uriel / Cervantes-Irurzo, Massiel Isabella / Comas-García, Andreu / Hernández-Maldonado, Fernando / Aguilar-Acosta, Carlos

International journal of medical informatics

2021  Band 153, Seite(n) 104508

Abstract: Background: The Health Sentinel (Centinela de la Salud, CDS), a mobile crowdsourcing platform that includes the CDS app, was deployed to assess its utility as a tool for COVID-19 surveillance in San Luis Potosí, Mexico.: Methods: The CDS app allowed ... ...

Abstract Background: The Health Sentinel (Centinela de la Salud, CDS), a mobile crowdsourcing platform that includes the CDS app, was deployed to assess its utility as a tool for COVID-19 surveillance in San Luis Potosí, Mexico.
Methods: The CDS app allowed anonymized individual surveys of demographic features and COVID-19 risk of transmission and exacerbation factors from users of the San Luis Potosí Metropolitan Area (SLPMA). The platform's data processing pipeline computed and geolocalized the risk index of each user and enabled the analysis of the variables and their association. Point process analysis identified geographic clustering patterns of users at risk and these were compared with the patterns of COVID-19 cases confirmed by the State Health Services.
Results: A total of 1554 COVID-19 surveys were administered through the CDS app. Among the respondents, 50.4 % were men and 49.6 % women, with an average age of 33.5 years. Overall risk index frequencies were, in descending order: no-risk 77.8 %, low risk 10.6 %, respiratory symptoms 6.7 %, medium risk 1.4 %, high risk 2.0 %, very high risk 1.5 %. Comorbidity was the most frequent vulnerability category (32.4 %), followed by the inability to keep home lockdown (19.2 %). Statistically significant risk clusters identified at a spatial scale between 5 and 730 m coincided with those in neighborhoods containing substantial numbers of confirmed COVID-19 cases.
Conclusions: The CDS platform enables the analysis of the sociodemographic features and spatial distribution of individual risk indexes of COVID-19 transmission and exacerbation. It is a useful epidemiological surveillance and early detection tool because it identifies statistically significant and consistent risk clusters in neighborhoods with a substantial number of confirmed COVID-19 cases.
Mesh-Begriff(e) Adult ; COVID-19 ; Communicable Disease Control ; Crowdsourcing ; Female ; Humans ; Male ; Mexico ; SARS-CoV-2 ; Self Report ; Surveys and Questionnaires
Sprache Englisch
Erscheinungsdatum 2021-05-28
Erscheinungsland Ireland
Dokumenttyp Journal Article ; Research Support, Non-U.S. Gov't
ZDB-ID 1466296-6
ISSN 1872-8243 ; 1386-5056
ISSN (online) 1872-8243
ISSN 1386-5056
DOI 10.1016/j.ijmedinf.2021.104508
Datenquelle MEDical Literature Analysis and Retrieval System OnLINE

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