Basic Reproduction Number (R₀) in Epidemiological Analysis: An Artificial Intelligence Approach to Assess BCG Vaccination Impact in Ecuador

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Abstract This study examines the significance of the basic reproduction number (R0) in epidemiological modeling, with a specific focus on tuberculosis (TB) control through Bacillus Calmette-Guérin (BCG) vaccination in Ecuador. Using artificial intelligence techniques, we developed a modified Susceptible-Infected-Recovered (SIR) model to evaluate the impact of Ecuador's single-dose BCG vaccination policy. Our analysis revealed an estimated average R0 of 0.00329, with BCG vaccination contributing to an average reduction of 54.59 cases per 100,000 population, representing a 49.65% decrease in TB incidence. This paper discusses the advantages and limitations of R0 calculation in epidemiological studies and highlights the implications for tuberculosis control strategies in Ecuador and similar settings. Our findings underscore the value of R0 as a critical parameter for assessing vaccination program effectiveness and guiding public health interventions.
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Basic Reproduction Number (R₀) in Epidemiological Analysis: An Artificial Intelligence Approach to Assess BCG Vaccination Impact in Ecuador | 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 Method Article Basic Reproduction Number (R₀) in Epidemiological Analysis: An Artificial Intelligence Approach to Assess BCG Vaccination Impact in Ecuador Jose Sanchez, Adrila This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6379000/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 This study examines the significance of the basic reproduction number (R0) in epidemiological modeling, with a specific focus on tuberculosis (TB) control through Bacillus Calmette-Guérin (BCG) vaccination in Ecuador. Using artificial intelligence techniques, we developed a modified Susceptible-Infected-Recovered (SIR) model to evaluate the impact of Ecuador's single-dose BCG vaccination policy. Our analysis revealed an estimated average R0 of 0.00329, with BCG vaccination contributing to an average reduction of 54.59 cases per 100,000 population, representing a 49.65% decrease in TB incidence. This paper discusses the advantages and limitations of R0 calculation in epidemiological studies and highlights the implications for tuberculosis control strategies in Ecuador and similar settings. Our findings underscore the value of R0 as a critical parameter for assessing vaccination program effectiveness and guiding public health interventions. Infectious Diseases Biostatistics Statistical Epidemiology Epidemiology Basic reproduction number Tuberculosis BCG vaccination Artificial intelligence Epidemiological modeling Ecuador Full Text Additional Declarations The authors declare no competing interests. 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. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. 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