Routine Hospital-based SARS-CoV-2 Testing Outperforms State-based Data in Predicting Clinical Burden

  title={Routine Hospital-based SARS-CoV-2 Testing Outperforms State-based Data in Predicting Clinical Burden},
  author={Leonard Covello and Andrew Gelman and Yajuan Si and Siquan Wang},
  journal={Epidemiology (Cambridge, Mass.)},
  pages={792 - 799}
Supplemental Digital Content is available in the text. Throughout the coronavirus disease 2019 (COVID-19) pandemic, government policy and healthcare implementation responses have been guided by reported positivity rates and counts of positive cases in the community. The selection bias of these data calls into question their validity as measures of the actual viral incidence in the community and as predictors of clinical burden. In the absence of any successful public or academic campaign for… 

Beyond Vaccination Rates: A Synthetic Random Proxy Metric of Total SARS-CoV-2 Immunity Seroprevalence in the Community

A synthetic random proxy based on routine hospital testing for estimating total immunoglobulin G (IgG) prevalence in the sampled community improves real-time understanding of immunity to COVID-19 as it evolves and the coordination of policy responses to the disease.

On the Use of Auxiliary Variables in Multilevel Regression and Poststratification

This paper builds up a systematic framework under MRP for statistical data integration and inferences and applies the approach to evaluate cognition performances of diverse groups of children in the ABCD study and finds that the adjustment of auxiliary variables has a substantial effect on the inference results.

Embedded Multilevel Regression and Poststratification: Model-based Inference with Incomplete Auxiliary Information

Embedded MRP is introduced, which embeds the estimation of population cell counts needed for poststratification into the MRP work and demonstrates EMRP’s improvements over alternatives on the bias-variance tradeoff to yield valid subpopulation inferences of interest.

Using leave-one-out cross-validation (LOO) in a multilevel regression and poststratification (MRP) workflow: A cautionary tale

In recent decades, multilevel regression and poststratification (MRP) has surged in popularity for population inference. However, the validity of the estimates can depend on details of the model, and



COVID-19 Antibody Seroprevalence in Santa Clara County, California

The population prevalence of SARS-CoV-2 antibodies in Santa Clara County implies that the infection is much more widespread than indicated by the number of confirmed cases.

Variation in False-Negative Rate of Reverse Transcriptase Polymerase Chain Reaction–Based SARS-CoV-2 Tests by Time Since Exposure

Care must be taken in interpreting RT-PCR tests for SARS-CoV-2 infection—particularly early in the course of infection—when using these results as a basis for removing precautions intended to prevent onward transmission.

The Incubation Period of Coronavirus Disease 2019 (COVID-19) From Publicly Reported Confirmed Cases: Estimation and Application

The results support current proposals for the length of quarantine or active monitoring of persons potentially exposed to SARS-CoV-2, although longer monitoring periods might be justified in extreme cases.

A framework for identifying regional outbreak and spread of COVID-19 from one-minute population-wide surveys

It is proposed that daily population-wide surveys that assess the development of symptoms caused by the virus could serve as a strategic and valuable tool for identifying such clusters to inform epidemiologists, public health officials, and policy makers.

Bayesian analysis of tests with unknown specificity and sensitivity

H hierarchical regression and post‐stratification models with code in Stan are demonstrated and their application to a controversial recent study of SARS‐CoV‐2 antibodies in a sample of people from the Stanford University area is discussed.

Multilevel regression and poststratification for small-area estimation of population health outcomes: a case study of chronic obstructive pulmonary disease prevalence using the behavioral risk factor surveillance system.

A multilevel logistic model with both state- and nested county-level random effects for chronic obstructive pulmonary disease (COPD) using 2011 data from the Behavioral Risk Factor Surveillance System is developed and poststratification with the (decennial) US Census 2010 counts of census-block population is applied.

Multilevel Regression and Poststratification: A Modeling Approach to Estimating Population Quantities From Highly Selected Survey Samples

Multilevel regression and poststratification provides a promising analytical approach to addressing potential participation bias in the estimation of population descriptive quantities from large-scale health surveys and cohort studies.

False Negative Tests for SARS-CoV-2 Infection - Challenges and Implications.

Diagnostic testing for SARS-CoV-2 will help in safely reopening the country, but only if tests are highly accurate, experts say.

Bayesian hierarchical weighting adjustment and survey inference

This work combines Bayesian prediction and weighted inference as a unified approach to survey inference and applies the proposal to the New York Longitudinal Study of Wellbeing, which demonstrates that model-based prediction and weighting inference outperform classical weighting.