Bayesian modelling for COVID-19 seroprevalence studies
Por um escritor misterioso
Descrição
Quantifying previous SARS-CoV-2 infection through mixture modelling of antibody levels
Adjusting COVID-19 seroprevalence survey results to account for test sensitivity and specificity
Estimates of the severity of coronavirus disease 2019: a model-based analysis - The Lancet Infectious Diseases
Dark matter', second waves and epidemiological modelling
Seroprevalence, spatial distribution, and social determinants of SARS-CoV-2 in three urban centers of Chile, BMC Infectious Diseases
Estimated transmissibility and impact of SARS-CoV-2 lineage B.1.1.7 in England
Full article: Bayesian network analysis of Covid-19 data reveals higher infection prevalence rates and lower fatality rates than widely reported
Full article: Bayesian network analysis of Covid-19 data reveals higher infection prevalence rates and lower fatality rates than widely reported
IJERPH, Free Full-Text
Bayesian inference across multiple models suggests a strong increase in lethality of COVID-19 in late 2020 in the UK
Extended Bayesian endemic–epidemic models to incorporate mobility data into COVID‐19 forecasting - Douwes‐Schultz - 2022 - Canadian Journal of Statistics - Wiley Online Library
Using test positivity and reported case rates to estimate state-level COVID-19 prevalence and seroprevalence in the United States
Data-driven modeling of covid-21 - living matter lab
Viruses, Free Full-Text
Variation in the COVID-19 infection–fatality ratio by age, time, and geography during the pre-vaccine era: a systematic analysis - The Lancet
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