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1.
European Journal of Public Health ; 32:III569-III569, 2022.
Article in English | Web of Science | ID: covidwho-2310321
2.
European Journal of Public Health ; 32:III578-III578, 2022.
Article in English | Web of Science | ID: covidwho-2310071
3.
European journal of public health ; 32(Suppl 3), 2022.
Article in English | EuropePMC | ID: covidwho-2102432

ABSTRACT

Influenza represents a major burden for public health. Healthcare workers (HCWs) are a priority target group for flu vaccination. During the COVID-19 pandemic, when SARS-CoV-2 vaccines were not yet available, susceptibility to influenza vaccination especially by HCWs increased. The aim of this study is to analyze the flu vaccination coverage among HCWs and to study which factors affected their adherence given the concomitant COVID-19 vaccination. The retrospective study was conducted in an Italian research hospital from October 2021 to January 2022. A total of 7,048 individuals was included. Age class, gender and job category variables were analyzed. Statistically significant differences among groups were tested through χ2 test. Univariate and multivariate analyses (p < 0,005) were performed to assess differences towards vaccination attitude. The flu vaccination coverage rate was 24.6%. Among the selected job categories, 29.8% of physicians, 19.9% of nurses and 19.7% of other HCWs were vaccinated with a statistically significant decrease (p < 0.001) across all categories respect with the last campaign. The findings of the logistic regression depicted that the 40-59 years old age class, compared with the youngest age class (OR 1.30, 95% CI 1.12-1.43) as well as being physician (OR 2.79, 95% CI 1.87-3.41) with the respect to being nurses, had a higher adherence to vaccination. Interestingly, being male, is associated with a statistically significant reduction (OR 0.71, 95% CI 0.59-0.87) in vaccination uptake. Study findings showed a several decline in the flu vaccination coverage comparing with previous campaigns, probably due to the concomitant administration of the booster dose against SARS-CoV-2. This alarm should not be underestimated and requires timely and innovative organizational approaches (i.e., combined vaccine). Further studies are needed to analyze the reasons for this poor adhesion and the strategies to be adopted to increase the awareness of the HCWs. Key messages • Reaching high coverage rates and restore a positive trend for the future campaign for flu vaccination it is essential strategy to protect HCWs themselves, their patients and the hospital community. • Decision-makers should implement consistent communication strategies to lessen vaccine hesitancy among HCWs.

4.
European journal of public health ; 32(Suppl 3), 2022.
Article in English | EuropePMC | ID: covidwho-2102220

ABSTRACT

Influencing behavioral patterns through primary prevention, possibly addressing more risk factors at a time, is the most effective means to tackle cardiovascular diseases. Many interdisciplinary prevention activities have been coordinated by community nurses outside of specialist centers, resulting in a more effective control of risk factors. Our study aims at describing the impact of an 18-month prevention and promotion, interdisciplinary intervention on lifestyle habits and cardiovascular risk. From December 2018 to May 2020, patients were recruited by 4 General Practitioners (GPs) in the Roman neighborhood of Torresina and received nutritional, physical and psychological counselling to learn healthy lifestyles. Until May 2020 patients had to self-manage their new healthy habits, but during this phase the SARS-CoV-2 pandemic broke out. Patients were assessed at baseline, 6, 12 and 18 months by a nutritionist, a physiotherapist, a psychologist, the 4 GPs and community nurses, and the cardiovascular risk score (CRS) was estimated at every examination. 76 patients were included, with a mean age of 54,6 years. Mean CRS showed a significant reduction between baseline and 12 months (from 4.9 to 3.8, p < 0.001), but this trend was not maintained at 18 months. As for variables included in the calculation of the cardiovascular risk score, both total cholesterol and systolic blood pressure significantly decreased at 6 months of follow up (respectively, from 211.1 to 192 (p < 0.001) and from 133.1 to 123.1(p < 0.001)). Nontheless, the reduction was maintained in the remaining points in time only for systolic blood pressure. Our interdisciplinary educational intervention in a primary care setting resulted in a CRS improvement at 12 months, but this changes where not maintained at 18 months. Community nurses were facilitators in improving health outcomes and patient's satisfaction in the described primary care setting. Key messages Our interdisciplinary educational intervention in a primary care setting resulted in a CRS improvement at 12 months, but this changes where not maintained at 18 months. Community nurses are facilitators in improving health outcomes and patient’s satisfaction in the described primary care setting.

9.
European Journal of Public Health ; 31, 2021.
Article in English | ProQuest Central | ID: covidwho-1515077

ABSTRACT

Healthcare-Associated Infections (HAIs) and Antimicrobial Resistance (AMR) involve high costs both in health and economic terms for patients and health systems. Implementing Infection Prevention and Control (IPC) programs is critical to decrease infectious agents' transmission in healthcare settings. The aim of this study is to assess if the monitoring of Contact Precautions could decrease the incidence of Multi-Drug Resistant Organisms (MRDOs) infections. This pilot study was conducted in a teaching hospital in Rome. A checklist of 16 items was developed to assess the compliance to Contact Precautions in 11 hospital wards in which MRDOs were detected between November and December 2020. It was administered on-site both interviewing healthcare professionals and through direct observation. A paired t-test with α = 5% was used to compare the number of alert organisms in the first quarter of 2020 respect to the first quarter of 2021 before and after implementing the surveillance checklist. A total of 30 checklists were analyzed. The rate of compliance to Contact Precautions was high for the proper use of personal protective equipment (100%), the intensified room cleaning (100%) and the presence of isolation mark (100%), while it was low for the active screening of contacts (53%). Mean MDROs infections rate decreased from 4.94 to 4.37 for every 1000 hospitalization day, with an average decrease of 0.57. However, the paired t-test showed that there was no statistically significant difference between the mean number of MDROs infections before and after the implementation of the checklist (p > 0.05). Despite the good adherence to IPC program, the low infection rate decrease, is probably due to the impact of COVID-19 on the HAIs surveillance and prevention practices. Even if the check-list administration could be a useful tool to reduce MDROs infections, it should be associated to other prevention strategies during the COVID-19 pandemic in order to achieve a successful outcome. Key messages Preventing Healthcare-Associated Infections represents a priority public health challenge in order to improve patient safety and health system economic sustainability. The COVID-19 pandemic has shown that healthcare facilities should enhance efforts in their IPC programs to reduce Healthcare-Associated Infections.

10.
European Journal of Public Health ; 31, 2021.
Article in English | ProQuest Central | ID: covidwho-1514820

ABSTRACT

Background Primary care physicians have a crucial role in determining the appropriate healthcare setting for their confirmed or suspect COVID-19 patients. Machine learning provides science-based tools that can be used for clinical decision-making which have already been applied to the fight against Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) both in the therapeutic and the prevention area. The aim of this study was to develop a machine learning-based tool to support primary care physicians to decide between home monitoring and hospitalization for their patients before diagnostic test results are available. Methods A retrospective cohort study with data from a hospital setting was performed. Patients' medical history and clinical, laboratory and radiological findings were collected and the dataset was used to train a predictive model for COVID-19 severity. The patients were divided between confirmed and suspect cases on the basis of the positivity of the nasopharyngeal RT-PCR test results. A splitting algorithm was recursively used to choose the predictor. A decision tree was built. Results A total of 198 subjects were enrolled for the study. Out of them, 28 cases were classified as mild disease, 62 as moderate disease, 64 as severe disease, and 44 as critical disease, according to WHO guidelines. The G2 value was used to determine the contribution of each obtained value to build the decision tree. The tree was, therefore, built choosing values that maximized G2 and LogWorth. SpO2 (cut point = 92%) was chosen for the optimal first split. The correspondence between inputs and outcomes was validated. Conclusions Our tool provides accurate clinical severity prediction for both confirmed and suspect COVID-19 patients. We, therefore, propose its implementation in the everyday life challenges of primary care physicians to support their clinical decision-making in providing appropriate and timely care for their patients. Key messages Primary care physicians have a crucial role in determining the appropriate healthcare setting for their confirmed or suspect COVID-19 patients. We propose a tool that provides an accurate clinical severity prediction for both confirmed and suspect COVID-19 patients to help choosing the appropriate healthcare setting for them.

11.
Ig Sanita Pubbl ; 78(4):526-544, 2021.
Article in English | PubMed | ID: covidwho-1407665

ABSTRACT

The COVID-19 pandemic crisis has strongly stressed national health systems and resulted in a global economic crisis. This paper aims to frame and evaluate the funding disbursed and the costs incurred by the National Health Service, in relation to the COVID-19 emergency. It also intends to assess current monetary policies. It aims also to suggest and provide proposals in the context of strengthening the NHS. A narrative review of the grey literature was conducted querying OpenGray, WONDER e Pro-quest's Digital Dissertations e Conference Papers Index and the major institutional websites. The ALTEMS COVID-19 Instant Reports and reports published by regional, national and European institutional bodies were used as main information sources. The discussion begins with the presentation of the economic-health and epidemiological situation, and ends with the proposal of possible initiatives aimed at economic and financial reinforcement of the NHS.

12.
Eur Rev Med Pharmacol Sci ; 25(6): 2785-2794, 2021 Mar.
Article in English | MEDLINE | ID: covidwho-1173128

ABSTRACT

OBJECTIVE: To develop a deep learning-based decision tree for the primary care setting, to stratify adult patients with confirmed and unconfirmed coronavirus disease 2019 (COVID-19), and to predict the need for hospitalization or home monitoring. PATIENTS AND METHODS: We performed a retrospective cohort study on data from patients admitted to a COVID hospital in Rome, Italy, between 5 March 2020 and 5 June 2020. A confirmed case was defined as a patient with a positive nasopharyngeal RT-PCR test result, while an unconfirmed case had negative results on repeated swabs. Patients' medical history and clinical, laboratory and radiological findings were collected, and the dataset was used to train a predictive model for COVID-19 severity. RESULTS: Data of 198 patients were included in the study. Twenty-eight (14.14%) had mild disease, 62 (31.31%) had moderate disease, 64 (32.32%) had severe disease, and 44 (22.22%) had critical disease. The G2 value assessed the contribution of each collected value to decision tree building. On this basis, SpO2 (%) with a cut point at 92 was chosen for the optimal first split. Therefore, the decision tree was built using values maximizing G2 and LogWorth. After the tree was built, the correspondence between inputs and outcomes was validated. CONCLUSIONS: We developed a machine learning-based tool that is easy to understand and apply. It provides good discrimination in stratifying confirmed and unconfirmed COVID-19 patients with different prognoses in every context. Our tool might allow general practitioners visiting patients at home to decide whether the patient needs to be hospitalized.


Subject(s)
Algorithms , COVID-19/diagnosis , COVID-19/therapy , Decision Trees , Home Care Services/statistics & numerical data , Hospitalization/statistics & numerical data , Aged , COVID-19/epidemiology , COVID-19/virology , COVID-19 Testing , Cohort Studies , Decision Making, Computer-Assisted , Female , Follow-Up Studies , Humans , Italy/epidemiology , Machine Learning , Male , Monitoring, Physiologic , Prognosis , Retrospective Studies , SARS-CoV-2/isolation & purification
13.
Ig Sanita Pubbl ; 76(2):107-118, 2020.
Article in Italian | MEDLINE | ID: covidwho-739595

ABSTRACT

Knowledge about the new infectious disease COVID-19, which first spread in the city of Wuhan in China, in December 2019, is based on the evidence retrieved from coronaviruses previously known to humans. The main transmission ways of the new SARS-CoV-2 virus are respiratory droplets and direct and close contact with infected individuals and contaminated surfaces. To date, some scientific publications provide initial evidence that SARS-CoV-2 can be detected in the air, thus assuming a further route of infection, that airborne, although these results are to be considered preliminary and they need careful interpretation. In support of this hypothesis, ventilation systems, aimed to improve indoor air, could represent an easy way to spread and promote the virus infection especially in hospitals and in all health facilities where the presence of infected individuals is potentially high as well as the possibility of infection by air. Indeed, by generating jets of air at different speeds, they can interfere with the mission of respiratory particles and determine an environmental diffusion of the potentially contaminating droplet. Therefore, ventilation systems could provide a potential transmission channel for the viral load able to spread out in indoor air. Nonetheless, good management, technical and operational practices may lead to a low risk of contagion, both in community and health environments.

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