Diagnostic models predicting paediatric viral acute respiratory infections: a systematic review.

OBJECTIVES: To systematically review and evaluate diagnostic models used to predict viral acute respiratory infections (ARIs) in children. DESIGN: Systematic review. DATA SOURCES: PubMed and Embase were searched from 1 January 1975 to 3 February 2022. ELIGIBILITY CRITERIA: We included diagnostic models predicting viral ARIs in children (<18 years) who sought medical attention from a healthcare setting and were written in English. Prediction model studies specific to SARS-CoV-2, COVID-19 or multisystem inflammatory syndrome in children were excluded. DATA EXTRACTION AND SYNTHESIS: Study screening, data extraction and quality assessment were performed by two independent reviewers. Study characteristics, including population, methods and results, were extracted and evaluated for bias and applicability using the Checklist for Critical Appraisal and Data Extraction for Systematic Reviews of Prediction Modelling Studies and PROBAST (Prediction model Risk Of Bias Assessment Tool). RESULTS: Of 7049 unique studies screened, 196 underwent full text review and 18 were included. The most common outcome was viral-specific influenza (n=7; 58%). Internal validation was performed in 8 studies (44%), 10 studies (56%) reported discrimination measures, 4 studies (22%) reported calibration measures and none performed external validation. According to PROBAST, a high risk of bias was identified in the analytic aspects in all studies. However, the existing studies had minimal bias concerns related to the study populations, inclusion and modelling of predictors, and outcome ascertainment. CONCLUSIONS: Diagnostic prediction can aid clinicians in aetiological diagnoses of viral ARIs. External validation should be performed on rigorously internally validated models with populations intended for model application. PROSPERO REGISTRATION NUMBER: CRD42022308917.

The impact of community closures among nonessential and essential workers, Nashville, Tennessee: A cross-sectional study.

Background and Aims: The effects of community closures and relaxing social distancing restrictions on severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) by occupational risk remain unclear. Therefore, we evaluated the impact of community closures and reopening phases with the prevalence of testing SARS-CoV-2-positive among nonessential and essential workers. Methods: We constructed a cross-sectional cohort from March 20 to July 31, 2020, of 344 adults from Metropolitan Nashville, Tennessee. We performed an unconditional logistic regression model to evaluate the impact of community closures and phase implementation on testing SARS-CoV-2 positive by occupation to estimate adjusted prevalence odds ratios (aPORs) and 95% confidence intervals (CIs). Results: During a stay-at-home/Phase I order, those with non-essential occupations had 59% decreased prevalence odds (aPOR:0.41; 95% CI: 0.20-0.84) of testing SARS-CoV-2-positive compared to when no restrictions were in place. Persons with essential occupations had four times the prevalence odds of testing SARS-CoV-2-positive (aPOR:4.19; 95% CI:1.57-11.18) compared with nonessential occupations when no community restrictions were established. Conclusion: Stay-at-home restrictions were associated with a lower risk of SARS-CoV-2 infection in the community for nonessential workers. Essential employees remained at increased risk for SARS-CoV-2, including when no community restrictions were in place and vaccines were not available. This study supports targeting prevention measures for these high-risk occupations.