Prospective Spatiotemporal Cluster Detection Using SaTScan: Tutorial for Designing and Fine-Tuning a System to Detect Reportable Communicable Disease Outbreaks.

Staff at public health departments have few training materials to learn how to design and fine-tune systems to quickly detect acute, localized, community-acquired outbreaks of infectious diseases. Since 2014, the Bureau of Communicable Disease at the New York City Department of Health and Mental Hygiene has analyzed reportable communicable diseases daily using SaTScan. SaTScan is a free software that analyzes data using scan statistics, which can detect increasing disease activity without a priori specification of temporal period, geographic location, or size.

A Trial of Automated Outbreak Detection to Reduce Hospital Pathogen Spread.

Background: Detection and containment of hospital outbreaks currently depend on variable and personnel-intensive surveillance methods. Whether automated statistical surveillance for outbreaks of health care-associated pathogens allows earlier containment efforts that would reduce the size of outbreaks is unknown.

Methods: We conducted a cluster-randomized trial in 82 community hospitals within a larger health care system.

Understanding the exceptional pre-vaccination Era East Asian COVID-19 outcomes.

During the first year of the pandemic, East Asian countries have reported fewer infections, hospitalizations, and deaths from COVID-19 disease than most countries in Europe and the Americas. Our goal in this paper is to generate and evaluate hypothesis that may explain this striking fact. We consider five possible explanations: (1) population age structure (younger people tend to have less severe COVID-19 disease upon infection than older people); (2) the early adoption of lockdown strategies to control disease spread; (3) genetic differences between East Asian population and European and American populations that confer protection against COVID-19 disease; (4) seasonal and climactic contributors to COVID-19 spread; and (5) immunological differences between East Asian countries and the rest of the world.

Sequential Data-Mining for Adverse Events After Recombinant Herpes Zoster Vaccination Using the Tree-Based Scan Statistic.

Tree-based scan statistics have been successfully used to study the safety of several vaccines without prespecifying health outcomes of concern. In this study, the binomial tree-based scan statistic was applied sequentially to detect adverse events in days 1-28 compared with days 29-56 after recombinant herpes zoster (RZV) vaccination, with 5 looks at the data and formal adjustment for the repeated analyses over time. IBM MarketScan data on commercially insured persons ≥50 years of age receiving RZV during January 1, 2018, to May 5, 2020, were used.

As Omicron Takes Hold and Other New Variants Arise, COVID-19 Testing Remains the Universally Agreed Tool to Effect Transition From Pandemic to Endemic State.

The COVID-19 pandemic has caused more than 448 million cases and 6 million deaths worldwide to date. Omicron is now the dominant SARS-CoV-2 variant, making up more than 90% of cases in countries reporting sequencing data. As the pandemic continues into its third year, continued testing is a strategic and necessary tool for transitioning to an endemic state of COVID-19.

A Broad Safety Assessment of the Recombinant Herpes Zoster Vaccine.

The recombinant herpes zoster vaccine (RZV), approved as a 2-dose series in the United States in October 2017, has proven highly effective and generally safe. However, a small risk of Guillain-Barré syndrome after vaccination was identified after approval, and questions remain about other possible adverse events. This data-mining study assessed RZV safety in the United States using the self-controlled tree-temporal scan statistic, scanning data on thousands of diagnoses recorded during follow-up to detect any statistically unusual temporal clustering of cases within a large hierarchy of diagnoses.

Mining Clinical Data for Novel Posttraumatic Stress Disorder Medications.

Background: Despite the prevalence and negative impact of posttraumatic stress disorder (PTSD), there are few medications approved by the U.S. Food and Drug Administration for treatment, and approved medications do not work well enough.

A novel data mining application to detect safety signals for newly approved medications in routine care of patients with diabetes.

Background: Clinical trials are often underpowered to detect serious but rare adverse events of a new medication. We applied a novel data mining tool to detect potential adverse events of canagliflozin, the first sodium glucose co-transporter 2 (SGLT2 inhibitor) in the United States, using real-world data from shortly after its market entry and before public awareness of its potential safety concerns.

Methods: In a U.

Exact sequential test for clinical trials and post-market drug and vaccine safety surveillance with Poisson and binary data.

In sequential analysis, hypothesis testing is performed repeatedly in a prospective manner as data accrue over time to quickly arrive at an accurate conclusion or decision. In this tutorial paper, detailed explanations are given for both designing and operating sequential testing. We describe the calculation of exact thresholds for stopping or signaling, statistical power, expected time to signal, and expected sample sizes for sequential analysis with Poisson and binary type data.

Detecting COVID-19 Clusters at High Spatiotemporal Resolution, New York City, New York, USA, June-July 2020.

A surveillance system that uses census tract resolution and the SaTScan prospective space-time scan statistic detected clusters of increasing severe acute respiratory syndrome coronavirus 2 test percent positivity in New York City, NY, USA. Clusters included one in which patients attended the same social gathering and another that led to targeted testing and outreach.

A General Propensity Score for Signal Identification Using Tree-Based Scan Statistics.

The tree-based scan statistic (TreeScan; Martin Kulldorff, Harvard Medical School, Boston, Massachusetts) is a data-mining method that adjusts for multiple testing of correlated hypotheses when screening thousands of potential adverse events for signal identification. Simulation has demonstrated the promise of TreeScan with a propensity score (PS)-matched cohort design. However, it is unclear which variables to include in a PS for applied signal identification studies to simultaneously adjust for confounding across potential outcomes.

A Broad Safety Assessment of the 9-Valent Human Papillomavirus Vaccine.

Parents indicate that safety is their top concern about human papillomavirus (HPV) vaccination. A data-mining method not requiring prespecification of health outcome(s) or postexposure period(s) of potentially increased risk can be used to identify possible associations between an exposure and any of thousands of medically attended health outcomes; this method was applied to data on the 9-valent HPV vaccine (HPV9) to detect potential safety problems. Data on 9- to 26-year-olds who had received HPV9 vaccine between November 4, 2016, and August 5, 2018, inclusive, were extracted from the MarketScan database and analyzed for statistically significant clustering of incident diagnoses within the hierarchy of diagnoses coded using the International Classification of Diseases and temporally within the 1 year after vaccination, using the self-controlled tree-temporal scan statistic and TreeScan software.

Active Surveillance of the Safety of Medications Used During Pregnancy.

The scientific community relies on postmarketing approaches to define the risk of using medications in pregnancy because information available at the time of drug approval is limited. Most studies carried out in pregnancy focus on a single outcome or selected outcomes. However, women must balance the benefit of treatment against all possible adverse effects.

Leveraging epidemiological principles to evaluate Sweden's COVID-19 response.

In the response to COVID-19, countries have implemented response strategies along a continuum of population- and venue-level specificity ranging from suppression to mitigation strategies. Suppression strategies generally include population-wide shelter-in-place mandates or lockdowns, closure of nonessential physical venues, travel bans, testing and contact tracing, and quarantines. Sweden followed a mitigation strategy focused on risk-tailored approaches to mitigate specific acquisition risks among the elderly, minimizing the disruption to education and the delivery of other health care services, and recommendations for social distancing to minimize the disease burden.

An Overview Of Vaccine Development, Approval, And Regulation, With Implications For COVID-19.

The Food and Drug Administration (FDA) approves vaccines when their benefits outweigh the risks for their intended use. In this article we review the standard FDA approach to vaccine evaluation, which underpins its current approaches to assessment of vaccines to prevent coronavirus disease 2019 (COVID-19). The FDA has established pathways to accelerate vaccine availability before approval, such as Emergency Use Authorization, and to channel resources to high-priority products and allow more flexibility in the evidence required for approval, including accelerated approval based on surrogate markers of effectiveness.

Data Mining for Adverse Events of Tumor Necrosis Factor-Alpha Inhibitors in Pediatric Patients: Tree-Based Scan Statistic Analyses of Danish Nationwide Health Data.

Background And Objectives: Tumor necrosis factor-alpha (TNF-α) inhibitors are efficacious and considered generally safe in adults. However, pediatric-specific safety evidence is scarce. The aim of this study was to screen for signals of previously unknown adverse events of TNF-α inhibitors in pediatric patients.

Screening Medications for Association with Progression to Wet Age-Related Macular Degeneration.

Purpose: There is an urgent need for treatments that prevent or delay development to advanced age-related macular degeneration (AMD). Drugs already on the market for other conditions could affect progression to neovascular AMD (nAMD). If identified, these drugs could provide insights for drug development targets.

Individual and Neighborhood Factors Associated With Failure to Vaccinate Against Influenza During Pregnancy.

Uptake of influenza vaccine among pregnant women remains low. We investigated whether unvaccinated pregnant women were clustered geographically and determined factors associated with failure to vaccinate using spatial and multivariate logistic regression analyses. Pregnant women who were members of Kaiser Permanente Northern California in 2015 or 2016 were included in the study.

Automated outbreak detection of hospital-associated pathogens: Value to infection prevention programs.

Objective: To assess the utility of an automated, statistically-based outbreak detection system to identify clusters of hospital-acquired microorganisms.

Design: Multicenter retrospective cohort study.

Setting: The study included 43 hospitals using a common infection prevention surveillance system.

The EMPagliflozin compaRative effectIveness and SafEty (EMPRISE) study programme: Design and exposure accrual for an evaluation of empagliflozin in routine clinical care.

Background: The EMPA-REG OUTCOME trial showed that empagliflozin reduced the risk of cardiovascular death and hospitalization for heart failure (HHF) in diabetic patients with cardiovascular disease. EMPRISE is a study programme on the effectiveness, safety and healthcare utilization of empagliflozin in routine care, leveraging real-world data from two commercial and one federal US data sources from 2014 to 2019.

Objectives: To describe rationale and design of EMPRISE, assess ability to minimize confounding and evaluate the time to reach sufficient statistical power for a key study outcome, HHF, using baseline information from the first year of EMPRISE.

Comment on Sarathkumara et al.: Exposure to Hantavirus is a Risk Factor Associated with Kidney Diseases in Sri Lanka: A Cross Sectional Study.

In a recent paper, Sarathkumara et al [...

Exact sequential analysis for multiple weighted binomial end points.

Sequential analysis is used in clinical trials and postmarket drug safety surveillance to prospectively monitor efficacy and safety to quickly detect benefits and problems, while taking the multiple testing of repeated analyses into account. When there are multiple outcomes, each one may be given a weight corresponding to its severity. This paper introduces an exact sequential analysis procedure for multiple weighted binomial end points; the analysis incorporates a drug's combined benefit and safety profile.

Variation in Prescription Drug Prices by Retail Pharmacy Type: A National Cross-sectional Study.

Background: Cash prices for prescription drugs vary widely in the United States.

Objective: To describe cash price variation by retail pharmacy type for 10 generic and 6 brand-name drugs throughout the United States and stratified by ZIP code.

Design: Cross-sectional study.