Prevalence of long covid symptoms in Tuscany, Italy: a population-representative cross-sectional telephone survey

意大利托斯卡纳地区新冠后遗症长期症状的患病率:一项具有人口代表性的横断面电话调查

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Abstract

OBJECTIVES: Long covid affects over 36 million individuals in the European region, but its clinical profile is still poorly defined, particularly in the general population with less severe acute disease. This study aimed to assess the prevalence of a broad spectrum of symptoms potentially linked to long covid in the general population of Tuscany, Italy. METHODS: A cross-sectional study was conducted in January-February 2024 using Computer-Assisted Telephone Interviews in a representative population sample of Tuscany. Based on the WHO questionnaire long covid symptom list, data on 33 symptoms experienced in the past 6 months were collected, along with demographic and clinical characteristics. After excluding patients with COVID-19 within the past 6 months and those failing a screening cognitive test, symptom prevalence and ORs adjusted for sex, time since infection, smoking and concurrent diseases (aOR) were calculated according to COVID-19 history. RESULTS: After excluding 129 failing the cognitive test (6.4%) and 123 recent COVID cases (6.1%), among 1753 participants interviewed, 1013 (57.8%) had a history of COVID-19. The symptoms significantly more prevalent in individuals with previous COVID-19 were fatigue (12.8% vs 8.9%, aOR 1.6 (95% CI 1.2 to 2.2)), concentration impairment (5.5% vs 2.4%, aOR 2.2 (95% CI 1.3 to 3.8)) and skin rashes (4.5% vs 2.4%, aOR 1.9 (95% CI 1.1 to 3.3)). Prevalences and ORs were higher in more recent COVID-19 cases, particularly females and individuals with concurrent diseases. CONCLUSIONS: We identified in a population-based study some symptoms significantly more common in individuals with previous COVID-19. This approach complements data collected in clinical settings and in patients selected by greater disease severity. The findings may help future surveillance efforts and targeted public health interventions directed at optimising care pathways and mitigating long-term consequences.

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