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1.
Journal of Datta Meghe Institute of Medical Sciences University ; 17(5):S63-S66, 2022.
Article in English | Scopus | ID: covidwho-2040150

ABSTRACT

Severe acute respiratory syndrome coronavirus 2 is a widespread worldwide public health malady due to a viral COVID-19 infection. The World Health Organization has affirmed this malady as a pandemic and Public Health Emergency of International Concern. A wide array of oral lesions has been reported in patients with COVID-19. Oral lesions can be an initial sign of COVID-19 or an alarming sign of peripheral thrombosis. However, there is a scarcity of published literature on the oral manifestations of COVID-19 in hospitalized patients. We present four different types of oral lesions in hospitalized patients with moderate-to-severe COVID-19 disease. This article proposes that a detailed examination of the oral cavity in patients admitted to COVID-19 intensive care unit/high dependency units will help to understand the significance of the oral lesions in the management of the disease. Dental professionals should be a part of the multidisciplinary treatment protocol, thus, emphasizing a detailed and meticulous oral examination and oral health amelioration of COVID-19 patients. © 2022 Wolters Kluwer Medknow Publications. All rights reserved.

2.
Sci Rep ; 11(1): 11549, 2021 06 15.
Article in English | MEDLINE | ID: covidwho-1270670

ABSTRACT

We show that malicious COVID-19 content, including racism, disinformation, and misinformation, exploits the multiverse of online hate to spread quickly beyond the control of any individual social media platform. We provide a first mapping of the online hate network across six major social media platforms. We demonstrate how malicious content can travel across this network in ways that subvert platform moderation efforts. Machine learning topic analysis shows quantitatively how online hate communities are sharpening COVID-19 as a weapon, with topics evolving rapidly and content becoming increasingly coherent. Based on mathematical modeling, we provide predictions of how changes to content moderation policies can slow the spread of malicious content.

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