ArticleStatistics in medicine2022
Extending the susceptible-exposed-infected-removed (SEIR) model to handle the false negative rate and symptom-based administration of COVID-19 diagnostic tests: SEIR-fansy.
Article in Statistics in medicine, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers, 1 of them a synthesis that pooled it.
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Who cites it
20 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Uncovering associations between pre-existing conditions and COVID-19 Severity: A polygenic risk score approach across three large biobanks.PLoS genetics · 2023Pooled it
- Multivariable Behavioral Change Modeling of Epidemics in the Presence of Undetected Infections.Statistics in medicine · 2026Article
- Overcoming bias in estimating epidemiological parameters with realistic history-dependent disease spread dynamics.Nature communications · 2024Article
- Epidemic Management via Imperfect Testing: A Multi-criterial Perspective.Bulletin of mathematical biology · 2023Article
- A mathematical model to assess the impact of testing and isolation compliance on the transmission of COVID-19.Infectious Disease Modelling · 2023Article
- Comparative impact assessment of COVID-19 policy interventions in five South Asian countries using reported and estimated unreported death counts during 2020-2021.PLOS global public health · 2023Article
- Assessing the impact of non-pharmaceutical interventions (NPIs) and BCG vaccine cross-protection in the transmission dynamics of SARS-CoV-2 in eastern Africa.BMC research notes · 2022Article
- Modeling Global COVID-19 Dissemination Data After the Emergence of Omicron Variant Using Multipronged Approaches.Current microbiology · 2022Article
- Lessons from SARS-CoV-2 in India: A data-driven framework for pandemic resilience.Science advances · 2022Article
- Extending the susceptible-exposed-infected-removed (SEIR) model to handle the false negative rate and symptom-based administration of COVID-19 diagnostic tests: SEIR-fansy.Statistics in medicine · 2022Article
- Using outbreak data to estimate the dynamic COVID-19 landscape in Eastern Africa.BMC infectious diseases · 2022Article
- A novel hybrid SEIQR model incorporating the effect of quarantine and lockdown regulations for COVID-19.Scientific reports · 2021Article
- Integro-differential approach for modeling the COVID-19 dynamics - Impact of confinement measures in Italy.Computers in biology and medicine · 2021Article
- How many more? Under-reporting of the COVID-19 deaths in Brazil in 2020.Tropical medicine & international health : TM & IH · 2021Article
- Estimating the wave 1 and wave 2 infection fatality rates from SARS-CoV-2 in India.BMC research notes · 2021Article
- Estimating COVID-19‒ Related Mortality in India: An Epidemiological Challenge With Insufficient Data.American journal of public health · 2021Article
- COVID-19 Pandemic in India: Through the Lens of Modeling.Global health, science and practice · 2021Article
- A comparison of five epidemiological models for transmission of SARS-CoV-2 in India.BMC infectious diseases · 2021Article
- Incorporating false negative tests in epidemiological models for SARS-CoV-2 transmission and reconciling with seroprevalence estimates.Scientific reports · 2021Article
- Discussion on "Regression Models for Understanding COVID-19 Epidemic Dynamics with Incomplete Data".Journal of the American Statistical Association · 2021Article
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7 authors.
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Abstract
False negative rates of severe acute respiratory coronavirus 2 diagnostic tests, together with selection bias due to prioritized testing can result in inaccurate modeling of COVID-19 transmission dynamics based on reported "case" counts. We propose an extension of the widely used Susceptible-Exposed-Infected-Removed (SEIR) model that accounts for misclassification error and selection bias, and derive an analytic expression for the basic reproduction number
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.