Resources Repository
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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…
Infectious Diseases | Decision Theory | Costing Methods | Health Outcomes | State-Transition | Decision Analysis | Policy/Regulation | Economics/Finance | Government/Law | Health/Medicine | Middle East & North Africa -
ArticlePublication 2021New Microsimulation Models to Inform Cervical Cancer Control
Health decision models consider the lifetime natural history of human papillomavirus (HPV) infection and pathogenesis …
Health decision models consider the lifetime natural history of human papillomavirus (HPV) infection and pathogenesis of cervical cancer, and estimate the long-term impact of preventive interventions. We propose a new health decision modeling framework that de-emphasizes previously used cytologic-colposcopic-histologic diagnoses, which are subjective and lack reproducibility, relying instead on HPV type and duration of infection as the major determinants of model transition probabilities. We posit that new model health states and corollary transitions are universal,…
Calibration/Validation | Infectious Diseases | Mathematical Models | Microsimulation | Decision Analysis | Cost-Effectiveness Analysis | Global -
ArticlePublication 2021Impact of COVID-19 on Cancer Diagnosis and Survival in Chile
This paper estimates the impact of the COVID-19 pandemic on delays in cancer diagnosis in …
This paper estimates the impact of the COVID-19 pandemic on delays in cancer diagnosis in Chile, using a microsimulation model of five cancers: breast, cervix, colorectal, prostate, and stomach. The model simulates cancer incidence and progression, as well as stage-specific cancer detection and survival probabilities, and was calibrated to empirical data on monthly detected cases, stage at diagnosis, and 5-year net survival. The analysis accounted for the impact of COVID-19 on month-by-month excess mortality and…
Calibration/Validation | Infectious Diseases | Health Outcomes | Microsimulation | Chronic Disease/Risk | Latin America & Caribbean -
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.
Infectious Diseases | Decision Theory | Priority Setting/Ethics | Policy/Regulation | Government/Law | Health/Medicine | 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 | Infectious Diseases | Test Performance | Technology Assessment | 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 | Infectious Diseases | Test Performance | 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 | Infectious Diseases | Test Performance | Health/Medicine | Science/Technology | Global -
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 -
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 | Infectious Diseases | Dynamic Transmission | Dynamic Simulation | Health Systems | Health/Medicine | Global