Legionella spp. and legionellosis in southeastern Italy: disease epidemiology and environmental surveillance in community and health care facilities

<p>Abstract</p> <p>Background</p> <p>Following the publication of the Italian Guidelines for the control and prevention of legionellosis an environmental and clinical surveillance has been carried out in Southeastern Italy. The aim of the study is to identify the risk factors for the disease, so allowing better programming of the necessary prevention measures.</p> <p>Methods</p> <p>During the period January 2000 - December 2009 the environmental surveillance was carried out by water sampling of 129 health care facilities (73 public and 56 private hospitals) and 533 buildings within the community (63 private apartments, 305 hotels, 19 offices, 4 churches, 116 gyms, 3 swimming pools and 23 schools). Water sampling and microbiological analysis were carried out following the Italian Guidelines. From January 2005, all facilities were subject to risk analysis through the use of a standardized report; the results were classified as <it>good </it>(G), <it>medium </it>(M) and <it>bad </it>(B). As well, all the clinical surveillance forms for legionellosis, which must be compiled by physicians and sent to the Regional Centre for Epidemiology (OER), were analyzed.</p> <p>Results</p> <p><it>Legionella </it>spp. was found in 102 (79.1%) health care facilities and in 238 (44.7%) community buildings. The percentages for the contamination levels < 1,000, 1,000-10,000, > 10,000 cfu/L were respectively 33.1%, 53.4% and 13.5% for samples from health care facilities and 33.5%, 43.3% and 23.2% for samples from the community. Both in hospital and community environments, <it>Legionella pneumophila </it>serogroup (<it>L. pn </it>sg) 2-14 was the most frequently isolate (respectively 54.8% and 40.8% of positive samples), followed by <it>L. pn </it>sg 1 (respectively 31.3% and 33%). The study showed a significant association between M or B score at the risk analysis and <it>Legionella </it>spp. positive microbiological test results (p < 0.001). From clinical surveillance, during the period January 2001 - August 2009, 97 cases of legionellosis were reported to the OER: 88 of community origin and 9 nosocomial. The most frequent symptoms were: fever (93.8%), cough (70.1%), dyspnea (58.8%), shivering (56.7%). Radiological evidence of pneumonia was reported in 68%. The laboratory diagnostic methods used were: urinary antigen (54.3%), single antibody titer (19.8%), only seroconversion (11.1%), other diagnostic methods (14.8%).</p> <p>Conclusions</p> <p>Our experience suggests that risk analysis and environmental microbiological surveillance should be carried out more frequently to control the environmental spread of <it>Legionella </it>spp. Furthermore, the laboratory diagnosis of legionellosis cannot be excluded only on the basis of a single negative test: some patients were positive to only one of the diagnostic tests.</p

Solitary waves in the Nonlinear Dirac Equation

In the present work, we consider the existence, stability, and dynamics of solitary waves in the nonlinear Dirac equation. We start by introducing the Soler model of self-interacting spinors, and discuss its localized waveforms in one, two, and three spatial dimensions and the equations they satisfy. We present the associated explicit solutions in one dimension and numerically obtain their analogues in higher dimensions. The stability is subsequently discussed from a theoretical perspective and then complemented with numerical computations. Finally, the dynamics of the solutions is explored and compared to its non-relativistic analogue, which is the nonlinear Schr{\"o}dinger equation. A few special topics are also explored, including the discrete variant of the nonlinear Dirac equation and its solitary wave properties, as well as the PT-symmetric variant of the model

Longitudinally Profiling Neutralizing Antibody Response to SARS Coronavirus with Pseudotypes

SARS-CoV spike protein pseudotypes are the basis of an in vitro microneutralization assay sensitive and specific for SARS-CoV neutralizing antibodies

A comparison of populations vaccinated in a public service and in a private hospital setting in the same area

<p>Abstract</p> <p>Background</p> <p>Improving immunisation rates in risk groups is one of the main objectives in vaccination strategies. However, achieving high vaccination rates in children with chronic conditions is difficult. Different types of vaccine providers may differently attract high risk children.</p> <p>Aim</p> <p>To describe the characteristics of two populations of children who attended a private and a public immunisation provider in the same area. Secondarily, to determine if prevalence of patients with underlying diseases by type of provider differs and to study if the choice of different providers influences timeliness in immunisation.</p> <p>Methods</p> <p>We performed a cross-sectional study on parents of children 2 – 36 months of age who attended a private hospital immunisation service or a public immunisation office serving the same metropolitan area of Rome, Italy. Data on personal characteristics and immunisation history were collected through a face to face interview with parents of vaccinees, and compared by type of provider. Prevalence of underlying conditions was compared in the two populations. Timeliness in immunisation and its determinants were analysed through a logistic regression model.</p> <p>Results</p> <p>A total of 202 parents of children 2–36 months of age were interviewed; 104 were in the public office, and 98 in the hospital practice. Children immunised in the hospital were more frequently firstborn female children, breast fed for a longer period, with a lower birthweight, and more frequently with a previous hospitalisation. The prevalence of high risk children immunised in the hospital was 9.2 vs 0% in the public service (P = 0.001). Immunisation delay for due vaccines was higher in the hospital practice than in the public service (DTP, polio, HBV, and Hib: 39.8% vs 22.1%; P = 0.005). Anyway multivariate analyses did not reveal differences in timeliness between the public and private hospital settings.</p> <p>Conclusion</p> <p>Children with underlying diseases or a low birthweight were more frequently immunised in the hospital. This finding suggests that offering immunisations in a hospital setting may facilitate vaccination uptake in high risk groups. An integration between public and hospital practices and an effort to improve communication on vaccines to parents, may significantly increase immunisation rates in high risk groups and in the general population, and prevent immunisation delays.</p

Epidemiological characteristics of COVID-19 cases in non-Italian nationals notified to the Italian surveillance system

BACKGROUND: International literature suggests that disadvantaged groups are at higher risk of morbidity and mortality from SARS-CoV-2 infection due to poorer living/working conditions and barriers to healthcare access. Yet, to date, there is no evidence of this disproportionate impact on non-national individuals, including economic migrants, short-term travellers and refugees. METHODS: We analyzed data from the Italian surveillance system of all COVID-19 laboratory-confirmed cases tested positive from the beginning of the outbreak (20th of February) to the 19th of July 2020. We used multilevel negative-binomial regression models to compare the case fatality and the rate of admission to hospital and intensive care unit (ICU) between Italian and non-Italian nationals. The analysis was adjusted for differences in demographic characteristics, pre-existing comorbidities, and period of diagnosis. RESULTS: We analyzed 213 180 COVID-19 cases, including 15 974 (7.5%) non-Italian nationals. We found that, compared to Italian cases, non-Italian cases were diagnosed at a later date and were more likely to be hospitalized {[adjusted rate ratio (ARR)=1.39, 95% confidence interval (CI): 1.33-1.44]} and admitted to ICU (ARR=1.19, 95% CI: 1.07-1.32), with differences being more pronounced in those coming from countries with lower human development index (HDI). We also observed an increased risk of death in non-Italian cases from low-HDI countries (ARR=1.32, 95% CI: 1.01-1.75). CONCLUSIONS: A delayed diagnosis in non-Italian cases could explain their worse outcomes compared to Italian cases. Ensuring early access to diagnosis and treatment to non-Italians could facilitate the control of SARS-CoV-2 transmission and improve health outcomes in all people living in Italy, regardless of nationality

MIQuant – Semi-Automation of Infarct Size Assessment in Models of Cardiac Ischemic Injury

BACKGROUND: The cardiac regenerative potential of newly developed therapies is traditionally evaluated in rodent models of surgically induced myocardial ischemia. A generally accepted key parameter for determining the success of the applied therapy is the infarct size. Although regarded as a gold standard method for infarct size estimation in heart ischemia, histological planimetry is time-consuming and highly variable amongst studies. The purpose of this work is to contribute towards the standardization and simplification of infarct size assessment by providing free access to a novel semi-automated software tool. The acronym MIQuant was attributed to this application. METHODOLOGY/PRINCIPAL FINDINGS: Mice were subject to permanent coronary artery ligation and the size of chronic infarcts was estimated by area and midline-length methods using manual planimetry and with MIQuant. Repeatability and reproducibility of MIQuant scores were verified. The validation showed high correlation (r(midline length) = 0.981; r(area) = 0.970 ) and agreement (Bland-Altman analysis), free from bias for midline length and negligible bias of 1.21% to 3.72% for area quantification. Further analysis demonstrated that MIQuant reduced by 4.5-fold the time spent on the analysis and, importantly, MIQuant effectiveness is independent of user proficiency. The results indicate that MIQuant can be regarded as a better alternative to manual measurement. CONCLUSIONS: We conclude that MIQuant is a reliable and an easy-to-use software for infarct size quantification. The widespread use of MIQuant will contribute towards the standardization of infarct size assessment across studies and, therefore, to the systematization of the evaluation of cardiac regenerative potential of emerging therapies

COVID-19 integrated surveillance in Italy: Outputs and related activities

OBJECTIVES: to describe the integrated surveillance system of COVID-19 in Italy, to illustrate the outputs used to return epidemiological information on the spread of the epidemic to the competent public health bodies and to the Italian popu-lation, and to describe how the surveillance data contributes to the ongoing weekly regional monitoring and risk assessment system. METHODS: the COVID-19 integrated surveillance system is the result of a close and continuous collaboration between the Italian National Institute of Health (ISS), the Italian Ministry of Health, and the regional and local health authorities. Through a web platform, it collects individual data of laboratory confirmed cases of SARS-CoV-2 infection and gathers information on their residence, laboratory diagnosis, hospital-isation, clinical status, risk factors, and outcome. Results, for different levels of aggregation and risk categories, are published daily and weekly on the ISS website, and made avail-able to national and regional public health authorities; these results contribute one of the information sources of the regional monitoring and risk assessment system. RESULTS: the COVID-19 integrated surveillance system mon-itors the space-time distribution of cases and their character-istics. Indicators used in the weekly regional monitoring and risk assessment system include process indicators on com-pleteness and results indicators on weekly trends of newly di-agnosed cases per Region. CONCLUSIONS: the outputs of the integrated surveillance system for COVID-19 provide timely information to health authorities and to the general population on the evolution of the epidemic in Italy. They also contribute to the continuous re-assessment of risk related to transmission and impact of the epidemic thus contributing to the management of COV-ID-19 in Italy