Work

Predicting influenza trends in the context of post-COVID immunity gaps in Macao, China

Year: 2025

Type: article

Abstract: We used Google and Baidu search data with machine learning to predict flu trends in Macao. ‘Cold’ was the strongest early indicator, with XGBoost showing the best performance. Findings support enhanced flu surveillance amid rising risks from post-COVID immunity debt and growing tourist inflow.

Source: Journal of Travel Medicine

DOI: 10.1093/jtm/taaf035

Authors: Ying Liu, Kefeng Li, Hoiman Ng, Qianhong Ye, Henry H Y Tong

Institutions: Xiamen University Tan Kah Kee College, Macao Polytechnic University, Kiang Wu Hospital

Language: English

Topic: Data-Driven Disease Surveillance

Subfield: Epidemiology

Field: Medicine

Domain: Health Sciences

SDG: Good health and well-being

Open Access status: hybrid

Estimated APC paid: $4,605