{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,8]],"date-time":"2026-10-08T06:51:38Z","timestamp":1791442298740,"version":"4.3.3"},"reference-count":44,"publisher":"Wiley","issue":"7","license":[{"start":{"date-parts":[[2023,5,25]],"date-time":"2023-05-25T00:00:00Z","timestamp":1684972800000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/onlinelibrary.wiley.com\/termsAndConditions#vor"}],"content-domain":{"domain":["onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["Tropical Med Int Health"],"published-print":{"date-parts":[[2023,7]]},"abstract":"<jats:title>Abstract<\/jats:title><jats:sec><jats:title>Objectives<\/jats:title><jats:p>Scrub typhus is an increasingly serious public health problem, which is becoming the most common vector\u2010borne disease in Guangzhou. This study aimed to analyse the correlation between scrub typhus incidence and potential factors and rank the importance of influential factors.<\/jats:p><\/jats:sec><jats:sec><jats:title>Methods<\/jats:title><jats:p>We collected monthly scrub typhus cases, meteorological variables, rodent density (RD), Normalised Difference Vegetation Index (NDVI), and land use type in Guangzhou from 2006 to 2019. Correlation analysis and a random forest model were used to identify the risk factors for scrub typhus and predict the importance rank of influencing factors related to scrub typhus incidence.<\/jats:p><\/jats:sec><jats:sec><jats:title>Results<\/jats:title><jats:p>The epidemiological results of the scrub typhus cases in Guangzhou between 2006 and 2019 showed that the incidence rate was on the rise. The results of correlation analysis revealed that a positive relationship between scrub typhus incidence and meteorological factors of mean temperature (T<jats:sub>mean<\/jats:sub>), accumulative rainfall (RF), relative humidity (RH), sunshine hours (SH), and NDVI, RD, population density, and green land coverage area (all <jats:italic>p<\/jats:italic>\u2009&lt;\u20090.001). Additionally, we tested the relationship between the incidence of scrub typhus and the lagging meteorological factors through cross\u2010correlation function, and found that incidence was positively correlated with 1\u2010month lag T<jats:sub>mean<\/jats:sub>, 2\u2010month lag RF, 2\u2010month lag RH, and 6\u2010month lag SH (all <jats:italic>p<\/jats:italic>\u2009&lt;\u20090.001). Based on the random forest model, we found that the T<jats:sub>mean<\/jats:sub> was the most important predictor among the influential factors, followed by NDVI.<\/jats:p><\/jats:sec><jats:sec><jats:title>Conclusions<\/jats:title><jats:p>Meteorological factors, NDVI, RD, and land use type jointly affect the incidence of scrub typhus in Guangzhou. Our results provide a better understanding of the influential factors correlated with scrub typus, which can improve our capacity for biological monitoring and help public health authorities to formulate disease control strategies.<\/jats:p><\/jats:sec>","DOI":"10.1111\/tmi.13896","type":"journal-article","created":{"date-parts":[[2023,5,25]],"date-time":"2023-05-25T23:44:26Z","timestamp":1685058266000},"page":"551-561","update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":14,"title":["Prediction of risk factors for scrub typhus from 2006 to 2019 based on random forest model in Guangzhou, China"],"prefix":"10.1111","volume":"28","author":[{"given":"Xiaobin","family":"Huang","sequence":"first","affiliation":[{"name":"School of Public Health Sun Yat\u2010Sen University  Guangzhou China"},{"name":"Department of Parasitic Disease and Endemic Disease Control and Prevention Guangzhou Center for Disease Control and Prevention  Guangzhou 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