TY - JOUR
T1 - Estimating the effective reproduction number of COVID-19 via the chain ladder method
AU - Lin, Xuanan
AU - Matsunaka, Yuki
AU - Shiraishi, Hiroshi
N1 - Publisher Copyright:
© The Author(s) under exclusive licence to Japanese Federation of Statistical Science Associations 2024.
PY - 2024/11
Y1 - 2024/11
N2 - This paper addressed a critical issue of reporting delays in estimating the effective reproduction number, focusing on the context of the COVID-19 pandemic. The reporting delay problem is a pervasive challenge, impacting the accuracy of the estimation and consequently influencing public health decision-making. Through the exploration of the application of the Chain Ladder method, a well-established technique from actuarial science, a novel approach to mitigate the effects of reporting delays in infectious disease epidemiology was proposed. By applying the Chain Ladder method to infectious disease data, we illustrated its potential to provide more accurate and timely estimation, accounting for reporting delays inherent in epidemiological surveillance systems.
AB - This paper addressed a critical issue of reporting delays in estimating the effective reproduction number, focusing on the context of the COVID-19 pandemic. The reporting delay problem is a pervasive challenge, impacting the accuracy of the estimation and consequently influencing public health decision-making. Through the exploration of the application of the Chain Ladder method, a well-established technique from actuarial science, a novel approach to mitigate the effects of reporting delays in infectious disease epidemiology was proposed. By applying the Chain Ladder method to infectious disease data, we illustrated its potential to provide more accurate and timely estimation, accounting for reporting delays inherent in epidemiological surveillance systems.
KW - COVID-19
KW - Chain ladder methods
KW - Effective reproduction number
KW - Mack’s model
KW - Reporting delay
UR - http://www.scopus.com/inward/record.url?scp=85194913798&partnerID=8YFLogxK
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U2 - 10.1007/s42081-024-00252-3
DO - 10.1007/s42081-024-00252-3
M3 - Article
AN - SCOPUS:85194913798
SN - 2520-8764
VL - 7
SP - 861
EP - 893
JO - Japanese Journal of Statistics and Data Science
JF - Japanese Journal of Statistics and Data Science
IS - 2
ER -
