Enhancing Public Health Surveillance: Outbreak Detection Algorithms Deployed for Syndromic Surveillance during Arbaeenia Mass Gatherings in Iraq

Enhancing Public Health Surveillance: Outbreak Detection Algorithms Deployed for Syndromic Surveillance during Arbaeenia Mass Gatherings in Iraq | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Enhancing Public Health Surveillance: Outbreak Detection Algorithms Deployed for Syndromic Surveillance during Arbaeenia Mass Gatherings in Iraq Mustafa Suraifi, Ali Delpisheh, Manoochehr Karami, Yadollah Mehrabi, and 2 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4137394/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 11 May, 2024 Read the published version in Cureus → Version 1 posted You are reading this latest preprint version Abstract Background Mass gatherings frequently include close, prolonged interactions between people, which present opportunities for infectious disease transmission. Few published studies have used outbreak detection algorithm methods for real syndrome data collected during mass gatherings. This study aimed to describe the implementation and effectiveness of outbreak detection algorithms for syndromic surveillance during mass gatherings in Iraq. Methods The field data collection involved the participation of 10 data collectors, who carried out the data collection activities over ten days, specifically from August 25, 2023, to September 3, 2023. The data were obtained from 10 healthcare clinics along the major route from Najaf to Karbala, specifically on Ya Hussein Road. The numbers of syndromes reported by applied outbreak detection algorithms include moving average (MA), cumulative sum (CUSUM), and exponential weighted moving average (EWMA). Results A total of 12,202 pilgrims (49.5% females and 50.5% males) visited the 10 health clinics over 10 days from 25 Aug 2023 to 03 Sep 2023. More than three-quarters of the pilgrims (77.4%, n = 9,444), were between the ages of 20 and 59. More than half of the pilgrims were foreigners, accounting for 58.1% (n = 7,092) of the total, and approximately 41.9% (n = 5,110) originated from Iraq. Of those, 40.5% (n = 4,938) had syndromes, 48.8% (n = 2411) had ILI syndromes, 21.2% (n = 1048) had food poisoning syndrome, 17.7% (n = 875) had heatstroke syndrome, 9.0% (n = 446) had febrile rash syndrome, and 3.2% (n = 158) had gastroenteritis syndrome. The CUSUM algorithm was preferable for detecting small shifts compared to the EWMA and MA algorithms. Conclusions The importance of robust public health surveillance systems, particularly during mass gatherings, is to promptly detect and respond to emerging health threats. By leveraging advanced algorithms and real-time data analysis, authorities can enhance their preparedness and response capabilities, ultimately safeguarding public health during such events. Public health surveillance Outbreak detection algorithms Syndromes Arbaeenia Mass gatherings Iraq Full Text Additional Declarations No competing interests reported. Cite Share Download PDF Status: Published Journal Publication published 11 May, 2024 Read the published version in Cureus → Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-4137394","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":283499215,"identity":"8d37b914-0d53-4ad0-bc49-59b4f0178331","order_by":0,"name":"Mustafa 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Iraq","lastPublishedDoi":"10.21203/rs.3.rs-4137394/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4137394/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003eMass gatherings frequently include close, prolonged interactions between people, which present opportunities for infectious disease transmission. Few published studies have used outbreak detection algorithm methods for real syndrome data collected during mass gatherings. This study aimed to describe the implementation and effectiveness of outbreak detection algorithms for syndromic surveillance during mass gatherings in Iraq.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eThe field data collection involved the participation of 10 data collectors, who carried out the data collection activities over ten days, specifically from August 25, 2023, to September 3, 2023. The data were obtained from 10 healthcare clinics along the major route from Najaf to Karbala, specifically on Ya Hussein Road. The numbers of syndromes reported by applied outbreak detection algorithms include moving average (MA), cumulative sum (CUSUM), and exponential weighted moving average (EWMA).\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eA total of 12,202 pilgrims (49.5% females and 50.5% males) visited the 10 health clinics over 10 days from 25 Aug 2023 to 03 Sep 2023. More than three-quarters of the pilgrims (77.4%, n\u0026thinsp;=\u0026thinsp;9,444), were between the ages of 20 and 59. More than half of the pilgrims were foreigners, accounting for 58.1% (n\u0026thinsp;=\u0026thinsp;7,092) of the total, and approximately 41.9% (n\u0026thinsp;=\u0026thinsp;5,110) originated from Iraq. Of those, 40.5% (n\u0026thinsp;=\u0026thinsp;4,938) had syndromes, 48.8% (n\u0026thinsp;=\u0026thinsp;2411) had ILI syndromes, 21.2% (n\u0026thinsp;=\u0026thinsp;1048) had food poisoning syndrome, 17.7% (n\u0026thinsp;=\u0026thinsp;875) had heatstroke syndrome, 9.0% (n\u0026thinsp;=\u0026thinsp;446) had febrile rash syndrome, and 3.2% (n\u0026thinsp;=\u0026thinsp;158) had gastroenteritis syndrome. The CUSUM algorithm was preferable for detecting small shifts compared to the EWMA and MA algorithms.\u003c/p\u003e\u003ch2\u003eConclusions\u003c/h2\u003e \u003cp\u003eThe importance of robust public health surveillance systems, particularly during mass gatherings, is to promptly detect and respond to emerging health threats. By leveraging advanced algorithms and real-time data analysis, authorities can enhance their preparedness and response capabilities, ultimately safeguarding public health during such events.\u003c/p\u003e","manuscriptTitle":"Enhancing Public Health Surveillance: Outbreak Detection Algorithms Deployed for Syndromic Surveillance during Arbaeenia Mass Gatherings in Iraq","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-03-28 04:40:35","doi":"10.21203/rs.3.rs-4137394/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"457c5e6b-51d5-4ef6-883e-b72375a938dd","owner":[],"postedDate":"March 28th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2024-05-13T15:13:15+00:00","versionOfRecord":{"articleIdentity":"rs-4137394","link":"https://doi.org/10.7759/cureus.60134","journal":{"identity":"cureus","isVorOnly":true,"title":"Cureus"},"publishedOn":"2024-05-12 00:00:00","publishedOnDateReadable":"May 12th, 2024"},"versionCreatedAt":"2024-03-28 04:40:35","video":"","vorDoi":"10.7759/cureus.60134","vorDoiUrl":"https://doi.org/10.7759/cureus.60134","workflowStages":[]},"version":"v1","identity":"rs-4137394","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4137394","identity":"rs-4137394","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}