{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,23]],"date-time":"2026-09-23T17:46:02Z","timestamp":1790185562450,"version":"4.1.0"},"reference-count":48,"publisher":"Frontiers Media SA","license":[{"start":{"date-parts":[[2026,4,29]],"date-time":"2026-04-29T00:00:00Z","timestamp":1777420800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["frontiersin.org"],"crossmark-restriction":true},"short-container-title":["Front. Public Health"],"abstract":"<jats:sec>\n                    <jats:title>Background<\/jats:title>\n                    <jats:p>Infectious diarrhea remains a significant public health challenge, with climatic factors potentially playing a crucial role in its epidemiological spread. However, the precise mechanisms through which the El Ni\u00f1o-Southern Oscillation (ENSO) influences diarrheal morbidity are still not fully understood.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>We collected monthly other infectious diarrhea (OID) incidence and climatic data across the 31 provincial administrative divisions of mainland China (2005\u20132019). Wavelet analysis was employed to examine the periodicity of OID and the phase relationships between ENSO, climate factors and OID. Generalized additive models (GAM) and Peter and Clark Momentary Conditional Independence (PCMCI) algorithm were used to quantify exposure-response relationship and establish causal pathways in China.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>From 2005 to 2019, a total of 13,620,167 OID cases were reported in 31 provincial regions of China, with the highest incidence of OID concentrated in the southern and eastern regions of China. Wavelet analysis identified a significant periodicity between ENSO cycles and diarrhea incidence patterns, demonstrating that La Ni\u00f1a events (characterized by low ENSO index) were associated with subsequent increases in incidence with a 6-month lag. The exposure-response relationship showed an inverted J-shaped curve in North and East China, while a nearly linear relationship was observed in Northeast, Central, Southwest and Northwest China. PCMCI analysis elucidated that precipitation is an indirect link between ENSO and OID.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusion<\/jats:title>\n                    <jats:p>Our study suggests that a low ENSO index (La Ni\u00f1a) may drive the incidence of OID in China. The findings provide a scientific basis for predicting and warning of OID based on ENSO.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.3389\/fpubh.2026.1791469","type":"journal-article","created":{"date-parts":[[2026,4,29]],"date-time":"2026-04-29T06:08:21Z","timestamp":1777442901000},"update-policy":"https:\/\/doi.org\/10.3389\/crossmark-policy","source":"Crossref","is-referenced-by-count":1,"title":["The impact of El Ni\u00f1o-Southern Oscillation on the incidence of infectious diarrhea in China: insights from a 15-year national surveillance analysis"],"prefix":"10.3389","volume":"14","author":[{"given":"Keer","family":"Ou","sequence":"first","affiliation":[{"name":"School of Public Health, Guangdong Pharmaceutical University","place":["Guangzhou, China"]},{"name":"Guangdong Provincial Institute of Public Health, Guangdong Provincial Center for Disease Control and Prevention","place":["Guangzhou, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xing","family":"Li","sequence":"additional","affiliation":[{"name":"Guangdong Provincial Institute of Public Health, Guangdong Provincial Center for Disease Control and Prevention","place":["Guangzhou, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Weilin","family":"Zeng","sequence":"additional","affiliation":[{"name":"Guangdong Provincial Institute of Public Health, Guangdong Provincial Center for Disease Control and Prevention","place":["Guangzhou, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yue","family":"Shi","sequence":"additional","affiliation":[{"name":"National Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases, Division of Infectious Disease, Chinese Center for Disease Control and Prevention (Chinese Academy of Preventive Medicine)","place":["Beijing, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Zuhua","family":"Rong","sequence":"additional","affiliation":[{"name":"Guangdong Provincial Institute of Public Health, Guangdong Provincial Center for Disease Control and Prevention","place":["Guangzhou, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yingtao","family":"Zhang","sequence":"additional","affiliation":[{"name":"Guangdong Provincial Center for Disease Control and Prevention","place":["Guangzhou, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Shu","family":"Xiao","sequence":"additional","affiliation":[{"name":"Guangdong Provincial Institute of Public Health, Guangdong Provincial Center for Disease Control and Prevention","place":["Guangzhou, China"]},{"name":"School of Medicine, Jinan University","place":["Guangzhou, Guangdong, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Zhongyi","family":"Fan","sequence":"additional","affiliation":[{"name":"Guangdong Provincial Institute of Public Health, Guangdong Provincial Center for Disease Control and Prevention","place":["Guangzhou, China"]},{"name":"School of Public Health, Southern Medical University","place":["Guangzhou, Guangdong, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Mengjie","family":"Geng","sequence":"additional","affiliation":[{"name":"National Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases, Division of Infectious Disease, Chinese Center for Disease Control and Prevention (Chinese Academy of Preventive Medicine)","place":["Beijing, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Hongwei","family":"Tu","sequence":"additional","affiliation":[{"name":"Guangdong Provincial Center for Disease Control and Prevention","place":["Guangzhou, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jianpeng","family":"Xiao","sequence":"additional","affiliation":[{"name":"School of Public Health, Guangdong Pharmaceutical University","place":["Guangzhou, China"]},{"name":"Guangdong Provincial Institute of Public Health, Guangdong Provincial Center for Disease Control and Prevention","place":["Guangzhou, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1965","published-online":{"date-parts":[[2026,4,29]]},"reference":[{"key":"ref1","doi-asserted-by":"publisher","first-page":"519","DOI":"10.1016\/S1473-3099(24)00691-1","article-title":"Global, regional, and national age-sex-specific burden of diarrhoeal diseases, their risk factors, and aetiologies, 1990\u20132021, for 204 countries and territories: a systematic analysis for the global burden of disease study 2021","volume":"25","year":"2025","journal-title":"Lancet Infect 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