Real-Time Use of a Dynamic Model To Measure the Impact of Public Health Interventions on Measles Outbreak Size and Duration - Chicago, Illinois, 2024.

Measles is a highly infectious, vaccine-preventable disease that can cause severe illness, hospitalization, and death. A measles outbreak associated with a migrant shelter in Chicago occurred during February-April 2024, in which a total of 57 confirmed cases were identified, including 52 among shelter residents, three among staff members, and two among community members with a known link to the shelter. CDC simulated a measles outbreak among shelter residents using a dynamic disease model, updated in real time as additional cases were identified, to produce outbreak forecasts and assess the impact of public health interventions.

Assessment of sewer connectivity in the United States and its implications for equity in wastewater-based epidemiology.

Wastewater-based epidemiology is a promising public health tool that can yield a more representative view of the population than case reporting. However, only about 80% of the U.S.

Nationwide Trends in COVID-19 Cases and SARS-CoV-2 RNA Wastewater Concentrations in the United States.

Wastewater-based epidemiology has emerged as a promising technology for population-level surveillance of COVID-19. In this study, we present results of a large nationwide SARS-CoV-2 wastewater monitoring system in the United States. We profile 55 locations with at least six months of sampling from April 2020 to May 2021.

A conserved Bacteroidetes antigen induces anti-inflammatory intestinal T lymphocytes.

The microbiome contributes to the development and maturation of the immune system. In response to commensal bacteria, intestinal CD4 T lymphocytes differentiate into functional subtypes with regulatory or effector functions. The development of small intestine intraepithelial lymphocytes that coexpress CD4 and CD8αα homodimers (CD4IELs) depends on the microbiota.

Uses of mathematical modeling to estimate the impact of mass drug administration of antibiotics on antimicrobial resistance within and between communities.

Background: Antibiotics are a key part of modern healthcare, but their use has downsides, including selecting for antibiotic resistance, both in the individuals treated with antibiotics and in the community at large. When evaluating the benefits and costs of mass administration of azithromycin to reduce childhood mortality, effects of antibiotic use on antibiotic resistance are important but difficult to measure, especially when evaluating resistance that "spills over" from antibiotic-treated individuals to other members of their community. The aim of this scoping review was to identify how the existing literature on antibiotic resistance modeling could be better leveraged to understand the effect of mass drug administration (MDA) on antibiotic resistance.

Infectious Disease Modeling: Recommendations for Public Health Decision-Makers.

Infectious disease modeling plays an important role in the response to infectious disease outbreaks, perhaps most notably during the coronavirus disease 2019 (COVID-19) pandemic. In our experience working with state and local governments during COVID-19 and previous public health crises, we have observed that, while the scientific literature focuses on models' accuracy and underlying assumptions, an important limitation on the effective application of modeling to public health decision-making is the ability of decision-makers and modelers to work together productively. We therefore propose a set of guiding principles, informed by our experience, for working relationships between decision-makers and modelers.

Pilot study of autologous fecal microbiota transplants in nursing home residents: Feasibility and safety.

Introduction: Antibiotic resistant bacterial infections (ARBIs) are extremely common in nursing home residents. These infections typically occur after a course of antibiotics, which eradicate both pathological and beneficial organisms. The eradication of beneficial organisms likely facilitates subsequent ARBIs.

Analysis of multiple bacterial species and antibiotic classes reveals large variation in the association between seasonal antibiotic use and resistance.

Understanding how antibiotic use drives resistance is crucial for guiding effective strategies to limit the spread of resistance, but the use-resistance relationship across pathogens and antibiotics remains unclear. We applied sinusoidal models to evaluate the seasonal use-resistance relationship across 3 species (Staphylococcus aureus, Escherichia coli, and Klebsiella pneumoniae) and 5 antibiotic classes (penicillins, macrolides, quinolones, tetracyclines, and nitrofurans) in Boston, Massachusetts. Outpatient use of all 5 classes and resistance in inpatient and outpatient isolates in 9 of 15 species-antibiotic combinations showed statistically significant amplitudes of seasonality (false discovery rate (FDR) < 0.

Wastewater network infrastructure in public health: Applications and learnings from the COVID-19 pandemic.

Accurate estimates of COVID-19 burden of infections in communities can inform public health strategy for the current pandemic. Wastewater based epidemiology (WBE) leverages sewer infrastructure to provide insights on rates of infection by measuring viral concentrations in wastewater. By accessing the sewer network at various junctures, important insights regarding COVID-19 disease activity can be gained.

Making waves: Defining the lead time of wastewater-based epidemiology for COVID-19.

Individuals infected with SARS-CoV-2, the virus that causes COVID-19, may shed the virus in stool before developing symptoms, suggesting that measurements of SARS-CoV-2 concentrations in wastewater could be a "leading indicator" of COVID-19 prevalence. Multiple studies have corroborated the leading indicator concept by showing that the correlation between wastewater measurements and COVID-19 case counts is maximized when case counts are lagged. However, the meaning of "leading indicator" will depend on the specific application of wastewater-based epidemiology, and the correlation analysis is not relevant for all applications.

Viral dynamics of acute SARS-CoV-2 infection and applications to diagnostic and public health strategies.

SARS-CoV-2 infections are characterized by viral proliferation and clearance phases and can be followed by low-level persistent viral RNA shedding. The dynamics of viral RNA concentration, particularly in the early stages of infection, can inform clinical measures and interventions such as test-based screening. We used prospective longitudinal quantitative reverse transcription PCR testing to measure the viral RNA trajectories for 68 individuals during the resumption of the 2019-2020 National Basketball Association season.

Stool Banking for Fecal Microbiota Transplantation: Methods and Operations at a Large Stool Bank.

Objectives: Fecal microbiota transplantation (FMT) is a recommended therapy for recurrent infection and is being investigated as a potential therapy for dozens of microbiota-mediated indications. Stool banks centralize FMT donor screening and FMT material preparation with the goal of expanding access to FMT material while simultaneously improving its safety, quality, and convenience. Although there are published consensuses on donor screening guidelines, there are few reports about the implementation of those guidelines in functioning stool banks.

16S rRNA sequencing of samples from universal stool bank donors.

Objectives: Universal stool banks provide stool to physicians for use in treating recurrent Clostridioides difficile infection via fecal microbiota transplantation. Stool donors providing the material are rigorously screened for diseases and disorders with a potential microbiome etiology, and they are likely healthier than the controls in most microbiome datasets. 16S rRNA sequencing was performed on samples from a selection of stool donors at a large stool bank, OpenBiome, to characterize their gut microbial community and to compare samples across different timepoints and sequencing runs.

Fecal Microbiota Transplants Annually and Their Positive Clinical Impact.

Introduction: Although fecal microbiota transplantation (FMT) is a recommended, clinically efficacious, and cost-effective treatment for recurrent Clostridioides difficile infection (CDI), the scale of FMT use in the United States is unknown.

Methods: We developed a population-level CDI model.

Results: We estimated that 48,000 FMTs could be performed annually, preventing 32,000 CDI recurrences.

Power calculations for detecting differences in efficacy of fecal microbiota donors.

Fecal microbiota transplantation (FMT) is a recommended therapy for recurrent infection and is being investigated as a potential therapy for dozens of other indications, notably inflammatory bowel disease. The immense variability in human stool, combined with anecdotal reports from FMT studies, have suggested the existence of "donor effects", in which stool from some FMT donors is more efficacious than stool from other donors. In this study, simulated clinical trials were used to estimate the number of patients that would be required to detect donor effects under a variety of study designs.

Modeling Donor Screening Strategies to Reduce the Risk of Severe Acute Respiratory Syndrome Coronavirus 2 Transmission via Fecal Microbiota Transplantation.

The potential for transmission of severe acute respiratory syndrome coronavirus 2 shed in stool via fecal microbiota transplantation is not yet known, and the effectiveness of various testing strategies to prevent fecal microbiota transplantation-based transmission has also not yet been quantified. In this study, we use a mathematical model to simulate the utility of different testing strategies.

Shiga Toxin-Producing Escherichia coli Transmission via Fecal Microbiota Transplant.

Fecal microbiota transplantation (FMT) is recommended therapy for multiply recurrent Clostridioides difficile infection. We report adverse events in 7 patients who received FMT from a stool donor who was colonized with Shiga toxin-producing Escherichia coli (STEC). No patients died of FMT-transmitted STEC.

The role of "spillover" in antibiotic resistance.

Antibiotic use is a key driver of antibiotic resistance. Understanding the quantitative association between antibiotic use and resulting resistance is important for predicting future rates of antibiotic resistance and for designing antibiotic stewardship policy. However, the use-resistance association is complicated by "spillover," in which one population's level of antibiotic use affects another population's level of resistance via the transmission of bacteria between those populations.

Re-Evaluating the Evidence for Faecal Microbiota Transplantation 'Super-Donors' in Inflammatory Bowel Disease.

Background: Faecal microbiota transplantation [FMT] is a recommended treatment for recurrent Clostridioides difficile infection, and there is promise that FMT may be effective for conditions such as inflammatory bowel disease [IBD]. Previous FMT clinical trials have considered the possibility of a 'donor effect', that is, that FMT material from different donors has different clinical efficacies.

Methods: Here we re-evaluate evidence for donor effects in published FMT clinical trials for IBD.

16S rRNA sequencing analysis: the devil is in the details.

User-friendly computational tools for 16S ribosomal RNA (rRNA) sequencing analysis enable researchers who are not bioinformaticians to analyze and interpret sequencing data from microbial communities. These tools' easy-to-use interfaces belie the sophisticated and rapidly-evolving science of their underlying algorithms. When analyzing 16S data from a simple microbiome experiment, we found that superficially unimportant decisions about the bioinformatic pipeline led to results with radically different biological interpretations.

Case-based surveillance of antimicrobial resistance with full susceptibility profiles.

Surveillance of antimicrobial resistance (AMR) is essential for clinical decision-making and for public health authorities to monitor patterns in resistance and evaluate the effectiveness of interventions and control measures. Existing AMR surveillance is typically based on reports from hospital laboratories and public health laboratories, comprising reports of pathogen frequencies and resistance frequencies among each species detected. Here we propose an improved framework for AMR surveillance, in which the unit of surveillance is patients with specific conditions, rather than biological samples of a particular type.

Levels of outpatient prescribing for four major antibiotic classes and rates of septicemia hospitalization in adults in different US states - a statistical analysis.

Background: Rates of sepsis/septicemia hospitalization in the US have risen significantly during recent years. Antibiotic resistance and use may contribute to those rates through various mechanisms, including lack of clearance of resistant infections following antibiotic treatment, with some of those infections subsequently devolving into sepsis. At the same time, there is limited information on the effect of prescribing of certain antibiotics vs.