<HashMap><database>biostudies-literature</database><scores/><additional><submitter>Wu R</submitter><funding>Scientific Research Project of Chongqing Talent Plan</funding><funding>the Key Research and Development Project in the Health Field of Chongqing</funding><pagination>2674</pagination><full_dataset_link>https://www.ebi.ac.uk/biostudies/studies/S-EPMC11443759</full_dataset_link><repository>biostudies-literature</repository><omics_type>Unknown</omics_type><volume>24(1)</volume><pubmed_abstract>&lt;h4>Background&lt;/h4>This study aimed to investigate the epidemiological changes in scarlet fever before, during and after the COVID-19 pandemic (2005-2023) and predict the incidence of the disease in 2024 and 2025 in Chongqing Municipality, Southwest China.&lt;h4>Methods&lt;/h4>Descriptive analysis was used to summarize the characteristics of the scarlet fever epidemic. Spatial autocorrelation analysis was utilized to explore the distribution pattern of the disease, and the seasonal autoregressive integrated moving average (SARIMA) model was constructed to predict its incidence in 2024 and 2025.&lt;h4>Results&lt;/h4>Between 2005 and 2023, 9,593 scarlet fever cases were reported in Chongqing, which resulted in an annual average incidence of 1.6694 per 100,000 people. Children aged 3-7 were the primary v</pubmed_abstract><journal>BMC public health</journal><pubmed_title>Epidemiological changes of scarlet fever before, during and after the COVID-19 pandemic in Chongqing, China: a 19-year surveillance and prediction study.</pubmed_title><pmcid>PMC11443759</pmcid><funding_grant_id>CSTC2021jscx-gksb-N0003</funding_grant_id><funding_grant_id>cstc2022ycjh-bgzxm0251</funding_grant_id><pubmed_authors>Yang J</pubmed_authors><pubmed_authors>Qi L</pubmed_authors><pubmed_authors>Yang L</pubmed_authors><pubmed_authors>Yin T</pubmed_authors><pubmed_authors>Long J</pubmed_authors><pubmed_authors>Li Q</pubmed_authors><pubmed_authors>Zhong X</pubmed_authors><pubmed_authors>Su K</pubmed_authors><pubmed_authors>Wang J</pubmed_authors><pubmed_authors>Xiong Y</pubmed_authors><pubmed_authors>Wu R</pubmed_authors><pubmed_authors>Chen Y</pubmed_authors><pubmed_authors>Li B</pubmed_authors><pubmed_authors>Tang W</pubmed_authors><pubmed_authors>Sun J</pubmed_authors><pubmed_authors>Zhao H</pubmed_authors></additional><is_claimable>false</is_claimable><name>Epidemiological changes of scarlet fever before, during and after the COVID-19 pandemic in Chongqing, China: a 19-year surveillance and prediction study.</name><description>&lt;h4>Background&lt;/h4>This study aimed to investigate the epidemiological changes in scarlet fever before, during and after the COVID-19 pandemic (2005-2023) and predict the incidence of the disease in 2024 and 2025 in Chongqing Municipality, Southwest China.&lt;h4>Methods&lt;/h4>Descriptive analysis was used to summarize the characteristics of the scarlet fever epidemic. Spatial autocorrelation analysis was utilized to explore the distribution pattern of the disease, and the seasonal autoregressive integrated moving average (SARIMA) model was constructed to predict its incidence in 2024 and 2025.&lt;h4>Results&lt;/h4>Between 2005 and 2023, 9,593 scarlet fever cases were reported in Chongqing, which resulted in an annual average incidence of 1.6694 per 100,000 people. Children aged 3-7 were the primary v</description><dates><release>2024-01-01T00:00:00Z</release><publication>2024 Sep</publication><modification>2026-06-06T22:18:59.491Z</modification><creation>2025-04-06T16:25:49.462Z</creation></dates><accession>S-EPMC11443759</accession><cross_references><pubmed>39350134</pubmed><doi>10.1186/s12889-024-20116-5</doi></cross_references></HashMap>