Forecasting influenza A and B positive case counts using a hybrid seasonal autoregressive integrated moving average and long short-term memory (SARIMA-LSTM) model: an epidemiological study from Jiande, Hangzhou, China

Authors

Fenglong Zhu
Cong Huang (ORCID: https://orcid.org/0000-0002-1119-431X)
Guisheng Liu

Institutions

Panzhihua Central Hospital (CN)
Affiliated Hangzhou First People's Hospital, Westlake University, School of Medicine (CN)

Publication Details

Journal: BMC Infectious Diseases
Published: 2026-10-06
DOI: https://doi.org/10.1186/s12879-026-14587-7
Primary Topic: Influenza Virus Research Studies
Type: article
Field-Weighted Citation Impact: 0.00

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article

Forecasting influenza A and B positive case counts using a hybrid seasonal autoregressive integrated moving average and long short-term memory (SARIMA-LSTM) model: an epidemiological study from Jiande, Hangzhou, China

Fenglong Zhu, Cong Huang, Guisheng Liu

Oct 6, 2026

BMC Infectious Diseases

Influenza Virus Research Studies

article

Forecasting influenza A and B positive case counts using a hybrid seasonal autoregressive integrated moving average and long short-term memory (SARIMA-LSTM) model: an epidemiological study from Jiande, Hangzhou, China

Fenglong Zhu, Cong Huang, Guisheng Liu

October 6, 2026article en

Abstract

No abstract available for this paper.

BMC Infectious Diseases

Panzhihua Central Hospital (CN), Affiliated Hangzhou First People's Hospital, Westlake University, School of Medicine (CN)

Openalex Percentile: Top 11%

Influenza Virus Research Studies

DOI Open Access PDF OpenAlex

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Forecasting influenza A and B positive case counts using a hybrid seasonal autoregressive integrated moving average and long short-term memory (SARIMA-LSTM) model: an epidemiological study from Jiande, Hangzhou, China — Fenglong Zhu, Cong Huang, et al. · BMC Infectious Diseases (2026) | TGRS Research Map | TGRS