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Meteorological Drivers of Influenza Spread in New South Wales: A Spatial Bayesian Distributed Lag Non-linear Model Approach

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Bibliographic Details
Published in:Spatial Demography
Format: Online Article RSS Article
Published: 2026
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container_title Spatial Demography
description
discipline_display Social Sciences
discipline_facet Social Sciences
format Online Article
RSS Article
genre Journal Article
id rss_article:32166
institution FRELIP
journal_source_facet Spatial Demography
publishDate 2026
publishDateSort 2026
record_format rss_article
spellingShingle Meteorological Drivers of Influenza Spread in New South Wales: A Spatial Bayesian Distributed Lag Non-linear Model Approach
— — — — — Demography and Population Studies
Psychology
Social Sciences
sub_discipline_display Psychology
sub_discipline_facet Psychology
subject_display — — — — — Demography and Population Studies
Psychology
Social Sciences
— — — — — Demography and Population Studies
Psychology
Social Sciences
subject_facet — — — — — Demography and Population Studies
Psychology
Social Sciences
title Meteorological Drivers of Influenza Spread in New South Wales: A Spatial Bayesian Distributed Lag Non-linear Model Approach
title_auth Meteorological Drivers of Influenza Spread in New South Wales: A Spatial Bayesian Distributed Lag Non-linear Model Approach
title_full Meteorological Drivers of Influenza Spread in New South Wales: A Spatial Bayesian Distributed Lag Non-linear Model Approach
title_fullStr Meteorological Drivers of Influenza Spread in New South Wales: A Spatial Bayesian Distributed Lag Non-linear Model Approach
title_full_unstemmed Meteorological Drivers of Influenza Spread in New South Wales: A Spatial Bayesian Distributed Lag Non-linear Model Approach
title_short Meteorological Drivers of Influenza Spread in New South Wales: A Spatial Bayesian Distributed Lag Non-linear Model Approach
title_sort meteorological drivers of influenza spread in new south wales: a spatial bayesian distributed lag non-linear model approach
topic — — — — — Demography and Population Studies
Psychology
Social Sciences
url https://link.springer.com/article/10.1007/s40980-026-00158-6