meakin sophie r CORD-Authors (Version 1)

Author: Meakin Sophie R
Affiliation: All authors Centre for Mathematical Modelling of Infectious Diseases
link: https://covid19-data.nist.gov/pid/rest/local/institution/all_authors_centre_for_mathematical_modelling_of_infectious_diseases
Paper Title: Exploring surveillance data biases when estimating the reproduction number: with insights into subpopulation transmission of COVID-19 in England
Paper Link: https://covid19-data.nist.gov/pid/rest/local/paper/exploring_surveillance_data_biases_when_estimating_the_reproduction_number_with_insights
Paper Title: Strategies to reduce the risk of SARS-CoV-2 re-introduction from international travellers
Paper Link: https://covid19-data.nist.gov/pid/rest/local/paper/strategies_to_reduce_the_risk_of_sars_cov_2_re_introduction_from_international_travellers
Paper Title: Strategies to reduce the risk of SARS-CoV-2 importation from international travellers: modelling estimations for the United Kingdom July 2020
Paper Link: https://covid19-data.nist.gov/pid/rest/local/paper/strategies_to_reduce_the_risk_of_sars_cov_2_importation_from_international_travellers
Paper Title: The contribution of asymptomatic SARS-CoV-2 infections to transmission - a model-based analysis of the Diamond Princess outbreak
Paper Link: https://covid19-data.nist.gov/pid/rest/local/paper/the_contribution_of_asymptomatic_sars_cov_2_infections_to_transmission_a_model_based
Paper Title: The potential for vaccination-induced herd immunity against the SARS-CoV-2 B.1.1.7 variant
Paper Link: https://covid19-data.nist.gov/pid/rest/local/paper/the_potential_for_vaccination_induced_herd_immunity_against_the_sars_cov_2_b_1_1_7
Paper Title: The importance of saturating density dependence for population-level predictions of SARS-CoV-2 resurgence compared with density-independent or linearly density-dependent models England 23 March to 31 July 2020
Paper Link: https://covid19-data.nist.gov/pid/rest/local/paper/the_importance_of_saturating_density_dependence_for_population_level_predictions_of