ArticlePLoS computational biology2020
Forecasting influenza in Europe using a metapopulation model incorporating cross-border commuting and air travel.
Article in PLoS computational biology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers, 1 of them a synthesis that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
16 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Global meta-analysis of short-term associations between ambient temperature and pathogen-specific respiratory infections, 2004 to 2023.Euro surveillance : bulletin Europeen sur les maladies transmissibles = European communicable disease bulletin · 2025Pooled it
- Networked SIRS model with Kalman filter state estimation for epidemic monitoring in Europe.Communications medicine · 2026Article
- A stacked ensemble model with NNLS-based weighting for influenza forecasting: a case study of Anhui Province, China.Frontiers in public health · 2026Article
- The tale of two assumptions: incorporating healthcare-seeking behaviour in epidemic forecasting.BMC infectious diseases · 2025Article
- Characterizing the interactions between influenza and respiratory syncytial viruses and their implications for epidemic control.Nature communications · 2024Article
- Inference on spatiotemporal dynamics for coupled biological populations.Journal of the Royal Society, Interface · 2024Article
- Temporal variations in international air travel: implications for modelling the spread of infectious diseases.Journal of travel medicine · 2024Article
- Population genetic models for the spatial spread of adaptive variants: A review in light of SARS-CoV-2 evolution.PLoS genetics · 2022Review
- Estimating and forecasting the burden and spread of Colombia's SARS-CoV2 first wave.Scientific reports · 2022Article
- Evaluating the impact of stay-at-home and quarantine measures on COVID-19 spread.BMC infectious diseases · 2022Article
- Learning transmission dynamics modelling of COVID-19 using comomodels.Mathematical biosciences · 2022Article
- Socioeconomic and environmental patterns behind H1N1 spreading in Sweden.Scientific reports · 2021Article
- A Spatiotemporal Tool to Project Hospital Critical Care Capacity and Mortality From COVID-19 in US Counties.American journal of public health · 2021Article
- Optimizing respiratory virus surveillance networks using uncertainty propagation.Nature communications · 2021Article
- A general method for estimating the prevalence of influenza-like-symptoms with Wikipedia data.PloS one · 2021Article
- Commentary on "Transparent modeling of influenza incidence": Because the model said so.International journal of forecastingArticle
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
Abstract
Past work has shown that models incorporating human travel can improve the quality of influenza forecasts. Here, we develop and validate a metapopulation model of twelve European countries, in which international translocation of virus is driven by observed commuting and air travel flows, and use this model to generate influenza forecasts in conjunction with incidence data from the World Health Organization. We find that, although the metapopulation model fits the data well, it offers no improvement over isolated models in forecast quality. We discuss several potential reasons for these results. In particular, we note the need for data that are more comparable from country to country, and offer suggestions as to how surveillance systems might be improved to achieve this goal.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.