Published on in Vol 23, No 2 (2021): February

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/26081, first published .
Dynamic Panel Data Modeling and Surveillance of COVID-19 in Metropolitan Areas in the United States: Longitudinal Trend Analysis

Dynamic Panel Data Modeling and Surveillance of COVID-19 in Metropolitan Areas in the United States: Longitudinal Trend Analysis

Dynamic Panel Data Modeling and Surveillance of COVID-19 in Metropolitan Areas in the United States: Longitudinal Trend Analysis

Journals

  1. Welch S, Kulasekere D, Prasad P, Moss C, Murphy R, Achenbach C, Ison M, Resnick D, Singh L, White J, Issa T, Culler K, Boctor M, Mason M, Oehmke J, Faber J, Post L. The Interplay Between Policy and COVID-19 Outbreaks in South Asia: Longitudinal Trend Analysis of Surveillance Data. JMIR Public Health and Surveillance 2021;7(6):e24251 View
  2. Lundberg A, Lorenzo-Redondo R, Ozer E, Hawkins C, Hultquist J, Welch S, Prasad P, Oehmke J, Achenbach C, Murphy R, White J, Havey R, Post L. Has Omicron Changed the Evolution of the Pandemic?. JMIR Public Health and Surveillance 2022;8(1):e35763 View
  3. Oehmke T, Moss C, Oehmke J. COVID-19 Surveillance Updates in US Metropolitan Areas: Dynamic Panel Data Modeling. JMIR Public Health and Surveillance 2022;8(2):e28737 View
  4. Lundberg A, Lorenzo-Redondo R, Hultquist J, Hawkins C, Ozer E, Welch S, Prasad P, Achenbach C, White J, Oehmke J, Murphy R, Havey R, Post L. Overlapping Delta and Omicron Outbreaks During the COVID-19 Pandemic: Dynamic Panel Data Estimates. JMIR Public Health and Surveillance 2022;8(6):e37377 View
  5. Wu D, Hua J, Xu F. pydynpd: A Python package for dynamic panel model. Journal of Open Source Software 2023;8(83):4416 View