| Title: |
A combination of annual and nonannual forces drive respiratory disease in the tropics |
| Authors: |
Yang, F; Servadio, JL; Le Thanh, NT; Lam, HM; Choisy, M; Thai, PQ; Nhu Thao, TT; Thao Vy, NH; Phuong, HT; Nguyen, TD; Hoai Tam, DT; Hanks, EM; Vinh, H; Bjornstad, ON; Van Vinh Chau, N; Boni, MF |
| Publisher Information: |
medRxiv |
| Publication Year: |
2025 |
| Collection: |
Oxford University Research Archive (ORA) |
| Description: |
BACKGROUND: It is well known that influenza and other respiratory viruses are wintertime-seasonal in temperate regions. However, respiratory disease seasonality in the tropics remains elusive. In this study, we aimed to characterize the seasonality of influenza-like illness (ILI) and influenza virus in Ho Chi Minh City (HCMC), Vietnam. METHODS: We monitored the daily number of ILI patients in 89 outpatient clinics from January 2010 to December 2019. We collected nasal swabs and tested for influenza from a subset of clinics from May 2012 to December 2019. We used spectral analysis to describe the periodicities in the system. We evaluated the contribution of these periodicities to predicting ILI and influenza patterns through lognormal and gamma hurdle models. FINDINGS: During ten years of community surveillance, 66,799 ILI reports were collected covering 2.9 million patient visits; 2604 nasal swabs were collected 559 of which were PCR-positive for influenza virus. Both annual and nonannual cycles were detected in the ILI time series, with the annual cycle showing 8.9% lower ILI activity (95% CI: 8.8%-9.0%) from February 24 to May 15. Nonannual cycles had substantial explanatory power for ILI trends (ΔAIC = 183) compared to all annual covariates (ΔAIC = 263). Near-annual signals were observed for PCR-confirmed influenza but were not consistent along in time or across influenza (sub)types. INTERPRETATION: Our study reveals a unique pattern of respiratory disease dynamics in a tropical setting influenced by both annual and nonannual drivers. Timing of vaccination campaigns and hospital capacity planning may require a complex forecasting approach. |
| Document Type: |
other/unknown material |
| Language: |
English |
| Relation: |
https://doi.org/10.1101/2023.03.28.23287862 |
| DOI: |
10.1101/2023.03.28.23287862 |
| Availability: |
https://doi.org/10.1101/2023.03.28.23287862; https://ora.ox.ac.uk/objects/uuid:190f4754-5d74-4e17-b7f7-e55cac23a97f |
| Rights: |
info:eu-repo/semantics/openAccess ; CC Attribution-NonCommercial-NoDerivatives (CC BY-NC-ND) |
| Accession Number: |
edsbas.A295EA43 |
| Database: |
BASE |