Resources Repository
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ReviewPublication 2016Decision Support for Infectious Disease Control
This report from RAND reviews decision-support tools, including models and nonmodeling approaches, that are relevant to …
This report from RAND reviews decision-support tools, including models and nonmodeling approaches, that are relevant to infectious disease prevention, detection, and response and aligns these tools with real-world policy questions that the tools can help address. This overview is designed to help modelers and other technical experts understand the questions that policymakers will raise and the decisions they must make. The report also presents policymakers with the capabilities and limitations of the different tools that may…
Dynamic Simulation | Health/Medicine | Global Governance | Infectious Diseases | Mathematical Models | State-Transition | Dynamic Transmission | Microsimulation | Government/Law | Military/Defense | Global -
ArticlePublication 2022Vaccinations versus Lockdowns to Prevent COVID-19 Mortality
This analysis estimated the costs associated with preventing Covid-19 deaths by vaccinations versus lockdowns. Publicly …
This analysis estimated the costs associated with preventing Covid-19 deaths by vaccinations versus lockdowns. Publicly available datasets from the Israeli Ministry of Health were used to model the parameters of the pandemic in Israel. The Oxford COVID-19 Government Response Tracker was used for quantitative data on government policies. Data on the Israeli economy were taken from the Central Bureau of Statistics. The models demonstrate that the first lockdown prevented 1022 COVID-19 deaths at the cost…
Decision Theory | Health/Medicine | Infectious Diseases | Costing Methods | Health Outcomes | State-Transition | Decision Analysis | Policy/Regulation | Economics/Finance | Government/Law | Middle East & North Africa -
ArticlePublication 2021Rational Policymaking during a Pandemic
Policymaking during a pandemic can be extremely challenging. As COVID-19 is a new disease and …
Policymaking during a pandemic can be extremely challenging. As COVID-19 is a new disease and its global impacts are unprecedented, decisions are taken in a highly uncertain, complex, and rapidly changing environment. In such a context, in which human lives and the economy are at stake, the authors argue that using ideas and constructs from modern decision theory, even informally, will make policymaking a more responsible and transparent process.
Decision Theory | Health/Medicine | Infectious Diseases | Priority Setting/Ethics | Policy/Regulation | Government/Law | Science/Technology | 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 | Infectious Diseases | Test Performance | Technology Assessment | 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 | Infectious Diseases | Test Performance | Technology Assessment | 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 | Infectious Diseases | Test Performance | Technology Assessment | 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 | Infectious Diseases | Test Performance | Clinical Care -
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 | Health/Medicine | Infectious Diseases | Test Performance | Clinical Care | 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 | Health/Medicine | Infectious Diseases | Test Performance | Science/Technology | Global