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Abstract/Summary
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Background!#!Healthcare workers are among the most exposed and potentially most threatened populations of the ongoing COVID-19 pandemic. Despite some reports on numbers of infections with SARS-CoV‑2 in German healthcare workers, the courses of their clinical presentation when affected by COVID-19 are not well described.!##!Objective!#!In this contribution, characteristics and progressions of infected cases among healthcare workers at the University Medical Center Hamburg-Eppendorf during the first wave of the COVID-19 pandemic will be presented.!##!Methods!#!Between 1 July and 28 July 2020, 67 healthcare workers, who previously tested positive for SARS-CoV‑2 via PCR, were invited via E‑mail to participate in an anonymous online questionnaire; 39 persons participated.!##!Results!#!Participants (58%) were mostly ≤ 39 years old (64%) and female (70%). Most healthcare workers were involved in direct patient management (85%), including contact with SARS-CoV‑2 positive patients (62%). All participants reported acute symptoms with a median duration of 19 days. The most frequent symptoms were fatigue (85%), anosmia (67%), cough (64%), headache (62%), and shortness of breath (51%). The disease course was mostly mild with low admission rates (5%). Ongoing symptoms lasting more than four weeks post-symptom-onset, particularly anosmia, fatigue, and shortness of breath, were reported by 38%. This group more frequently had pre-existing conditions (53% vs. 12%, p = 0.010), specifically hypertension (27% vs. 4%, p = 0.062).!##!Discussion!#!Healthcare workers reported mostly mild courses of COVID-19 despite increased contact with SARS-CoV-2 patients. However, some reported persistent symptoms months after infection.
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1000
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Hinweis
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DeepGreen-ID: 1c64153a363040e59724b367faf09c1a ; metadata provieded by: DeepGreen (https://www.oa-deepgreen.de/api/v1/), LIVIVO search scope life sciences (http://z3950.zbmed.de:6210/livivo), Crossref Unified Resource API (https://api.crossref.org/swagger-ui/index.html), to.science.api (https://frl.publisso.de/), ZDB JSON-API (beta) (https://zeitschriftendatenbank.de/api/), lobid - Dateninfrastruktur für Bibliotheken (https://lobid.org/resources/search)
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