{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,10]],"date-time":"2026-06-10T15:53:48Z","timestamp":1781106828191,"version":"3.54.1"},"reference-count":63,"publisher":"National Academy of Sciences","issue":"2","license":[{"start":{"date-parts":[[2024,1,5]],"date-time":"2024-01-05T00:00:00Z","timestamp":1704412800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/100010946","name":"UC | UCSF | School of Medicine, University of California, San Francisco","doi-asserted-by":"publisher","award":["UCSF Institute for Global Health Sciences Affiliate Faculty Seed Award"],"award-info":[{"award-number":["UCSF Institute for Global Health Sciences Affiliate Faculty Seed Award"]}],"id":[{"id":"10.13039\/100010946","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100009663","name":"University Health Network","doi-asserted-by":"publisher","award":["."],"award-info":[{"award-number":["."]}],"id":[{"id":"10.13039\/100009663","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000060","name":"HHS | NIH | National Institute of Allergy and Infectious Diseases","doi-asserted-by":"publisher","award":["DP2AI170485"],"award-info":[{"award-number":["DP2AI170485"]}],"id":[{"id":"10.13039\/100000060","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["www.pnas.org"],"crossmark-restriction":true},"short-container-title":["Proc. Natl. Acad. Sci. U.S.A."],"published-print":{"date-parts":[[2024,1,9]]},"abstract":"<jats:p>\n                    Schistosomiasis is a neglected tropical disease affecting over 150 million people. Hotspots of\n                    <jats:italic>Schistosoma<\/jats:italic>\n                    transmission\u2014communities where infection prevalence does not decline adequately with mass drug administration\u2014present a key challenge in eliminating schistosomiasis. Current approaches to identify hotspots require evaluation 2\u20135 y after a baseline survey and subsequent mass drug administration. Here, we develop statistical models to predict hotspots at baseline prior to treatment comparing three common hotspot definitions, using epidemiologic, survey-based, and remote sensing data. In a reanalysis of randomized trials in 589 communities in five endemic countries, a regression model predicts whether\n                    <jats:italic>Schistosoma mansoni<\/jats:italic>\n                    infection prevalence will exceed the WHO threshold of 10% in year 5 (\u201cprevalence hotspot\u201d) with 86% sensitivity, 74% specificity, and 93% negative predictive value (NPV; assuming 30% hotspot prevalence), and a regression model for\n                    <jats:italic>Schistosoma haematobium<\/jats:italic>\n                    achieves 90% sensitivity, 90% specificity, and 96% NPV. A random forest model predicts whether\n                    <jats:italic>S. mansoni<\/jats:italic>\n                    moderate and heavy infection prevalence will exceed a public health goal of 1% in year 5 (\u201cintensity hotspot\u201d) with 92% sensitivity, 79% specificity, and 96% NPV, and a boosted trees model for\n                    <jats:italic>S. haematobium<\/jats:italic>\n                    achieves 77% sensitivity, 95% specificity, and 91% NPV. Baseline prevalence is a top predictor in all models. Prediction is less accurate in countries not represented in training data and for a third hotspot definition based on relative prevalence reduction over time (\u201cpersistent hotspot\u201d). These models may be a tool to prioritize high-risk communities for more frequent surveillance or intervention against schistosomiasis, but prediction of hotspots remains a challenge.\n                  <\/jats:p>","DOI":"10.1073\/pnas.2315463120","type":"journal-article","created":{"date-parts":[[2024,1,5]],"date-time":"2024-01-05T13:43:43Z","timestamp":1704462223000},"update-policy":"https:\/\/doi.org\/10.1073\/pnas.cm10313","source":"Crossref","is-referenced-by-count":12,"title":["Development of prediction models to identify hotspots of schistosomiasis in endemic regions to guide mass drug administration"],"prefix":"10.1073","volume":"121","author":[{"given":"Benjamin J.","family":"Singer","sequence":"first","affiliation":[{"name":"Division of Infectious Diseases and Geographic Medicine, Department of Medicine, Stanford University, Stanford, CA 94304"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jean T.","family":"Coulibaly","sequence":"additional","affiliation":[{"name":"Unit\u00e9 de Formation et de Recherche Biosciences, Universit\u00e9 F\u00e9lix Houphou\u00ebt-Boigny, Abidjan, C\u00f4te d\u2019Ivoire"},{"name":"Centre Suisse de Recherches Scientifiques en C\u00f4te d\u2019Ivoire, Abidjan, C\u00f4te d\u2019Ivoire"},{"name":"Swiss Tropical and Public Health Institute, Basel, Allschwil 4123 Switzerland"},{"name":"University of Basel, Basel 4001, Switzerland"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Hailey J.","family":"Park","sequence":"additional","affiliation":[{"name":"Division of Infectious Diseases and Geographic Medicine, Department of Medicine, Stanford University, Stanford, CA 94304"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jason R.","family":"Andrews","sequence":"additional","affiliation":[{"name":"Division of Infectious Diseases and Geographic Medicine, Department of Medicine, Stanford University, Stanford, CA 94304"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Isaac I.","family":"Bogoch","sequence":"additional","affiliation":[{"name":"Department of Medicine, University of Toronto, Toronto, ON M5S 1A8, Canada"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5407-2005","authenticated-orcid":false,"given":"Nathan C.","family":"Lo","sequence":"additional","affiliation":[{"name":"Division of Infectious Diseases and Geographic Medicine, Department of Medicine, Stanford University, Stanford, CA 94304"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"341","published-online":{"date-parts":[[2024,1,5]]},"reference":[{"key":"e_1_3_4_1_2","doi-asserted-by":"publisher","DOI":"10.1016\/S1473-3099(21)00090-6"},{"key":"e_1_3_4_2_2","doi-asserted-by":"publisher","DOI":"10.1016\/S0140-6736(12)61729-2"},{"key":"e_1_3_4_3_2","doi-asserted-by":"publisher","DOI":"10.1016\/S1665-2681(19)32186-6"},{"key":"e_1_3_4_4_2","doi-asserted-by":"publisher","DOI":"10.1016\/S0140-6736(13)61949-2"},{"key":"e_1_3_4_5_2","doi-asserted-by":"publisher","DOI":"10.1136\/gut.31.4.439"},{"key":"e_1_3_4_6_2","first-page":"1","article-title":"Helminths in the induction of cancer II. 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