{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,7]],"date-time":"2026-08-07T16:24:00Z","timestamp":1786119840800,"version":"build-2736575974"},"reference-count":50,"publisher":"American Geophysical Union (AGU)","issue":"5","license":[{"start":{"date-parts":[[2026,5,22]],"date-time":"2026-05-22T00:00:00Z","timestamp":1779408000000},"content-version":"vor","delay-in-days":21,"URL":"http:\/\/creativecommons.org\/licenses\/by-nc\/4.0\/"},{"start":{"date-parts":[[2026,5,1]],"date-time":"2026-05-01T00:00:00Z","timestamp":1777593600000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/doi.wiley.com\/10.1002\/tdm_license_1.1"}],"content-domain":{"domain":["agupubs.onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["GeoHealth"],"published-print":{"date-parts":[[2026,5]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:p>Understanding how climate modulates infectious disease dynamics is critical for anticipating epidemic patterns. After a hot debate on potential facilitation of population spread by climate factors during the first 2 years of the COVID\u201019 pandemics, not much attention has been devoted to assess whether the ensuing SARS\u2010CoV\u20102 waves also displayed similar climatic facilitation, or conversely, whether immunity dismissed any such forcing and potential signatures. This study examines the association between climatological variables\u2014specifically temperature and absolute humidity (AH)\u2014and the global incidence of the SARS\u2010CoV\u20102 Omicron variant (B.1.1.529) during its massive epidemic wave (2021\u20132022). Using global\u2010scale epidemiological and climate data, we applied the scale\u2010dependent correlation analysis to identify transient, scale\u2010specific non\u2010linear associations between factors and the disease across regions. We found consistent significant local negative correlations between incidence and both temperature ( to ) and AH ( to ), particularly in mid\u2010latitudes during colder months. Threshold analyses revealed temperature and humidity ranges of 12\u00b0C\u201321\u00b0C and 8\u201312\u00a0g , respectively, where transmission was most favored, fully in line with previous results obtained for the first COVID\u201019 variants. A stochastic population\u2010based model incorporating a temperature\u2010modulated infection rate reproduced epidemic dynamics more accurately than constant or seasonal formulations, reducing normalized residuals by approximately 40%\u201350%. These results largely demonstrate a robust climatic influence also on Omicron transmission yet underscoring the value of integrating environmental drivers into epidemic modeling and early\u2010warning frameworks.<\/jats:p>","DOI":"10.1029\/2025gh001750","type":"journal-article","created":{"date-parts":[[2026,5,22]],"date-time":"2026-05-22T09:11:21Z","timestamp":1779441081000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Climatic Influence on COVID\u201019: Investigating the Role of Temperature and Humidity in the Spread of the Omicron Variant"],"prefix":"10.1029","volume":"10","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-5351-9899","authenticated-orcid":false,"given":"Leonardo","family":"L\u00f3pez","sequence":"first","affiliation":[{"name":"Climate and Health Group CANU Barcelona Institute of Global Health (ISGlobal)  Barcelona Spain"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1138-2158","authenticated-orcid":false,"given":"Alejandro","family":"Fontal","sequence":"additional","affiliation":[{"name":"Climate and Health Group CANU Barcelona Institute of Global Health (ISGlobal)  Barcelona Spain"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Brandon","family":"Alfaro","sequence":"additional","affiliation":[{"name":"Barcelona University (UB)  Barcelona Spain"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4843-6180","authenticated-orcid":false,"given":"Xavier","family":"Rod\u00f3","sequence":"additional","affiliation":[{"name":"Climate and Health Group CANU Barcelona Institute of Global Health (ISGlobal)  Barcelona Spain"},{"name":"Catalan Institution for Research and Advanced Studies (ICREA)  Barcelona Spain"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"13","published-online":{"date-parts":[[2026,5,22]]},"reference":[{"key":"e_1_2_8_1_2_1","doi-asserted-by":"publisher","DOI":"10.1016\/s0140\u20106736(22)00941\u20102"},{"key":"e_1_2_8_1_3_1","doi-asserted-by":"publisher","DOI":"10.1073\/pnas.1321656111"},{"key":"e_1_2_8_1_4_1","doi-asserted-by":"publisher","DOI":"10.3201\/eid2905.221752"},{"key":"e_1_2_8_1_5_1","doi-asserted-by":"publisher","unstructured":"Center for International Earth Science Information Network (CIESIN). 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