Adherence to social distancing and use of personal protective equipment and the risk of SARS-CoV-2 infection in a cohort of patients with multiple sclerosis.


Journal

Multiple sclerosis and related disorders
ISSN: 2211-0356
Titre abrégé: Mult Scler Relat Disord
Pays: Netherlands
ID NLM: 101580247

Informations de publication

Date de publication:
Oct 2020
Historique:
received: 07 06 2020
revised: 25 06 2020
accepted: 02 07 2020
pubmed: 15 7 2020
medline: 30 10 2020
entrez: 15 7 2020
Statut: ppublish

Résumé

Background Aiming to safeguard its population from COVID19 infection, Italian government provided specific advices, especially to fragile individuals such those affected by Multiple Sclerosis (MS), to respect social distancing, to arrange remote work and to use personal protective equipment (PPE). The aim of this study is to investigate real adherence to these measures among MS patients and to evaluate its impact on exposure to infection. Methods MS patients followed at the MS center of Tor Vergata University hospital, Rome, Italy were asked to complete an anonymous 35-items web-survey exploring demographics, residency, employment, social distancing habits, use of PPE, MS features and COVID19 infection data, including self-reported information about contacts with SARS-CoV-2 positive/presumed positive persons. In order to estimate adherence to social distancing and use of PPE, an overall 'Lockdown Score' (LS) on 0-10 scale was created analyzing four main domains (Working (0 - 4), Social distancing and PPE use (0 - 4), Assistance for shopping needs (0 - 2), Residency (-2 - 0)). Mean scores for several pre-defined subgroups of patients were compared using both univariable and multivariable analyses. Accuracy of the score in discriminating subjects at higher risk of coming in contact with SARS-CoV-2 positive/presumed positive individuals was calculated as the area under the receiver-operator characteristic curve (AUC). The optimal cut-off was identified and used to dichotomize LS (high/ low). Logistic regression model was applied to estimate individuals' characteristics associated with high/low LS and odds ratio of coming in contact with SARS-CoV-2 positive/presumed positive persons based on continous and dichotomised LS. Results Respondents (N = 551) had a mean(±SD) overall LS of 6.52±2.11 (Working 3.16±1.19, Social distancing and PPE use 2.69±1.33, Assistance 0.66± 0.62, Residency penalty applied in 4 cases). Female, disabled and unemployed individuals had significantly higher mean LS (p<0.05). The AUC of the LS was 0.68 (95% CI, 0.59-0.77) and the optimal LS cut-off for discrimination was 6.0. Consistently, female, disabled and unemployed individuals had higher odd of getting a high LS (≥ 6) compared to male, independent and employed (p<0.05). Odd of coming in contact with SARS-CoV-2 positive/presumed positive individuals was significantly reduced for one-unit increase in LS (0.74 (95% CI: 0.64-0.85)) and among individuals with high LS (0.37 (95% CI: 0.19-0.72)). Only one subject among respondents declared to have been diagnosed with COVID19. Conclusions MS patients, especially those with social unfavorable conditions, demonstrated good adherence to social distancing and use of protection equipment. Implementing domains, such as social assistance, may improve protection from infection. LS score is potentially able to identify subjects with behaviors at greater risk of infection, although it needs to be validated against MS population living in higher incidence areas.

Identifiants

pubmed: 32663793
pii: S2211-0348(20)30434-X
doi: 10.1016/j.msard.2020.102359
pmc: PMC7333605
pii:
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

102359

Informations de copyright

Copyright © 2020. Published by Elsevier B.V.

Déclaration de conflit d'intérêts

Declaration on Competing Interest Landi D has no interests to disclose; Ponzano M has no interests to disclose; Nicoletti CG has no interests to disclose; Cecchi G has no interests to disclose; Cola G has no interests to disclose; Mataluni G has no interests to disclose; Mercuri NB has no interests to disclose; Sormani MP has no interests to disclose; Marfia GA has no interests to disclose. The study did not received funds.

Références

Neurol Sci. 2020 Jun;41(6):1369-1371
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pubmed: 32497632
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pubmed: 32339832
Front Public Health. 2018 Jun 11;6:149
pubmed: 29942800
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pubmed: 32319647
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pubmed: 32464584
Lancet Neurol. 2020 Jun;19(6):481-482
pubmed: 32359409
BMC Public Health. 2012 Aug 20;12:679
pubmed: 22905965
Acta Neurol Belg. 2019 Sep 30;:
pubmed: 31571134

Auteurs

Doriana Landi (D)

Department of Medicine of the Systems, Tor Vergata University, Rome, Italy; Multiple Sclerosis Clinical and Research Unit, Fondazione Policlinico di Tor Vergata, Rome, Italy. Electronic address: doriana.landi@gmail.com.

Marta Ponzano (M)

Department of Health Sciences, University of Genoa, Italy.

Carolina Gabri Nicoletti (CG)

Department of Medicine of the Systems, Tor Vergata University, Rome, Italy; Multiple Sclerosis Clinical and Research Unit, Fondazione Policlinico di Tor Vergata, Rome, Italy.

Gianluca Cecchi (G)

Department of Medicine of the Systems, Tor Vergata University, Rome, Italy; Multiple Sclerosis Clinical and Research Unit, Fondazione Policlinico di Tor Vergata, Rome, Italy.

Gaia Cola (G)

Department of Medicine of the Systems, Tor Vergata University, Rome, Italy; Multiple Sclerosis Clinical and Research Unit, Fondazione Policlinico di Tor Vergata, Rome, Italy.

Giorgia Mataluni (G)

Department of Medicine of the Systems, Tor Vergata University, Rome, Italy; Multiple Sclerosis Clinical and Research Unit, Fondazione Policlinico di Tor Vergata, Rome, Italy.

Nicola Biagio Mercuri (NB)

Department of Medicine of the Systems, Tor Vergata University, Rome, Italy; Neurology Unit, Fondazione Policlinico di Tor Vergata, Rome, Italy.

Maria Pia Sormani (MP)

Department of Health Sciences, University of Genoa, Italy.

Girolama Alessandra Marfia (GA)

Department of Medicine of the Systems, Tor Vergata University, Rome, Italy; Multiple Sclerosis Clinical and Research Unit, Fondazione Policlinico di Tor Vergata, Rome, Italy.

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Classifications MeSH