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arXiv · 2603.01374

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

M. J. Plank·A. R. Young·K. L. Senior·R. J. Tobin·M. O'Hara-Wild·F. Callaghan·F. Shearer·O. Eales
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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. Models were run weekly from May to October 2025 on these real-time disease surveillance data and provided a quantitative representation of the current epidemic trend, along with estimates of the epidemic growth rate and 28-day ahead forecasts of case incidence. Model results and interpretation were provided in weekly reports to public health partners as part of a trans-Tasman winter programme run by the Australia--Aotearoa Consortium for Epidemic Forecasting and Analytics (ACEFA). We compare in-season results that were included in these reports to a retrospective analysis of the complete data for the season. We conclude that real-time analyses performed reasonably well, and identify some areas for improvement in future winter situational assessment programmes.

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M. J. Plank, A. R. Young, K. L. Senior, R. J. Tobin, M. O'Hara-Wild, F. Callaghan, F. Shearer, O. Eales. 2026-03-02. Multi-pathogen situational assessment and forecasting of respiratory disease in Aotearoa New Zealand. https://doi.org/10.1098/rsos.260536

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