suspected transmission of tuberculosis in a maternity ward from a smear positive nurse preliminary results of clinical evaluations and testing of neonates potentially exposed rome italy 1 january to 28 july 2011

We report preventive measures adopted after tuberculosis (TB) transmission from a nurse to a newborn assessed in late July 2011. All exposed neonates born between January and July 2011 were clinically evaluated and tested by QuantiFERON TB gold in-tube; newborns testing positive were referred for prophylaxis. Of 1,340 newborns, 118 (9%) tested positive and no other active cases of TB were found. Active surveillance for TB will be continued over the next three years for all those exposed

Surgical site infection after caesarean section. Space for post-discharge surveillance improvements and reliable comparisons

Surgical site infections (SSI) after caesarean section (CS) represent a substantial health system concern. Surveying SSI has been associated with a reduction in SSI incidence. We report the findings of three (2008, 2011 and 2013) regional active SSI surveillances after CS in community hospital of the Latium region determining the incidence of SSI. Each CS was surveyed for SSI occurrence by trained staff up to 30 post-operative days, and association of SSI with relevant characteristics was assessed using binomial logistic regression. A total of 3,685 CS were included in the study. A complete 30 day post-operation follow-up was achieved in over 94% of procedures. Overall 145 SSI were observed (3.9% cumulative incidence) of which 131 (90.3%) were superficial and 14 (9.7%) complex (deep or organ/space) SSI; overall 129 SSI (of which 89.9% superficial) were diagnosed post-discharge. Only higher NNIS score was significantly associated with SSI occurrence in the regression analysis. Our work provides the first regional data on CS-associated SSI incidence, highlighting the need for a post-discharge surveillance which should assure 30 days post-operation to not miss data on complex SSI, as well as being less labour intensive

SNAPSHOT USA 2020: A second coordinated national camera trap survey of the United States during the COVID-19 pandemic

Managing wildlife populations in the face of global change requires regular data on the abundance and distribution of wild animals, but acquiring these over appropriate spatial scales in a sustainable way has proven challenging. Here we present the data from Snapshot USA 2020, a second annual national mammal survey of the USA. This project involved 152 scientists setting camera traps in a standardized protocol at 1485 locations across 103 arrays in 43 states for a total of 52,710 trap-nights of survey effort. Most (58) of these arrays were also sampled during the same months (September and October) in 2019, providing a direct comparison of animal populations in 2 years that includes data from both during and before the COVID-19 pandemic. All data were managed by the eMammal system, with all species identifications checked by at least two reviewers. In total, we recorded 117,415 detections of 78 species of wild mammals, 9236 detections of at least 43 species of birds, 15,851 detections of six domestic animals and 23,825 detections of humans or their vehicles. Spatial differences across arrays explained more variation in the relative abundance than temporal variation across years for all 38 species modeled, although there are examples of significant site-level differences among years for many species. Temporal results show how species allocate their time and can be used to study species interactions, including between humans and wildlife. These data provide a snapshot of the mammal community of the USA for 2020 and will be useful for exploring the drivers of spatial and temporal changes in relative abundance and distribution, and the impacts of species interactions on daily activity patterns. There are no copyright restrictions, and please cite this paper when using these data, or a subset of these data, for publication

Simulation framework for pedestrian dynamics: Modelling and calibration

Pedestrian flow efficiency and safety are primary requirements in the effective configuration and management of urban gathering spaces, such as railway stations, stadiums, or shopping malls. Moreover, the quality and comfort level of available walking environments play a key role in the challenge of sustainable mobility. As a consequence, there has been growing interest in developing methodologies for analysing the walking transport mode. In this context, the authors deem crucial to build a pedestrian dynamics simulation framework that they can completely control, from the modelling and calibration under different flow conditions to the implementation of a user-friendly tool that allows testing the model in a variety of case studies. In this study, they focus on the implementation and calibration of an agent-based model that microscopically simulates the interactions between individuals and with the environment. They calibrate the model parameters with a behavioural-based approach that relies on observed motion behaviours. Additionally, they present preliminary findings from pedestrian flow experiments performed and monitored with dedicated video recording systems. The collected data are meant to improve the calibration and validate the simulator, but they also provide insights into the emergence of collective behaviours, which can have significant upshots on the theoretical framework