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1.
BMJ Open ; 12(12): e062487, 2022 12 23.
Article in English | MEDLINE | ID: covidwho-2193764

ABSTRACT

OBJECTIVES: To estimate the risk factors for SARS-CoV-2 transmission in close contacts of adults at high risk of infection due to occupation, participants of the CoVIDA study, in Bogotá D.C., Colombia. SETTING: The CoVIDA study was the largest COVID-19 intensified sentinel epidemiological surveillance study in Colombia thus far, performing over 60 000 RT-PCR tests for SARS-CoV-2 infection. The study implemented a contact tracing strategy (via telephone call) to support traditional surveillance actions performed by the local health authority. PARTICIPANTS: Close contacts of participants from the CoVIDA study. PRIMARY AND SECONDARY OUTCOME MEASURES: SARS-CoV-2 testing results were obtained (RT-PCR with CoVIDA or self-reported results). The secondary attack rate (SAR) was calculated using contacts and primary cases features. RESULTS: The CoVIDA study performed 1257 contact tracing procedures on primary cases. A total of 5551 close contacts were identified and 1050 secondary cases (21.1%) were found. The highest SAR was found in close contacts: (1) who were spouses (SAR=32.7%; 95% CI 29.1% to 36.4%), (2) of informally employed or unemployed primary cases (SAR=29.1%; 95% CI 25.5% to 32.8%), (3) of symptomatic primary cases (SAR of 25.9%; 95% CI 24.0% to 27.9%) and (4) living in households with more than three people (SAR=22.2%; 95% CI 20.7% to 23.8%). The spouses (OR 3.85; 95% CI 2.60 to 5.70), relatives (OR 1.89; 95% CI 1.33 to 2.70) and close contacts of a symptomatic primary case (OR 1.48; 95% CI 1.24 to 1.77) had an increased risk of being secondary cases compared with non-relatives and close contacts of an asymptomatic index case, respectively. CONCLUSIONS: Contact tracing strategies must focus on households with socioeconomic vulnerabilities to guarantee isolation and testing to stop the spread of the disease.


Subject(s)
COVID-19 , SARS-CoV-2 , Adult , Humans , COVID-19/epidemiology , COVID-19/prevention & control , Contact Tracing/methods , Colombia/epidemiology , COVID-19 Testing , Risk Factors , Occupations
2.
Trials ; 23(1): 698, 2022 Aug 20.
Article in English | MEDLINE | ID: covidwho-2002215

ABSTRACT

BACKGROUND: The use of respiratory devices can mitigate the spread of diseases such as COVID-19 in community settings. We aimed to determine the effectiveness of closed face shields with surgical face masks to prevent SARS-CoV-2 transmission in working adults during the COVID-19 pandemic in Bogotá, Colombia. METHODS: An open-label non-inferiority randomized controlled trial that randomly assigned participants to one of two groups: the intervention group was instructed to wear closed face shields with surgical face masks, and the active control group was instructed to wear only surgical face masks. The primary outcome was a positive reverse transcription polymerase chain reaction test, IgG/IgM antibody test for SARS-CoV-2 detection, or both during and at the end of the follow-up period of 21 days. The non-inferiority limit was established at - 5%. RESULTS: A total of 316 participants were randomized, 160 participants were assigned to the intervention group and 156 to the active control group. In total, 141 (88.1%) participants in the intervention group and 142 (91.0%) in the active control group completed the follow-up. PRIMARY OUTCOME: a positive SARS-CoV-2 test result was identified in one (0.71%) participant in the intervention group and three (2.1%) in the active control group. In the intention-to-treat analysis, the absolute risk difference was - 1.40% (95% CI [- 4.14%, 1.33%]), and in the per-protocol analysis, the risk difference was - 1.40% (95% CI [- 4.20, 1.40]), indicating non-inferiority of the closed face shield plus face mask (did not cross the non-inferiority limit). CONCLUSIONS: The use of closed face shields and surgical face masks was non-inferior to the surgical face mask alone in the prevention of SARS-CoV-2 infection in highly exposed groups. Settings with highly active viral transmission and conditions such as poor ventilation, crowding, and high mobility due to occupation may benefit from the combined use of masks and closed face shields to mitigate SARS-CoV-2 transmission. TRIAL REGISTRATION: ClinicalTrials.gov NCT04647305 . Registered on November 30, 2020.


Subject(s)
COVID-19 , Adult , COVID-19/prevention & control , Humans , Masks , Pandemics/prevention & control , Risk Assessment , SARS-CoV-2
3.
Prev Med Rep ; 27: 101798, 2022 Jun.
Article in English | MEDLINE | ID: covidwho-1796218

ABSTRACT

Symptoms-based models for predicting SARS-CoV-2 infection may improve clinical decision-making and be an alternative to resource allocation in under-resourced settings. In this study we aimed to test a model based on symptoms to predict a positive test result for SARS-CoV-2 infection during the COVID-19 pandemic using logistic regression and a machine-learning approach, in Bogotá, Colombia. Participants from the CoVIDA project were included. A logistic regression using the model was chosen based on biological plausibility and the Akaike Information criterion. Also, we performed an analysis using machine learning with random forest, support vector machine, and extreme gradient boosting. The study included 58,577 participants with a positivity rate of 5.7%. The logistic regression showed that anosmia (aOR = 7.76, 95% CI [6.19, 9.73]), fever (aOR = 4.29, 95% CI [3.07, 6.02]), headache (aOR = 3.29, 95% CI [1.78, 6.07]), dry cough (aOR = 2.96, 95% CI [2.44, 3.58]), and fatigue (aOR = 1.93, 95% CI [1.57, 2.93]) were independently associated with SARS-CoV-2 infection. Our final model had an area under the curve of 0.73. The symptoms-based model correctly identified over 85% of participants. This model can be used to prioritize resource allocation related to COVID-19 diagnosis, to decide on early isolation, and contact-tracing strategies in individuals with a high probability of infection before receiving a confirmatory test result. This strategy has public health and clinical decision-making significance in low- and middle-income settings like Latin America.

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