cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.3535/z0t-5j0-66k
title: Animalia

description: Digital Specimen for the physical specimen hosted at Naturalis Biodiversity Center.
DOI: 10.3535/ret-4gz-r91
title: Mammalia Linnaeus, 1758

description: Digital Specimen for the physical specimen hosted at Naturalis Biodiversity Center.
DOI: 10.3535/w2e-9dp-as0
title: Plantae

description: Digital Specimen for the physical specimen hosted at Naturalis Biodiversity Center.
DOI: 10.3535/5aa-le8-h99
title: Animalia

description: Digital Specimen for the physical specimen hosted at Naturalis Biodiversity Center.
DOI: 10.3535/ysl-x10-1ya
title: Brachiopoda Duméril, 1805

description: Digital Specimen for the physical specimen hosted at Naturalis Biodiversity Center.
DOI: 10.3535/7gm-1md-jd2
title: Animalia

description: Digital Specimen for the physical specimen hosted at Naturalis Biodiversity Center.
DOI: 10.3535/wyn-36k-1jn
title: Mammalia Linnaeus, 1758

description: Digital Specimen for the physical specimen hosted at Naturalis Biodiversity Center.
DOI: 10.3535/2cb-2pa-fqt
title: Mammalia Linnaeus, 1758

description: Digital Specimen for the physical specimen hosted at Naturalis Biodiversity Center.
DOI: 10.3535/ccv-t3j-nzh
title: Hoplites

description: Digital Specimen for the physical specimen hosted at Naturalis Biodiversity Center.
DOI: 10.3535/lfb-zxd-r34
title: Mammalia Linnaeus, 1758

description: Digital Specimen for the physical specimen hosted at Naturalis Biodiversity Center.
DOI: 10.3535/07v-ej3-pel
title: Mammalia Linnaeus, 1758

description: Digital Specimen for the physical specimen hosted at Naturalis Biodiversity Center.
DOI: 10.3535/7a5-xgg-rr0
title: Animalia

description: Digital Specimen for the physical specimen hosted at Naturalis Biodiversity Center.
DOI: 10.3535/8q2-aej-4c9
title: Mammalia Linnaeus, 1758

description: Digital Specimen for the physical specimen hosted at Naturalis Biodiversity Center.
DOI: 10.3535/fdt-h3h-a9b
title: Mammalia Linnaeus, 1758

description: Digital Specimen for the physical specimen hosted at Naturalis Biodiversity Center.
DOI: 10.5281/zenodo.18282273
title: ГЛОБАЛЬНЫЕ РИСКИ В ДЕЯТЕЛЬНОСТИ МЕЖДУНАРОДНЫХ КОМПАНИЙ В УСЛОВИЯХ ЭКОНОМИЧЕСКОЙ ИНТЕГРАЦИИ

description: Международные компании в условиях глобализации сталкиваются с многоуровневыми глобальными рисками: экономическими, финансовыми, политическими, технологическими, социальными и ESG. Для повышения устойчивости применяются KRI, интегрированные модели управления рисками, стандарты ISO 31000 и COSO ERM, цифровые технологии и сценарное прогнозирование. Такой подход позволяет рассматривать риск как стратегический ресурс, повышая адаптивность и конкурентоспособность компаний.
DOI: 10.5281/zenodo.18282272
title: ГЛОБАЛЬНЫЕ РИСКИ В ДЕЯТЕЛЬНОСТИ МЕЖДУНАРОДНЫХ КОМПАНИЙ В УСЛОВИЯХ ЭКОНОМИЧЕСКОЙ ИНТЕГРАЦИИ

description: Международные компании в условиях глобализации сталкиваются с многоуровневыми глобальными рисками: экономическими, финансовыми, политическими, технологическими, социальными и ESG. Для повышения устойчивости применяются KRI, интегрированные модели управления рисками, стандарты ISO 31000 и COSO ERM, цифровые технологии и сценарное прогнозирование. Такой подход позволяет рассматривать риск как стратегический ресурс, повышая адаптивность и конкурентоспособность компаний.
DOI: 10.13140/rg.2.2.28978.67522
title: Address of my article "Aspects of Mary Wollstonecraft’s thought" - Polis Magazino - https://www.polismagazino.gr/gianluigi-segalerba-aspects-of-mary-wollstonecrafts-thought/?fbclid=IwY2xjawPYl11leHRuA2FlbQIxMQBzcnRjBmFwcF9pZBAyMjIwMzkxNzg4MjAwODkyAAEerc6dpnaA2nF1OyybKB_QnSjcUZSgJQJTWsF_tl8OjrbspXTlJsjPPJCtTqQ_aem_TEZtmLvbHnd4hWaNdFS-ow
DOI: 10.15468/dl.vh6jyg
title: Occurrence Download

description: A dataset containing 1979 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Continent is Asia",
 "Country is China",
 "GadmGid is CHN.15_1",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Ardea cinerea",
 "Year 2015-2026"
 ]
}

 The dataset includes 1979 records from 5 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0016832-260108223611665/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.3886/e244315
title: Weekly Differences in Cumulative COVID-19 Vaccination Coverage and Comparison Between 2024–25 and 2023–24 Among Adults 18 Years, Overall, by Selected Demographics

description: • Weekly COVID-19 Vaccination Coverage and Comparison among adults 18 Years and Older by Selected Demographics and by Season

• Weekly estimates of COVID-19 vaccination coverage and intent for vaccination among adults are calculated using data from the National Immunization Surveys (NIS)-Fall Respiratory Virus Module (NIS-FRVM) (https://www.cdc.gov/nis/about/index.html).

• The NIS–FRVM is an ongoing random-digit-dial cellular telephone survey of households with adults 18 years and older. All estimates are based upon self-reported receipt of vaccination and month of that vaccination.

• Weekly comparisons to previous season should take into account differences between seasons in vaccine availability dates. 2023–24 COVID-19 vaccines were first available mid-September 2023, and 2024–25 and 2025–26 COVID-19 vaccines were first available at the end of August 2024 and 2025, respectively.

• The NIS-FRVM data posted on the dashboard below are currently a few days behind the data that are posted on the Respiratory Illnesses Data Channel (https://www.cdc.gov/respiratory-viruses/data/index.html). This lag is due to the time it takes to review data by geographic and sociodemographic characteristics and summarize the findings.  
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DOI: 10.3886/e244315v1
title: Weekly Differences in Cumulative COVID-19 Vaccination Coverage and Comparison Between 2024–25 and 2023–24 Among Adults 18 Years, Overall, by Selected Demographics

description: • Weekly COVID-19 Vaccination Coverage and Comparison among adults 18 Years and Older by Selected Demographics and by Season

• Weekly estimates of COVID-19 vaccination coverage and intent for vaccination among adults are calculated using data from the National Immunization Surveys (NIS)-Fall Respiratory Virus Module (NIS-FRVM) (https://www.cdc.gov/nis/about/index.html).

• The NIS–FRVM is an ongoing random-digit-dial cellular telephone survey of households with adults 18 years and older. All estimates are based upon self-reported receipt of vaccination and month of that vaccination.

• Weekly comparisons to previous season should take into account differences between seasons in vaccine availability dates. 2023–24 COVID-19 vaccines were first available mid-September 2023, and 2024–25 and 2025–26 COVID-19 vaccines were first available at the end of August 2024 and 2025, respectively.

• The NIS-FRVM data posted on the dashboard below are currently a few days behind the data that are posted on the Respiratory Illnesses Data Channel (https://www.cdc.gov/respiratory-viruses/data/index.html). This lag is due to the time it takes to review data by geographic and sociodemographic characteristics and summarize the findings.  
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description: (Downloaded 1/16/2026)
DOI: 10.5281/zenodo.18282284
title: O'QUVCHILARINI PIRLS XALQARO BAHOLASH DASTURIGA TAYYORLASHDA ILG'OR TAJRIBALARDAN FOYDALANISH

description: Mazkur maqola boshlang‘ich sinf o‘quvchilarini PIRLS (Progress in International Reading Literacy Study) xalqaro baholash dasturiga tayyorlashda ilg‘or tajribalardan foydalanish masalalariga bag‘ishlangan. Maqolada PIRLS dasturining nazariy asoslari, o‘qish savodxonligining asosiy komponentlari, O‘zbekistonning 2021 yildagi natijalari va muammolari, shuningdek, yuqori natija ko‘rsatgan mamlakatlar (Singapur, Irlandiya, Hong Kong, Rossiya, Angliya va boshqalar)ning pedagogik tajribalari batafsil tahlil qilinadi. Ushbu tajribalarni O‘zbekiston ta’lim tizimiga moslashtirish yo‘llari va amaliy tavsiyalar keltiriladi. Tadqiqot nazariy tahlil va qiyosiy metodlarga asoslanib, tajriba sinovlari o‘tkazilmagan holda, xalqaro adabiyotlar va hisobotlar asosida yozilgan. Maqola o‘qituvchilar, metodistlar va ta’lim siyosatchilari uchun nazariy va metodik qo‘llanma sifatida xizmat qiladi.
DOI: 10.5281/zenodo.18282285
title: O'QUVCHILARINI PIRLS XALQARO BAHOLASH DASTURIGA TAYYORLASHDA ILG'OR TAJRIBALARDAN FOYDALANISH

description: Mazkur maqola boshlang‘ich sinf o‘quvchilarini PIRLS (Progress in International Reading Literacy Study) xalqaro baholash dasturiga tayyorlashda ilg‘or tajribalardan foydalanish masalalariga bag‘ishlangan. Maqolada PIRLS dasturining nazariy asoslari, o‘qish savodxonligining asosiy komponentlari, O‘zbekistonning 2021 yildagi natijalari va muammolari, shuningdek, yuqori natija ko‘rsatgan mamlakatlar (Singapur, Irlandiya, Hong Kong, Rossiya, Angliya va boshqalar)ning pedagogik tajribalari batafsil tahlil qilinadi. Ushbu tajribalarni O‘zbekiston ta’lim tizimiga moslashtirish yo‘llari va amaliy tavsiyalar keltiriladi. Tadqiqot nazariy tahlil va qiyosiy metodlarga asoslanib, tajriba sinovlari o‘tkazilmagan holda, xalqaro adabiyotlar va hisobotlar asosida yozilgan. Maqola o‘qituvchilar, metodistlar va ta’lim siyosatchilari uchun nazariy va metodik qo‘llanma sifatida xizmat qiladi.
DOI: 10.5281/zenodo.18282256
title: Dataset for Figs. 1–2 of the study "On the testing of grain shape corrections to bedload transport equations with grain-resolved numerical simulations".
DOI: 10.5281/zenodo.18282255
title: Dataset for Figs. 1–2 of the study "On the testing of grain shape corrections to bedload transport equations with grain-resolved numerical simulations".
DOI: 10.5281/zenodo.18281737
title: SuperDARN data in netCDF format (1998-Mar)

description: 1998-Mar SuperDARN radar data in netCDF format. These files were produced using version 3.0 of the public FitACF algorithm, using the AACGM v2 coordinate system. Cite this dataset if using our data in a publication.


The RST is available here: https://github.com/SuperDARN/rst



The research enabled by SuperDARN is due to the efforts of teams of scientists and engineers working in many countries to build and operate radars, process data and provide access, develop and improve data products, and assist users in interpretation.
Users of SuperDARN data and data products are asked to acknowledge this support in presentations and publications.
A brief statement on how to acknowledge use of SuperDARN data is provided below.




Users are also asked to consult with a SuperDARN PI prior to submission of work intended for publication.
A listing of radars and PIs with contact information can be found here:
(SuperDARN Radar Overview)



Recommended form of acknowledgement for the use of SuperDARN data:



'The authors acknowledge the use of SuperDARN data. SuperDARN is a collection of radars funded by national scientific funding agencies of Australia, Canada, China, France, Italy, Japan, Norway, South Africa, United Kingdom and the United States of America.'
DOI: 10.5281/zenodo.6808654
title: SuperDARN data in netCDF format (1998-Mar)

description: 1998-Mar SuperDARN radar data in netCDF format. These files were produced using version 3.0 of the public FitACF algorithm, using the AACGM v2 coordinate system. Cite this dataset if using our data in a publication.


The RST is available here: https://github.com/SuperDARN/rst



The research enabled by SuperDARN is due to the efforts of teams of scientists and engineers working in many countries to build and operate radars, process data and provide access, develop and improve data products, and assist users in interpretation.
Users of SuperDARN data and data products are asked to acknowledge this support in presentations and publications.
A brief statement on how to acknowledge use of SuperDARN data is provided below.




Users are also asked to consult with a SuperDARN PI prior to submission of work intended for publication.
A listing of radars and PIs with contact information can be found here:
(SuperDARN Radar Overview)



Recommended form of acknowledgement for the use of SuperDARN data:



'The authors acknowledge the use of SuperDARN data. SuperDARN is a collection of radars funded by national scientific funding agencies of Australia, Canada, China, France, Italy, Japan, Norway, South Africa, United Kingdom and the United States of America.'
DOI: 10.5281/zenodo.18282296
title: Hymenoxys tweediei Hook. & Arn. In: Marchesi E., Mailhos A. & Bonifacino J.M. (Eds.). Flora Uruguaya: Flora Vascular del Uruguay. ISSN 3121-2050, V. 1.0.

description: Citable snapshot. Includes PDF and CSV of collections. Date: January 13th, 2026 at 16:48
DOI: 10.5281/zenodo.18282295
title: Hymenoxys tweediei Hook. & Arn. In: Marchesi E., Mailhos A. & Bonifacino J.M. (Eds.). Flora Uruguaya: Flora Vascular del Uruguay. ISSN 3121-2050, V. 1.0.

description: Citable snapshot. Includes PDF and CSV of collections. Date: January 13th, 2026 at 16:48
DOI: 10.5281/zenodo.18282288
title: A Data-Driven Decision Support Approach for Recalibration Service Satisfaction Using Decision Tree Analysis (Case Study: Directorate of Metrology Bandung)

description: The increasing digitalization of public services has created new opportunities for government institutions to leverage data-driven approaches in improving service quality and decision-making processes. In the context of public metrology services, customer satisfaction plays a critical role in ensuring service effectiveness, institutional trust, and continuous improvement. This study proposes an interpretable machine learning–based approach to support service evaluation and managerial decision-making by applying a decision tree (C4.5) classification model to recalibration service satisfaction data at the Directorate of Metrology Bandung, Indonesia. Using historical customer satisfaction data collected through digital questionnaires, the study develops a classification model to identify satisfaction levels and uncover service patterns that influence user perceptions. Rather than focusing solely on predictive performance, this research emphasizes the role of explainable models in transforming operational data into actionable insights for public service governance. The results demonstrate that decision tree–based analysis can effectively support the identification of critical service attributes and provide transparent decision rules that are understandable to non-technical stakeholders. The findings highlight the potential of data-driven decision support systems to enhance service management, promote accountability, and support smarter public service delivery within a digital governance framework.
DOI: 10.5281/zenodo.18282289
title: A Data-Driven Decision Support Approach for Recalibration Service Satisfaction Using Decision Tree Analysis (Case Study: Directorate of Metrology Bandung)

description: The increasing digitalization of public services has created new opportunities for government institutions to leverage data-driven approaches in improving service quality and decision-making processes. In the context of public metrology services, customer satisfaction plays a critical role in ensuring service effectiveness, institutional trust, and continuous improvement. This study proposes an interpretable machine learning–based approach to support service evaluation and managerial decision-making by applying a decision tree (C4.5) classification model to recalibration service satisfaction data at the Directorate of Metrology Bandung, Indonesia. Using historical customer satisfaction data collected through digital questionnaires, the study develops a classification model to identify satisfaction levels and uncover service patterns that influence user perceptions. Rather than focusing solely on predictive performance, this research emphasizes the role of explainable models in transforming operational data into actionable insights for public service governance. The results demonstrate that decision tree–based analysis can effectively support the identification of critical service attributes and provide transparent decision rules that are understandable to non-technical stakeholders. The findings highlight the potential of data-driven decision support systems to enhance service management, promote accountability, and support smarter public service delivery within a digital governance framework.
DOI: 10.5281/zenodo.18282299
title: Hyoscyamus L. In: Marchesi E., Mailhos A. & Bonifacino J.M. (Eds.). Flora Uruguaya: Flora Vascular del Uruguay. ISSN 3121-2050, V. 1.0.

description: Citable snapshot. Includes PDF and CSV of collections. Date: January 13th, 2026 at 16:48
DOI: 10.5281/zenodo.18282300
title: Hyoscyamus L. In: Marchesi E., Mailhos A. & Bonifacino J.M. (Eds.). Flora Uruguaya: Flora Vascular del Uruguay. ISSN 3121-2050, V. 1.0.

description: Citable snapshot. Includes PDF and CSV of collections. Date: January 13th, 2026 at 16:48
DOI: 10.3886/e244316
title: Weekly Differences in Cumulative RSV Vaccination Coverage Among Adults 75 and Older and 60–74 Years with High-Risk Conditions Ever Vaccinated with RSV Vaccine, Overall, by Selected Demographics

description: • Weekly Cumulative RSV Vaccination Coverage and Intent Among Adults 75 Years and Older and 60─74 Years with High Risk Conditions Ever Vaccinated with RSV Vaccine by Demographic Characteristics and Jurisdiction
• Weekly estimates of RSV vaccination coverage and intent among adults 75 years and older and 60─74 years with high risk conditions are calculated using data from the National Immunization Survey–Adult COVID Module (NIS–ACM) (https://www.cdc.gov/nis/about/)
• In June 2023, the Advisory Committee on Immunization Practices (ACIP) voted to recommend that adults aged ≥60 years may receive a single dose of an RSV vaccine, using shared clinical decision-making. In June 2024, the ACIP voted to recommend a single dose of RSV vaccine for all adults 75 years and older and adults 60–74 years who are at increased risk for severe RSV disease. The data below captures ever receiving a dose of an RSV vaccine by adults 60 years and older. 
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DOI: 10.3886/e244316v1
title: Weekly Differences in Cumulative RSV Vaccination Coverage Among Adults 75 and Older and 60–74 Years with High-Risk Conditions Ever Vaccinated with RSV Vaccine, Overall, by Selected Demographics

description: • Weekly Cumulative RSV Vaccination Coverage and Intent Among Adults 75 Years and Older and 60─74 Years with High Risk Conditions Ever Vaccinated with RSV Vaccine by Demographic Characteristics and Jurisdiction
• Weekly estimates of RSV vaccination coverage and intent among adults 75 years and older and 60─74 years with high risk conditions are calculated using data from the National Immunization Survey–Adult COVID Module (NIS–ACM) (https://www.cdc.gov/nis/about/)
• In June 2023, the Advisory Committee on Immunization Practices (ACIP) voted to recommend that adults aged ≥60 years may receive a single dose of an RSV vaccine, using shared clinical decision-making. In June 2024, the ACIP voted to recommend a single dose of RSV vaccine for all adults 75 years and older and adults 60–74 years who are at increased risk for severe RSV disease. The data below captures ever receiving a dose of an RSV vaccine by adults 60 years and older. 
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description: (Downloaded 1/16/2026)
DOI: 10.5281/zenodo.18282301
title: Hyoscyamus albus L. In: Marchesi E., Mailhos A. & Bonifacino J.M. (Eds.). Flora Uruguaya: Flora Vascular del Uruguay. ISSN 3121-2050, V. 1.0.

description: Citable snapshot. Includes PDF and CSV of collections. Date: January 13th, 2026 at 16:48
DOI: 10.5281/zenodo.18282302
title: Hyoscyamus albus L. In: Marchesi E., Mailhos A. & Bonifacino J.M. (Eds.). Flora Uruguaya: Flora Vascular del Uruguay. ISSN 3121-2050, V. 1.0.

description: Citable snapshot. Includes PDF and CSV of collections. Date: January 13th, 2026 at 16:48
DOI: 10.5281/zenodo.18282307
title: Hyoseris L. In: Marchesi E., Mailhos A. & Bonifacino J.M. (Eds.). Flora Uruguaya: Flora Vascular del Uruguay. ISSN 3121-2050, V. 1.0.

description: Citable snapshot. Includes PDF and CSV of collections. Date: January 13th, 2026 at 16:48
DOI: 10.5281/zenodo.18282308
title: Hyoseris L. In: Marchesi E., Mailhos A. & Bonifacino J.M. (Eds.). Flora Uruguaya: Flora Vascular del Uruguay. ISSN 3121-2050, V. 1.0.

description: Citable snapshot. Includes PDF and CSV of collections. Date: January 13th, 2026 at 16:48
DOI: 10.5281/zenodo.18282293
title: O'QUVCHILARNI TIMSS XALQARO BAHOLASH DASTURIGA TAYYORLASHDA INNOVATSION TEXNOLOGIYALARINING O'RNI

description: Ushbu maqola xalqaro TIMSS (Trends in International Mathematics and Science Study) baholash dasturiga o‘quvchilarni tayyorlash jarayonida innovatsion texnologiyalarning o‘rni va ahamiyatini nazariy jihatdan tahlil qilishga bag‘ishlangan. Maqola IMRAD strukturasiga asoslangan holda, TIMSS dasturining xususiyatlari, zamonaviy innovatsion texnologiyalarning pedagogik imkoniyatlari, ularning o‘quv jarayoniga integratsiyasi va o‘quvchilarning matematika hamda tabiiy fanlar bo‘yicha funksional savodxonligini oshirishdagi nazariy asoslari ko‘rib chiqiladi. Tadqiqot natijalari shuni ko‘rsatadiki, raqamli platformalar, adaptiv ta’lim tizimlari, virtual laboratoriyalar va sun’iy intellektga asoslangan vositalar TIMSS talablariga mos keladigan yuqori darajadagi fikrlash ko‘nikmalarini shakllantirishda muhim o‘rin tutadi. Maqola o‘qituvchilar va ta’lim tizimi mutaxassislari uchun nazariy asos va metodik yo‘nalish sifatida xizmat qiladi.
DOI: 10.5281/zenodo.18282292
title: O'QUVCHILARNI TIMSS XALQARO BAHOLASH DASTURIGA TAYYORLASHDA INNOVATSION TEXNOLOGIYALARINING O'RNI

description: Ushbu maqola xalqaro TIMSS (Trends in International Mathematics and Science Study) baholash dasturiga o‘quvchilarni tayyorlash jarayonida innovatsion texnologiyalarning o‘rni va ahamiyatini nazariy jihatdan tahlil qilishga bag‘ishlangan. Maqola IMRAD strukturasiga asoslangan holda, TIMSS dasturining xususiyatlari, zamonaviy innovatsion texnologiyalarning pedagogik imkoniyatlari, ularning o‘quv jarayoniga integratsiyasi va o‘quvchilarning matematika hamda tabiiy fanlar bo‘yicha funksional savodxonligini oshirishdagi nazariy asoslari ko‘rib chiqiladi. Tadqiqot natijalari shuni ko‘rsatadiki, raqamli platformalar, adaptiv ta’lim tizimlari, virtual laboratoriyalar va sun’iy intellektga asoslangan vositalar TIMSS talablariga mos keladigan yuqori darajadagi fikrlash ko‘nikmalarini shakllantirishda muhim o‘rin tutadi. Maqola o‘qituvchilar va ta’lim tizimi mutaxassislari uchun nazariy asos va metodik yo‘nalish sifatida xizmat qiladi.
DOI: 10.3886/e244317
title: Weekly Cumulative Influenza Vaccination Coverage and Comparison Between 2024–25 and 2023–24, Overall, by Jurisdiction, Among Adults 18 Years and Older

description: • Weekly Influenza Vaccination Coverage Map and Comparison Between 2025-26 and 2024-25 among adults 18 Years and Older by Jurisdiction.

• Weekly estimates of influenza vaccination coverage and intent for vaccination among adults are calculated using data from the National Immunization Surveys (NIS)-Fall Respiratory Virus Module (NIS-FRVM) (https://www.cdc.gov/nis/about/index.html). The NIS-FRVM is an ongoing random-digit-dial cellular telephone survey of households with adults 18 years and older. All estimates are based upon self-reported receipt of vaccination and month of that vaccination.

• The NIS-FRVM data posted on the dashboard below are currently a few days behind the data that are posted on the Respiratory Illnesses Data Channel (https://www.cdc.gov/respiratory-viruses/data/index.html). This lag is due to the time it takes to review data by geographic and sociodemographic characteristics and summarize the findings.
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description: (Downloaded 1/16/2026)