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

Early Results from COVID-19 Studies (466) Public (e)Health, Digital Epidemiology and Public Health Informatics (2391) Surveillance Systems (697) Behavioural Surveillance for Public Health (509) Innovative Methods in Public Health and Surveillance (529) Ecological Momentary Assessment (EMA) (529) JMIR Theme Issue: COVID-19 Special Issue (4238)

Published on in Vol 7 (2023)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/46357, first published .
Young Asian woman wearing a face mask outdoors, looking to the side.

Vector Autoregression for Forecasting the Number of COVID-19 Cases and Analyzing Behavioral Indicators in the Philippines: Ecologic Time-Trend Study

Vector Autoregression for Forecasting the Number of COVID-19 Cases and Analyzing Behavioral Indicators in the Philippines: Ecologic Time-Trend Study

Authors of this article:

Angelica Anne Eligado Latorre1, 2 Author Orcid Image ;   Keiko Nakamura1 Author Orcid Image ;   Kaoruko Seino1 Author Orcid Image ;   Takanori Hasegawa3 Author Orcid Image
Article Authors Cited by (2) Tweetations (2) Metrics

Journals

  1. Eligado A, Hattori Y, Bersales L, Asaad A, Nakamura K. Vector autoregression model using behavioral data successfully forecasts COVID-19 cases: An application of big data. Communications in Statistics: Case Studies, Data Analysis and Applications 2026;12(2):257 View
  2. Lin Y, Qu Y, Qiu X, Huan Q, Wang J, Fang T, Qiu Z, Xie Y. Global population-level concurrence and directional associations between rheumatoid arthritis and depressive disorders: an SDI-stratified time-series analysis using GBD 2021. Clinical Rheumatology 2026 View