Introduction to the special issue on Data Science for COVID-19

DOI10.1080/10485252.2022.2108288zbMath1495.00077OpenAlexW4294811435MaRDI QIDQ5102527

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Publication date: 23 September 2022

Published in: Journal of Nonparametric Statistics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/10485252.2022.2108288

Mathematics Subject Classification ID

Applications of statistics to biology and medical sciences; meta analysis (62P10) Proceedings, conferences, collections, etc. pertaining to statistics (62-06) Collections of articles of miscellaneous specific interest (00B15)

Uses Software

• epinet

Cites Work

• Unnamed Item
• Mathematical epidemiology.
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• Assessment of the influence of features on a classification problem: an application to COVID-19 patients
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• Nonparametric Bayesian functional meta-regression: applications in environmental epidemiology
• Closed-form expressions and nonparametric estimation of COVID-19 infection rate
• A data-adaptive method for estimating density level sets under shape conditions
• Efficient empirical likelihood inference for recovery rate of COVID19 under double-censoring
• Study of the trend pattern of COVID-19 using spline-based time series model: a Bayesian paradigm
• Forecasting epidemics through nonparametric estimation of time-dependent transmission rates using the SEIR model
• A non-parametric method for determining epidemiological reproduction numbers
• Bayesian Inference for Contact Networks Given Epidemic Data
• Synthesis of Evidence from Epidemiological Studies with Interval-Censored Exposure Due to Grouping
• Confidence Intervals for the Relative Risk Ratio Parameter from Survival Data Under a Random Censorship Model in Biomedical and Epidemiologic Studies (By Simulation)
• Bayesian Inference for Stochastic Epidemics in Populations with Random Social Structure
• Semi-parametric estimation of incubation and generation times by means of Laguerre polynomials
• Truncation data analysis for the under-reporting probability in COVID-19 pandemic
• A semiparametric Bayesian approach to epidemics, with application to the spread of the coronavirus MERS in South Korea in 2015
• Nonparametric estimation of highest density regions for COVID-19
• Nonparametric estimation and inference for spatiotemporal epidemic models
• Bayesian penalized B-spline estimation approach for epidemic models
• A Non Parametric Exact Test Based on the Number of Records for an Early Detection of Emerging Events: Illustration in Epidemiology
• Nonparametric Estimation of Multiplicative Counting Process Intensity Functions with an Application to the Beijing SARS Epidemic
• Estimation of incubation period and generation time based on observed length‐biased epidemic cohort with censoring for COVID‐19 outbreak in China
• Semiparametric regression analysis of doubly-censored data with applications to incubation period estimation

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