{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,30]],"date-time":"2026-09-30T16:38:16Z","timestamp":1790786296191,"version":"4.1.0"},"reference-count":21,"publisher":"Public Library of Science (PLoS)","issue":"4","license":[{"start":{"date-parts":[[2023,4,26]],"date-time":"2023-04-26T00:00:00Z","timestamp":1682467200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/publicdomain\/zero\/1.0\/"}],"content-domain":{"domain":["www.plosone.org"],"crossmark-restriction":false},"short-container-title":["PLoS ONE"],"abstract":"<jats:p>The San Francisco Bay Area has experienced a rapid rise in homelessness over the past decade. There is a critical need for quantitative analysis to help determine how to increase the amount of housing to meet the needs of people experiencing homelessness. Noting that the shortage of housing available through the homelessness response system can be modeled as a queue, we propose a discrete-event simulation to model the long-term flow of people through the homelessness response system. The model takes as input the rate of additional housing and shelter available each year and delivers as output the predicted number of people housed, sheltered, or unsheltered in the system. We worked with a team of stakeholders to analyze the data and processes for Alameda County in California and use this information to build and calibrate two simulation models. One model looks at aggregate need for housing, while the other differentiates the housing needs of the population into eight different types. The model suggests that a large investment in permanent housing and an initial ramp up of shelter is needed to solve unsheltered homelessness and accommodate future inflow to the system.<\/jats:p>","DOI":"10.1371\/journal.pone.0284336","type":"journal-article","created":{"date-parts":[[2023,4,26]],"date-time":"2023-04-26T13:26:15Z","timestamp":1682515575000},"page":"e0284336","update-policy":"https:\/\/doi.org\/10.1371\/journal.pone.corrections_policy","source":"Crossref","is-referenced-by-count":8,"title":["Discrete-event simulation modeling for housing of homeless populations"],"prefix":"10.1371","volume":"18","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-4201-4585","authenticated-orcid":true,"given":"Dashi I.","family":"Singham","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jennifer","family":"Lucky","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Stephanie","family":"Reinauer","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"340","published-online":{"date-parts":[[2023,4,26]]},"reference":[{"key":"pone.0284336.ref001","unstructured":"HUD exchange, https:\/\/www.hudexchange.info. 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Optimal Service Portfolio of Non-Profits that Serve Distressed Individuals","author":"Arora Priyank","year":"2021","journal-title":"Manufacturing & Service Operations Management"},{"key":"pone.0284336.ref015","doi-asserted-by":"crossref","unstructured":"Aida Rahmattalabi, Phebe Vayanos, Kathryn Dullerud, and Eric Rice. Learning Resource Allocation Policies from Observational Data with an Application to Homeless Services Delivery. In 022 ACM Conference on Fairness, Accountability, and Transparency (FAccT\u201922), New York, NY, 2022. 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Report for the Alameda County Office of Homeless Care and Coordination. https:\/\/homelessness.acgov.org\/homelessness-assets\/img\/reports\/Final%20PRK%20Report%20Summary.pdf"}],"container-title":["PLOS ONE"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/dx.plos.org\/10.1371\/journal.pone.0284336","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,4,26]],"date-time":"2023-04-26T13:26:38Z","timestamp":1682515598000},"score":1,"resource":{"primary":{"URL":"https:\/\/dx.plos.org\/10.1371\/journal.pone.0284336"}},"subtitle":[],"editor":[{"given":"Argimiro","family":"Arratia","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"editor"}]}],"short-title":[],"issued":{"date-parts":[[2023,4,26]]},"references-count":21,"journal-issue":{"issue":"4","published-online":{"date-parts":[[2023,4,26]]}},"URL":"https:\/\/doi.org\/10.1371\/journal.pone.0284336","relation":{},"ISSN":["1932-6203"],"issn-type":[{"value":"1932-6203","type":"electronic"}],"subject":[],"published":{"date-parts":[[2023,4,26]]}}}