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Extending the susceptible‐exposed‐infected‐removed (SEIR) model to handle the false negative rate and symptom‐based administration of COVID‐19 diagnostic tests: <i>SEIR‐fansy</i>
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 …