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Multi-pathogen situational assessment and forecasting of ...
[Submitted on 2 Mar 2026 (v1), last revised 9 Jun 2026 (this ver · 2026-06-10 · via stat updates on arXiv.org

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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.

Submission history

From: Michael Plank [view email]
[v1] Mon, 2 Mar 2026 02:15:51 UTC (4,615 KB)
[v2] Tue, 9 Jun 2026 02:05:57 UTC (6,383 KB)