A combination of annual and nonannual forces drive respiratory disease in the tropics

Author:

Yang FuhanORCID,Servadio Joseph L,Thanh Nguyen Thi Le,Lam Ha MinhORCID,Choisy Marc,Thai Pham Quang,Thao Tran Thi Nhu,Vy Nguyen Ha Thao,Phuong Huynh Thi,Nguyen Tran Dang,Tam Dong Thi Hoai,Hanks Ephraim M,Vinh Ha,Bjornstad Ottar N,Chau Nguyen Van Vinh,Boni Maciej F

Abstract

IntroductionIt is well known that influenza and other respiratory viruses are wintertime-seasonal in temperate regions. However, respiratory disease seasonality in the tropics is less well understood. In this study, we aimed to characterise the seasonality of influenza-like illness (ILI) and influenza virus in Ho Chi Minh City, Vietnam.MethodsWe 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 periodic signals in the system. We evaluated the contribution of these periodic signals to predicting ILI and influenza patterns through lognormal and gamma hurdle models.ResultsDuring 10 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% to 9.0%) from February 24 to May 15. Nonannual cycles had substantial explanatory power for ILI trends (ΔAIC=183) compared with all annual covariates (ΔAIC=263) in lognormal regression. Near-annual signals were observed for PCR-confirmed influenza but were not consistent over time or across influenza (sub)types. The explanatory power of climate factors for ILI and influenza virus trends was weak.ConclusionOur study reveals a unique pattern of respiratory disease dynamics in a tropical setting influenced by both annual and nonannual drivers, with influenza dynamics showing near-annual periodicities. Timing of vaccination campaigns and hospital capacity planning may require a complex forecasting approach.

Funder

National Science Fundation

National Science Foundation

National Institute of Health

Bill and Melinda Gates Foundation

Center of Excellence in Influenza Research and Surveillance, NIH/NIAID

Wellcome Trust

Publisher

BMJ

Subject

Public Health, Environmental and Occupational Health,Health Policy

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