Background: Long COVID is a syndrome characterized by the persistence of SARS-CoV-2 infection symptoms. Among HCWs, prolonged COVID symptoms could lead to the inability to perform work tasks. The aim of this study is to investigate 35-day long-COVID (35-LC) characteristics and risk factors in a one-year period. Methods: We carried out a retrospective cohort study during the COVID-19 pandemic at University Hospital of Bari. A total of 5750 HCWs were tested for close contact with a confirmed case, in the absence of personal protective equipment, or for symptom development. Results: Each positive HCW was investigated for cardiovascular risk factors or respiratory diseases. An amount of 352 HCWs (6.1%) were infected by SARS-CoV-2, and 168 cases evolved to long COVID. The 35-LC group showed mean BMI values higher than the non-35-LC group (25.9 kg/m2 vs. 24.8 kg/m2, respectively), and this difference was significant (p-value: 0.020). Moreover, HCWs who suffered from pulmonary disease (OR = 3.7, CL 95%: 1.35–10.53; p-value = 0.007) or overweight (OR = 1.6 CL 95%: 1.05–2.56; p-value = 0.029) had an increased risk of developing 35-LC. Conclusions: Long COVID is an emerging problem for hospital managers as it may reduce the number of HCWs deployed in the fight against COVID-19. High BMI and previous pulmonary disease could be risk factors for 35-LC development in exposed HCWs.

Background: SARS-CoV-2 has infected many healthcare workers and (HCWs) worldwide. The aim of this study was to determine, analyze, and compare the frequency and characteristics of COVID-19 cases among HCWs of the University Hospital of Bari. Methods: A retrospective observational study was conducted after preventive protocol implementation. The SARS-CoV-2 infection frequency was determined by real-time reverse transcription-polymerase chain reaction on nasopharyngeal samples. Results: Overall, 519 HCWs (9%) tested positive among a total of 6030 HCWs during the three waves. The highest frequency of COVID-19 cases (n = 326; 63%) was observed during the 2nd wave, from September 2020 to December 2020, and the lowest (n = 34; 7%) was observed during the 1st wave, from March 2020 to August 2020 (p < 0.001). Working in a designated COVID-19 department was not a risk factor for infection. Conclusions: The correct use of personal protective equipment and the early identification of symptomatic workers are still essential factors to avoid nosocomial clusters, even in this current phase of vaccine availability.

Lockdown measures were initiated in Italy on March 9th after the start of the SARS-CoV-2 epidemic to flatten the epidemic curve. The aim of the present study was to assess the impact of restrictive measures in the Apulia Region, southern Italy, on air quality from March to April 2020. We applied a dual-track approach. We assessed citizen mobility and vehicle traffic with mobility network data and information obtained from satellite tracking, and we evaluated and compared pollutant concentration data as measured by monitoring stations maintained by the Regional Agency for Environmental Protection and Prevention of Apulia (ARPA). The results showed a decrease in the weekly mean NO2 concentration recorded by urban traffic stations during the lockdown period. In particular, in the city of Bari, the average NO2 concentration decreased from 62.2 μg/m3 in March 2019 to 48.2 μg/m3 in March 2020. Regarding PM10 levels, the average concentrations at the individual traffic stations showed no particular variation compared to those in the same months of the previous year, except for Bari-Caldarola Station in March 2019/2020 (p-value &lt; 0.001) and in April 2019/2020 (p-value = 0.04). In particular the average in March 2019 was ~26.9 μg/m3, while that in March 2020 was ~22.9 μg/m3. For April, the average concentration of PM10 in 2019 was 27.9 μg/m3, while in 2020, the average was ~22.4 μg/m3. This can be explained by the fact that PM10 levels are influenced by multiple variables such as weather and climate conditions and desert dust advections.

Background Multiple sclerosis (MS) is the most common cause of nontraumatic chronic neurological disability affecting young adults during their crucial employment years. Objectives To evaluate patients and disease related factors associated to unemployment in a cohort of relapsing–remitting (RR) MS patients. Methods We included RRMS patients with a follow-up of at least 1 year. We collected data about years of school education and employment status. Patients underwent a neuropsychological evaluation using the Brief International Cognitive Assessment for Multiple Sclerosis (BICAMS). Demographic and clinical predictors of unemployment were assessed through a multivariable stepwise logistic regression model. Results We evaluated 260 consecutive RRMS patients. Employed patients were less frequently female (68.4% vs 83.3%, p = 0.006), less disabled (median Expanded Disability Status Scale (EDSS) score: 2.0 (0–7.0) vs 2.5 (0–7.5), p < 0.001), with more years of school education (mean ± standard deviation (SD), years: 13.74 ± 0.30 vs 10.86 ± 3.47, p < 0.001). Female sex and a higher EDSS score resulted associated with a greater risk of unemployment (OR 3.510, 95% CI 1.654–7.448, p = 0.001; OR 1.366, 95% CI 1.074–1.737, p = 0.011, respectively), whereas a greater number of years of schooling and current disease-modifying therapy exposure resulted protective factors (OR 0.788, 95% CI 0.723–0.858, p < 0,001; OR 0.414, 95% CI 0.217–0.790, p = 0.008, respectively). Conclusions Understanding work is pervasively influenced by consequences of MS, we confirmed the impact of demographic, physical, and cognitive factors on employment status in RRMS patients.

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