Hospital acquired infections in COVID-19 patients in sub intensive care unit: analysis of two waves of admissions.

BACKGROUND AND AIM: The pandemic caused by SARS-COV-2 has increased Semi-Intensive Care Unit (SICU) admission, causing an increase in healthcare-associated infection (HAI). Mostly HAI reveals the same risk factors, but fewer studies have analyzed the possibility of multiple coinfections in these patients. The study aimed was to identify patterns of co-presence of different species describing at the same time the association between such patterns and patient demographics and, finally, comparing the patterns between the two cohorts of COVID-19 patients admitted at Policlinico during the first wave and the second one). METHODS: All the patients admitted to SICUs during two COVID-19 waves, from March to June 2020 months and from October to December 2020, were screened following the local infection control surveillance program; whoever manifested fever has undergone on microbiological culture to detect bacterial species. Statistical analysis was performed to observe the existence of microbiological patterns through DBSCAN method. RESULTS: 246 patients were investigated and 83 patients were considered in our study because they presented infection symptoms with a mean age of 67 years and 33.7% of female patients. During the first and second waves were found respectively 10 and 8 bacterial clusters with no difference regarding the most frequent species. CONCLUSIONS: The results show the importance of an analysis which considers the risk factors for the possibility of co- and superinfection (such as age and gender) to structure a good prognostic tool to predict which patients will encounter severe coinfections during hospitalization.

The first major vaccination campaign against smallpox in Lombardy: the mass vaccination campaign against coronavirus nothing new only terminology.

Terminology, technology, communication and organizational strategies are different but we tried to compare the mass vaccination campaign against smallpox with the one we are doing against coronavirus.

Are Epidemiological Estimates Able to Describe the Ability of Health Systems to Cope with COVID-19 Epidemic?

INTRODUCTION: The coronavirus disease 2019 (COVID-19) epidemic is an infectious disease which was declared a pandemic and hit countries worldwide from the beginning of the year 2020. Despite the emergency vigilance plans, health systems in all countries experienced a different ratio of lethality, amount of admissions to intensive care units and quarantine management of positive patients. The aim of this study is to investigate whether some epidemiological estimates could have been useful in understanding the capacity of the Italian Regional Health Services to manage the COVID-19 epidemic. METHODS: We have compared data between two different Italian regions in the Northern part of Italy (Lombardy and Veneto) and the national data to determine whether different health strategies might be significant in explaining dissimilar patterns of the COVID-19 epidemic in Italy. Data have been extracted from a public database and were available only in an aggregated form. RESULTS: The regions in question displayed two different health policies to face the COVID-19 epidemic: while Veneto's health service was largely territorially oriented, Lombardy's strategy was more hospital-centered. DISCUSSION: The key to facing epidemics like this one consists in identifying solutions outside of hospitals. This however requires there be well-trained general practitioners and enough healthcare personnel working outside hospitals.

CoViD-19, learning from the past: A wavelet and cross-correlation analysis of the epidemic dynamics looking to emergency calls and Twitter trends in Italian Lombardy region.

The first case of Coronavirus Disease 2019 in Italy was detected on February the 20th in Lombardy region. Since that date, Lombardy has been the most affected Italian region by the epidemic, and its healthcare system underwent a severe overload during the outbreak. From a public health point of view, therefore, it is fundamental to provide healthcare services with tools that can reveal possible new health system stress periods with a certain time anticipation, which is the main aim of the present study. Moreover, the sequence of law decrees to face the epidemic and the large amount of news generated in the population feelings of anxiety and suspicion. Considering this whole complex context, it is easily understandable how people "overcrowded" social media with messages dealing with the pandemic, and emergency numbers were overwhelmed by the calls. Thus, in order to find potential predictors of possible new health system overloads, we analysed data both from Twitter and emergency services comparing them to the daily infected time series at a regional level. Particularly, we performed a wavelet analysis in the time-frequency plane, to finely discriminate over time the anticipation capability of the considered potential predictors. In addition, a cross-correlation analysis has been performed to find a synthetic indicator of the time delay between the predictor and the infected time series. Our results show that Twitter data are more related to social and political dynamics, while the emergency calls trends can be further evaluated as a powerful tool to potentially forecast new stress periods. Since we analysed aggregated regional data, and taking into account also the huge geographical heterogeneity of the epidemic spread, a future perspective would be to conduct the same analysis on a more local basis.

COVID-19: new scenario old problems.

The short paper present the problem of hospital acquired infection in subintensive units og a research and teaching hospital.

Hospital Acquired Infections in COVID-19 patients in sub intensive care unit.

The aim of this study is to assess the association among species of bacteria and to identify the presence of clusters of patients in sub intensive care unit with different profiles of infection, and to study the relationship between such profiles and patient demographics (gender, age), kind of investigations and  material used to detect the infection. The findings need to analyse a bigger amount of data in the same setting to make evident that it is constant the infection only with Escherichia coli and Staphylocossus epidemidis and a third case in which more bacteria are inlvolved.

COVID-19: What happened to the healthcare workers of a research and teaching hospital in Milan, Italy?

The paper wants to present the data of infection of the Health Care Workers of a research and teaching hospital in Milan, Italy. The majority (2554, 55.9%) of 4572 HCWs were tested for SARS-CoV-2 and 8.8% were found positive. Most of the tested workers were women, but we found higher relative frequency of positivity for men, even after adjustment for age, working area, and occupation. The higher frequency of positive tests in the medicine area is probably explained by the higher concentration in that area of COVID-19 patients. Conversely, the low frequency of positive HCWs in intensive care units is  probably explained by the diffuse and continuous use of PPD. Our results show that HCWs in a research and teaching hospital in the most hit Region in Italy had a similar pattern of infection as all other HCWs all over the world. The problem of SARS-CoV-2 infections among the hospital personnel HCWs should remind us  the concerns about hospital acquired infections both for patients and HCWs.