ArticlePLoS computational biology2025
An application of nowcasting methods: Cases of norovirus during the winter 2023/2024 in England.
Article in PLoS computational biology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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Who cites it
2 citing papers in PubMed.
- Evaluation of short-term multi-target respiratory forecasts over winter 2024-25 in England using sub-ensemble contribution analyses.PLoS computational biology · 2026Article
- Baseline nowcasting methods for handling delays in epidemiological data.Wellcome open research · 2025Article
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Authors and funding
10 authors.
Funding
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Abstract
backgroundNorovirus is a leading cause of acute gastroenteritis, adding to strain on healthcare systems. Diagnostic test reporting of norovirus is often delayed, resulting in incomplete data for real-time surveillance.
methodsTo nowcast the real-time case burden of norovirus a generalised additive model (GAM), semi-mechanistic Bayesian joint process and delay model "epinowcast", and Bayesian structural time series (BSTS) model including syndromic surveillance data were developed. These models were evaluated over weekly nowcasts using a probabilistic scoring framework.
resultsUsing the weighted interval score (WIS) we show a heuristic approach is outperformed by models harnessing time delay corrections, with daily mean WIS = 7.73, 3.03, 2.29 for the baseline, "epinowcast", and GAM, respectively. Forecasting approaches were reliable in the event of temporally changing reporting values, with WIS = 4.57 for the BSTS model. However, the syndromic surveillance (111 online pathways) did not improve the BSTS model, WIS = 10.28, potentially indicating poor correspondence between surveillance indicators.
interpretationAnalysis of surveillance data enhanced by nowcasting delayed reporting improves understanding over simple model assumptions, important for real-time decision making. The modelling approach needs to be informed by the patterns of the reporting delay and can have large impacts on operational performance and insights produced.
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