{"action":"create","ckan_id":null,"date_created":"Sat, 04 Apr 2026 23:37:35 GMT","date_finished":null,"harvest_job_id":"3ce2a2ca-8175-4a38-9100-b654c34c1b5c","harvest_source_id":"bebdce30-696c-424b-ad16-eca2913bde29","id":"031a0d1a-4adc-4976-8266-7956df934ea6","identifier":"https://data.cdc.gov/api/views/xnjn-rdmd","parent_identifier":null,"source_hash":"b4a1b91110abeac31351babe0206453c3cd087360fbe11a225250ded8bb8f71f","source_raw":"{\"@type\": \"dcat:Dataset\", \"accessLevel\": \"public\", \"accrualPeriodicity\": \"Weekly\", \"bureauCode\": [\"009:20\"], \"contactPoint\": {\"@type\": \"vcard:Contact\", \"fn\": \"CDC-INFO\", \"hasEmail\": \"mailto:cdcinfo@cdcinquiry.onmicrosoft.com\"}, \"description\": \"This dataset represents preliminary weekly estimates of cumulative U.S. COVID-19-associated hospitalizations for the 2024-2025 period. The weekly cumulatve COVID-19 \\u2013associated hospitalization estimates are preliminary, and use reported weekly hospitalizations among laboratory-confirmed severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infections. The data are updated week-by-week as new COVID-19 hospitalizations are reported to CDC from the COVID-NET system and include both new admissions that occurred during the reporting week, as well as those admitted in previous weeks that may not have been included in earlier reporting. Each week CDC estimates a range (i.e., lower estimate and an upper estimate) of COVID-19 -associated hospitalizations that have occurred since October 1, 2024. For details, please refer to the publication [7]. \\n \\nNote: Data are preliminary and subject to change as more data become available. Rates for recent COVID-19-associated hospital admissions are subject to reporting delays; as new data are received each week, previous rates are updated accordingly.\\n\\nReferences\\n
  1. Reed C, Chaves SS, Daily Kirley P, et al. Estimating influenza disease burden from population-based surveillance data in the United States. PLoS One. 2015;10(3):e0118369. https://doi.org/10.1371/journal.pone.0118369\\u202f
  2. Rolfes, MA, Foppa, IM, Garg, S, et al. Annual estimates of the burden of seasonal influenza in the United States: A tool for strengthening influenza surveillance and preparedness. Influenza Other Respi Viruses. 2018; 12: 132\\u2013 137. https://doi.org/10.1111/irv.12486
  3. Tokars JI, Rolfes MA, Foppa IM, Reed C. An evaluation and update of methods for estimating the number of influenza cases averted by vaccination in the United States. Vaccine. 2018;36(48):7331-7337. doi:10.1016/j.vaccine.2018.10.026\\u202f
  4. Collier SA, Deng L, Adam EA, Benedict KM, Beshearse EM, Blackstock AJ, Bruce BB, Derado G, Edens C, Fullerton KE, Gargano JW, Geissler AL, Hall AJ, Havelaar AH, Hill VR, Hoekstra RM, Reddy SC, Scallan E, Stokes EK, Yoder JS, Beach MJ. Estimate of Burden and Direct Healthcare Cost of Infectious Waterborne Disease in the United States. Emerg Infect Dis. 2021 Jan;27(1):140-149. doi: 10.3201/eid2701.190676. PMID: 33350905; PMCID: PMC7774540.
  5. Reed C, Kim IK, Singleton JA,\\u202f et al. Estimated influenza illnesses and hospitalizations averted by vaccination\\u2013United States, 2013-14 influenza season. MMWR Morb Mortal Wkly Rep. 2014 Dec 12;63(49):1151-4. https://www.cdc.gov/mmwr/preview/mmwrhtml/mm6349a2.htm\\u202f
  6. Reed C, Angulo FJ, Swerdlow DL, et al. Estimates of the Prevalence of Pandemic (H1N1) 2009, United States, April\\u2013July 2009. Emerg Infect Dis. 2009;15(12):2004-2007. https://dx.doi.org/10.3201/eid1512.091413 \\u202f
  7. Devine O, Pham H, Gunnels B, et al. Extrapolating Sentinel Surveillance Information to Estimate National COVID-19 Hospital Admission Rates: A Bayesian Modeling Approach. Influenza and Other Respiratory Viruses. https://onlinelibrary.wiley.com/doi/10.1111/irv.70026. Volume18, Issue10. October 2024.
  8. COVID-NET | COVID-19 | CDC\\u202f
  9. https://www.cdc.gov/covid/hcp/clinical-care/systematic-review-process.html\\u202f
  10. Excess natural-cause deaths in California by cause and setting: March 2020 through February 2021 | PNAS Nexus | Oxford Academic (oup.com)
  11. Kruschke, J. K. 2011. Doing Bayesian data analysis: a tutorial with R and BUGS. Elsevier, Amsterdam, Section 3.3.5.
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