Resources Repository
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ExerciseNone, Teaching Resource 2024Lab: Giant Cell Arteritis Decision Tree Model
This tutorial walks through the development of a decision tree model focused on Giant Cell …
This tutorial walks through the development of a decision tree model focused on Giant Cell Arteritis. It describes how to build the model structure, assign probabilities and outcomes based on imperfect test characteristics and epidemiologic estimates, evaluate alternative treatment strategies, and conduct one-way sensitivity analyses to assess which model parameters may impact the optimal treatment choice. Amua, the Swahili word meaning “decide”/“solve”, is an open source modeling framework and probabilistic programming language for decision analysis…
Probability/Bayes | Health/Medicine | Mathematical Models | Decision Analysis | Clinical Care | Graduate | Doctoral | Professional -
ArticlePublication 2023Simulation-Based Comparative Effectiveness Analysis of Policies to Improve Global Maternal Health Outcomes
The Sustainable Development Goals include a target to reduce the global maternal mortality ratio (MMR) …
The Sustainable Development Goals include a target to reduce the global maternal mortality ratio (MMR) to less than 70 maternal deaths per 100,000 live births by 2030, with no individual country exceeding 140. However, on current trends the goals are unlikely to be met. The authors used an empirically calibrated Global Maternal Health microsimulation model, which simulates individual women in 200 countries and territories to evaluate the impact of different interventions and strategies from 2022…
Calibration/Validation | Health/Medicine | Health Outcomes | Mathematical Models | Microsimulation | Maternal/Reproductive Health | Health Systems | Clinical Care | Global -
ArticlePublication 2023Simulation-Based Estimates and Projections of Global, Regional and Country-Level Maternal Mortality by Cause, 1990-2050
While progress has been made globally to reduce maternal deaths, measurement remains a challenge given …
While progress has been made globally to reduce maternal deaths, measurement remains a challenge given the many causes and frequent underreporting of maternal deaths. The authors developed a structural microsimulation model of Global Maternal Health (GMatH) for 200 countries and territories using demographic, epidemiologic, clinical and health system data synthesized from the medical literature, Civil Registration Vital Statistics systems and Demographic and Health Survey data. The model was calibrated to empirical data from 1990 to…
Calibration/Validation | Health/Medicine | Health Outcomes | Evidence Synthesis | Microsimulation | Maternal/Reproductive Health | Health Systems | Clinical Care | Global -
Resource PackWeb Portal, Teaching Resource 2023Resource Pack: Maternal Health Models and CEA
This resource pack, curated by the Center for Health Decision Science, provides selected examples of …
This resource pack, curated by the Center for Health Decision Science, provides selected examples of modeling approaches used to conduct analyses relevant to maternal and reproductive health. Some papers focus on a particular problem (e.g., screening for prenatal syphilis, comparison of alternative strategies for safe abortion), while others explore strategies for reducing morbidity and mortality from the entire spectrum of pregnancy and childbirth-related complications. Several of the examples model the primary drivers of maternal mortality (e.g.,…
Calibration/Validation | Health/Medicine | Costing Methods | Evidence Synthesis | Mathematical Models | Microsimulation | Cost-Effectiveness Analysis | Maternal/Reproductive Health | Health Systems | Clinical Care | Science/Technology | Global | Sub-Saharan Africa | Middle East & North Africa | Latin America & Caribbean | Asia & Pacific -
ArticlePublication 2020Perceptions of COVID-19 around the World
This study evaluates public risk perception of COVID-19 around the world in ten countries across …
This study evaluates public risk perception of COVID-19 around the world in ten countries across Europe, America, and Asia. They found that significant predictors of risk perception included personal experience with the virus, individualistic and prosocial values, hearing about the virus from friends and family, trust in government, science, and medical professionals, personal knowledge of government strategy, and personal and collective efficacy. Although there was substantial variability across cultures, individualistic worldviews, personal experience, prosocial values,…
Risk Analysis | Health/Medicine | Decision Psychology | Preferences/Values | Infectious Diseases | Culture/Society | Global -
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 | Health/Medicine | Test Performance | Technology Assessment | Infectious Diseases | Clinical Care -
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 | Health/Medicine | Test Performance | Technology Assessment | Infectious Diseases | Clinical Care | Science/Technology -
EditorialPublication 2020Waiting for Certainty on COVID-19 Antibody Tests — At What Cost?
This perspective anticipates the availability of serologic antibody testing and considers its potential usefulness in mitigation …
This perspective anticipates the availability of serologic antibody testing and considers its potential usefulness in mitigation policy to reduce COVID-19 transmission. For example: Could we screen for serologic antibodies as a proxy for possible immunity and identify people who could return to the workplace with less severe mitigation measures? The authors acknowledge the uncertainties raised by many policy actors, including the WHO, such as, "Do antibodies confer immunity and, if so, for how long? How accurate is…
Probability/Bayes | Health/Medicine | Test Performance | Technology Assessment | Infectious Diseases | Health Systems | Policy/Regulation | Government/Law | Global | North America -
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 | Health/Medicine | Test Performance | Infectious Diseases | Clinical Care