View daily updates and historical trends for Maryland Coronavirus Cases Currently Hospitalized. Source: US Department of Health & Human Services. Track ec…

The dataset is a collection of positive COVID-19 positive test results among Maryland resident that have been reported each day by the local health department via the ESSENCE system to the State department of health. The dataset is at county level and can be viewed and downloaded in a CSV file format.

View daily updates and historical trends for Maryland Coronavirus Tests Administered Per Day. Source: US Department of Health & Human Services. Track econ…

The dataset comprises of the collection of the statewide cumulative total of Maryland individuals (or residents) who tested positive for COVID-19 that have been reported each day by each local health department as having been hospitalized. As published to coronavirus.maryland.gov, this is the "Ever Hospitalized" number. "Ever Hospitalized" refers to the cumulative number of individuals who were admitted to the hospital at some point during their COVID-19 illness. The dataset can be downloaded and viewed in a CSV file format.

On March 10, 2023, the Johns Hopkins Coronavirus Resource Center ceased its collecting and reporting of global COVID-19 data. For updated cases, deaths, and vaccine data please visit: U.S. Centers for Disease Control and Prevention (CDC)For more information, visit the Johns Hopkins Coronavirus Resource Center.This map is updated weekly and currently shows data through Mar 5, 2023. Notes: as of 5/25/2021, Nebraska stopped sharing COVID-19 testing and on 9/26/21 began, but with a lump sum for the previous four months. Nebraska's reporting became unconsumable by JHU on July 1, 2022. Maryland stopped reporting results for several weeks on 12/4/2021 due to a website hack.It shows COVID-19 Trend for the most recent Monday with a colored dot for each county. The larger the dot, the longer the county has had this trend.Includes Puerto Rico, Guam, Northern Marianas, U.S. Virgin Islands.The intent of this map is to give more context than just the current day of new data because daily data for COVID-19 cases is volatile and can be unreliable on the day it is first reported. Weekly summaries in the counts of new cases smooth out this volatility.Click or tap on a county to see a history of trend changes and a weekly graph of new cases going back to February 1, 2020.For more information about COVID-19 trends, see the full methodology.Data Source: Johns Hopkins University CSSE US Cases by County dashboard and USAFacts for Utah County level Data.

The dataset comprises of the cumulative number of confirmed COVID-19-related deaths among Maryland residents within a single Maryland jurisdiction. It is a collection of the confirmed COVID-19 related deaths that have been reported each day by the Vital Statistics Administration that have occurred in each Maryland jurisdiction. A death is classified as confirmed if the person had a laboratory-confirmed positive COVID-19 test result. Dataset can be viewed and downloaded in a CSV file format.

As of March 10, 2023, the death rate from COVID-19 in the state of New York was 397 per 100,000 people. New York is one of the states with the highest number of COVID-19 cases.

This file contains COVID-19 death counts, death rates, and percent of total deaths by jurisdiction of residence. The data is grouped by different time periods including 3-month period, weekly, and total (cumulative since January 1, 2020). United States death counts and rates include the 50 states, plus the District of Columbia and New York City. New York state estimates exclude New York City. Puerto Rico is included in HHS Region 2 estimates. Deaths with confirmed or presumed COVID-19, coded to ICD–10 code U07.1. Number of deaths reported in this file are the total number of COVID-19 deaths received and coded as of the date of analysis and may not represent all deaths that occurred in that period. Counts of deaths occurring before or after the reporting period are not included in the file. Data during recent periods are incomplete because of the lag in time between when the death occurred and when the death certificate is completed, submitted to NCHS and processed for reporting purposes. This delay can range from 1 week to 8 weeks or more, depending on the jurisdiction and cause of death. Death counts should not be compared across states. Data timeliness varies by state. Some states report deaths on a daily basis, while other states report deaths weekly or monthly. The ten (10) United States Department of Health and Human Services (HHS) regions include the following jurisdictions. Region 1: Connecticut, Maine, Massachusetts, New Hampshire, Rhode Island, Vermont; Region 2: New Jersey, New York, New York City, Puerto Rico; Region 3: Delaware, District of Columbia, Maryland, Pennsylvania, Virginia, West Virginia; Region 4: Alabama, Florida, Georgia, Kentucky, Mississippi, North Carolina, South Carolina, Tennessee; Region 5: Illinois, Indiana, Michigan, Minnesota, Ohio, Wisconsin; Region 6: Arkansas, Louisiana, New Mexico, Oklahoma, Texas; Region 7: Iowa, Kansas, Missouri, Nebraska; Region 8: Colorado, Montana, North Dakota, South Dakota, Utah, Wyoming; Region 9: Arizona, California, Hawaii, Nevada; Region 10: Alaska, Idaho, Oregon, Washington. Rates were calculated using the population estimates for 2021, which are estimated as of July 1, 2021 based on the Blended Base produced by the US Census Bureau in lieu of the April 1, 2020 decennial population count. The Blended Base consists of the blend of Vintage 2020 postcensal population estimates, 2020 Demographic Analysis Estimates, and 2020 Census PL 94-171 Redistricting File (see https://www2.census.gov/programs-surveys/popest/technical-documentation/methodology/2020-2021/methods-statement-v2021.pdf). Rates are based on deaths occurring in the specified week/month and are age-adjusted to the 2000 standard population using the direct method (see https://www.cdc.gov/nchs/data/nvsr/nvsr70/nvsr70-08-508.pdf). These rates differ from annual age-adjusted rates, typically presented in NCHS publications based on a full year of data and annualized weekly/monthly age-adjusted rates which have been adjusted to allow comparison with annual rates. Annualization rates presents deaths per year per 100,000 population that would be expected in a year if the observed period specific (weekly/monthly) rate prevailed for a full year. Sub-national death counts between 1-9 are suppressed in accordance with NCHS data confidentiality standards. Rates based on death counts less than 20 are suppressed in accordance with NCHS standards of reliability as specified in NCHS Data Presentation Standards for Proportions (available from: https://www.cdc.gov/nchs/data/series/sr_02/sr02_175.pdf.).

Virulent infectious agents such as SARS-CoV-2 and Methicillin Resistant Staphylococcus Aureus (MRSA) induce tissue damage that recruits neutrophils and monocyte/macrophages that promote T cell exhaustion, fibrosis, vascular leak, epithelial cell depletion, and fatal organ damage. Neutrophils and macrophages recruited to pathogen infected lungs, including SARS-CoV-2 infected lungs, express phosphatidylinositol 3-kinase gamma (PI3Kg), a signaling protein that coordinately controls granulocyte and monocyte trafficking to diseased tissues and immune suppressive, pro-fibrotic transcription in myeloid cells. PI3Kg deletion and inhibition with the clinical PI3Kg inhibitor eganelisib promoted survival in models of infectious diseases, including SARS-CoV-2 and MRSA, by suppressing inflammation, vascular leak, organ damage and cytokine storm. These results demonstrate essential roles for PI3Kg in inflammatory lung disease and support the potential use of PI3Kg inhibitors to suppress inflammation in severe infectious diseases. Methods Human subjects All human tissue analyses were conducted on de-identified tissue under guidelines established by the Institutional Review Board for human subject research of the University of California, San Diego. Postmortem tissue studies received IRB exemption from oversight as research on deceased patients is not classified as human subjects research by the US Department of Health and Human Services or the US Food and Drug Administration. All patients in this study were admitted early in the pandemic during the first 3-6 months after the first cases of COVID-19 were reported in the US when no specific therapeutics had been developed. De-identified lung tissue was obtained upon rapid autopsy of deceased COVID-19 patients formalin-fixed for 48h and processed by the Department of Pathology, UCSD, into paraffin-embedded tissue blocks by the Moores Cancer Center histology shared resource, UCSD, San Diego, CA. Normal human lung tissue was obtained from consented patients during lung cancer surgery at the Moores Cancer Center, UCSD and processed into paraffin embedded tissue blocks by the UCSD Department of Pathology. Bronchoalveolar lavage cells from COVID positive and from COVID-19 negative patients were pelleted, fixed, paraffin embedded and sectioned. All tissue was used for immunohistochemical and bioinformatics analysis. Animals 8-9-week-old C57BL/6 stock 000664 (RRID:IMSR_JAX:000664) male and female mice were purchased from Jackson Laboratories, Bar Harbor, ME. K18-hACE2 (RRID:IMSR_JAX:034860) 6-8 week old male mice were purchased from Jackson Laboratories. 10-month-old female Balb/c animals (RRID:IMSR_CRL:028) were purchased from Charles River for SARS-CoV-2 infection studies. Golden Syrian Hamsters (Mesocricetus auratus; genotype: HsdHan: AURA) six- to seven-week-old were from Envigo, USA. Pik3cg-/- mice in the C57BL/6 background (RRID:MGI:3619226) were maintained in the Varner lab at the University of California, San Diego. MRSA, MHV studies and ARDS studies were performed at the University of California, San Diego with the approval of the Institutional Animal Care and Use Committees and Institutional Biosafety Committees of the University of California, San Diego. SARS-CoV-2. SARS-CoV-2 infection of K18-hACE2 mice studies were performed at The Scripps Research Institute, La Jolla, CA with the approval of the Institutional Animal Care and Use Committee of The Scripps Research Institute. maSARS-CoV-2 mouse models were performed with support from the NIH-ACTIV program of NIAID, NIH at The Institute for Antiviral Research, Animal, Dairy and Veterinary Science, Utah State University, Logan, UT, with the approval of the Institutional Animal Care and Use Committees and Institutional Biosafety Committees of Utah State University. SARS-CoV-2 hamster studies were performed at the Department of Infectious Diseases and Global Health, Tufts University Cummings School of Veterinary Medicine, North Grafton, MA, USA. All animal experiments were performed with the approval of the Institutional Animal Care and Use Committees and Institutional Biosafety Committees of Tufts University. SARS-CoV-2 hamster experiments were conducted in ABSL3 facilities on the campus of Tufts University. Reagents Murine L929 cells (RRID:CVCL_0462, L cell, L-929, derivative of Strain L) were purchased from ATCC (Bethesda, MD) and maintained in completed Dulbecco’s Modified Eagle Medium (DMEM) media supplemented with 10% heat-inactivated fetal bovine serum (FBS) and antibiotics (100 μg/mL penicillin and 100 μg/mL streptomycin). Murine hepatitis virus MHV-A59 infectious clone in L929 cells (BEI NR-43000). SARS-CoV-2, Mouse-Adapted, MA10 variant, infectious clone in Calu-3 cells (BEI NR-55429) were obtained from BEI Resources, NIAID, NIH, Bethesda, Maryland, USA). Formulated IPI-549 and vehicle were provided by Infinity Pharmaceuticals (Cambridge, MA). Human histopathology Lung tissue was obtained upon rapid autopsy of recently deceased COVID-19 patients by the Department of Pathology, UCSD, formalin fixed for 48h, and processed into paraffin embedded tissue blocks by the Moores Cancer Center histology shared resource, UCSD, San Diego, CA. Normal human lung tissue was obtained during lung cancer surgery at the Moores Cancer Center, UCSD and processed into paraffin embedded tissue blocks by the UCSD Department of Pathology. Bronchoalveolar lavage cells from COVID-19 positive and from COVID-19 negative patients were pelleted, fixed, paraffin embedded and sectioned. Glass slides containing 4-5µm thick tissue sections were deparaffinized and stained with hematoxylin and eosin or Mason’s Trichrome by the Moores Cancer Center histology shared resource. Alternatively, slides were deparaffinized, rehydrated and treated for 20 minutes with Diva Decloaker (901-DV2004X-071017 Biocare Medical) antigen retrieval solution followed by with endogenous peroxidase blocking, and incubation with 5% normal goat serum for 1h. Slides were then incubated with 1:200 anti-human CD68 (RRID:AB_2074844 clone PG-M1, Dako/Agilent), 1:400 anti-PI3 Kinase-gamma (RRID:AB_1904087 Cell Signaling Technology, Inc., clone D55D5, #5405) or 1:200 anti-Myeloperoxidase (RRID:AB_2864724 ab208670, Abcam). Following primary antibody incubation, slides were washed in Tris buffered saline containing Tween 20 (TBST) and incubated with anti-rabbit horseradish peroxidase (HRP)-conjugated polymer (RRID:AB_2336820 Vectastain Elite ABC-HRP PK-6101, Vector Laboratories) for 30 minutes at room temperature, washed in TBST and counterstained with hematoxylin. Slides were mounted with Cytoseal permanent mounting medium (Richard-Allan Scientific Cat #8310-4). Biomarker quantification was performed using QPath open source digital image analysis software. Multiplex IHC Sequential IHC was performed on 5 μm FFPE sections using an adapted protocol based on methodology previously described (14-15). Briefly, slides were deparaffinized and stained with hematoxylin (S3301, Dako, Santa Clara, CA), followed by whole-slide scanning at 20X magnification on an Aperio AT2 (Leica Biosystems, Wetzlar, Germany). Tissues then underwent 20 minutes heat-mediated antigen retrieval in pH 6.0 Citra solution (BioGenex, Fremont, CA), followed by 10 minutes endogenous peroxidase blocking in Dako Dual Endogenous Enzyme Block (S2003, Dako, Santa Clara, CA), then 10 minutes protein blocking with 5% normal goat serum and 2.5% BSA in TBST. Primary antibody conditions are listed in Supplementary Table 1. Following primary antibody incubation, slides were washed in TBST, and incubated with either anti-rat, anti-mouse, or anti-rabbit Histofine Simple Stain MAX PO horseradish peroxidase (HRP)-conjugated polymer (RRID:AB_2811178 Biosciences, Tokyo, Japan) for 30 minutes at room temperature, followed by AEC chromogen (RRID:AB_2336076 Vector Laboratories, Burlingame, CA). Slides were digitally scanned following each chromogen development, then AEC was removed with 100% EtOH. Between rounds, peroxidase blocking with Dako Dual Endogenous Enzyme Block was performed for 10 minutes at RT to inactivate HRP enzyme still present upon the secondary antibody of the previous round. Another primary produced in a distinct species could be utilized within the same staining cycle. Between cycles, citrate antigen retrieval was completed as described above to remove all primary antibodies primary-secondary antibody complexes. Following iterative staining, computational image processes and analysis was performed. Scanned images were registered in MATLAB version R2018b using the SURF algorithm in the Computer Vision Toolbox (The MathWorks, Inc., Natick, MA). Image processing and cell quantification were performed using FIJI (FIJI Is Just ImageJ) (62). AEC signal was extracted for quantification and visualization in FIJI using a custom macro for color deconvolution. Briefly, the FIJI plugin Color_Deconvolution [H AEC] was used to separate hematoxylin, followed by postprocessing steps for signal cleaning and background elimination. AEC signal was extracted in FIJI using with the NIH plugin RGB_to_CMYK. Color deconvoluted images were processed in CellProfiler Version 3.5.1 (63) to quantify single cell mean intensity signal measurements for every stained marker. FCS Express 6 Image Cytometry RUO (De Novo Software, Glendale, CA) was used to perform hierarchical gating and cell classification based on expression of known markers as shown in Supp. Data. Fig. 1. For visualization, signal-extracted images were overlaid and pseudocolored in FIJI. TempoSeq FFPE tissue RNA Sequencing Two five-micron FFPE sections from each of twelve postmortem lung specimens from COVID-19 patients, five normal lung specimens, eight BALF specimens from COVID-19 patients and five BALF specimens from normal patients were used to perform TempoSeq (Templated Oligo assay with Sequencing readout) FFPE human whole transcriptome RNA sequencing at BioSpyder

This dataset contains de-identified patient data of 941 patients from 21 centers across the United States who were enrolled in the CONTAIN COVID-19 randomized controlled trial that ran from 4/17/2020-3/15/2021. The information in this dataset was used to conduct the analysis reported in the CONTAIN COVID-19 manuscript published in JAMA Internal Medicine (doi: 10.1001/jamainternmed.2021.6850) and includes demographic information, baseline history, baseline medications, baseline laboratory values, clinical status based on the WHO 11-point scale at 14 and 28 days after randomization, antibody titers, randomization arms.

The dataset comprises of the cumulative number of positive COVID-19 cases among Maryland residents by gender: Female; Male; and Unknown. It is a collection of positive COVID-19 test results that have been reported each day by the local health department via the ESSENCE system to the Maryland Department of Health who reports daily on COVID-19 cases by county. Dataset can be viewed and downloaded in a CSV file format.

This Project Tycho dataset includes a CSV file with COVID-19 data reported in UNITED STATES OF AMERICA: 2019-12-30 - 2021-07-31. It contains counts of cases, deaths, hospitalizations, and demographics. Data for this Project Tycho dataset comes from: "Alabama Department of Public Health Website Dashboard", "Arkansas Department of Health COVID-19 Website Dashboard", "California Health and Human Services Open Data Portal, California Department of Public Health COVID-19 Data", "Colorado Department of Public Health and Environment Open Data Website", "Connecticut Open Data Website, Department of Public Health COVID-19 Data", "Delaware Environmental Public Health Tracking Network, Delaware Health and Social Services Website", "Georgia Department of Public Health Website", "Illinois Department of Public Health Website", "Indiana Data Hub Website, Indiana State Department of Health COVID-19 Data", "COVID-19 Data Repository by the Center for Systems Science and Engineering (CSSE) at Johns Hopkins University", "Kentucky Department of Public Health COVID-19 Website Dashboard", "Maine Center for Disease Control & Prevention; Division of the Maine Department of Health and Human Services Website", "Maryland Department of Health COVID-19 Website Dashboard", "Minnesota Department of Health COVID-19 Website Dashboard", "Montana Department of Health & Human Services COVID-19 Website Dashboard", "New York State Department of Health Data Website", "COVID-19 Data Repository by The New York Times", "Ohio Department of Health COVID-19 website", "Pennsylvania Department of Health Data Website", "Tennessee Department of Health Website", "Texas Department of Health Services Website", "United States Centers for Disease Control and Prevention, COVID-19 Response", "Vermont Department of Health, Vermont Center for Geographic Information Open Geodata Portal", "Virginia Department of Health Website", "European Centre for Disease Prevention and Control Website", "World Health Organization COVID-19 Dashboard". The data have been pre-processed into the standard Project Tycho data format v1.1.

ObjectiveThe Dietary Guidelines for Americans has recommended consumption of a Mediterranean diet (MD) for overall health and wellbeing, and the US News & World Report has ranked the MD as the top diet overall for the past six consecutive years. However, it is uncertain if university students in the United States (US) have increased their adoption of this dietary approach over these past six years.DesignLongitudinal cross-sectional survey conducted in three cohorts (2018, 2020, 2022) utilizing regression models to assess MD Adherence and other relevant outcomes variables.SettingUniversity in the southern US.ParticipantsStudents (n = 761) enrolled in undergraduate introductory nutrition course.ResultsSurvey respondents were 83% female, 91% white, and 97% ages 18–24. Predictors of MD adherence were older age, female gender, and health-related qualifications. MD adherence was lowest in 2022. The 2022 group perceived less MD health benefits, weight loss, ethical concerns, natural content, and sensory appeal compared to the 2018 group. During the COVID-19 pandemic, changes in eating behavior were examined in the 2020 and 2022 groups. We observed that participants in the 2022 group had a greater frequency of snacking and a lower frequency of eating out compared to 2020 group.ConclusionMD adherence did not increase over time in US university students. These findings underscore the need for targeted interventions and education to promote healthier eating habits in university students.