{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,9,29]],"date-time":"2025-09-29T00:12:46Z","timestamp":1759104766071,"version":"3.41.0"},"reference-count":36,"publisher":"SAGE Publications","issue":"7","license":[{"start":{"date-parts":[[2017,2,8]],"date-time":"2017-02-08T00:00:00Z","timestamp":1486512000000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/journals.sagepub.com\/page\/policies\/text-and-data-mining-license"}],"content-domain":{"domain":["journals.sagepub.com"],"crossmark-restriction":true},"short-container-title":["SIMULATION"],"published-print":{"date-parts":[[2017,7]]},"abstract":"<jats:p>Epidemic modeling can be used to gain better understanding of infectious diseases, such as diarrhea. In the presented research, a continuous mathematical model has been formulated for diarrhea caused by salmonella. This model has been analyzed and simulated to be established in a functioning form.<\/jats:p><jats:p>Elementary model analysis, such as working out the disease-free state and basic reproduction number, has been done for this model. The basic reproduction number has been calculated using the next generation matrix method. Stability analysis of the model has been done using the Routh\u2013Hurwitz method. Sensitivity analysis and parameter estimation have been completed for the system too using MATLAB packages that work on the Latin Hypercube Sampling and Partial Rank Correlation Coefficient methods.<\/jats:p><jats:p>It was established that as long as R<jats:sub>0<\/jats:sub>&lt; 1, there will be no epidemic. Upon simulation using assumed parameter values, the results produced comprehended the epidemic theory and practical situations. The system was proven stable using the Routh\u2013Hurwitz criterion and parameter estimation was successfully completed.<\/jats:p><jats:p>Salmonella diarrhea has been successfully modeled and analyzed in this research. This model has been flexibly built and it can be integrated onto certain platforms to be used as a predictive system to prevent further infections of salmonella diarrhea.<\/jats:p>","DOI":"10.1177\/0037549716685409","type":"journal-article","created":{"date-parts":[[2017,2,8]],"date-time":"2017-02-08T09:58:33Z","timestamp":1486547913000},"page":"543-552","update-policy":"https:\/\/doi.org\/10.1177\/sage-journals-update-policy","source":"Crossref","is-referenced-by-count":3,"title":["Epidemic model formulation and analysis for diarrheal infections caused by salmonella"],"prefix":"10.1177","volume":"93","author":[{"given":"Ojaswita","family":"Chaturvedi","sequence":"first","affiliation":[{"name":"Department of Electrical and Electronics Engineering, University of Botswana, Botswana"}]},{"given":"Mandu","family":"Jeffrey","sequence":"additional","affiliation":[{"name":"Department of Electrical and Electronics Engineering, University of Botswana, Botswana"}]},{"given":"Edward","family":"Lungu","sequence":"additional","affiliation":[{"name":"Botswana International University of Science and Technology, Botswana"}]},{"given":"Shedden","family":"Masupe","sequence":"additional","affiliation":[{"name":"Botswana Institute of Technology Research and Innovation, Botswana"}]}],"member":"179","published-online":{"date-parts":[[2017,2,8]]},"reference":[{"unstructured":"Bayor College of Medicine, Department of Molecular Virology and Microbiology, Research \u2013 Emerging Infectious Diseases.","key":"bibr1-0037549716685409"},{"doi-asserted-by":"publisher","key":"bibr2-0037549716685409","DOI":"10.1136\/jech.2003.011593"},{"unstructured":"Introduction to Epidemiology. 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