1. Willingness to share contacts in case of COVID-19 positivity–predictors of collaboration resistance in a nation-wide Italian survey.
- Author
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Bikbov, Boris, Tettamanti, Mauro, Bikbov, Alexander, D'Avanzo, Barbara, Galbussera, Alessia Antonella, Nobili, Alessandro, Calamandrei, Gemma, Candini, Valentina, Starace, Fabrizio, Zarbo, Cristina, and de Girolamo, Giovanni
- Subjects
CONTACT tracing ,PRINCIPAL components analysis ,AKAIKE information criterion ,HOMELESSNESS ,COVID-19 pandemic ,COVID-19 ,INTERNET surveys ,HOMELESS persons - Abstract
Background: The unwillingness to share contacts is one of the least explored aspects of the COVID-19 pandemic. Here we report the factors associated with resistance to collaborate on contact tracing, based on the results of a nation-wide survey conducted in Italy in January-March 2021. Methods and findings: The repeated cross-sectional on-line survey was conducted among 7,513 respondents (mean age 45.7, 50.4% women) selected to represent the Italian adult population 18–70 years old. Two groups were defined based on the direct question response expressing (1) unwillingness or (2) willingness to share the names of individuals with whom respondents had contact. We selected 70% of participants (training data set) to produce several multivariable binomial generalized linear models and estimated the proportion of variation explained by the model by McFadden R
2 , and the model's discriminatory ability by the index of concordance. Then, we have validated the regression models using the remaining 30% of respondents (testing data set), and identified the best performing model by removing the variables based on their impact on the Akaike information criterion and then evaluating the model predictive accuracy. We also performed a sensitivity analysis using principal component analysis. Overall, 5.5% of the respondents indicated that in case of positive SARS-CoV-2 test they would not share contacts. Of note, this percentage varied from 0.8% to 46.5% depending on the answers to other survey questions. From the 139 questions included in the multivariable analysis, the initial model proposed 20 independent factors that were reduced to the 6 factors with only modest changes in the model performance. The 6-variables model demonstrated good performance in the training (c-index 0.85 and McFadden R2 criteria 0.25) and in the testing data set (93.3% accuracy, AUC 0.78, sensitivity 30.4% and specificity 97.4%). The most influential factors related to unwillingness to share contacts were the lack of intention to perform the test in case of contact with a COVID-19 positive individual (OR 5.60, 95% CI 4.14 to 7.58, in a fully adjusted multivariable analysis), disagreement that the government should be allowed to force people into self-isolation (OR 1.79, 95% CI 1.12 to 2.84), disagreement with the national vaccination schedule (OR 2.63, 95% CI 1.86 to 3.69), not following to the preventive anti-COVID measures (OR 3.23, 95% CI 1.85 to 5.59), the absence of people in the immediate social environment who have been infected with COVID-19 (1.66, 95% CI 1.24 to 2.21), as well as difficulties in finding or understanding the information about the infection or related recommendations. A limitation of this study is the under-representation of persons not participating in internet-based surveys and some vulnerable groups like homeless people, persons with disabilities or migrants. Conclusions: Our analysis revealed several groups that expressed unwillingness to collaborate on contact tracing. The identified patterns may play a principal role not only in the COVID-19 epidemic but also be important for possible future public health threats, and appropriate interventions for their correction should be developed and ready for the implementation. [ABSTRACT FROM AUTHOR]- Published
- 2022
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