After over two years of public reporting, the State Profile Report will no longer be produced and distributed after February 2023. The final release was on February 23, 2023. We want to thank everyone who contributed to the design, production, and review of this report and we hope that it provided insight into the data trends throughout the COVID-19 pandemic. Data about COVID-19 will continue to be updated at CDC’s COVID Data Tracker.

The State Profile Report (SPR) is generated by the Data Strategy and Execution Workgroup in the Joint Coordination Cell, in collaboration with the White House. It is managed by an interagency team with representatives from multiple agencies and offices (including the United States Department of Health and Human Services (HHS), the Centers for Disease Control and Prevention, the HHS Assistant Secretary for Preparedness and Response, and the Indian Health Service). The SPR provides easily interpretable information on key indicators for each state, down to the county level.

It is a weekly snapshot in time that:

• Focuses on recent outcomes in the last seven days and changes relative to the month prior
• Provides additional contextual information at the county level for each state, and includes national level information
• Supports rapid visual interpretation of results with color thresholds

This dataset provides a single table of historical outbreak data as reported by public health departments to the Michigan Department of Health and Human Services from August 22, 2020 to February 11, 2021. Additional information about the dataset and more current data tables can be found here: https://www.michigan.gov/coronavirus/0,9753,7-406-98163_98173_102057---,00.html.

Context

COVID-19 is on a rise worldwide. It was first identified in the city of Wuhan in China in 2019 and has now spread into a global pandemic. Michigan is currently the third largest affected state in USA. The state's confirmed cases have been on a rise since early March 2020. In this dire time, it is extremely important to understand the factors affecting the spread of the virus in Michigan, identify susceptible population and predict the trajectory of the infected and dead cases on a daily basis.

Content

Update: April 4, 2020 2:00 PM Eastern Standard Time (EST)

This data currently contains information about COVID-19 confirmed cases (14225) and deaths (540) in Michigan counties. The dataset also includes percentage of COVID-19 confirmed and dead cases by age, gender, race and ethnicity. The information is published by www.michigan.gov on a daily basis at 2:00 PM EST. The results are included as of 10:00 AM every day.

Acknowledgements

Michigan.gov - Coronavirus

Inspiration

1. This dataset will be useful in understanding and predicting the trajectory of the infected and dead cases in Michigan in the coming days.
2. The dataset can also give insight about the most vulnerable age groups in Michigan.

Please consider upvoting if the data is found useful in any way. If there are any improvement suggestions, do let me know.

The New York Times is releasing a series of data files with cumulative counts of coronavirus cases in the United States, at the state and county level, over time. We are compiling this time series data from state and local governments and health departments in an attempt to provide a complete record of the ongoing outbreak.

Since late January, The Times has tracked cases of coronavirus in real time as they were identified after testing. Because of the widespread shortage of testing, however, the data is necessarily limited in the picture it presents of the outbreak.

We have used this data to power our maps and reporting tracking the outbreak, and it is now being made available to the public in response to requests from researchers, scientists and government officials who would like access to the data to better understand the outbreak.

The data begins with the first reported coronavirus case in Washington State on Jan. 21, 2020. We will publish regular updates to the data in this repository.

The single biggest need in the parts of Detroit that have been the hardest hit by the coronavirus is food. That's according to data available in a recently released COVID-19 Dashboard put together by Michigan 211.

This dataset tracks the updates made on the dataset "COVID-19 State Profile Report - Michigan" as a repository for previous versions of the data and metadata.

Data published on potential COVID-19 symptoms reported through NHS Pathways and 111 online Dashboard shows the total number of NHS Pathways triages through 111 and 999, and online assessments in 111 online which have received a potential COVID-19 final disposition. This data is based on potential COVID-19 symptoms reported by members of the public to NHS Pathways through NHS 111 or 999 and 111 online, and is not based on the outcomes of tests for coronavirus. This is not a count of people.

The COVID-19 pandemic exacerbated equity issues in education spanning race, disability, language, and socio-economic status. However, few studies examine the ways that district or state educational leaders consider equity in their decision-making during a crisis. This study examines how K-12 state and local leaders conceptualized equity and actualized equitable policies and practices during the pandemic. We conducted a multi-level case study, interviewing state and local-level educational leaders (n=64) from five school districts in the state of Michigan. Our findings reveal that leaders formed equity visions focused on meeting students’ individual needs, which were enacted differently at the state and local levels. Interview questions focused on leaders’ priorities and efforts to support staff, students, and families during the height of the COVID-19 pandemic. For example, interview questions prompted leaders to share their specific approaches for promoting student learning and engagement amidst the pandemic, key collaborators in this work, relevant successes and challenges, and any initiatives designed to support specific student populations (e.g., English learners, students receiving special education services, etc.). Additional topics include reflections on any lessons learned about equity during the 2019-20 and 2020-21 school years, including how leaders' thoughts on equity may have shifted due to the pandemic.

United States SB: MI: COVID-19 Impact: Little or Number Effect data was reported at 21.000 % in 11 Apr 2022. This records a decrease from the previous number of 22.800 % for 04 Apr 2022. United States SB: MI: COVID-19 Impact: Little or Number Effect data is updated weekly, averaging 22.350 % from Nov 2021 (Median) to 11 Apr 2022, with 18 observations. The data reached an all-time high of 27.600 % in 14 Mar 2022 and a record low of 19.700 % in 28 Feb 2022. United States SB: MI: COVID-19 Impact: Little or Number Effect data remains active status in CEIC and is reported by U.S. Census Bureau. The data is categorized under Global Database’s United States – Table US.S047: Small Business Pulse Survey: by State: Midwest Region: Weekly, Beg Monday (Discontinued).

Data published on potential COVID-19 symptoms reported through NHS Pathways and 111 online shows the total number of NHS Pathways triages through 111 and 999, and online assessments in 111 online which have received a potential COVID-19 final disposition. This data is based on potential COVID-19 symptoms reported by members of the public to NHS Pathways through NHS 111 or 999 and 111 online, and is not based on the outcomes of tests for coronavirus. It is not a count of people.

United States SB: MI: COVID-19 Impact: Large Positive Effect data was reported at 2.100 % in 04 Apr 2022. This records a decrease from the previous number of 2.300 % for 28 Mar 2022. United States SB: MI: COVID-19 Impact: Large Positive Effect data is updated weekly, averaging 1.900 % from Nov 2021 (Median) to 04 Apr 2022, with 6 observations. The data reached an all-time high of 3.200 % in 07 Mar 2022 and a record low of 1.900 % in 20 Dec 2021. United States SB: MI: COVID-19 Impact: Large Positive Effect data remains active status in CEIC and is reported by U.S. Census Bureau. The data is categorized under Global Database’s United States – Table US.S: Small Business Pulse Survey: by State: Midwest Region: Weekly, Beg Monday (Discontinued).

BackgroundMass vaccination serves as an effective strategy to combat the COVID-19 pandemic. Vaccine hesitancy is a recognized impediment to achieving a vaccination rate necessary to protect communities. However, solutions and interventions to address this issue are limited by a lack of prior research.MethodsOver 200 patients from 18 Michigan counties participated in this study. Each participant received an initial survey, including demographical questions and knowledge and opinion questions regarding COVID-19 and vaccines. Participants were randomly assigned an educational intervention in either video or infographic format. Patients received a post-survey to assess changes in knowledge and attitudes. Paired sample t-tests and ANOVA were used to measure the effectiveness of the educational interventions. Participants also elected to complete a 3-month follow-up survey.ResultsPatients showed increased knowledge after the educational intervention in six out of seven COVID-19 topics (p 

IntroductionCOVID-19 can cause Myocardial Injury (MI) during acute illness, which has been strongly associated with worse outcomes during hospitalization, however, more research is required on its effects on long-term outcomes, especially in underexplored regions in the literature such as Latin America.MethodsThis multicenter prospective cohort study follows up with patients with previous severe COVID-19 at a 2-year follow-up encounter. Comprehensive assessments were conducted including demographic data, clinical variables, psychiatric evaluations, and echocardiographic studies. Patients were stratified by the presence or absence of MI during their acute COVID-19 hospitalization. Statistical analyses included logistic regression and univariate comparisons.ResultsOf the 210 patients included, 53 (25%) had MI. Patients with MI were older, had a higher prevalence of comorbidities (e.g., hypertension, chronic kidney disease, atrial fibrillation), and were more likely to require intensive care unit admission, invasive mechanical ventilation, and vasopressor or inotropic support during acute COVID-19. Regarding long-term cardiovascular outcomes, no significant differences were observed in de novo cardiovascular disease, venous thromboembolism, or acute cardiovascular events. Patients with MI had greater odds of cardiopulmonary hospitalizations during follow-up (aOR 3.67, 95% CI 1.07–13.07, p = 0.037) after adjusting for age and sex.ConclusionPatients with prior MI during COVID-19 had a higher prevalence of comorbidities, poorer functional status, and increased odds of cardiopulmonary hospitalizations over a two-year follow-up evaluation compared to those without MI. Although prior studies suggest an association between MI and worse long-term outcomes, the evidence remains inconsistent. These findings emphasize the need for ongoing research to clarify how MI contributes to worsened long-term outcomes.

The COVID-19 Coping Study is a national, longitudinal cohort study of 6,938 US adults aged ≥55 enrolled from April 2nd through May 31st, 2020 in all 50 US states, the District of Columbia, and Puerto Rico. Participants were recruited through a non-probability multi-frame sampling strategy, and completed data collection through online questionnaires administered via the University of Michigan Qualtrics in English (N=6,886) and Spanish (N=52). Data were collected on a variety of demographic, social, and health-related topics including COVID-19 symptom and testing history, COVID-19-related stressors and worries, self-isolation and social distancing practices, behavior changes and coping mechanisms, mental health symptom scales, and living arrangements. A sub-set of the baseline sample (N=4,401) were sent monthly follow-up questionnaires over the following 12 months. The included files contain baseline through 6-month of follow-up data from the COVID-19 Coping Study. Data are available in Stata (C19CS.dta), a CSV file with value labels (C19CS Labelled.csv), and a CSV file with numeric values (C19CS Numeric.csv).

This is a release of management information for anonymous summary data for those patients that have been identified on the Shielded Patient List (SPL). Its purpose is to make the summary data available to a wider audience as open data to enable a broad base of users to perform analysis from it. The purpose behind releasing this data is to present regional and local data to allow for its use in public health. It will also allow for greater analysis, modelling and planning to be performed using the latest data to aid in the response to the pandemic. We will update this weekly and we would welcome your feedback to help us develop our open data sets. The data that is published is based on version 33 of the SPL clinical methodology, with the data extracted as at 19 November 2020.

This file contains COVID-19 death counts and rates by month and year of death, jurisdiction of residence (U.S., HHS Region) and demographic characteristics (sex, age, race and Hispanic origin, and age/race and Hispanic origin). United States death counts and rates include the 50 states, plus the District of Columbia. 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 jurisdictions. 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; 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). Rate are based on deaths occurring in the specified week 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 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) 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.).

United States SB: MI: COVID-19 Impact: Moderate Negative Effect data was reported at 46.900 % in 11 Apr 2022. This records an increase from the previous number of 45.700 % for 04 Apr 2022. United States SB: MI: COVID-19 Impact: Moderate Negative Effect data is updated weekly, averaging 46.150 % from Nov 2021 (Median) to 11 Apr 2022, with 18 observations. The data reached an all-time high of 48.400 % in 28 Feb 2022 and a record low of 40.500 % in 22 Nov 2021. United States SB: MI: COVID-19 Impact: Moderate Negative Effect data remains active status in CEIC and is reported by U.S. Census Bureau. The data is categorized under Global Database’s United States – Table US.S047: Small Business Pulse Survey: by State: Midwest Region: Weekly, Beg Monday (Discontinued).

This is a prospective, multi-site study designed to evaluate whether the use of hydroxychloroquine in healthcare workers (HCW), Nursing Home Workers (NHW), first responders (FR), and Detroit Department of Transportation bus drivers (DDOT) in SE, Michigan, can prevent the acquisition, symptoms and clinical COVID-19 infection

The primary objective of this study is to determine whether the use of daily or weekly oral hydroxychloroquine (HCQ) therapy will prevent SARS-CoV-2 infection and COVID-19 viremia and clinical COVID-19 infection healthcare workers (HCW) and first responders (FR) (EMS, Fire, Police, bus drivers) in Southeast Michigan.

Preventing COVID-19 transmission to HCW, FR, and Detroit Department of Transportation (DDOT) bus drivers is a critical step in preserving the health care and first responder force, the prevention of COVID-19 transmission in health care facilities, with the potential to preserve thousands of lives in addition to sustaining health care systems and civil services both nationally and globally. If efficacious, further studies on the use of hydroxychloroquine to prevent COVID-19 in the general population could be undertaken, with a potential impact on hundreds of thousands of lives.

Context This is a dataset i've using of ECG Classification of Patients including COVID-19

Content The dataset regroups differents kinds of ECG signal : COVID-19, Abnormal Heartbeat (HB), Normal Heartbeat, Myocardial Infarction (MI) and Patient that have History of MI (PMI ). The original dataset is a 12-lead based standard ECG images for differents patients with differents heart conditions. The signal was obtains by turning each image of the Lead II (unlike the previous dataset which used the lead 4) into an ECG signal. After that, we use Neurokit2 to extract each heartbeat. Finally, we applied data augmentation techniques ( Time and Magnitude warping) to get the final train dataset. Class label : - Normal ECG ( Label 0) - Abnormal ECG (Label 1) - ECG of patient with an history of myocardial infarction ( Label 2) - ECG of patient with myocardial infarction (Label 3) - ECG of COVID-19 patients ( Label 4)

Two versions are present : - 125 Hz for wearables portables - 250 Hz

Acknowledgements Sources : Original dataset (Non-cropped images) : https://doi.org/10.1016/j.dib.2021.106762

Multivariate analysis and adjusted logistic regression for predictors of death.