This paper is in the following e-collection/theme issue:

Statistical Methods for Surveillance and Population Health (188) Surveillance Systems (514) Innovative Methods in Public Health and Surveillance (383) Outbreak and Pandemic Preparedness and Management (1826) Epidemiology (196) Descriptive Epidemiology and Population Size Estimates (140)

Published on in Vol 10 (2024)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/53719, first published .
Handling Missing Data in COVID-19 Incidence Estimation: Secondary Data Analysis

Handling Missing Data in COVID-19 Incidence Estimation: Secondary Data Analysis

Handling Missing Data in COVID-19 Incidence Estimation: Secondary Data Analysis

Authors of this article:

Hai-Thanh Pham1 Author Orcid Image ;   Toan Do1 Author Orcid Image ;   Jonggyu Baek2 Author Orcid Image ;   Cong-Khanh Nguyen3 Author Orcid Image ;   Quang-Thai Pham1, 3 Author Orcid Image ;   Hoa L Nguyen2 Author Orcid Image ;   Robert Goldberg2 Author Orcid Image ;   Quang Loc Pham1 Author Orcid Image ;   Le Minh Giang1 Author Orcid Image
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Journals

  1. Brown S, Kudia O, Kleine K, Kidd B, Wines R, Meckes N. Comparing Multiple Imputation Methods to Address Missing Patient Demographics in Immunization Information Systems: Retrospective Cohort Study. JMIR Public Health and Surveillance 2025;11:e73916 View