Multi-pathogen situational assessment and forecasting of respiratory disease in Aotearoa New Zealand

Real-time analysis of epidemic trends and forecasts can help support public health planning and the response to seasonal respiratory disease. Here, we present two models that were used in a 2025 New Zealand winter situational assessment programme for three respiratory pathogens: SARS-CoV-2, influenza and respiratory syncytial virus (RSV). Data on SARS-CoV-2 were obtained from the national Covid-19 surveillance system; data on influenza and RSV were limited to a sentinel hospital surveillance programme.

Citation:
Plank MJ, Young AR, Senior KL, Tobin RJ, ……. Shearer FM, Eales O. Multi-pathogen situational assessment and forecasting of respiratory disease in Aotearoa New Zealand. R Soc Open Sci. 2026;13(8).

Keywords:
Bayesian P-splines, disease surveillance, hidden-state model, infectious disease epidemiology, public health, mathematical modelling

Abstract:
Real-time analysis of epidemic trends and forecasts can help support public health planning and the response to seasonal respiratory disease. Here, we present two models that were used in a 2025 New Zealand winter situational assessment programme for three respiratory pathogens: SARS-CoV-2, influenza and respiratory syncytial virus (RSV). Data on SARS-CoV-2 were obtained from the national Covid-19 surveillance system; data on influenza and RSV were limited to a sentinel hospital surveillance programme.