Impact of the SARS-CoV-2 epidemic on tuberculosis treatment outcome in Northern Italy.
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ABSTRACT:
SUBMITTER: Magro P
PROVIDER: S-EPMC7377210 | biostudies-literature | 2020 Oct
REPOSITORIES: biostudies-literature
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Impact of the SARS-CoV-2 epidemic on tuberculosis treatment outcome in Northern Italy.
Magro Paola P Formenti Beatrice B Marchese Valentina V Gulletta Maurizio M Tomasoni Lina Rachele LR Caligaris Silvio S Castelli Francesco F Matteelli Alberto A
The European respiratory journal 20201001 4
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Project description:BackgroundThe aim of this study is to compare the 2021-2022 bronchiolitis season to the four previous years (2017-2018, 2018-2019, 2019-2020, 2020-2021) to see if there was an anticipation of the peak, an overall increase of cases, and an increased need of intensive care.MethodsA retrospective single-centre study in the San Gerardo Hospital Fondazione MBBM, Monza, Italy was performed. Emergency Departments (ED) visits of patients aged < 18 years and ≤ 12 months were analyzed: the incidence of bronchiolitis on total assessments, the urgency level at triage and the hospitalization rate were compared. Data of children admitted to the Pediatric Department due to bronchiolitis were analyzed in terms of need of intensive care, respiratory support (type and duration), length of hospital stay, main etiological agent, patient characteristics.ResultsDuring 2020-2021 (first pandemic period) an important reduction in the ED attendance for bronchiolitis was observed, while in 2021-2022 there was an increase in incidence of bronchiolitis (13% of visits in infants < 1 year) and in the rate of urgent accesses (p = 0.0002), but hospitalization rates did not differ compared to previous years. Furthermore, an anticipated peak in November 2021 was observed. In the 2021-2022 cohort of admitted children to the Pediatric Department, a statistically significative increased need of intensive care unit was detected (Odds Ratio 3.1, 95% CI 1.4-6.8 after adjustment for severity and clinical characteristics). Instead, respiratory support (type and duration) and length of hospital stay did not differ. RSV was the main etiological agent and RSV-bronchiolitis determined a more severe infection (type and duration of breathing support, intensive care need and length of hospital stay).ConclusionsDuring Sars-CoV-2 lockdowns (2020-2021), there was a dramatic decrease of bronchiolitis and others respiratory infections. In the following season, 2021-2022, an overall increase of cases with an anticipated peak was observed and data analysis confirmed that patients in 2021-2022 required more intensive care than children in the four previous seasons.
| S-EPMC9942300 | biostudies-literature
Project description:We report 25 cases of infection with SARS-CoV-2 Omicron variant containing spike protein L452R mutation in northern Lombardy, Italy. Prevalence of this variant was >30% in this region, compared with <0.5% worldwide. Many laboratories are using previously developed L452R-specific PCRs to discriminate Omicron from Delta mutations, but these tests may be unreliable.
| S-EPMC9155861 | biostudies-literature
Project description:Italy was the first European country affected by the Sars-Cov-2 pandemic, with the first autochthonous case identified on Feb 21st. Specific control measures restricting social contacts were introduced by the Italian government starting from the beginning of March. In the current study we analyzed public data from the four most affected Italian regions. We (i) estimated the time-varying reproduction number (R t ), the average number of secondary cases that each infected individual would infect at time t, to monitor the positive impact of restriction measures; (ii) applied the generalized logistic and the modified Richards models to describe the epidemic pattern and obtain short-term forecasts. We observed a monotonic decrease of R t over time in all regions, and the peak of incident cases ~2 weeks after the implementation of the first strict containment measures. Our results show that phenomenological approaches may be useful to monitor the epidemic growth in its initial phases and suggest that costly and disruptive public health controls might have had a positive impact in limiting the Sars-Cov-2 spread in Northern Italy.
| S-EPMC7256452 | biostudies-literature
Project description:BackgroundEritrea has achieved the global target (90%) for tuberculosis (TB) treatment success rate. Though, events of unsuccessful TB treatment outcomes (death, treatment failure, lost to follow up and not evaluated) could lead to further TB transmission and the development of resistant strains. Hence, factors related to these events should be explored and addressed. This study aims to fill the gap in evidence by identifying the determinants of unsuccessful TB treatment outcomes in Eritrea's Northern Red Sea region.MethodsA retrospective cohort study was conducted in Eritrea's Northern Red Sea region. Data collected using a data extraction tool was analyzed using Stata version 13. Frequencies, proportions, median and standard deviations were used to describe the data. Furthermore, univariable and multivariable logistic regression analysis were performed to determine the risk factors for unsuccessful TB treatment outcomes. Crude odds ratio (COR) and adjusted odds ratio (AOR) with their 95% confidence interval (CI) presented and p-value < 0.05 was considered statistically significant.ResultsAmong 1227 TB patients included in this study, 9.6% had unsuccessful TB treatment outcomes. In multivariable logistic regression analysis, TB cases 55-64 years old (AOR: 2.75[CI: 1.21-6.32], p = 0.016) and those ≥ 65 years old (AOR: 4.02[CI: 1.72-9.45], p = 0.001) had 2.7 and 4 times higher likelihood of unsuccessful TB treatment outcome respectively. In addition, HIV positive TB patients (AOR: 5.13[CI: 1.87-14.06], p = 0.002) were 5 times more likely to have unsuccessful TB treatment outcome. TB treatment in Ghindae Regional Referral Hospital (AOR: 5.01[2.61-9.61], p < 0.001), Massawa Hospital (AOR: 4.35[2.28-8.30], p< 0.001) and Nakfa Hospital (AOR: 2.53[1.15-5.53], p = 0.021) was associated with 5, 4 and 2.5 higher odds of unsuccessful TB treatment outcome respectively.ConclusionIn this setting, old age, HIV co-infection and health facility were the independent predictors of unsuccessful TB treatment outcome.
| S-EPMC9377576 | biostudies-literature
Project description:The outbreak and prevalence of SARS-CoV-2 have severely affected social security. Physical isolation is an effective control that affects the short-term human-to-human transmission of the epidemic, although weather presents a long-term effect. Understanding the effect of weather on the outbreak allow it to be contained at the earliest possible. China is selected as the study area, and six weather factors that receive the most attention from January 20, 2020 to April 30, 2020 are selected to investigate the correlation between weather and SARS-CoV-2 to provide a theoretical basis for long-term epidemic prevention and control. The results show that (1) the average growth rate (GR) of SARS-CoV-2 in each province is logarithmically distributed with a mean value of 5.15%. The GR of the southeastern region is higher than that of the northwestern region, which is consistent with the Hu Line. (2) The specific humidity, 2-m temperature (T), ultraviolet (UV) radiation, and wind speed (WS) adversely affect the GR. By contrast, the total precipitation (TP) and surface pressure (SP) promote the GR. (3) For every 1 unit increase in UV radiation, the GR decreases by 0.30% in 11 days, and the UV radiation in China is higher than that worldwide (0.92% higher per day). Higher population aggregation and urbanization directly affect the epidemic, and weather is an indirect factor.
| S-EPMC10374073 | biostudies-literature
Project description:On March 11, 2020, Italy imposed a national lockdown to curtail the spread of severe acute respiratory syndrome coronavirus 2. We estimate that, 14 days after lockdown, the net reproduction number had dropped below 1 and remained stable at »0.76 (95% CI 0.67-0.85) in all regions for >3 of the following weeks.
| S-EPMC7774526 | biostudies-literature
Project description:ObjectiveTo report mode of delivery and immediate neonatal outcome in women infected with COVID-19.DesignRetrospective study.SettingTwelve hospitals in northern Italy.ParticipantsPregnant women with COVID-19-confirmed infection who delivered.ExposureCOVID 19 infection in pregnancy.MethodsSARS-CoV-2-infected women who were admitted and delivered from 1 to 20 March 2020 were eligible. Data were collected from the clinical records using a standardised questionnaire on maternal general characteristics, any medical or obstetric co-morbidity, course of pregnancy, clinical signs and symptoms, treatment of COVID 19 infection, mode of delivery, neonatal data and breastfeeding.Main outcome and measuresData on mode of delivery and neonatal outcome.ResultsIn all, 42 women with COVID-19 delivered at the participating centres; 24 (57.1%, 95% CI 41.0-72.3) delivered vaginally. An elective caesarean section was performed in 18/42 (42.9%, 95% CI 27.7-59.0) cases: in eight cases the indication was unrelated to COVID-19 infection. Pneumonia was diagnosed in 19/42 (45.2%, 95% CI 29.8-61.3) cases: of these, 7/19 (36.8%, 95% CI 16.3-61.6) required oxygen support and 4/19 (21.1%, 95% CI 6.1-45.6) were admitted to a critical care unit. Two women with COVID-19 breastfed without a mask because infection was diagnosed in the postpartum period: their newborns tested positive for SARS-Cov-2 infection. In one case, a newborn had a positive test after a vaginal operative delivery.ConclusionsAlthough postpartum infection cannot be excluded with 100% certainty, these findings suggest that vaginal delivery is associated with a low risk of intrapartum SARS-Cov-2 transmission to the newborn.Tweetable abstractThis study suggests that vaginal delivery may be associated with a low risk of intrapartum SARS-Cov-2 transmission to the newborn.
| S-EPMC7267664 | biostudies-literature
Project description:Following the outbreak of Severe Acute Respiratory Syndrome CoronaVirus 2 (SARS-CoV-2) last December 2019 in China, Italy was the first European country to be severely affected, with the first local case diagnosed on 20 February 2020. The virus spread quickly, particularly in the North of Italy, with three regions (Lombardy, Veneto and Emilia-Romagna) being the most severely affected. These three regions accounted for >80% of SARS-CoV-2 positive cases when the tight lockdown was established (March 8). These regions include one of Europe's areas of heaviest air pollution, the Po valley. Air pollution has been recently proposed as a possible risk factor of SARS-CoV-2 infection, due to its adverse effect on immunity and to the possibility that polluted air may even carry the virus. We investigated the association between air pollution and subsequent spread of the SARS-CoV-2 infection within these regions. We collected NO2 tropospheric levels using satellite data available at the European Space Agency before the lockdown. Using a multivariable restricted cubic spline regression model, we compared NO2 levels with SARS-CoV-2 infection prevalence rate at different time points after the lockdown, namely March 8, 22 and April 5, in the 28 provinces of Lombardy, Veneto and Emilia-Romagna. We found little association of NO2 levels with SARS-CoV-2 prevalence up to about 130 μmol/m2, while a positive association was evident at higher levels at each time point. Notwithstanding the limitations of the use of aggregated data, these findings lend some support to the hypothesis that high levels of air pollution may favor the spread of the SARS-CoV-2 infection.
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Project description:The aim of this study is the characterization and genomic tracing by phylogenetic analyses of 59 new SARS-CoV-2 Italian isolates obtained from patients attending clinical centres in North and Central Italy until the end of April 2020. All but one of the newly-characterized genomes belonged to the lineage B.1, the most frequently identified in European countries, including Italy. Only a single sequence was found to belong to lineage B. A mean of 6 nucleotide substitutions per viral genome was observed, without significant differences between synonymous and non-synonymous mutations, indicating genetic drift as a major source for virus evolution. tMRCA estimation confirmed the probable origin of the epidemic between the end of January and the beginning of February with a rapid increase in the number of infections between the end of February and mid-March. Since early February, an effective reproduction number (Re) greater than 1 was estimated, which then increased reaching the peak of 2.3 in early March, confirming the circulation of the virus before the first COVID-19 cases were documented. Continuous use of state-of-the-art methods for molecular surveillance is warranted to trace virus circulation and evolution and inform effective prevention and containment of future SARS-CoV-2 outbreaks.
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Project description:We evaluated the performance of the exponentially weighted moving average (EWMA) model for comparing two families of predictors (i.e., structured and unstructured data from visits to the emergency department (ED)) for the early detection of SARS-CoV-2 epidemic waves. The study included data from 1,282,100 ED visits between 1 January 2011 and 9 December 2021 to a local health unit in Lombardy, Italy. A regression model with an autoregressive integrated moving average (ARIMA) error term was fitted. EWMA residual charts were then plotted to detect outliers in the frequency of the daily ED visits made due to the presence of a respiratory syndrome (based on coded diagnoses) or respiratory symptoms (based on free text data). Alarm signals were compared with the number of confirmed SARS-CoV-2 infections. Overall, 150,300 ED visits were encoded as relating to respiratory syndromes and 87,696 to respiratory symptoms. Four strong alarm signals were detected in March and November 2020 and 2021, coinciding with the onset of the pandemic waves. Alarm signals generated for the respiratory symptoms preceded the occurrence of the first and last pandemic waves. We concluded that the EWMA model is a promising tool for predicting pandemic wave onset.
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