{"paper_id":"37bebc95-c7be-4159-b6b7-3dc0c4816696","body_text":"On the use of Structural Equation Modeling in Infectious Disease Epidemiology: a systematic and critical review | 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 On the use of Structural Equation Modeling in Infectious Disease Epidemiology: a systematic and critical review Bissilimou Rachidatou Orounla, Kolawolé Valère Salako, Justice Moses K. Aheto, and 1 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6789648/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Structural Equation Modeling (SEM) is a multivariate statistical technique increasingly used in epidemiology to analyze complex causal relationships. This paper focuses on the practical use of the SEM technique and analyze applications in terms of model design, model development, and model evaluation to address epidemics-related problems based on articles published from 2013 to 2022. The selection of articles was based on the PRISMA methodology. The review was based on 111 scientific papers after applying the exclusion criteria. Data on research design, sample size, software, estimation methods and evaluation methods were extracted.Findings reveal a significant rise in SEM applications over the past decade, particularly during the COVID-19 pandemic, with 70.45 % of the studies focused on COVID-19-related issues. Partial Least Squares SEM (PLS-SEM) was the most frequently applied estimation method (50 %), followed by Maximum Likelihood Estimation (29.17 %) and Bayesian approaches (8.33 %). The most commonly used software included AMOS (25.68 %), SPSS (24.32 %), and Smart-PLS (14.86 %). Model evaluation relied on absolute fit indices such as Root Mean Square Error of Approximation (RMSEA; 14.47 %), Chi-square (7 %), and Standardized Root Mean Square Residual (SRMR ; 7.23 %), as well as incremental indices like Comparative Fit Index (CFI; 14.47%) and Tucker-Lewis Index (TLI; 7.55 %). Only 3.85 % of the studies had sample sizes below 100, while 24.03 % had 1,000 or more. An illustrative example of SEM applied to COVID-19 data is provided. This review underscores the growing relevance of SEM in epidemiology, emphasizing both its potential and the methodological considerations needed to ensure robust and interpretable results in public health research. Epidemiology SEM Estimation methods COVID-19 PRISMA Sample size Full Text Additional Declarations No competing interests reported. Cite Share Download PDF Status: Posted 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. 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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-6789648\",\"acceptedTermsAndConditions\":true,\"allowDirectSubmit\":true,\"archivedVersions\":[],\"articleType\":\"Research Article\",\"associatedPublications\":[],\"authors\":[{\"id\":473185189,\"identity\":\"0afc795c-05a4-42a0-8eca-c1adc3c3774e\",\"order_by\":0,\"name\":\"Bissilimou Rachidatou Orounla\",\"email\":\"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAxklEQVRIiWNgGAWjYHACNgbGBgkGfhAzoYAULZINIC0GxGthYDA4AGITo8W8/fCzBx93WNgbn1+d+OGBAYM8v9gB/FpkzqSZG848I5G47cbbzRJAhxnOnJ2AX4sEQw6bNG+bRILZjbMbQFoSDG4T0sL/BqzF3njG2c0/iNMiAbGFcQN/7zYibZF4ZiYJ8suMG7zbLBIMJIjwC3/yM4mPO+rs+fvPbr75o8JGnl+agBYkzWCVEsQqBwH+A6SoHgWjYBSMgpEEAJ1wP5LR+eInAAAAAElFTkSuQmCC\",\"orcid\":\"\",\"institution\":\"Université d'Abomey-Calavi\",\"correspondingAuthor\":true,\"prefix\":\"\",\"firstName\":\"Bissilimou\",\"middleName\":\"Rachidatou\",\"lastName\":\"Orounla\",\"suffix\":\"\"},{\"id\":473185190,\"identity\":\"8bb0984a-3bfe-46be-a8c1-da944622be89\",\"order_by\":1,\"name\":\"Kolawolé Valère Salako\",\"email\":\"\",\"orcid\":\"\",\"institution\":\"Université d'Abomey-Calavi\",\"correspondingAuthor\":false,\"prefix\":\"\",\"firstName\":\"Kolawolé\",\"middleName\":\"Valère\",\"lastName\":\"Salako\",\"suffix\":\"\"},{\"id\":473185191,\"identity\":\"7efcf7d1-48a1-4961-8733-4003e8bf3a06\",\"order_by\":2,\"name\":\"Justice Moses K. 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This paper focuses on the practical use of the SEM technique and analyze applications in terms of model design, model development, and model evaluation to address epidemics-related problems based on articles published from 2013 to 2022. The selection of articles was based on the PRISMA methodology. The review was based on 111 scientific papers after applying the exclusion criteria. Data on research design, sample size, software, estimation methods and evaluation methods were extracted.Findings reveal a significant rise in SEM applications over the past decade, particularly during the COVID-19 pandemic, with 70.45 % of the studies focused on COVID-19-related issues. Partial Least Squares SEM (PLS-SEM) was the most frequently applied estimation method (50 %), followed by Maximum Likelihood Estimation (29.17 %) and Bayesian approaches (8.33 %). The most commonly used software included AMOS (25.68 %), SPSS (24.32 %), and Smart-PLS (14.86 %). 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This review underscores the growing relevance of SEM in epidemiology, emphasizing both its potential and the methodological considerations needed to ensure robust and interpretable results in public health research.\\u003c/p\\u003e\",\"manuscriptTitle\":\"On the use of Structural Equation Modeling in Infectious Disease Epidemiology: a systematic and critical review\",\"msid\":\"\",\"msnumber\":\"\",\"nonDraftVersions\":[{\"code\":1,\"date\":\"2025-06-20 07:18:41\",\"doi\":\"10.21203/rs.3.rs-6789648/v1\",\"editorialEvents\":[{\"type\":\"communityComments\",\"content\":0}],\"status\":\"published\",\"journal\":{\"display\":true,\"email\":\"info@researchsquare.com\",\"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\":\"0d2d7cda-eae7-4a4b-ab41-abb21fed7aca\",\"owner\":[],\"postedDate\":\"June 20th, 2025\",\"published\":true,\"recentEditorialEvents\":[],\"rejectedJournal\":[],\"revision\":\"\",\"amendment\":\"\",\"status\":\"posted\",\"subjectAreas\":[],\"tags\":[],\"updatedAt\":\"2025-08-04T11:53:28+00:00\",\"versionOfRecord\":[],\"versionCreatedAt\":\"2025-06-20 07:18:41\",\"video\":\"\",\"vorDoi\":\"\",\"vorDoiUrl\":\"\",\"workflowStages\":[]},\"version\":\"v1\",\"identity\":\"rs-6789648\",\"journalConfig\":\"researchsquare\"},\"__N_SSP\":true},\"page\":\"/article/[identity]/[[...version]]\",\"query\":{\"redirect\":\"/article/rs-6789648\",\"identity\":\"rs-6789648\",\"version\":[\"v1\"]},\"buildId\":\"XKTyCvWXoU3ODBz1xrDgd\",\"isFallback\":false,\"isExperimentalCompile\":false,\"dynamicIds\":[84888],\"gssp\":true,\"scriptLoader\":[]}","source_license":"CC-BY-4.0","license_restricted":false}