San Mateo County And California Crime Rates 2000-2014

Violent and property crime rates per 100,000 population for San Mateo County and the State of California. The total crimes used to calculate the rates for San Mateo County include data from: Sheriff's Department Unincorporated, Atherton, Belmont, Brisbane, Broadmoor, Burlingame, Colma, Daly City, East Palo Alto, Foster City, Half Moon Bay, Hillsborough, Menlo Park, Millbrae, Pacifica, Redwood City, San Bruno, San Carlos, San Mateo, South San Francisco, Bay Area DPR, BART, Union Pacific Railroad, and CA Highway Patrol.

CHSA - ECON -- Food Insecurity --- 2-Year Dissected

Percent of People who Cannot Afford to Feed Themselves Sufficiently. U.S. Census Bureau, Current Population Survey, December Supplement (AKA USDA Food Security Supplement). Dissected by Year, Geographic Area, Age Category, and Race/Ethnicity.

CHSA - ECON -- Food Insecurity --- 1-Year Overall

Percent of People who Cannot Afford to Feed Themselves Sufficiently. U.S. Census Bureau, Current Population Survey, December Supplement (AKA USDA Food Security Supplement). Dissected by Year and Geographic Area

COVID-19 Deaths by Population Characteristics Over Time

<strong>A. SUMMARY</strong> This dataset shows San Francisco COVID-19 deaths by population characteristics and by date. This data may not be immediately available for recently reported deaths. Data updates as more information becomes available. Because of this, death totals for previous days may increase or decrease. More recent data is less reliable. Population characteristics are subgroups, or demographic cross-sections, like age, race, or gender. The City tracks how deaths have been distributed among different subgroups. This information can reveal trends and disparities among groups. <strong>B. HOW THE DATASET IS CREATED</strong> As of January 1, 2023, COVID-19 deaths are defined as persons who had COVID-19 listed as a cause of death or a significant condition contributing to their death on their death certificate. This definition is in alignment with the California Department of Public Health and the national <a href = "https://preparedness.cste.org/wp-content/uploads/2022/12/CSTE-Revised-Classification-of-COVID-19-associated-Deaths.Final_.11.22.22.pdf">Council of State and Territorial Epidemiologists</a>. Death certificates are maintained by the California Department of Public Health. Data on the population characteristics of COVID-19 deaths are from: *Case reports *Medical records *Electronic lab reports *Death certificates Data are continually updated to maximize completeness of information and reporting on San Francisco COVID-19 deaths. To protect resident privacy, we summarize COVID-19 data by only one characteristic at a time. Data are not shown until cumulative citywide deaths reach five or more. Data notes on each population characteristic type is listed below. <u> Race/ethnicity</u> * We include all race/ethnicity categories that are collected for COVID-19 cases. <u>Gender</u> * The City collects information on gender identity using <u><a href="https://www.sfdph.org/dph/files/PoliciesProcedures/COM5_SexGenderGuidelines.pdf">these guidelines</a></u>. <strong>C. UPDATE PROCESS</strong> Updates automatically at 06:30 and 07:30 AM Pacific Time on Wednesday each week. Dataset will not update on the business day following any federal holiday. <strong>D. HOW TO USE THIS DATASET</strong> Population estimates are only available for age groups and race/ethnicity categories. San Francisco population estimates for race/ethnicity and age groups can be found in a <a href="https://data.sfgov.org/d/cedd-86uf">view based on the San Francisco Population and Demographic Census dataset</a>. These population estimates are from the 2016-2020 5-year American Community Survey (ACS). This dataset includes many different types of characteristics. Filter the “Characteristic Type” column to explore a topic area. Then, the “Characteristic Group” column shows each group or category within that topic area and the number of deaths on each date. New deaths are the count of deaths within that characteristic group on that specific date. Cumulative deaths are the running total of all San Francisco COVID-19 deaths in that characteristic group up to the date listed. This data may not be immediately available for more recent deaths. Data updates as more information becomes available. To explore data on the total number of deaths, use <u><a href="https://data.sfgov.org/COVID-19/COVID-19-Deaths-Over-Time/g2di-xufg">the COVID-19 Deaths Over Time dataset</a></u>. <strong>E. CHANGE LOG</strong> <UL><LI>9/11/2023 - on this date, we began using an updated definition of a COVID-19 death to align with the California Department of Public Health. This change was applied to COVID-19 deaths retrospectively beginning on 1/1/2023. More information about the recommendation by the Council of State and Territorial Epidemiologists that motivated this change can be found <a href = "https://preparedness.cste.org/wp-content/uploads/2022/12/CSTE-Revised-Classification-of-COVID-19-associated-Deaths.Final_.11.22.22.pdf">here</a>. <LI>6/6/2023 - d

Vital Signs: Fatalities From Crashes – by metro

VITAL SIGNS INDICATOR Injuries From Crashes (EN4-6) FULL MEASURE NAME Fatalities from crashes (traffic collisions) LAST UPDATED October 2017 DESCRIPTION Fatalities from crashes refers to deaths as a result of injuries sustained in collisions. The California Highway Patrol includes deaths within 30 days of the collision that are a result of injuries sustained as part of this metric. This total fatalities dataset includes fatality counts for the region and counties, as well as individual collision data and metropolitan area data. DATA SOURCE National Highway Safety Administration: Fatality Analysis Reporting System CONTACT INFORMATION vitalsigns.info@bayareametro.gov METHODOLOGY NOTES (across all datasets for this indicator) The data is reported by the National Highway Safety Administration's Fatalities Analysis Reporting System. 2016 data comes from the California Highway Patrol (CHP) to the Statewide Integrated Traffic Records System (SWITRS), which was accessed via SafeTREC’s Transportation Injury Mapping System (TIMS). The data was tabulated using provided categories specifying injury level, individuals involved, causes of collision, and location/jurisdiction of collision (for more: http://tims.berkeley.edu/help/files/switrs_codebook.doc). Fatalities were normalized over historic population data from the US Census and California Department of Finance and vehicle miles traveled (VMT) data from the Federal Highway Administration. For more regarding reporting procedures and injury classification see the California Highway Patrol Manual (http://www.nhtsa.gov/nhtsa/stateCatalog/states/ca/docs/CA_CHP555_Manual_2_2003_ch1-13.pdf).

Napa County and California Population Totals 2011-2020

Data Source: CA Department of Finance Data: Population estimates for January 1, 2011, through January 1, 2020. The population estimates benchmark for April 1, 2010 is also provided. Citation: State of California, Department of Finance, E-4 Population Estimates for Cities, Counties, and the State, 2011-2020, with 2010 Census Benchmark. Sacramento, California, May 2022. For detailed information on methodology and other data considerations, visit: https://dof.ca.gov/Forecasting/Demographics/Estimates/e-4-population-estimates-for-cities-counties-and-the-state-2011-2020-with-2010-census-benchmark-new/

Chicago COVID-19 Community Vulnerability Index (CCVI)

The Chicago CCVI identifies communities that have been disproportionately affected by COVID-19 and are vulnerable to barriers to COVID-19 vaccine uptake​. Vulnerability is defined as a combination of sociodemographic factors, epidemiological factors​, occupational factors​, and cumulative COVID-19 burden. The 10 components of the index include COVID-19 specific risk factors and outcomes and social factors known to be associated with social vulnerability in the context of emergency preparedness. The CCVI is derived from ranking values of the components by Chicago Community Area, then synthesizing them into a single composite weighted score. The higher the score, the more vulnerable the geographic area. ZIP Code CCVI is included to enable comparison with other COVID-19 data available on the Chicago Data Portal. Some elements of the CCVI are not available by ZIP Code. To create ZIP Code CCVI, the proportion of the ZIP Code population contributed by each Community Areas was determined. The apportioned populations were then weighted by the Community Area CCVI score and averaged to determine a ZIP Code CCVI score. The COVID-19 Community Vulnerability Index (CCVI) is adapted and modified from a Surgo Ventures collaboration (https://precisionforcovid.org/ccvi) and the CDC Social Vulnerability Index​. ZIP Codes are based on ZIP Code Tabulation Areas (ZCTAs) developed by the U.S. Census Bureau. For full documentation see: https://www.chicago.gov/content/dam/city/sites/covid/reports/012521/Community_Vulnerability_Index_012521.pdf

Mpox Vaccinations Given to SF Residents by Demographics

<strong>UPDATE 1/3/2023: Due to low case numbers, this page will no longer include vaccinations after 12/31/2022. </strong> <strong>A. SUMMARY </strong> This dataset represents doses of mpox vaccine (JYNNEOS) administered in California to residents of San Francisco ages 18 years or older. This dataset only includes doses of the JYNNEOS vaccine given on or after 5/1/2022. All vaccines given to people who live in San Francisco are included, no matter where the vaccination took place. The data are broken down by multiple demographic stratifications. <strong>B. HOW THE DATASET IS CREATED </strong> Information on doses administered to those who live in San Francisco is from the <a href="https://cdph.ca.gov/CAIR">California Immunization Registry (CAIR2)</a>, run by the California Department of Public Health (CDPH). Information on individuals’ city of residence, age, race, ethnicity, and sex are recorded in CAIR2 and are self-reported at the time of vaccine administration. Because CAIR2 does not include information on sexual orientation, we pull information from the San Francisco Department of Public Health’s Epic Electronic Health Record (EHR). The populations represented in our Epic data and the CAIR2 data are different. Epic data only include vaccinations administered at SFDPH managed sites to SF residents. Data notes for population characteristic types are listed below. <u>Age </u> * Data only include individuals who are 18 years of age or older. <u>Race/ethnicity </u> * The response option "Other Race" is categorized by the data source system, and the response option "Unknown" refers to a lack of data. <u>Sex </u> * The response option "Other" is categorized by the source system, and the response option "Unknown" refers to a lack of data. <u>Sexual orientation </u> * The response option “Unknown/Declined” refers to a lack of data or individuals who reported multiple different sexual orientations during their most recent interaction with SFDPH. For convenience, we provide <a href="https://data.sfgov.org/d/4qbq-hvtt"> the 2020 5-year American Community Survey population estimates</a>. <strong>C. UPDATE PROCESS </strong> Updated daily via automated process. <strong>D. HOW TO USE THIS DATASET </strong> This dataset includes many different types of demographic groups. Filter the “demographic_group” column to explore a topic area. Then, the “demographic_subgroup” column shows each group or category within that topic area and the total count of doses administered to that population subgroup.

2015 University Of California Payroll (Geocoded)

CA Department of Finance Population Projections for Napa County

Report P-3: Population Projections Race/Ethnicity and Sex by Individual Years of Age, 2010 to 2060 California (2019 Baseline) Data Notes: "The California Department of Finance (DOF), Demographic Research Unit is responsible by statute for maintaining postcensal population projections which are calculated using the demographic balancing equation: Current Population = Previous Population + (Births - Deaths) +Net Migration This method calculates the population in the target year by starting with the population from the previous year, adding natural increase (births minus deaths) and net migration that occurred during the time period between the two years. The births, deaths, and migration anticipated during the time period are called the components of change. A cohort-component method traces people born in a given year throughout their lives. As each year passes, cohorts change due to the mortality and migration assumptions. Applying fertility assumptions to women of childbearing age forms new cohorts at age zero. These 2019 baseline projections incorporate the latest historical population, birth, death, and migration data available as of July 1, 2020. Historical trends from 1990 through 2020 for births, deaths, and migration are examined. County populations by age, sex, and race/ethnicity are projected to 2060. The county projections are then summed to obtain data for the state. " View the Methodology at: https://dof.ca.gov/Forecasting/Demographics/Projections/ Published by: Demographic Research Unit Department of Finance Website: www.dof.ca.gov/Forecasting/Demographics/Projections/ Phone: 916-323-4086 Suggested Citation California Department of Finance. Demographic Research Unit. Report P-3: Population Projections, California, 2010-2060 (Baseline 2019 Population Projections; Vintage 2020 Release). Sacramento: California. July 2021. Data dictionary: https://dof.ca.gov/wp-content/uploads/sites/352/Forecasting/Demographics/Documents/P3_Dictionary.txt