Resources Repository
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ArticlePublication 2020Testing for SARS-CoV-2 Antibodies
Antibody testing can determine previous exposure to SARS-CoV-2 virus. Recently, the UK government has made …
Antibody testing can determine previous exposure to SARS-CoV-2 virus. Recently, the UK government has made antibody testing available to anyone wanting it, even if there is no clinical indication. The purpose of this article is to provide guidance for when to consider antibody testing in individuals with and without symptoms suggestive of current or past SARS-CoV-2 infection. Key points made by the authors include: (1) antibody testing is likely to be most useful 2 weeks…
Probability/Bayes | Test Performance | Technology Assessment | Infectious Diseases | Clinical Care | Health/Medicine -
ArticlePublication 2020Bayes' Theorem, COVID-19, and Screening Tests
This article reviews the implications of increased testing for COVID-19 using reverse transcriptase polymerase chain …
This article reviews the implications of increased testing for COVID-19 using reverse transcriptase polymerase chain reaction (rRT-PCR) through the application of Bayes’ Theorem for three hypothetical, stylized case scenarios. The scenarios involve three patients with a low, moderate, and high pre-test probability of COVID-19 infection. The category of low probability would include "asymptomatic individuals in a presumed low prevalence environment" and might vary from 10 to 20%. The category of moderate probability would include "individuals…
Probability/Bayes | Test Performance | Infectious Diseases | Clinical Care | Health/Medicine -
ArticlePublication 2020Interpreting COVID-19 Test Results: A Bayesian Approach
This article considers the following question with respect to interpreting the results of polymerase chain reaction …
This article considers the following question with respect to interpreting the results of polymerase chain reaction (PCR) assays from nasal and pharyngeal swabs for COVID-19 to inform clinical decision making: "While a positive result in an acutely ill patient is straightforward, how should physicians interpret negative tests in patients with suspected COVID-19 infection?" Using an assumption of near-perfect specificity of PCR assays for COVID-19, the authors acknowledge the uncertainty of test sensitivity. They consider two clinical scenarios…
Probability/Bayes | Test Performance | Infectious Diseases | Health/Medicine | Science/Technology | Global -
ArticlePublication 2020Clinical Decision Making: Using a Diagnostic Test
This article is part of a 6-part series on clinical decision making. The authors use …
This article is part of a 6-part series on clinical decision making. The authors use two clinical examples to review the principles of interpreting diagnostic test results. They outline an approach that can be used to determine how to select and apply tests and their results to the practice of internal medicine. Topics covered in the two case studies include sensitivity and specificity, positive predictive and negative predictive value of tests, and how to estimate…
Probability/Bayes | Test Performance | Clinical Care | Health/Medicine -
ArticlePublication 2020Expanding Oral Disease Treatment is Cost Effective
This study developed a stochastic microsimulation model of oral health conditions, type-2 diabetes (T2D), T2D-related …
This study developed a stochastic microsimulation model of oral health conditions, type-2 diabetes (T2D), T2D-related microvascular diseases, and CVD, to project the cost-effectiveness of expanding periodontal treatment coverage among patients with T2D and periodontitis. Previous randomized trials found that treating periodontitis improved glycemic control in patients with type 2 diabetes (T2D), thus lowering the risks of developing T2D-related microvascular diseases and cardiovascular disease (CVD). The micro-simulation model parameters were obtained from the nationally representative National…
Calibration/Validation | Mathematical Models | Microsimulation | Cost-Effectiveness Analysis | Chronic Disease/Risk | Health/Medicine | North America | Graduate -
ArticlePublication 2017Benefit and Harm of Intensive Blood Pressure Treatment: Derivation and Validation of Risk Models Using Data from the Sprint and Accord Trials
Intensive blood pressure (BP) treatment can avert cardiovascular disease (CVD) events but can cause some …
Intensive blood pressure (BP) treatment can avert cardiovascular disease (CVD) events but can cause some serious adverse events. The authors sought to create risk calculators to estimate individual patients’ chances of benefit and harm from intensive treatment. They developed statistical models of cardiovascular events and serious adverse events from individual participant data from the Systolic Blood Pressure Intervention Trial (SPRINT) of intensive blood pressure treatment (N = 9,069 with complete covariate data) and validated them…
Probability/Bayes | Health Outcomes | Evidence Synthesis | Chronic Disease/Risk -
ArticlePublication 2017Using Data-Driven Agent-Based Models to Forecast Emerging Infectious Diseases
This paper describes an agent-based model framework developed to forecast the 2014-15 Ebola epidemic, which …
This paper describes an agent-based model framework developed to forecast the 2014-15 Ebola epidemic, which was subsequently used in the Ebola forecasting challenge. Producing timely and reliable forecasts for an epidemic of an emerging infectious disease is a challenge. Epidemiologists and policy makers have to deal with poor data quality, limited understanding of the disease dynamics, a rapidly changing social environment and the uncertainty around the effects of various interventions in place. In this setting,…
Calibration/Validation | Microsimulation | Dynamic Simulation | Infectious Diseases | Health/Medicine | Sub-Saharan Africa -
ArticlePublication 2017Likelihood Approach for Calibration of Stochastic Epidemic Models
Stochastic transmission dynamic models are especially useful for studying the early emergence of novel pathogens …
Stochastic transmission dynamic models are especially useful for studying the early emergence of novel pathogens given the importance of chance events when the number of infectious individuals is small. However, methods for parameter estimation and prediction for these types of stochastic models remain limited. This paper describes a calibration and prediction framework for stochastic compartmental transmission models of epidemics. The proposed method applies a linear noise approximation to describe the size of the fluctuations, and…
Calibration/Validation | Dynamic Transmission | Dynamic Simulation | Infectious Diseases | Health Systems | Health/Medicine | Global -
ArticlePublication 2015Cancer Models and Real-World Data: Better Together
Decision-analytic models synthesize available data on disease burden and intervention effectiveness to project estimates of …
Decision-analytic models synthesize available data on disease burden and intervention effectiveness to project estimates of the long-term consequences of care. While models have been influential in informing US cancer screening guidelines under ideal conditions, incorporating detailed data on real-world screening practice has been limited given the complexity of screening processes and behaviors throughout diverse health delivery systems in the United States. The authors describe the synergies that exist between decision-analytic models and health care utilization…
Calibration/Validation | Evidence Synthesis | Mathematical Models | Chronic Disease/Risk | Health Systems | Clinical Care | Health/Medicine | Science/Technology | North America