{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,24]],"date-time":"2026-08-24T14:48:37Z","timestamp":1787582917613,"version":"build-2736575974"},"reference-count":50,"publisher":"Frontiers Media SA","license":[{"start":{"date-parts":[[2025,7,1]],"date-time":"2025-07-01T00:00:00Z","timestamp":1751328000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100002428","name":"Austrian Science Fund","doi-asserted-by":"publisher","award":["I5117"],"award-info":[{"award-number":["I5117"]}],"id":[{"id":"10.13039\/501100002428","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000030","name":"Centers for Disease Control and Prevention","doi-asserted-by":"publisher","award":["CDC-RFA-FT-23-0069"],"award-info":[{"award-number":["CDC-RFA-FT-23-0069"]}],"id":[{"id":"10.13039\/100000030","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000057","name":"National Institute of General Medical Sciences","doi-asserted-by":"publisher","award":["R01GM130668"],"award-info":[{"award-number":["R01GM130668"]}],"id":[{"id":"10.13039\/100000057","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["frontiersin.org"],"crossmark-restriction":true},"short-container-title":["Front. Public Health"],"abstract":"<jats:sec><jats:title>Objectives<\/jats:title><jats:p>Due to political polarization, adherence to public health measures varied across US states during the COVID-19 pandemic. Although social media posts have been shown effective in anticipating COVID-19 surges, the impact of political leaning on the effectiveness of different topics for early warning remains mostly unexplored. Our study examines the spatio-temporal early warning potential of different geo-social media topics across republican, democrat, and swing states.<\/jats:p><\/jats:sec><jats:sec><jats:title>Methods<\/jats:title><jats:p>Using keyword filtering, we identified eight COVID-19-related geo-social media topics. We then utilized Chatterjee's rank correlation to assess their early warning capability for COVID-19 cases 7 to 42 days in advance across six infection waves. A mixed-effect model was used to evaluate the impact of timeframe and political leaning on the early warning capabilities of these topics.<\/jats:p><\/jats:sec><jats:sec><jats:title>Results<\/jats:title><jats:p>Many topics exhibited significant spatial clustering over time, with quarantine and vaccination-related posts occurring in opposing spatial regimes in the second timeframe. We also found significant variation in the early warning capabilities of geo-social media topics over time and across political clusters. In detail, quarantine related geo-social media post were significantly less correlated to COVID-19 cases in republican states than in democrat states. Further, preventive measure and quarantine-related posts exhibited declining correlations to COVID-19 cases over time, while the correlations of vaccine and virus-related posts with COVID-19 infections.<\/jats:p><\/jats:sec><jats:sec><jats:title>Conclusion<\/jats:title><jats:p>Our results highlight the need for a dynamic spatially targeted approach that accounts for both how regional geosocial media topics of interest change over time and the impact of local political ideology on their epidemiological early warning capabilities.<\/jats:p><\/jats:sec>","DOI":"10.3389\/fpubh.2025.1618347","type":"journal-article","created":{"date-parts":[[2025,7,1]],"date-time":"2025-07-01T05:29:25Z","timestamp":1751347765000},"update-policy":"https:\/\/doi.org\/10.3389\/crossmark-policy","source":"Crossref","is-referenced-by-count":1,"title":["How politics affect pandemic forecasting: spatio-temporal early warning capabilities of different geo-social media topics in the context of state-level political leaning"],"prefix":"10.3389","volume":"13","author":[{"given":"Dorian","family":"Arifi","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Bernd","family":"Resch","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Mauricio","family":"Santillana","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Steffen","family":"Knoblauch","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Sven","family":"Lautenbach","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Thomas","family":"Jaenisch","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ivonne","family":"Morales","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1965","published-online":{"date-parts":[[2025,7,1]]},"reference":[{"key":"B1","doi-asserted-by":"publisher","first-page":"365","DOI":"10.1080\/10408363.2020.1783198","article-title":"The COVID-19 pandemic","volume":"57","author":"Ciotti","year":"2020","journal-title":"Crit Rev Clin Lab Sci."},{"key":"B2","doi-asserted-by":"publisher","first-page":"105986","DOI":"10.1016\/j.compbiomed.2022.105986","article-title":"COVID-19 forecasting using new viral variants and vaccination effectiveness models","volume":"149","author":"Rashed","year":"2022","journal-title":"Comput Biol Med."},{"key":"B3","doi-asserted-by":"publisher","first-page":"679","DOI":"10.1177\/1075547020950735","article-title":"Politicization and polarization in COVID-19 news coverage","volume":"42","author":"Hart","year":"2020","journal-title":"Sci Commun."},{"key":"B4","doi-asserted-by":"publisher","first-page":"163","DOI":"10.1057\/s41302-020-00186-0","article-title":"Politicizing the mask: political, economic and demographic factors affecting mask wearing behavior in the USA","volume":"47","author":"Kahane","year":"2021","journal-title":"Eastern Econ J."},{"key":"B5","doi-asserted-by":"publisher","first-page":"23780231211023657","DOI":"10.1177\/23780231211023657","article-title":"COVID-19 vaccine hesitancy is the new terrain for political division among Americans","volume":"7","author":"Cowan","year":"2021","journal-title":"Socius."},{"key":"B6","doi-asserted-by":"publisher","first-page":"200","DOI":"10.1002\/hbe2.202","article-title":"Political polarization drives online conversations about COVID-19 in the United States","volume":"2","author":"Jiang","year":"2020","journal-title":"Hum Behav Emerg Technol."},{"key":"B7","unstructured":"Tyson\n              A\n            \n            \n              Johnson\n              C\n            \n            \n              Funk\n              C\n            \n          \n          US Public Now Divided Over Whether To Get COVID-19 Vaccine.\n          \n          2020"},{"key":"B8","doi-asserted-by":"publisher","first-page":"e20285","DOI":"10.2196\/20285","article-title":"Real-time forecasting of the COVID-19 outbreak in Chinese Provinces: machine learning approach using novel digital data and estimates from mechanistic models","volume":"22","author":"Liu","year":"2020","journal-title":"J Med Internet Res."},{"key":"B9","doi-asserted-by":"publisher","first-page":"eabq0199","DOI":"10.1126\/sciadv.abq0199","article-title":"Using digital traces to build prospective and real-time county-level early warning systems to anticipate COVID-19 outbreaks in the United States","volume":"9","author":"Stolerman","year":"2023","journal-title":"Sci Adv"},{"key":"B10","doi-asserted-by":"publisher","first-page":"eabd6989","DOI":"10.1126\/sciadv.abd6989","article-title":"An early warning approach to monitor COVID-19 activity with multiple digital traces in near real time","volume":"7","author":"Kogan","year":"2021","journal-title":"Sci. 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