Usefulness of Routine Laboratory Tests for Follow up of Patients Receiving Outpatient Parenteral Antimicrobial Therapy Run by Infectious Diseases Fellows.

Background: The infectious disease society of America (IDSA) recommends routine laboratory tests for all patients receiving outpatient parenteral antimicrobial therapy (OPAT) to monitor for adverse events. There are no data to support how often patients should take monitoring laboratory tests. In addition, the relevance of different laboratory tests commonly used for OPAT follow up is not clearly known.

Clinical Features and Treatment Outcomes of Pulmonary Complex With and Without Coinfections.

Coinfections are more common in patients with cystic fibrosis and bronchiectasis. Infiltrates on imaging studies are seen more commonly in patients with coinfections, but coinfections did not affect treatment outcomes of pulmonary complex.

Estimating pediatric cases of COVID-19 over time in the United States: Filling in a gap in public use data.

Background: COVID-19 continues to disturb nearly all aspects of life, leaving us striving to reach herd immunity. Currently, only weekly standardized incidence rate data per age group are publicly available, limiting assessment of herd immunity. Here, we estimate the time-series case counts of COVID-19 among age groups currently ineligible for vaccination in the USA.

Methodology minute: A statistical test primer for infection prevention and control.

Selecting the appropriate statistical tests for data analysis is a critical skill for the infection preventionist (IP), both for analyzing their own data as well as evaluating the scientific literature methodology. Obtaining results from data analyses has never been easier thanks to computational improvements, but the interpretation of results relies on a keen awareness that the approach was sound. The purpose of this primer is to introduce the infection preventionist to the ideas behind hypothesis testing with a focus on statistical test selection.

Excess mortality in the United States in 2020: Forecasting and anomaly detection.

All-cause mortality may be better than disease-specific data for computing excess COVID-19 mortality. We documented approximately 350,000 excess deaths using a 20-year forecast of all-cause mortality compared to provisional estimates. We must develop more granular approaches to the collection of mortality data for real-time evaluation of excess deaths.

Thresholds versus Anomaly Detection for Surveillance of Pneumonia and Influenza Mortality.

Computational surveillance of pneumonia and influenza mortality in the United States using FluView uses epidemic thresholds to identify high mortality rates but is limited by statistical issues such as seasonality and autocorrelation. We used time series anomaly detection to improve recognition of high mortality rates. Results suggest that anomaly detection can complement mortality reporting.