NO LONGER UPDATED. Data source: County of San Diego, Health and Human Services Agency, Public Health Services, Epidemiology and Immunization Services Branch

Notice: Data is preliminary and subject to change. This dataset is updated in the evening on a daily basis. There is a delay in the Esri Hub caching process of between 5 - 10 minutes. Download requests will be queued in your browser prior to execution during the caching process and resume once the data cache is rebuilt.COVID-19 Statistics San Diego CountyData source: County of San Diego, Health and Human Services Agency, Public Health Services, Epidemiology and Immunization Services Branch

Includes number of total confirmed positive cases in San Diego as posted by https://www.sandiegocounty.gov/content/sdc/hhsa/programs/phs/community_epidemiology/dc/2019-nCoV/status.html.

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County of San Diego confirmed COVID cases by zip code. NO LONGER UPDATED. Updated dataset can be found: https://data.sandiegocounty.gov/dataset/COVID-19-Statistics-by-Zip-Code/jtds-js8h

Note: This dataset is no longer being updated due to the end of the COVID-19 Public Health Emergency. Note: On 2/16/22, 17,467 cases based on at-home positive test results were excluded from the probable case counts. Per national case classification guidelines, cases based on at-home positive results are now classified as “suspect” cases. The majority of these cases were identified between November 2021 and February 2022. CDPH tracks both probable and confirmed cases of COVID-19 to better understand how the virus is impacting our communities. Probable cases are defined as individuals with a positive antigen test that detects the presence of viral antigens. Antigen testing is useful when rapid results are needed, or in settings where laboratory resources may be limited. Confirmed cases are defined as individuals with a positive molecular test, which tests for viral genetic material, such as a PCR or polymerase chain reaction test. Results from both types of tests are reported to CDPH. Due to the expanded use of antigen testing, surveillance of probable cases is increasingly important. The proportion of probable cases among the total cases in California has increased. To provide a more complete picture of trends in case volume, it is now more important to provide probable case data in addition to confirmed case data. The Centers for Disease Control and Prevention (CDC) has begun publishing probable case data for states. Testing data is updated weekly. Due to small numbers, the percentage of probable cases in the first two weeks of the month may change. Probable case data from San Diego County is not included in the statewide table at this time. For more information, please see https://www.cdph.ca.gov/Programs/CID/DCDC/Pages/COVID-19/Probable-Cases.aspx

This project uses locations of testing sites and hospitals, as well as census information by census tracts in San Diego, to compare infection risks between white and non-white areas. Linear regression has been used to find correlation between population characteristics and testing site patterns.Additional information in the Project PDFNotable Modules Used: Python: pandas, geopandas, numpy, matplotlib, sklearn ArcGIS: find_existing_locations, enrich_layer, join_features

This project aims to build a model that is able to generate risk scores for schools in different areas of San Diego and provide insights for schools to take the appropriate precautionary measures when reopening for in-person instructions. We plan to utilize the 2020 synthetic population data for simulating transportation from and to schools. Combining the trips data with school information and case rates in individual census tracts, we can then assign weights to various factors and compute the final risk score for schools in each census tract. The final result can also serve as a baseline for agent-based model to simulate COVID-19 spread on campus.Notable Modules Used:Matplotlib We used matplotlib to plot some of our data into graph to better view them in a visualized way.Geopandas We used geopandas to read in the shape files in our data.Pandas We used pandas to handle dataframe and have done some preprocessing using it.Numpy We used numpy for some arithmetic operations.ArcGIS Feature Module It is mainly used for feature summarization. Using the summarize_within function provided in this module, we are able to turn our zip code based COVID data into MGRA based COVID data.

Univariate and multivariable logistic regression analysis of factors associated with parental vaccination endorsement for COVID-19.

COVID 19 Category Archives — Immigration Lawyer Blog Published by San Diego Immigration Attorney — Jacob J. Sapochnick | Published by San Diego Immigration Attorney — Jacob J. Sapochnick

Observational data from March 2020 to May 2020 of COVID-19 ICU outcomes at a US-MX hospital.

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.

Linear regression analysis of anxious temperament, self-infection and COVID-19-related fear of loved ones’ infection as predictors of cyberchondria in the whole sample (N = 499) with variance inflation factor (VIF).

This project analyzed the increase of food delivery services and Covid exposure risk correlations. It used geoenrichment to create a feature layer in ArcGIS for each business, created a feature layer for the Covid Case rate by ZIP code, and applied spatial join to generate a 'risk' level for each business for analysis.Additional information in the Project PDFNotable Modules Used: Python: pandas, numpy, matplotlib ArcGIS: enrich, BufferStudyArea

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Infection by SARS-CoV-2 and subsequent COVID-19 can cause viral sepsis and septic shock. Our past studies demonstrated that dysregulated systemic proteolysis is associated with the pathological mechanism in bacterial septic shock. Thus, here we perform shotgun proteomics and peptidomics analysis by LC-MS/MS to identify and quantify the circulating protein and peptide profile of COVID-19 patient plasma. Plasma samples from four COVID-19 patients were collected at different time points of their ICU stay, including samples from a patient with COVID-19-induced sepsis and bacterial superinfection. By combining mass spectrometry analysis with enzymatic activity assays, our study elucidates the possible pathological involvement of proteolysis in COVID-19-induced sepsis, with particular insight into the dyregulation of protease-mediated systems, such as the coagulation cascade.

Descriptive statistics, skewness and kurtosis values for analysed variables in the whole sample (N = 499).

This is the daily information that are used in the public CoVID-19 Surveillance, Trends, and Progress and Warnings Dashboards. Each field is updated after 6pm CST Monday through Friday. Weekend data is added on Monday as individual records, along with Monday's reported data. The Surveillance Dashboard is live and available here.Backlog CoVID-19 cases are cases that are reported more than 14-days after the event date (date of Test or date of onset of symptoms). Backlog cases are reported along with the Monday Cumulative Cases, but are not included in in the daily Case Change.This data reflects information provided by the City of San Antonio Metro Health Department, and is released Monday through Friday at 6PM on the City of San Antonio CoVID-19 website.