{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,11]],"date-time":"2026-05-11T21:36:43Z","timestamp":1778535403947,"version":"3.51.4"},"update-to":[{"DOI":"10.1371\/journal.pntd.0013973","type":"new_version","label":"New version","source":"publisher","updated":{"date-parts":[[2026,2,20]],"date-time":"2026-02-20T00:00:00Z","timestamp":1771545600000}}],"reference-count":25,"publisher":"Public Library of Science (PLoS)","issue":"2","license":[{"start":{"date-parts":[[2026,2,17]],"date-time":"2026-02-17T00:00:00Z","timestamp":1771286400000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/100000865","name":"Bill and Melinda Gates Foundation","doi-asserted-by":"publisher","award":["INV-002381"],"award-info":[{"award-number":["INV-002381"]}],"id":[{"id":"10.13039\/100000865","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["www.plosntds.org"],"crossmark-restriction":false},"short-container-title":["PLoS Negl Trop Dis"],"abstract":"<jats:sec id=\"sec001\">\n                    <jats:title>Background<\/jats:title>\n                    <jats:p>Monitoring wastewater is vital for tracking typhoid fever in endemic areas. This study evaluated the performance of both spatial and non-spatial models in predicting Salmonella Typhi detection in wastewater from the Asante Akim North district in Ghana and identified key environmental risk factors.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec id=\"sec002\">\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>We collected wastewater samples of Moore swabs at 40 sites across Agogo, Juansa, Hwidiem, and Domeabra over a period of 27 months. Multiplex PCR was used to detect Salmonella Typhi, focusing on the ttr, tviB, and staG genes. An Aquaprobe AP-2000 was also used to measure different physicochemical factors, such as pH, temperature, dissolved oxygen, and salinity. Three non-spatial models, namely Generalized Estimating Equations (Logistic), Mixed-Effects Models, and Random Forest, as well as four spatial models, including Bayesian Generalized Additive Models (GAM) and Spatial Generalized Linear Mixed Models (GLMM), were fitted to the wastewater dataset. Model fitting was done using 5-fold cross-validation, stratified by site. Model performance was evaluated using accuracy, sensitivity, and specificity. We also used SHapley Additive exPlanations (SHAP) analysis to find the most important predictors.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec id=\"sec003\">\n                    <jats:title>Findings<\/jats:title>\n                    <jats:p>In general, 44.13% of the samples tested positive for S. Typhi. Detection was much higher during wet seasons (50.17% vs. 35.11%; p\u2009&lt;\u20090.001), with fast flows (64.45%), and in channels that were 1\u20132 meters wide (58.70%). Positive samples had relatively higher pH (7.46 vs. 7.40; p\u2009&lt;\u20090.001), dissolved oxygen (46.97% vs. 36.77%; p\u2009&lt;\u20090.001), and rainfall (3.92mm vs. 3.30mm; p\u2009=\u20090.022). In comparing both non-spatial and spatial models, the non-spatial Random Forest model demonstrated the highest performance with an accuracy of 0.993, sensitivity of 0.997, and specificity of 0.989. In the SHAP analysis of the preferred non-spatial random forest model, it was found that pH, season, dissolved oxygen, positivity from the previous month, and channel width were identified as the best predictors.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec id=\"sec004\">\n                    <jats:title>Conclusion<\/jats:title>\n                    <jats:p>S. Typhi detection is influenced by wastewater physicochemical properties, with pH, seasonal rainfall, and hydraulic conditions being the most significant. The non-spatial random forest model significantly outperforms both spatial and other non-spatial statistical methods.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1371\/journal.pntd.0013973","type":"journal-article","created":{"date-parts":[[2026,2,17]],"date-time":"2026-02-17T18:42:29Z","timestamp":1771353749000},"page":"e0013973","update-policy":"https:\/\/doi.org\/10.1371\/journal.pntd.corrections_policy","source":"Crossref","is-referenced-by-count":1,"title":["Statistical methods for predicting the presence of Salmonella Typhi in wastewater samples at Asante Akyem Agogo, Ghana"],"prefix":"10.1371","volume":"20","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-2196-0310","authenticated-orcid":true,"given":"Sampson","family":"Twumasi-Ankrah","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Michael","family":"Owusu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Michael","family":"Owusu-Ansah","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Seidu","family":"Amenyaglo","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Caleb","family":"Osei-Wusu Sarfo","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Eric","family":"Darko","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Portia","family":"Okyere Boakye","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Christopher B.","family":"Uzzell","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Isobel M.","family":"Blake","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Nicholas C.","family":"Grassly","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yaw","family":"Adu-Sarkodie","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ellis","family":"Owusu-Dabo","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"340","published-online":{"date-parts":[[2026,2,17]]},"reference":[{"issue":"11","key":"pntd.0013973.ref001","doi-asserted-by":"crossref","first-page":"1796","DOI":"10.3201\/eid1611.100388","article-title":"Typhoid fever among children, Ghana","volume":"16","author":"F Marks","year":"2010","journal-title":"Emerg Infect Dis"},{"issue":"1","key":"pntd.0013973.ref002","doi-asserted-by":"crossref","first-page":"111","DOI":"10.5334\/aogh.2833","article-title":"Prevalence of typhoid and paratyphoid fever in the hohoe municipality of the Volta Region, Ghana: a five-year retrospective trend analysis","volume":"86","author":"A Fusheini","year":"2020","journal-title":"Ann Glob Health"},{"issue":"2","key":"pntd.0013973.ref003","doi-asserted-by":"crossref","first-page":"1503","DOI":"10.1111\/jam.15237","article-title":"Optimized methods for detecting Salmonella Typhi in the environment using validated field sampling, culture and confirmatory molecular approaches","volume":"132","author":"J Rigby","year":"2022","journal-title":"J Appl Microbiol"},{"key":"pntd.0013973.ref004","doi-asserted-by":"crossref","unstructured":"Hughes M, Appiah G, Watkins LF. Typhoid and paratyphoid fever CDC Yellow Book. 2023. https:\/\/wwwnc.cdc.gov\/travel\/yellowbook\/2024\/infections-diseases\/typhoid-and-paratyphoid-fever","DOI":"10.70470\/SHIFAA\/2024\/007"},{"issue":"2","key":"pntd.0013973.ref005","article-title":"Mapping the incidence rate of typhoid fever in sub-Saharan Africa","volume":"18","author":"J-H Kim","year":"2024","journal-title":"PLoS Negl Trop Dis"},{"issue":"11","key":"pntd.0013973.ref006","article-title":"Spatial and temporal heterogeneities of district-level typhoid morbidities in Ghana: a requisite insight for informed public health response","volume":"13","author":"FB Osei","year":"2018","journal-title":"PLoS One"},{"issue":"4","key":"pntd.0013973.ref007","doi-asserted-by":"crossref","DOI":"10.1016\/S2214-109X(24)00007-X","article-title":"Incidence of typhoid fever in Burkina Faso, Democratic Republic of the Congo, Ethiopia, Ghana, Madagascar, and Nigeria (the Severe Typhoid in Africa programme): a population-based study","volume":"12","author":"F Marks","year":"2024","journal-title":"Lancet Glob Health"},{"issue":"1","key":"pntd.0013973.ref008","doi-asserted-by":"crossref","first-page":"229","DOI":"10.1007\/s11739-022-03101-x","article-title":"A comparison of machine learning algorithms in predicting COVID-19 prognostics","volume":"18","author":"S Ustebay","year":"2023","journal-title":"Intern Emerg Med"},{"issue":"48","key":"pntd.0013973.ref009","doi-asserted-by":"crossref","first-page":"1374","DOI":"10.15585\/mmwr.mm6548a4","article-title":"CDC grand rounds: modeling and public health decision-making","volume":"65","author":"LS Fischer","year":"2016","journal-title":"MMWR Morb Mortal Wkly Rep"},{"issue":"1","key":"pntd.0013973.ref010","doi-asserted-by":"crossref","first-page":"309","DOI":"10.1186\/s12911-022-02057-4","article-title":"Comparison of machine learning methods with logistic regression analysis in creating predictive models for risk of critical in-hospital events in COVID-19 patients on hospital admission","volume":"22","author":"AW Sievering","year":"2022","journal-title":"BMC Med Inform Decis Mak"},{"key":"pntd.0013973.ref011","author":"D Guo","year":"2022"},{"issue":"8","key":"pntd.0013973.ref012","doi-asserted-by":"crossref","first-page":"1377","DOI":"10.1093\/infdis\/jiaa175","article-title":"Characterizing Environmental Surveillance Sites in Nigeria and Their Sensitivity to Detect Poliovirus and Other Enteroviruses","volume":"225","author":"AW Hamisu","year":"2022","journal-title":"J Infect Dis"},{"issue":"4","key":"pntd.0013973.ref013","doi-asserted-by":"crossref","first-page":"979","DOI":"10.1093\/infdis\/jiad427","article-title":"Environmental surveillance for Salmonella Typhi and its association with typhoid fever incidence in India and Malawi","volume":"229","author":"CB Uzzell","year":"2024","journal-title":"J Infect Dis"},{"key":"pntd.0013973.ref014","article-title":"Environmental surveillance as a tool for estimating the burden of S.Typhi at the Asante Akim North district of Ashanti region \u2013 Ghana","author":"M Owusu","year":"2025","journal-title":"Public Library Sci"},{"key":"pntd.0013973.ref015","doi-asserted-by":"crossref","first-page":"9","DOI":"10.12688\/wellcomeopenres.17687.1","article-title":"Environmental surveillance for Salmonella Typhi as a tool to estimate the incidence of typhoid fever in low-income populations.","volume":"8","author":"CB Uzzell","year":"2023","journal-title":"Wellcome Open Res"},{"issue":"13","key":"pntd.0013973.ref016","doi-asserted-by":"crossref","first-page":"7754","DOI":"10.1021\/acs.est.0c02388","article-title":"Wastewater-based epidemiology: global collaborative to maximize contributions in the fight against COVID-19","volume":"54","author":"A Bivins","year":"2020","journal-title":"Environ Sci Technol"},{"issue":"10","key":"pntd.0013973.ref017","first-page":"1162","article-title":"The effect of channel flow velocity on the transport and distribution of Escherichia coli in water","volume":"49","author":"G Lutterodt","year":"2014","journal-title":"J Environ Sci Health Part A"},{"issue":"4","key":"pntd.0013973.ref018","doi-asserted-by":"crossref","first-page":"369","DOI":"10.1016\/S1473-3099(18)30685-6","article-title":"The global burden of typhoid and paratyphoid fevers: a systematic analysis for the Global Burden of Disease Study 2017","volume":"19","author":"GBD 2017 Typhoid and Paratyphoid Collaborators","year":"2019","journal-title":"Lancet Infect Dis"},{"issue":"1","key":"pntd.0013973.ref019","doi-asserted-by":"crossref","first-page":"17164","DOI":"10.1038\/s41598-024-66436-9","article-title":"Modelling Salmonella Typhi in high-density urban Blantyre neighbourhood, Malawi, using point pattern methods","volume":"14","author":"JJ Khaki","year":"2024","journal-title":"Sci Rep"},{"issue":"2","key":"pntd.0013973.ref020","doi-asserted-by":"crossref","DOI":"10.1371\/journal.pntd.0011912","article-title":"Detection of Salmonella Typhi bacteriophages in surface waters as a scalable approach to environmental surveillance","volume":"18","author":"S Shrestha","year":"2024","journal-title":"PLoS Negl Trop Dis"},{"issue":"9","key":"pntd.0013973.ref021","doi-asserted-by":"crossref","DOI":"10.1371\/journal.pntd.0012518","article-title":"Environmental surveillance for Salmonella Typhi in rivers and wastewater from an informal sewage network in Blantyre, Malawi","volume":"18","author":"CB Uzzell","year":"2024","journal-title":"PLoS Negl Trop Dis"},{"key":"pntd.0013973.ref022","author":"S Alam Mohammed","year":"2013","journal-title":"Random Forest Classification for Detecting android Malware"},{"key":"pntd.0013973.ref023","author":"M Denil","year":"2013"},{"issue":"1","key":"pntd.0013973.ref024","doi-asserted-by":"crossref","first-page":"5","DOI":"10.1023\/A:1010933404324","article-title":"Random Forests","volume":"45","author":"L Breiman","year":"2001","journal-title":"Mach Learn"},{"key":"pntd.0013973.ref025","article-title":"A unified approach to interpreting model predictions","volume":"30","author":"SM Lundberg","year":"2017","journal-title":"Adv Neural Inf Process Syst"}],"updated-by":[{"DOI":"10.1371\/journal.pntd.0013973","type":"new_version","label":"New version","source":"publisher","updated":{"date-parts":[[2026,2,20]],"date-time":"2026-02-20T00:00:00Z","timestamp":1771545600000}}],"container-title":["PLOS Neglected Tropical Diseases"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/dx.plos.org\/10.1371\/journal.pntd.0013973","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,2,20]],"date-time":"2026-02-20T18:58:30Z","timestamp":1771613910000},"score":1,"resource":{"primary":{"URL":"https:\/\/dx.plos.org\/10.1371\/journal.pntd.0013973"}},"subtitle":[],"editor":[{"given":"Travis J","family":"Bourret","sequence":"first","affiliation":[],"role":[{"role":"editor","vocabulary":"crossref"}]}],"short-title":[],"issued":{"date-parts":[[2026,2,17]]},"references-count":25,"journal-issue":{"issue":"2","published-online":{"date-parts":[[2026,2,17]]}},"URL":"https:\/\/doi.org\/10.1371\/journal.pntd.0013973","relation":{},"ISSN":["1935-2735"],"issn-type":[{"value":"1935-2735","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026,2,17]]}}}