PyMC: a modern, and comprehensive probabilistic programming framework in Python.

PyMC is a probabilistic programming library for Python that provides tools for constructing and fitting Bayesian models. It offers an intuitive, readable syntax that is close to the natural syntax statisticians use to describe models. PyMC leverages the symbolic computation library PyTensor, allowing it to be compiled into a variety of computational backends, such as C, JAX, and Numba, which in turn offer access to different computational architectures including CPU, GPU, and TPU.

The Changing Landscape of Pediatric Viral Enteropathogens in the Post-Rotavirus Vaccine Era.

Background: Acute gastroenteritis (AGE) is a common reason for children to receive medical care. However, the viral etiology of AGE illness is not well described in the post-rotavirus vaccine era, particularly in the outpatient (OP) setting.

Methods: Between 2012 and 2015, children 15 days through 17 years old presenting to Vanderbilt Children's Hospital, Nashville, Tennessee, with AGE were enrolled prospectively from the inpatient, emergency department, and OP settings, and stool specimens were collected.

A nonparametric updating method to correct clinical prediction model drift.

Objective: Clinical prediction models require updating as performance deteriorates over time. We developed a testing procedure to select updating methods that minimizes overfitting, incorporates uncertainty associated with updating sample sizes, and is applicable to both parametric and nonparametric models.

Materials And Methods: We describe a procedure to select an updating method for dichotomous outcome models by balancing simplicity against accuracy.

Concurrent assessment of epidemiological and operational uncertainties for optimal outbreak control: Ebola as a case study.

Determining how best to manage an infectious disease outbreak may be hindered by both epidemiological uncertainty (i.e. about epidemiological processes) and operational uncertainty (i.

Context matters: using reinforcement learning to develop human-readable, state-dependent outbreak response policies.

The number of all possible epidemics of a given infectious disease that could occur on a given landscape is large for systems of real-world complexity. Furthermore, there is no guarantee that the control actions that are optimal, on average, over all possible epidemics are also best for each possible epidemic. Reinforcement learning (RL) and Monte Carlo control have been used to develop machine-readable context-dependent solutions for complex problems with many possible realizations ranging from video-games to the game of Go.

Distinct mucosal microbial communities in infants with surgical necrotizing enterocolitis correlate with age and antibiotic exposure.

Objective: Necrotizing enterocolitis (NEC) is the most common surgical emergency in preterm infants, and pathogenesis associates with changes in the fecal microbiome. As fecal samples incompletely represent microbial communities in intestinal mucosa, we sought to determine the NEC tissue-specific microbiome and assess its contribution to pathogenesis.

Design: We amplified and sequenced the V1-V3 hypervariable region of the bacterial 16S rRNA gene extracted from intestinal tissue and corresponding fecal samples from 12 surgical patients with NEC and 14 surgical patients without NEC.

Body mass index and health-related quality of life.

Objective: There are conflicting data regarding the association between body mass index (BMI) and health-related quality of life (HRQoL), especially among certain population subgroups and for mental and physical health domains.

Methods: This study analysed the relationship between BMI and HRQoL (Patient-Reported Outcomes Measurement Information System mental and physical health scales) using ordinary least squares regression. Each model allowed for the possibility of a non-linear relationship between BMI and the outcome, adjusting for age, gender, comorbidities, diet and physical activity.

Multiple Introductions and Antigenic Mismatch with Vaccines May Contribute to Increased Predominance of G12P[8] Rotaviruses in the United States.

Rotavirus is the leading global cause of diarrheal mortality for unvaccinated children under 5 years of age. The outer capsid of rotavirus virions consists of VP7 and VP4 proteins, which determine viral G and P types, respectively, and are primary targets of neutralizing antibodies. Successful vaccination depends upon generating broadly protective immune responses following exposure to rotaviruses presenting a limited number of G- and P-type antigens.

Severe outcomes associated with respiratory viruses in newborns and infants: a prospective viral surveillance study in Jordan.

Objective: To assess virus-specific hospitalisation rates, risk factors for illness severity and seasonal trends in children hospitalised with acute respiratory infections (ARI).

Design: Prospective cohort study.

Setting: A government hospital serving low-income and middle-income population in Amman, Jordan.

Bacterial Burden in Critically Injured Ventilated Patients Does Not Correlate with Progression to Pneumonia.

Background: Ventilator-associated pneumonia (VAP) is common in critically injured patients. The pathogenesis of VAP is not completely understood. We hypothesized that mechanically ventilated trauma patients who develop pneumonia have a progressive increase in pathogen burden over the course of ventilation until a threshold for symptomatic pneumonia is reached, leading to clinical suspicion of VAP.

Measles outbreak response decision-making under uncertainty: a retrospective analysis.

Resurgent outbreaks of vaccine-preventable diseases that have previously been controlled or eliminated have been observed in many settings. Reactive vaccination campaigns may successfully control outbreaks but must necessarily be implemented in the face of considerable uncertainty. Real-time surveillance may provide critical information about at-risk population and optimal vaccination targets, but may itself be limited by the specificity of disease confirmation.

Diarrheagenic Escherichia coli and Acute Gastroenteritis in Children in Davidson County, Tennessee, United States: A Case-control Study.

Background: Diarrheagenic Escherichia coli (DEC) is an important cause of acute gastroenteritis in children; however, there is limited information available on the epidemiology, phylogenetics, serotyping and antibiotic susceptibility of DEC in children in the United States. The aim of this study was to determine the molecular epidemiology of DEC among children with and without acute gastroenteritis in Davidson County, Tennessee.

Methods: This prospective, frequency matched, case-control study recruited subjects 15 days to 17 years of age and detected DEC with polymerase chain reaction from stool samples.

The Listening and Spoken Language Data Repository: Design and Project Overview.

Purpose: The purpose of the Listening and Spoken Language Data Repository (LSL-DR) was to address a critical need for a systemwide outcome data-monitoring program for the development of listening and spoken language skills in highly specialized educational programs for children with hearing loss highlighted in Goal 3b of the 2007 Joint Committee on Infant Hearing position statement supplement.

Method: The LSL-DR is a multicenter, international data repository for recording and tracking the demographics and longitudinal outcomes achieved by children who have hearing loss who are enrolled in private, specialized programs focused on supporting listening and spoken language development. Since 2010, annual speech-language-hearing outcomes have been prospectively obtained by qualified clinicians and teachers across 48 programs in 4 countries.

AHRQ series on complex intervention systematic reviews-paper 5: advanced analytic methods.

Background And Objective: Advanced analytic methods for synthesizing evidence about complex interventions continue to be developed. In this paper, we emphasize that the specific research question posed in the review should be used as a guide for choosing the appropriate analytic method.

Methods: We present advanced analytic approaches that address four common questions that guide reviews of complex interventions: (1) How effective is the intervention? (2) For whom does the intervention work and in what contexts? (3) What happens when the intervention is implemented? and (4) What decisions are possible given the results of the synthesis?

Conclusion: The analytic approaches presented in this paper are particularly useful when each primary study differs in components, mechanisms of action, context, implementation, timing, and many other domains.

Essential information: Uncertainty and optimal control of Ebola outbreaks.

Early resolution of uncertainty during an epidemic outbreak can lead to rapid and efficient decision making, provided that the uncertainty affects prioritization of actions. The wide range in caseload projections for the 2014 Ebola outbreak caused great concern and debate about the utility of models. By coding and running 37 published Ebola models with five candidate interventions, we found that, despite this large variation in caseload projection, the ranking of management options was relatively consistent.

A Bayesian Double Fusion Model for Resting-State Brain Connectivity Using Joint Functional and Structural Data.

Current approaches separately analyze concurrently acquired diffusion tensor imaging (DTI) and functional magnetic resonance imaging (fMRI) data. The primary limitation of these approaches is that they do not take advantage of the information from DTI that could potentially enhance estimation of resting-state functional connectivity (FC) between brain regions. To overcome this limitation, we develop a Bayesian hierarchical spatiotemporal model that incorporates structural connectivity (SC) into estimating FC.

Quantifying the Value of Perfect Information in Emergency Vaccination Campaigns.

Foot-and-mouth disease outbreaks in non-endemic countries can lead to large economic costs and livestock losses but the use of vaccination has been contentious, partly due to uncertainty about emergency FMD vaccination. Value of information methods can be applied to disease outbreak problems such as FMD in order to investigate the performance improvement from resolving uncertainties. Here we calculate the expected value of resolving uncertainty about vaccine efficacy, time delay to immunity after vaccination and daily vaccination capacity for a hypothetical FMD outbreak in the UK.

Tonsillectomy for Obstructive Sleep-Disordered Breathing: A Meta-analysis.

Context: The effectiveness of tonsillectomy or adenotonsillectomy (hereafter, "tonsillectomy") for obstructive sleep-disordered breathing (OSDB) compared with watchful waiting with supportive care is poorly understood.

Objective: To compare sleep, cognitive or behavioral, and health outcomes of tonsillectomy versus watchful waiting with supportive care in children with OSDB.

Data Sources: Medline, Embase, and the Cochrane Library.

Postoperative Bleeding and Associated Utilization following Tonsillectomy in Children.

Objective To assess posttonsillectomy hemorrhage (PTH), associated nonoperative readmissions/revisits, and reoperations in children. Data Sources MEDLINE, EMBASE, and the Cochrane Library. Review Methods Two investigators independently screened studies against predetermined criteria and extracted key data.