On 6/28/2023, data on cases by vaccination status will be archived and will no longer update.

A. SUMMARY This dataset represents San Francisco COVID-19 positive confirmed cases by vaccination status over time, starting January 1, 2021. Cases are included on the date the positive test was collected (the specimen collection date). Cases are counted in three categories: (1) all cases; (2) unvaccinated cases; and (3) completed primary series cases.

1. All cases: Includes cases among all San Francisco residents regardless of vaccination status.

2. Unvaccinated cases: Cases are considered unvaccinated if their positive COVID-19 test was before receiving any vaccine. Cases that are not matched to a COVID-19 vaccination record are considered unvaccinated.

3. Completed primary series cases: Cases are considered completed primary series if their positive COVID-19 test was 14 days or more after they received their 2nd dose in a 2-dose COVID-19 series or the single dose of a 1-dose vaccine. These are also called “breakthrough cases.”

On September 12, 2021, a new case definition of COVID-19 was introduced that includes criteria for enumerating new infections after previous probable or confirmed infections (also known as reinfections). A reinfection is defined as a confirmed positive PCR lab test more than 90 days after a positive PCR or antigen test. The first reinfection case was identified on December 7, 2021.

Data is lagged by eight days, meaning the most recent specimen collection date included is eight days prior to today. All data updates daily as more information becomes available.

B. HOW THE DATASET IS CREATED Case information is based on confirmed positive laboratory tests reported to the City. The City then completes quality assurance and other data verification processes. Vaccination data comes from the California Immunization Registry (CAIR2). The California Department of Public Health runs CAIR2. Individual-level case and vaccination data are matched to identify cases by vaccination status in this dataset. Case records are matched to vaccine records using first name, last name, date of birth, phone number, and email address.

We include vaccination records from all nine Bay Area counties in order to improve matching rates. This allows us to identify breakthrough cases among people who moved to the City from other Bay Area counties after completing their vaccine series. Only cases among San Francisco residents are included.

C. UPDATE PROCESS Updates automatically at 08:00 AM Pacific Time each day.

D. HOW TO USE THIS DATASET Total San Francisco population estimates can be found in a view based on the San Francisco Population and Demographic Census dataset. These population estimates are from the 2016-2020 5-year American Community Survey (ACS). To identify total San Francisco population estimates, filter the view on “demographic_category_label” = “all ages”.

Population estimates by vaccination status are derived from our publicly reported vaccination counts, which can be found at COVID-19 Vaccinations Given to SF Residents Over Time.

The dataset includes new cases, 7-day average new cases, new case rates, 7-day average new case rates, percent of total cases, and 7-day average percent of total cases for each vaccination category.

New cases are the count of cases where the positive tests were collected on that specific specimen collection date. The 7-day rolling average shows the trend in new cases. The rolling average is calculated by averaging the new cases for a particular day with the prior 6 days.

New case rates are the count of new cases per 100,000 residents in each vaccination status group. The 7-day rolling average shows the trend in case rates. The rolling average is calculated by averaging the case rate for a particular day with the prior six days. Percent of total new cases shows the percent of all cases on each day that were among a particular vaccination status.

Here is more information on how each case rate is calculated:

1. The case rate for all cases is equal to the number of new cases among all residents divided by the estimated total resident population.

2. Unvaccinated case rates are equal to the number of new cases among unvaccinated residents divided by the estimated number of unvaccinated residents. The estimated number of unvaccinated residents is calculated by subtracting the number of residents that have received at least one dose of a vaccine from the total estimated resident population.

3. Completed primary series case rates are equal to the number of new cases among completed primary series residents divided by the estimated number of completed primary series residents. The estimated number of completed primary series residents is calculated by taking the number of residents who have completed their primary series over time and adding a 14-day delay to the “date_administered” column, to align with the definition of “Completed primary series cases” above.

E. CHANGE LOG

• 6/28/2023 - data on cases by vaccination status are no longer being updated. This data is currently through 6/20/2023 (as of 6/28/2023) and will not include any new data after this date.
  
• 4/6/2023 - the State implemented system updates to improve the integrity of historical data.
• 2/21/2023 - system updates to improve reliability and accuracy of cases data were implemented.
• 1/31/2023 - updated “sf_population” column to reflect the 2020 Census Bureau American Community Survey (ACS) San Francisco Population estimates.
• 1/31/2023 - renamed column “last_updated_at” to “data_as_of”.
• 1/22/2022 - system updates to improve timeliness and accuracy of cases and deaths data were implemented.
• 7/15/2022 - reinfections added to cases dataset. See section SUMMARY for more information on how reinfections are identified.
• 7/15/2022 - references to “fully vaccinated” replaced with “completed primary series” in column “vaccination_status".
• 7/15/2022 - rows with “partially vaccinated” in column “vaccination_status” removed from dataset.

On 6/28/2023, data on cases by vaccination status will be archived and will no longer update. A. SUMMARY This dataset represents San Francisco COVID-19 positive confirmed cases by vaccination status over time, starting January 1, 2021. Cases are included on the date the positive test was collected (the specimen collection date). Cases are counted in three categories: (1) all cases; (2) unvaccinated cases; and (3) completed primary series cases. All cases: Includes cases among all San Francisco residents regardless of vaccination status. Unvaccinated cases: Cases are considered unvaccinated if their positive COVID-19 test was before receiving any vaccine. Cases that are not matched to a COVID-19 vaccination record are considered unvaccinated. Completed primary series cases: Cases are considered completed primary series if their positive COVID-19 test was 14 days or more after they received their 2nd dose in a 2-dose COVID-19 series or the single dose of a 1-dose vaccine. These are also called “breakthrough cases.” On September 12, 2021, a new case definition of COVID-19 was introduced that includes criteria for enumerating new infections after previous probable or confirmed infections (also known as reinfections). A reinfection is defined as a confirmed positive PCR lab test more than 90 days after a positive PCR or antigen test. The first reinfection case was identified on December 7, 2021. Data is lagged by eight days, meaning the most recent specimen collection date included is eight days prior to today. All data updates daily as more information becomes available. B. HOW THE DATASET IS CREATED Case information is based on confirmed positive laboratory tests reported to the City. The City then completes quality assurance and other data verification processes. Vaccination data comes from the California Immunization Registry (CAIR2). The California Department of Public Health runs CAIR2. Individual-level case and vaccination data are matched to identify cases by vaccination status in this dataset. Case records are matched to vaccine records using first name, last name, date of birth, phone number, and email address. We include vaccination records from all nine Bay Area counties in order to improve matching rates. This allows us to identify breakthrough cases among people who moved to the City from other Bay Area counties after completing their vaccine series. Only cases among San Francisco residents are included. C. UPDATE PROCESS Updates automatically at 08:00 AM Pacific Time each day. D. HOW TO USE THIS DATASET Total San Francisco population estimates can be found in a view based on the San Francisco Population and Demographic Census dataset. These population estimates are from the 2016-2020 5-year American Community Survey (ACS). To identify total San Francisco population estimates, filter the view on “demographic_category_label” = “all ages”. Population estimates by vaccination status are derived from our publicly reported vaccination counts, which can be found at COVID-19 Vaccinations Given to SF Residents Over Time. The dataset includes new cases, 7-day average new cases, new case rates, 7-day average new case rates, percent of total cases, and 7-day average percent of total cases for each vaccination category. New cases are the count of cases where the positive tests were collected on that specific specimen collection date. The 7-day rolling average shows the trend in new cases. The rolling average is calculated by averaging the new cases for a particular day with the prior 6 days. New case rates are the count of new cases per 100,000 residents in each vaccination status group. The 7-day rolling average shows the trend in case rates. The rolling average is calculated by averaging the case rate for a part

*** The County of Santa Clara Public Health Department discontinued updates to the COVID-19 data tables effective June 30, 2025. The COVID-19 data tables will be removed from the Open Data Portal on December 30, 2025. For current information on COVID-19 in Santa Clara County, please visit the Respiratory Virus Dashboard [sccphd.org/respiratoryvirusdata]. For any questions, please contact phinternet@phd.sccgov.org ***

Percentage of county residents who are boosted with COVID-19 vaccines by census tract of residence. Source: California Immunization Registry. Note: Doses administered are categorized as a booster dose if the dose is a third dose administered six or more months after a second dose of Pfizer or Moderna or if the dose is a second dose administered two or more months after a dose of Janssen/Johnson & Johnson. Percent of residents who are boosted with COVID-19 vaccines and population age 12 years and older is based in part on estimates of the number of people residing in the census tract from a population-based survey sample, which is subject to error. As a result, percent vaccinated may be over- or under-estimated. For this reason, the displayed percent of residents vaccinated in a census tract is capped at 95%.

COVID-19 vaccination among county residents by census tract is updated every Tuesday. This table was updated for the last time on January 24, 2023.

This dataset contains immunization status of kindergarten students in California in schools. Explanation of the different immunizations is in the attached data dictionary. The California Health and Safety Code Section 120325-75 requires students to provide proof of immunization for school and child care entry. Additionally, California Health and Safety Code Section 120375 and California Code of Regulation Section 6075 require all schools and child care facilities to assess and report annually the immunization status of their enrollees.

The annual kindergarten assessment is conducted each fall to monitor compliance with the California School Immunization law. Results from this assessment are used to measure immunization coverage among students entering kindergarten. Not all schools reported. This data set presents results from the kindergarten assessment and immunization coverage in kindergarten schools by county. To review individual school coverage and exemption rates in a separate lookup format, go to the School Lookup page at the Immunization Branch's Shots for School website: http://www.shotsforschool.org/lookup/

To see the PDF reports by year go to:https://www.shotsforschool.org/k-12/reporting-data/

See the attached file 'Notes on Methods' for data suppression in the '2016-17 ' data and after.

For earlier years of data: https://www.shotsforschool.org/k-12/reporting-data/

Created for the 2023-2025 State of Black Los Angeles County (SBLA) interactive report. To learn more about this effort, please visit the report home page at https://ceo.lacounty.gov/ardi/sbla/. For more information about the purpose of this data, please contact CEO-ARDI. For more information about the configuration of this data, please contact ISD-Enterprise GIS. table_name indicator_name Universe source timeframe source_url

life_expectancy_countyhealthrankings_2020 Life Expectancy Total Population County Health Rankings 2018-2020 https://www.countyhealthrankings.org/app/california/2022/measure/outcomes/147/data

obese_est_adult_lachs_2018 Obese Estimate (#) Adults (Ages 18 Years and Older) LAC Health Survey 2018 www.publichealth.lacounty.gov/ha/LACHSDataTopics2018.htm

obese_perc_adult_lachs_2018 Obese Percent (%) Adults (Ages 18 Years and Older) LAC Health Survey 2018www.publichealth.lacounty.gov/ha/LACHSDataTopics2018.htm

overweight_est_adult_lachs_2018 Overweight Estimate (#) Adults (Ages 18 Years and Older) LAC Health Survey 2018 www.publichealth.lacounty.gov/ha/LACHSDataTopics2018.htm

overweight_perc_adult_lachs_2018 Overweight Percent (%) Adults (Ages 18 Years and Older) LAC Health Survey 2018 www.publichealth.lacounty.gov/ha/LACHSDataTopics2018.htm

diabetes_est_adult_lachs_2018 Ever Diagnosed with Diabetes Estimate (#) Adults (Ages 18 Years and Older) LAC Health Survey 2018 www.publichealth.lacounty.gov/ha/LACHSDataTopics2018.htm

diabetes_perc_adult_lachs_2018 Ever Diagnosed with Diabetes Percent (%) Adults (Ages 18 Years and Older) LAC Health Survey 2018 www.publichealth.lacounty.gov/ha/LACHSDataTopics2018.htm

regular_source_of_care_est_adult_lachs_2018 Reported Having a Regular Source of Health Care Estimate (#) Adults (Ages 18 Years and Older) LAC Health Survey 2018www.publichealth.lacounty.gov/ha/LACHSDataTopics2018.htm

regular_source_of_care_perc_adult_lachs_2018 Reported Having a Regular Source of Health Care Percent (%) Adults (Ages 18 Years and Older) LAC Health Survey 2018 www.publichealth.lacounty.gov/ha/LACHSDataTopics2018.htm

depression_est_adult_lachs_2018 Ever Diagnosed with Depression Estimate (#) Adults (Ages 18 Years and Older) LAC Health Survey 2018www.publichealth.lacounty.gov/ha/LACHSDataTopics2018.htm

depression_perc_adult_lachs_2018 Ever Diagnosed with Depression Percent (%) Adults (Ages 18 Years and Older) LAC Health Survey 2018www.publichealth.lacounty.gov/ha/LACHSDataTopics2018.htm

perceived_safe_est_adult_lachs_2018 Perceived Their Neighborhood to Be Safe from Crime Estimate (#) Adults (Ages 18 Years and Older) LAC Health Survey 2018 www.publichealth.lacounty.gov/ha/LACHSDataTopics2018.htm

perceived_safe_perc_adult_lachs_2018 Perceived Their Neighborhood to Be Safe from Crime Estimate (%) Adults (Ages 18 Years and Older) LAC Health Survey 2018 www.publichealth.lacounty.gov/ha/LACHSDataTopics2018.htm

dental_care_est_child_lachs_2018 Had Dental Care within the past Year Estimate (#) Children (Ages 17 Years and Younger) LAC Health Survey 2018www.publichealth.lacounty.gov/ha/LACHSDataTopics2018.htm

dental_care_perc_child_lachs_2018 Had Dental Care within the past Year Percent (%) Children (Ages 17 Years and Younger) LAC Health Survey 2018www.publichealth.lacounty.gov/ha/LACHSDataTopics2018.htm

no_usual_source_est_chis_2020 No usual source of care Estimate (#) Total Population California Health Interview Survey 2020 https://ask.chis.ucla.edu/AskCHIS/tools/_layouts/AskChisTool/home.aspx

no_usual_source_perc_chis_2020 No usual source of care Percent (%) Total Population California Health Interview Survey 2020 https://ask.chis.ucla.edu/AskCHIS/tools/_layouts/AskChisTool/home.aspx

delayed_care_est_chis_2020 Delayed or didn't get medical care last year Estimate (#) Total Population California Health Interview Survey 2020 https://ask.chis.ucla.edu/AskCHIS/tools/_layouts/AskChisTool/home.aspx

delayed_care_est_chis_2020 Delayed or didn't get medical care last year Percent (%) Total Population California Health Interview Survey 2020 https://ask.chis.ucla.edu/AskCHIS/tools/_layouts/AskChisTool/home.aspx

covid_vax_one_or_more_est_2022 COVID-19 Vaccination 1+ Dose Estimate (#) Population 6 months and older LAC DPH Sep-22 publichealth.lacounty.gov/media/coronavirus/vaccine/vaccine-dashboard.htm

covid_vax_one_or_more_perc_2022 COVID-19 Vaccination 1+ Dose Percent (%) Population 6 months and older LAC DPH Sep-22 publichealth.lacounty.gov/media/coronavirus/vaccine/vaccine-dashboard.htm

covid_vax_full_est_2022 COVID-19 Fully Vaccinated Estimate (#) Population 6 months and older LAC DPH Sep-22publichealth.lacounty.gov/media/coronavirus/vaccine/vaccine-dashboard.htm

covid_vax_full_perc_2022 COVID-19 Fully Vaccinated Percent (%) Population 6 months and older LAC DPH Sep-22 publichealth.lacounty.gov/media/coronavirus/vaccine/vaccine-dashboard.htm

covid_vax_one_or_more_children_est_2022 COVID-19 Vaccination 1+ Dose - Children under 5 Estimate (#) Population older than 6 months and under 5 years LAC DPH Sep-22 publichealth.lacounty.gov/media/coronavirus/vaccine/vaccine-dashboard.htm

covid_vax_one_or_more_children_perc_2022 COVID-19 Vaccination 1+ Dose Children under 5 Percent (%) Population older than 6 months and under 5 years LAC DPH Sep-22 publichealth.lacounty.gov/media/coronavirus/vaccine/vaccine-dashboard.htm

covid_vax_one_or_more_youth_est_2022 COVID-19 Vaccination 1+ Dose - Youth 5-17 Estimate (#) Population 5-17 years LAC DPH Sep-22publichealth.lacounty.gov/media/coronavirus/vaccine/vaccine-dashboard.htm

covid_vax_one_or_more_youth_perc_2022 COVID-19 Vaccination 1+ Dose Youth 5-17 Percent (%) Population 5-17 years LAC DPH Sep-22 publichealth.lacounty.gov/media/coronavirus/vaccine/vaccine-dashboard.htm

covid_vax_one_or_more_adults_est_2022 COVID-19 Vaccination 1+ Dose - Adults Estimate (#) Population 18 and older LAC DPH Sep-22 publichealth.lacounty.gov/media/coronavirus/vaccine/vaccine-dashboard.htm

covid_vax_one_or_more_adults_perc_2022 COVID-19 Vaccination 1+ Dose Adults Percent (%) Population 18 and older LAC DPH Sep-22 publichealth.lacounty.gov/media/coronavirus/vaccine/vaccine-dashboard.htm

insured_pop_est_acs_2020 Insured population # Civilian noninstitutionalized population 2016-2020 ACS - S2701 https://data.census.gov/cedsci/table?g=0500000US06037&tid=ACSST5Y2020.S2701

insured_pop_perc_acs_2020 Insured population % Civilian noninstitutionalized population 2016-2020 ACS - S2701 https://data.census.gov/cedsci/table?g=0500000US06037&tid=ACSST5Y2020.S2701

mch_indicators_2019 Babies Born with Positive MCH Indicators Babies born in time frame Strong Start Index 2016-2019 https://infogram.com/1pj576jwy166z1s6ywvk32l5lkammrym3wy?live

current_asthma Percent of Adults (Ages 18 Years and Older) with Current Asthma Adults Los Angeles County Health Survey 2018 https://www.publichealth.lacounty.gov/ha/HA_DATA_TRENDS.htm

no_med_insurance Percent of Insured Adults (Ages 18 Years and Older) Who Reported a Time Without Medical Insurance in the past 12 Months. Adults Los Angeles County Health Survey 2011 https://www.publichealth.lacounty.gov/ha/HA_DATA_TRENDS.htm

transportation_problems Percent of Adults (Ages 18 Years and Older) Who Reported That Transportation Problems Kept Them from Obtaining Needed Medical Care in the past Year. Adults Los Angeles County Health Survey 2007 https://www.publichealth.lacounty.gov/ha/HA_DATA_TRENDS.htm

As of March 10, 2023, there have been 1.1 million deaths related to COVID-19 in the United States. There have been 101,159 deaths in the state of California, more than any other state in the country – California is also the state with the highest number of COVID-19 cases.

The vaccine rollout in the U.S. Since the start of the pandemic, the world has eagerly awaited the arrival of a safe and effective COVID-19 vaccine. In the United States, the immunization campaign started in mid-December 2020 following the approval of a vaccine jointly developed by Pfizer and BioNTech. As of March 22, 2023, the number of COVID-19 vaccine doses administered in the U.S. had reached roughly 673 million. The states with the highest number of vaccines administered are California, Texas, and New York.

Vaccines achieved due to work of research groups Chinese authorities initially shared the genetic sequence to the novel coronavirus in January 2020, allowing research groups to start studying how it invades human cells. The surface of the virus is covered with spike proteins, which enable it to bind to human cells. Once attached, the virus can enter the cells and start to make people ill. These spikes were of particular interest to vaccine manufacturers because they hold the key to preventing viral entry.

The Child Health and Disability Prevention (CHDP) annual report for state fiscal years (SFY) 2008-14 provides an aggregate level data drawn from the Confidential Screening/Billing Report (PM-160) form used for fee-for-service (FFS) reimbursement of services, and/or for reporting preventive health assessment services. The display of the data in this report is intended to provide a detailed view of the health assessments provided to CHDP eligible children and youth as reported to the California Department of Health Care Services (DHCS) during SFY 2008-14. CHDP eligible children and youth are those whose gross family incomes are at or below 200 percent of the federal poverty level, age restriction for full-scope Medi-Cal of less than 21 years of age, presumptive eligibility (the Gateway process), or children and youth with no health insurance for health assessments who must be less than 19 years of age. CHDP children and youth receive immunizations against specific infectious diseases according to the age-based CHDP Periodicity Schedule or when assessments and screenings are considered medically necessary.

The project is a collaborative effort of investigators from the University of California, Berkeley’s Innovative Genomics Institute (IGI) and School of Public Health (SPH); Kaiser Permanente Northern California (KPNC); and the California Department of Public Health (CDPH), with administrative and programmatic support provided by Heluna Health. Over the project period, the collaborating investigators will analyze approximately 35,000 genomes of SARS-CoV-2 specimens obtained from KPNC members and sequenced by the CDPH through its COVIDNet activities. By combining results from the genomic analysis of low-frequency alleles with clinical and epidemiologic data available in patient records, including demographic variables, COVID-19 vaccination status (dates of vaccination; number of doses; manufacturer), COVID-19 disease severity, and underlying medical conditions, we assessed which shared genomic variations are associated with a greater risk of symptomatic infection and severe clinical outcomes; COVID-19 vaccine effectiveness; and transmission of SARS-CoV-2 in the household. The project and its results can serve as a model for community-based monitoring of the evolution and spread of SARS-CoV-2 and use of the data to inform decisions about the formulation and use of COVID-19 vaccines, including booster doses and next-generation vaccines. Methods Sample collection Our samples are from Kaiser Northern California patients testing positive for SARS-CoV-2 starting June 1, 2021, and through the present. The RNA is sent to the California Department of Public Health (CDPH) lab to be sequenced by COVIDNet–a consortium of primarily UC system labs helping CDPH with the overflow and backlog of samples. Once the genomes have been sequenced, the lineage information and unique deidentified PAUI number are returned to Kaiser where this information is recorded. Metadata from this list of PAUI’s is sent weekly to UC Berkeley. The KPNC sequencing data is returned to us through a third party that is processing all CDPH genomes and stored on a server at UC Berkeley and matched with metadata using PAUI’s. Sequence analysis The raw sequencing data is processed through a SARS-CoV-2 analysis pipeline that has been modified for this work as follows. Adapter removal and trimming are performed using bbduk. The reads are then aligned to the Wuhan reference genome using minimap2 followed by primer trimming using iVAR . We next create a pileup file using samtools and use that input to create a consensus file. This consensus file is created with iVAR using a minimum depth of 10 reads and majority rule for base calling. We next use iVAR to call variants from the pileup file where we set the threshold for calling a mutation to be 0.01. This will call mutations for any loci where at least one percent of the reads are non-reference. This very low threshold allows us to capture all variation that is seen in the sequencing data. The list of variants is then annotated with the gene and amino acid change (if there is one), and whether the mutation is considered defining in any SARS-CoV-2 variants and whether that mutation is seen in only one variant. This dataset includes the fasta consensus sequences and mutation calls for each genome.

As of January 23, 2021, Vermont had the highest Rt value of any U.S. state. The Rt value indicates the average number of people that one person with COVID-19 is expected to infect. A number higher than one means each infected person is passing the virus to more than one other person.

Which are the hardest-hit states? The U.S. reported its first confirmed coronavirus case toward the end of January 2020. More than 28 million positive cases have since been recorded as of February 24, 2021 – California and Texas are the states with the highest number of coronavirus cases in the United States. When figures are adjusted to reflect each state’s population, North Dakota has the highest rate of coronavirus cases. The vaccine rollout has provided Americans with a significant morale boost, and California is the state with the highest number of COVID-19 vaccine doses administered.

How have other nations responded? Countries around the world have responded to the pandemic in varied ways. The United Kingdom has approved three vaccines for emergency use and ranks among the countries with the highest number of COVID-19 vaccine doses administered worldwide. In the Asia-Pacific region, the outbreak has been brought under control in New Zealand, and the country’s response to the pandemic has been widely praised.

CD1 mice were immunized twice with different doses of the candidate vaccine, and HI titers were determined 21 days after the first (d21) and 21 days after the booster immunization (d42) to calculate the percentage of seroconversion (%SC), geometric mean titers (GMT), and effective dose 50 (ED50) based on an HI titer of ≥40.

This dataset represents preliminary estimates of cumulative U.S. COVID-19 disease burden for the 2024-2025 period, including illnesses, outpatient visits, hospitalizations, and deaths. The weekly COVID-19-associated burden estimates are preliminary and based on continuously collected surveillance data from patients hospitalized with laboratory-confirmed severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infections. The data come from the Coronavirus Disease 2019 (COVID-19)-Associated Hospitalization Surveillance Network (COVID-NET), a surveillance platform that captures data from hospitals that serve about 10% of the U.S. population. Each week CDC estimates a range (i.e., lower estimate and an upper estimate) of COVID-19 -associated burden that have occurred since October 1, 2024.

Note: Data are preliminary and subject to change as more data become available. Rates for recent COVID-19-associated hospital admissions are subject to reporting delays; as new data are received each week, previous rates are updated accordingly.

References

1. Reed C, Chaves SS, Daily Kirley P, et al. Estimating influenza disease burden from population-based surveillance data in the United States. PLoS One. 2015;10(3):e0118369. https://doi.org/10.1371/journal.pone.0118369 
2. Rolfes, MA, Foppa, IM, Garg, S, et al. Annual estimates of the burden of seasonal influenza in the United States: A tool for strengthening influenza surveillance and preparedness. Influenza Other Respi Viruses. 2018; 12: 132– 137. https://doi.org/10.1111/irv.12486
3. Tokars JI, Rolfes MA, Foppa IM, Reed C. An evaluation and update of methods for estimating the number of influenza cases averted by vaccination in the United States. Vaccine. 2018;36(48):7331-7337. doi:10.1016/j.vaccine.2018.10.026 
4. Collier SA, Deng L, Adam EA, Benedict KM, Beshearse EM, Blackstock AJ, Bruce BB, Derado G, Edens C, Fullerton KE, Gargano JW, Geissler AL, Hall AJ, Havelaar AH, Hill VR, Hoekstra RM, Reddy SC, Scallan E, Stokes EK, Yoder JS, Beach MJ. Estimate of Burden and Direct Healthcare Cost of Infectious Waterborne Disease in the United States. Emerg Infect Dis. 2021 Jan;27(1):140-149. doi: 10.3201/eid2701.190676. PMID: 33350905; PMCID: PMC7774540.
5. Reed C, Kim IK, Singleton JA,  et al. Estimated influenza illnesses and hospitalizations averted by vaccination–United States, 2013-14 influenza season. MMWR Morb Mortal Wkly Rep. 2014 Dec 12;63(49):1151-4. https://www.cdc.gov/mmwr/preview/mmwrhtml/mm6349a2.htm 
6. Reed C, Angulo FJ, Swerdlow DL, et al. Estimates of the Prevalence of Pandemic (H1N1) 2009, United States, April–July 2009. Emerg Infect Dis. 2009;15(12):2004-2007. https://dx.doi.org/10.3201/eid1512.091413  
7. Devine O, Pham H, Gunnels B, et al. Extrapolating Sentinel Surveillance Information to Estimate National COVID-19 Hospital Admission Rates: A Bayesian Modeling Approach. Influenza and Other Respiratory Viruses. https://onlinelibrary.wiley.com/doi/10.1111/irv.70026. Volume18, Issue10. October 2024.
8. https://www.cdc.gov/covid/php/covid-net/index.html">COVID-NET | COVID-19 | CDC 
9. https://www.cdc.gov/covid/hcp/clinical-care/systematic-review-process.html 
10. https://academic.oup.com/pnasnexus/article/1/3/pgac079/6604394?login=false">Excess natural-cause deaths in California by cause and setting: March 2020 through February 2021 | PNAS Nexus | Oxford Academic (oup.com)
11. Kruschke, J. K. 2011. Doing Bayesian data analysis: a tutorial with R and BUGS. Elsevier, Amsterdam, Section 3.3.5.

The Child Health and Disability Prevention (CHDP) annual report for state fiscal years (SFY) specified in the title provides an aggregate level data drawn from the Confidential Screening/Billing Report (PM-160) form used for fee-for-service (FFS) reimbursement of services, and/or for reporting preventive health assessment services. The display of the data in this report is intended to provide a detailed view of the health assessments provided to CHDP eligible children and youth as reported to the California Department of Health Care Services (DHCS) during SFY 2008-12. CHDP eligible children and youth are those whose gross family incomes are at or below 200 percent of the federal poverty level, age restriction for full-scope Medi-Cal of less than 21 years of age, presumptive eligibility (the Gateway process), or children and youth with no health insurance for health assessments who must be less than 19 years of age. CHDP children and youth receive health assessments and screenings according to the age-based CHDP Periodicity Schedule or when assessments and screenings are considered medically necessary. Note: Empty Cells represent values that are not shown to protect confidentiality of the individuals summarized in the data.