Resources Repository
-
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 | Infectious Diseases | Test Performance | Technology Assessment | Clinical Care | Health/Medicine -
ToolInteractive 2020COVID-19 Antibody Tests: Calculator for Interpreting Test Results
Antibody testing can determine previous exposure to SARS-CoV-2 virus. This interactive calculator, linked to the article …
Antibody testing can determine previous exposure to SARS-CoV-2 virus. This interactive calculator, linked to the article below* on antibody testing for SARS-CoV-2 virus, allows users to vary the prior probability of infection, the sensitivity of SARS-CoV-2 antibody testing, and the specificity of SARS-CoV-2 antibody testing. Key points made in the article accompanying the interactive include: (1) antibody testing is likely to be most useful 2 weeks after infection, (2) sensitivity and specificity will vary over time and…
Probability/Bayes | Infectious Diseases | Test Performance | Technology Assessment | Clinical Care | Health/Medicine | Science/Technology -
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 | Infectious Diseases | Test Performance | Clinical Care | Health/Medicine -
Tools/ModelsInteractive, Teaching Resource 2020Interactive Graphic: Interpreting a COVID-19 Test Result
Currently, the most common diagnostic test for COVID-19 relies on reverse transcriptase polymerase chain reaction …
Currently, the most common diagnostic test for COVID-19 relies on reverse transcriptase polymerase chain reaction (RT-PCR), and most often uses samples obtained from the respiratory tract by nasopharyngeal swab. This interactive graphic demonstrates the influence of the prior probability of COVID-19, the test sensitivity (i.e., the probability of a positive test conditional on disease presence), and the test specificity (i.e., the probability of a negative test conditional on disease absence) on the post-test probability of…
Probability/Bayes | Infectious Diseases | Test Performance | Clinical Care | Health/Medicine | Science/Technology | High School | College | Graduate | Doctoral | Professional | Graphics/Visualization | Quantitative Literacy -
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 | Infectious Diseases | Test Performance | Health/Medicine | Science/Technology | Global -
Resource PortalWeb Portal, Teaching Resource 2024Millennium Mathematics Project (MMP)
The Millennium Mathematics Project (MMP), a collaboration between the Faculties of Mathematics and Education at the …
The Millennium Mathematics Project (MMP), a collaboration between the Faculties of Mathematics and Education at the University of Cambridge, is a maths education and outreach initiative for ages 3 to 19 and the general public. The focus is on increasing mathematical understanding, confidence and enjoyment, developing problem-solving skills, and promoting creative and imaginative approaches to maths. The project consists of a family of complementary programmes, including the NRICH website, Plus online mathematics magazine, Wild Maths, and…
Probability/Bayes | Infectious Diseases | Test Performance | Mathematical Models | Decision Analysis | Risk Analysis | Child/Nutrition | Environmental Health | Health/Medicine | Science/Technology | Europe | High School | College | Graphics/Visualization | Quantitative Literacy -
Tutorial/PrimerPublication, Teaching Resource 2017Bayesian Methods for Calibrating Health Policy Models: A Tutorial
This article provides a tutorial on Bayesian approaches for model calibration. It describes the theoretical …
This article provides a tutorial on Bayesian approaches for model calibration. It describes the theoretical basis for Bayesian calibration approaches as well as pragmatic considerations that arise in the tasks of creating calibration targets, estimating the posterior distribution, and obtaining results to inform the policy decision. These considerations, as well as the specific steps for implementing the calibration, are described in the context of an extended worked example about the policy choice to provide (or…
Calibration/Validation | Infectious Diseases | Health/Medicine -
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 | Infectious Diseases | Microsimulation | Dynamic Simulation | Health/Medicine | Sub-Saharan Africa -
Teaching PackWeb Portal, Teaching Resource 2018Teaching Pack: Teaching Prototypes for Decision Analysis
These videos, developed by Professor Myriam Hunink during an immersion residency at the Center for …
These videos, developed by Professor Myriam Hunink during an immersion residency at the Center for Health Decision Science (CHDS) Media Hub, reflect experiments to augment brick and mortar teaching with multimedia materials that emphasize visualization of basic concepts. The first video introduces decision making under uncertainty, and illustrates the use of probability and odds to quantitatively express uncertainty. The second and third videos introduce probability revision visually and analytically, showing how an initial probability is…
Probability/Bayes | Health Systems | Test Performance | Value of Information | Chronic Disease/Risk | Health/Medicine | North America | Europe | High School | College | Graduate | Doctoral | Critical Thinking/Analysis | Graphics/Visualization | Quantitative Literacy