TY - JOUR
T1 - Epidemiological characterisation of asymptomatic carriers of COVID-19 in Colombia
T2 - A cross-sectional study
AU - Teherán, Aníbal A.
AU - Camero Ramos, Gabriel
AU - Prado De La Guardia, Ronald
AU - Hernández, Carolina
AU - Herrera, Giovanny
AU - Pombo, Luis M.
AU - Avila, Albert Alejandro
AU - Flórez, Carolina
AU - Barros, Esther C.
AU - Perez-Garcia, Luis
AU - Paniz-Mondolfi, Alberto
AU - Ramírez, Juan David
N1 - Publisher Copyright:
©
Copyright:
Copyright 2020 Elsevier B.V., All rights reserved.
PY - 2020/12/7
Y1 - 2020/12/7
N2 - Introduction Asymptomatic carriers (AC) of the new SARS-CoV-2 represent an important source of spread for COVID-19. Early diagnosis of these cases is a powerful tool to control the pandemic. Our objective was to characterise patients with AC status and identify associated sociodemographic factors. Methods Using a cross-sectional design and the national database of daily occurrence of COVID-19, we characterised both socially and demographically all ACs. Additional correspondence analysis and logistic regression model were performed to identify characteristics associated with AC state (OR, 95% CI). Results 76.162 ACs (12.1%; 95% CI 12.0% to 12.2%) were identified, mainly before epidemiological week 35. Age≤26 years (1.18; 1.09 to 1.28), male sex (1.51; 1.40 to 1.62), cases imported from Venezuela, Argentina, Brazil, Germany, Puerto Rico, Spain, USA or Mexico (12.6; 3.03 to 52.5) and autochthonous cases (22.6; 5.62 to 91.4) increased the risk of identifying ACs. We also identified groups of departments with moderate (1.23; 1.13 to 1.34) and strong (19.8; 18.6 to 21.0) association with ACs. Conclusion Sociodemographic characteristics strongly associated with AC were identified, which may explain its epidemiological relevance and usefulness to optimise mass screening strategies and prevent person-to-person transmission.
AB - Introduction Asymptomatic carriers (AC) of the new SARS-CoV-2 represent an important source of spread for COVID-19. Early diagnosis of these cases is a powerful tool to control the pandemic. Our objective was to characterise patients with AC status and identify associated sociodemographic factors. Methods Using a cross-sectional design and the national database of daily occurrence of COVID-19, we characterised both socially and demographically all ACs. Additional correspondence analysis and logistic regression model were performed to identify characteristics associated with AC state (OR, 95% CI). Results 76.162 ACs (12.1%; 95% CI 12.0% to 12.2%) were identified, mainly before epidemiological week 35. Age≤26 years (1.18; 1.09 to 1.28), male sex (1.51; 1.40 to 1.62), cases imported from Venezuela, Argentina, Brazil, Germany, Puerto Rico, Spain, USA or Mexico (12.6; 3.03 to 52.5) and autochthonous cases (22.6; 5.62 to 91.4) increased the risk of identifying ACs. We also identified groups of departments with moderate (1.23; 1.13 to 1.34) and strong (19.8; 18.6 to 21.0) association with ACs. Conclusion Sociodemographic characteristics strongly associated with AC were identified, which may explain its epidemiological relevance and usefulness to optimise mass screening strategies and prevent person-to-person transmission.
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U2 - 10.1136/bmjopen-2020-042122
DO - 10.1136/bmjopen-2020-042122
M3 - Research Article
C2 - 33293326
AN - SCOPUS:85097514749
SN - 2044-6055
VL - 10
JO - BMJ Open
JF - BMJ Open
IS - 12
M1 - e042122
ER -