[Results of PCR Pool Testing In Primary and Special Needs Schools In Bavaria For The School Year 2021/2022: Sentinel Surveillance In Face-To-Face Teaching During The Sars-CoV-2 Pandemic]. / Ergebnisse von PCR-Pooltestungen an bayerischen Grund- und Förderschulen im Schuljahr 2021/2022 zur Surveillance im Präsenzunterricht während der SARS-CoV-2-Pandemie.

In the school years 2019/20 and 2020/21, children were physically, psychologically, and socially stressed by school closures caused by the SARS-CoV-2 pandemic. To ensure attendance with optimal infection protection, PCR pool testing was conducted during the 2021/22 school year at Bavarian elementary schools and schools for pupils with special needs for timely detection of SARS-CoV-2 infection. This study analyzes the results of PCR pool testing over time stratified by region, school type, and age of children. The data were obtained from classes in elementary and special needs schools, involving pupils aged 6 to 11 years, who participated in the Bavaria-wide PCR pool testing from 09/20/21 to 04/08/22. Samples were collected twice weekly, consisting of PCR pool samples and individual PCR samples, which were only evaluated in case of a positive pool test. A class was considered positive if at least one individual sample from that class was positive within a calendar week (CW). A school (class) was considered to be infection-prone if three or more classes in that school (students in that class) were positive within a CW. The data included 2,430 elementary schools (339 special needs schools) with 23,021 (2,711) classes and 456,478 (29,200) children. A total of 1,157,617 pools (of which 3.37% were positive) and 724,438 individual samples (6.76% positive) were analyzed. Larger schools exhibited higher PR compared to smaller schools. From January 2022, the Omicron variant led to a massive increase in PR across Bavaria. The incidence rates per 100,000 person-weeks within the individual school samples were significantly lower than the concurrently reported age-specific and general infection incidences in the overall Bavarian population. PCR pool testing revealed relatively few positive pools, with an average of four children per one hundred pools testing positive. Schools and classes were rarely considered infection-prone, even during periods of high incidences outside of schools. The combination of PCR pool testing and hygiene measures allowed for a largely safe in-person education for pupils in primary and special needs schools in the school year 2021/22.

Methods to incorporate patient preferences into medical decision algorithms and models and their quantification, balancing and evaluation: a scoping review protocol.

OBJECTIVE: The objective of this scoping review is to identify and map methods used to incorporate patient preferences into medical algorithms and models as well report on their quantification, balancing, and evaluation in the literature. It will focus on computational methods used for incorporating patient preferences into algorithms and models at an individual level as well as the types of medical algorithms and models where these methods have been applied. INTRODUCTION: Medical algorithms and models are increasingly being used to support clinical and shared decision-making; however, their effectiveness, accuracy, acceptance, and comprehension may be limited if patients' preferences are not considered. To address this issue, it is important to explore methods integrating patient preferences. INCLUSION CRITERIA: This review will investigate patient preferences and their integration into medical algorithms and models for individual-level clinical decision-making. The scoping review will include diverse sources, such as peer-reviewed articles, clinical practice guidelines, gray literature, government reports, guidelines, and expert opinions for a comprehensive investigation of the subject. METHODS: This scoping review will follow JBI methodology. A comprehensive search will be conducted in PubMed, Web of Science, ACM Digital Library, IEEE Xplore, the Cochrane Library, OpenGrey, the National Technical Reports Library, and the first 20 pages of Google Scholar. The search strategy will include keywords related to patient preferences, medical algorithms and models, decision-making, and software tools and frameworks. Data extraction and analysis will be guided by the JBI framework, which includes an explorative and qualitative analysis. REVIEW REGISTRATION: Open Science Framework https://osf.io/qg3b5.