Correction of Daily Positivity Rates for contribution of various test protocols being used in a pandemic.
Bansal, B.
Show abstract
Daily positivity rate (DPR) is a popular metric to judge the prevalence of an infection in the population and the testing response to it as a single number. It has been widely implicated in predicting future course of the SARS CoV-2 pandemic in India. With increasing use of multiple testing protocols with varying sensitivity and specificity in various proportions, the naive calculation loses meaning particularly during comparison between states/countries with large daily variations in contribution of different testing protocols to the testing response. We propose an adjustment to the naive DPR based on the testing parameters and the relative proportional use of each such protocol. Such a correction has become essential for comparing testing response of Indian states from Jun 2020 - Aug 2020 because of steep variations in testing protocol in certain states.
Matching journals
The top 9 journals account for 50% of the predicted probability mass.
Similar papers in this journal
- Evaluating diagnostic accuracies of Panbio ™ COVID-19 rapid antigen test and RT-PCR for the detection of SARS-CoV-2 in Addis Ababa, Ethiopia using Bayesian Latent-Class Models (BLCM) 93%
- Interdependence between confirmed and discarded cases of dengue, chikungunya and Zika viruses in Brazil: A multivariate time-series analysis 93%
- Emergence to dominance: Estimating time to dominance of SARS-CoV-2 variants using nonlinear statistical models 92%
Similar papers in this journal
- The burden of active infection and anti-SARS-CoV-2 IgG antibodies in the general population: Results from a statewide survey in Karnataka, India 92%
- Transmission potential of COVID-19 in South Korea 91%
- Estimating the undetected infections in the Covid-19 outbreak by harnessing capture-recapture methods 90%
Similar papers in this journal
Similar papers in this journal
- RNA-extraction-free diagnostic method to detect SARS-CoV-2: an assessment from two States, India 92%
- The basic reproduction number and prediction of the epidemic size of the novel coronavirus (COVID-19) in Shahroud, Iran 92%
- Estimating the Case Fatality Ratio for COVID-19 using a Time-Shifted Distribution Analysis 92%
Similar papers in this journal
- Climate influences scrub typhus occurrence in Vellore, Tamil Nadu, India: Analysis of a 15 year dataset 92%
- A new, simple method of describing COVID-19 trajectory and dynamics in any country based on Johnson Cumulative Distribution Function fitting 92%
- Predicting dengue importation into Europe, using machine learning and model-agnostic methods. 92%
"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.