Estimating the instantaneous reproduction number (Rt) by using particle filter

[1]  D. Calvetti,et al.  Bayesian particle filter algorithm for learning epidemic dynamics , 2021, Inverse Problems.

[2]  Muluneh Alene,et al.  Serial interval and incubation period of COVID-19: a systematic review and meta-analysis , 2021, BMC Infectious Diseases.

[3]  G. Gao,et al.  Evidence for pre‐symptomatic transmission of coronavirus disease 2019 (COVID‐19) in China , 2020, Influenza and other respiratory viruses.

[4]  T. Stadler,et al.  Practical considerations for measuring the effective reproductive number, Rt , 2020, medRxiv.

[5]  N. Nuraini,et al.  A new estimation method for COVID-19 time-varying reproduction number using active cases , 2020, Scientific Reports.

[6]  Limin Cao,et al.  Epidemiological characteristics and incubation period of 7,015 confirmed cases with Coronavirus Disease 2019 outside Hubei Province in China , 2020, The Journal of infectious diseases.

[7]  C. Faes,et al.  Estimating the generation interval for coronavirus disease (COVID-19) based on symptom onset data, March 2020 , 2020, Euro surveillance : bulletin Europeen sur les maladies transmissibles = European communicable disease bulletin.

[8]  Eric H. Y. Lau,et al.  Temporal dynamics in viral shedding and transmissibility of COVID-19 , 2020, Nature Medicine.

[9]  N. Linton,et al.  Serial interval of novel coronavirus (COVID-19) infections , 2020, International Journal of Infectious Diseases.

[10]  Yang Liu,et al.  Early dynamics of transmission and control of COVID-19: a mathematical modelling study , 2020, The Lancet Infectious Diseases.

[11]  L. Gostin,et al.  The Novel Coronavirus Originating in Wuhan, China: Challenges for Global Health Governance. , 2020, JAMA.

[12]  N. Linton,et al.  Incubation Period and Other Epidemiological Characteristics of 2019 Novel Coronavirus Infections with Right Truncation: A Statistical Analysis of Publicly Available Case Data , 2020, medRxiv.

[13]  Hongzhou Lu,et al.  Outbreak of pneumonia of unknown etiology in Wuhan, China: The mystery and the miracle , 2020, Journal of medical virology.

[14]  N. Osgood,et al.  Predictive accuracy of particle filtering in dynamic models supporting outbreak projections , 2017, BMC Infectious Diseases.

[15]  Alicia Karspeck,et al.  Comparison of Filtering Methods for the Modeling and Retrospective Forecasting of Influenza Epidemics , 2014, PLoS Comput. Biol..

[16]  C. Fraser,et al.  A New Framework and Software to Estimate Time-Varying Reproduction Numbers During Epidemics , 2013, American journal of epidemiology.

[17]  Nicholas G. Polson,et al.  Tracking Epidemics With Google Flu Trends Data and a State-Space SEIR Model , 2012, Journal of the American Statistical Association.

[18]  E. Faerstein,et al.  A DICTIONARY OF EPIDEMIOLOGY , 2016 .

[19]  C. Fraser Estimating Individual and Household Reproduction Numbers in an Emerging Epidemic , 2007, PloS one.

[20]  J. Wallinga,et al.  Different Epidemic Curves for Severe Acute Respiratory Syndrome Reveal Similar Impacts of Control Measures , 2004, American journal of epidemiology.

[21]  P. Fine The interval between successive cases of an infectious disease. , 2003, American journal of epidemiology.

[22]  Neil J. Gordon,et al.  A tutorial on particle filters for online nonlinear/non-Gaussian Bayesian tracking , 2002, IEEE Trans. Signal Process..

[23]  D. Gillespie Exact Stochastic Simulation of Coupled Chemical Reactions , 1977 .

[24]  D. Gillespie A General Method for Numerically Simulating the Stochastic Time Evolution of Coupled Chemical Reactions , 1976 .

[25]  S. Kucinskas,et al.  Tracking [Formula: see text] of COVID-19: A new real-time estimation using the Kalman filter. , 2021, PloS one.

[26]  Robin N. Thompson,et al.  Estimating the time-varying reproduction number of SARS-CoV-2 using national and subnational case counts [version 2; peer review: 1 approved with reservations] , 2021 .

[27]  C. Paasch,et al.  WORKING , 2021, The Digital Environment.