Pursuant to Local Laws 126, 127, and 128 of 2016, certain demographic data is collected voluntarily and anonymously by persons voluntarily seeking social services. This data can be used by agencies and the public to better understand the demographic makeup of client populations and to better understand and serve residents of all backgrounds and identities. The data presented here has been collected through either electronic form or paper surveys offered at the point of application for services. These surveys are anonymous. Each record represents an anonymized demographic profile of an individual applicant for social services, disaggregated by response option, agency, and program. Response options include information regarding ancestry, race, primary and secondary languages, English proficiency, gender identity, and sexual orientation. Idiosyncrasies or Limitations: Note that while the dataset contains the total number of individuals who have identified their ancestry or languages spoke, because such data is collected anonymously, there may be instances of a single individual completing multiple voluntary surveys. Additionally, the survey being both voluntary and anonymous has advantages as well as disadvantages: it increases the likelihood of full and honest answers, but since it is not connected to the individual case, it does not directly inform delivery of services to the applicant. The paper and online versions of the survey ask the same questions but free-form text is handled differently. Free-form text fields are expected to be entered in English although the form is available in several languages. Surveys are presented in 11 languages. Paper Surveys 1. Are optional 2. Survey taker is expected to specify agency that provides service 2. Survey taker can skip or elect not to answer questions 3. Invalid/unreadable data may be entered for survey date or date may be skipped 4. OCRing of free-form tet fields may fail. 5. Analytical value of free-form text answers is unclear Online Survey 1. Are optional 2. Agency is defaulted based on the URL 3. Some questions must be answered 4. Date of survey is automated

this form described the socio demographic characteristics of the participants

This is replication package for task description granularity experiment conducted in University of Oulu. The package includes the necessary materials for replicating the experiment. In addition, data and analysis scripts for the original experiment are included. Experiment Materials:- Experiment protocol- Programming task descriptions- Project templates for Eclipse IDE - Acceptance test suites- Data extraction and intervention protocols- Template for data extraction- Survey form for demographic information- Survey form for task and performance evaluationData and Analysis Files:- Raw data files in CSV and R data formats- Data analysis scripts for R- Data analysis report

Note: Reporting of new COVID-19 Case Surveillance data will be discontinued July 1, 2024, to align with the process of removing SARS-CoV-2 infections (COVID-19 cases) from the list of nationally notifiable diseases. Although these data will continue to be publicly available, the dataset will no longer be updated.

Authorizations to collect certain public health data expired at the end of the U.S. public health emergency declaration on May 11, 2023. The following jurisdictions discontinued COVID-19 case notifications to CDC: Iowa (11/8/21), Kansas (5/12/23), Kentucky (1/1/24), Louisiana (10/31/23), New Hampshire (5/23/23), and Oklahoma (5/2/23). Please note that these jurisdictions will not routinely send new case data after the dates indicated. As of 7/13/23, case notifications from Oregon will only include pediatric cases resulting in death.

This case surveillance public use dataset has 12 elements for all COVID-19 cases shared with CDC and includes demographics, any exposure history, disease severity indicators and outcomes, presence of any underlying medical conditions and risk behaviors, and no geographic data.

CDC has three COVID-19 case surveillance datasets:

• COVID-19 Case Surveillance Public Use Data with Geography: Public use, patient-level dataset with clinical data (including symptoms), demographics, and county and state of residence. (19 data elements)
• COVID-19 Case Surveillance Public Use Data: Public use, patient-level dataset with clinical and symptom data and demographics, with no geographic data. (12 data elements)
• COVID-19 Case Surveillance Restricted Access Detailed Data: Restricted access, patient-level dataset with clinical and symptom data, demographics, and state and county of residence. Access requires a registration process and a data use agreement. (33 data elements)

• Data elements can be found on the COVID-19 case report form located at www.cdc.gov/coronavirus/2019-ncov/downloads/pui-form.pdf.
• Data are considered provisional by CDC and are subject to change until the data are reconciled and verified with the state and territorial data providers.
• Some data cells are suppressed to protect individual privacy.
• The datasets will include all cases with the earliest date available in each record (date received by CDC or date related to illness/specimen collection) at least 14 days prior to the creation of the current datasets. This 14-day lag allows case reporting to be stabilized and ensures that time-dependent outcome data are accurately captured.
• Datasets are updated monthly.
• Datasets are created using CDC’s Policy on Public Health Research and Nonresearch Data Management and Access and include protections designed to protect individual privacy.
• For more information about data collection and reporting, please see https://www.cdc.gov/coronavirus/2019-ncov/covid-data/about-us-cases-deaths.html.
• For more information about the COVID-19 case surveillance data, please see https://www.cdc.gov/coronavirus/2019-ncov/covid-data/faq-surveillance.html
  

Overview

The COVID-19 case surveillance database includes individual-level data reported to U.S. states and autonomous reporting entities, including New York City and the District of Columbia (D.C.), as well as U.S. territories and affiliates. On April 5, 2020, COVID-19 was added to the Nationally Notifiable Condition List and classified as “immediately notifiable, urgent (within 24 hours)” by a Council of State and Territorial Epidemiologists (CSTE) Interim Position Statement (Interim-20-ID-01). CSTE updated the position statement on August 5, 2020, to clarify the interpretation of antigen detection tests and serologic test results within the case classification (Interim-20-ID-02). The statement also recommended that all states and territories enact laws to make COVID-19 reportable in their jurisdiction, and that jurisdictions conducting surveillance should submit case notifications to CDC. COVID-19 case surveillance data are collected by jurisdictions and reported voluntarily to CDC.

For more information: NNDSS Supports the COVID-19 Response | CDC.

The deidentified data in the “COVID-19 Case Surveillance Public Use Data” include demographic characteristics, any exposure history, disease severity indicators and outcomes, clinical data, laboratory diagnostic test results, and presence of any underlying medical conditions and risk behaviors. All data elements can be found on the COVID-19 case report form located at www.cdc.gov/coronavirus/2019-ncov/downloads/pui-form.pdf.

COVID-19 Case Reports

COVID-19 case reports have been routinely submitted using nationally standardized case reporting forms. On April 5, 2020, CSTE released an Interim Position Statement with national surveillance case definitions for COVID-19 included. Current versions of these case definitions are available here: https://ndc.services.cdc.gov/case-definitions/coronavirus-disease-2019-2021/.

All cases reported on or after were requested to be shared by public health departments to CDC using the standardized case definitions for laboratory-confirmed or probable cases. On May 5, 2020, the standardized case reporting form was revised. Case reporting using this new form is ongoing among U.S. states and territories.

Data are Considered Provisional

• The COVID-19 case surveillance data are dynamic; case reports can be modified at any time by the jurisdictions sharing COVID-19 data with CDC. CDC may update prior cases shared with CDC based on any updated information from jurisdictions. For instance, as new information is gathered about previously reported cases, health departments provide updated data to CDC. As more information and data become available, analyses might find changes in surveillance data and trends during a previously reported time window. Data may also be shared late with CDC due to the volume of COVID-19 cases.
• Annual finalized data: To create the final NNDSS data used in the annual tables, CDC works carefully with the reporting jurisdictions to reconcile the data received during the year until each state or territorial epidemiologist confirms that the data from their area are correct.
• Access Addressing Gaps in Public Health Reporting of Race and Ethnicity for COVID-19, a report from the Council of State and Territorial Epidemiologists, to better understand the challenges in completing race and ethnicity data for COVID-19 and recommendations for improvement.

Data Limitations

To learn more about the limitations in using case surveillance data, visit FAQ: COVID-19 Data and Surveillance.

Data Quality Assurance Procedures

CDC’s Case Surveillance Section routinely performs data quality assurance procedures (i.e., ongoing corrections and logic checks to address data errors). To date, the following data cleaning steps have been implemented:

• Questions that have been left unanswered (blank) on the case report form are reclassified to a Missing value, if applicable to the question. For example, in the question “Was the individual hospitalized?” where the possible answer choices include “Yes,” “No,” or “Unknown,” the blank value is recoded to Missing because the case report form did not include a response to the question.
• Logic checks are performed for date data. If an illogical date has been provided, CDC reviews the data with the reporting jurisdiction. For example, if a symptom onset date in the future is reported to CDC, this value is set to null until the reporting jurisdiction updates the date appropriately.
• Additional data quality processing to recode free text data is ongoing. Data on symptoms, race and ethnicity, and healthcare worker status have been prioritized.

Data Suppression

To prevent release of data that could be used to identify people, data cells are suppressed for low frequency (<5) records and indirect identifiers (e.g., date of first positive specimen). Suppression includes rare combinations of demographic characteristics (sex, age group, race/ethnicity). Suppressed values are re-coded to the NA answer option; records with data suppression are never removed.

For questions, please contact Ask SRRG (eocevent394@cdc.gov).

Additional COVID-19 Data

COVID-19 data are available to the public as summary or aggregate count files, including total counts of cases and deaths by state and by county. These

Abstract

The main objective of the HEIS survey is to obtain detailed data on household expenditure and income, linked to various demographic and socio-economic variables, to enable computation of poverty indices and determine the characteristics of the poor and prepare poverty maps. Therefore, to achieve these goals, the sample had to be representative on the sub-district level. The raw survey data provided by the Statistical Office was cleaned and harmonized by the Economic Research Forum, in the context of a major research project to develop and expand knowledge on equity and inequality in the Arab region. The main focus of the project is to measure the magnitude and direction of change in inequality and to understand the complex contributing social, political and economic forces influencing its levels. However, the measurement and analysis of the magnitude and direction of change in this inequality cannot be consistently carried out without harmonized and comparable micro-level data on income and expenditures. Therefore, one important component of this research project is securing and harmonizing household surveys from as many countries in the region as possible, adhering to international statistics on household living standards distribution. Once the dataset has been compiled, the Economic Research Forum makes it available, subject to confidentiality agreements, to all researchers and institutions concerned with data collection and issues of inequality.

Data collected through the survey helped in achieving the following objectives: 1. Provide data weights that reflect the relative importance of consumer expenditure items used in the preparation of the consumer price index 2. Study the consumer expenditure pattern prevailing in the society and the impact of demograohic and socio-economic variables on those patterns 3. Calculate the average annual income of the household and the individual, and assess the relationship between income and different economic and social factors, such as profession and educational level of the head of the household and other indicators 4. Study the distribution of individuals and households by income and expenditure categories and analyze the factors associated with it 5. Provide the necessary data for the national accounts related to overall consumption and income of the household sector 6. Provide the necessary income data to serve in calculating poverty indices and identifying the poor chracteristics as well as drawing poverty maps 7. Provide the data necessary for the formulation, follow-up and evaluation of economic and social development programs, including those addressed to eradicate poverty

Geographic coverage

National

Analysis unit

• Household/families
• Individuals

Universe

The survey covered a national sample of households and all individuals permanently residing in surveyed households.

Kind of data

Sample survey data [ssd]

Sampling procedure

The 2008 Household Expenditure and Income Survey sample was designed using two-stage cluster stratified sampling method. In the first stage, the primary sampling units (PSUs), the blocks, were drawn using probability proportionate to the size, through considering the number of households in each block to be the block size. The second stage included drawing the household sample (8 households from each PSU) using the systematic sampling method. Fourth substitute households from each PSU were drawn, using the systematic sampling method, to be used on the first visit to the block in case that any of the main sample households was not visited for any reason.

To estimate the sample size, the coefficient of variation and design effect in each subdistrict were calculated for the expenditure variable from data of the 2006 Household Expenditure and Income Survey. This results was used to estimate the sample size at sub-district level, provided that the coefficient of variation of the expenditure variable at the sub-district level did not exceed 10%, with a minimum number of clusters that should not be less than 6 at the district level, that is to ensure good clusters representation in the administrative areas to enable drawing poverty pockets.

It is worth mentioning that the expected non-response in addition to areas where poor families are concentrated in the major cities were taken into consideration in designing the sample. Therefore, a larger sample size was taken from these areas compared to other ones, in order to help in reaching the poverty pockets and covering them.

Mode of data collection

Face-to-face [f2f]

Research instrument

List of survey questionnaires: (1) General Form (2) Expenditure on food commodities Form (3) Expenditure on non-food commodities Form

Cleaning operations

Raw Data The design and implementation of this survey procedures were: 1. Sample design and selection 2. Design of forms/questionnaires, guidelines to assist in filling out the questionnaires, and preparing instruction manuals 3. Design the tables template to be used for the dissemination of the survey results 4. Preparation of the fieldwork phase including printing forms/questionnaires, instruction manuals, data collection instructions, data checking instructions and codebooks 5. Selection and training of survey staff to collect data and run required data checkings 6. Preparation and implementation of the pretest phase for the survey designed to test and develop forms/questionnaires, instructions and software programs required for data processing and production of survey results 7. Data collection 8. Data checking and coding 9. Data entry 10. Data cleaning using data validation programs 11. Data accuracy and consistency checks 12. Data tabulation and preliminary results 13. Preparation of the final report and dissemination of final results

Harmonized Data - The Statistical Package for Social Science (SPSS) was used to clean and harmonize the datasets - The harmonization process started with cleaning all raw data files received from the Statistical Office - Cleaned data files were then all merged to produce one data file on the individual level containing all variables subject to harmonization - A country-specific program was generated for each dataset to generate/compute/recode/rename/format/label harmonized variables - A post-harmonization cleaning process was run on the data - Harmonized data was saved on the household as well as the individual level, in SPSS and converted to STATA format

Abstract

The 2010 Saint Lucia Population and Housing Census is conducted by the Central Statistical Office staff. The island-nation of Saint Lucia recorded an overall household population increase of 5 percent from May 2001 to May 2010 based on estimates derived from a complete enumeration of the population of Saint Lucia during the conduct of the recently completed 2010 Population and Housing Census. Saint Lucia's total resident population as at midnight on Census Day, the 10th May 2010 stood at 166,526 persons. Saint Lucia's total population including non-resident persons was estimated to be 173,720, the total number of non-resident persons was 7,194. The preliminary count of Saint Lucia's enumerated population was 151,864 persons reflecting a response rate to the census of 92%. The total resident population of St. Lucia is comprised of 82,926 males and 83,600 females. Out of this sum, there were 165,595 individuals residing in private households, 931 persons living in institutions.

A modern population and housing census is the process of collecting, compiling, analyzing, and publishing demographic, socio-economic, and environmental data pertaining to all persons in a country and the national housing stock at a specified time. A census is a form of national stocktaking. Since the census is a complete count of the population and living quarters, it provides detailed benchmark data on the size of the population, age structure, educational attainment, economic activity, disability, housing, and household amenities as well as other major socio-economic characteristics.

Geographic coverage

National Coverage includes all Administrative Districts and Political Constituencies

Analysis unit

• Households,
• Individuals.

Universe

The Census covered all de jure household members (usual residents of St Lucia based on the six month criteria). The fertility of all women aged 15-49 years resident in the household, and all children aged 0-4 years (under age 5) resident in the household. The Census also collected data on dwelling and housing conditions of all resident householders. In the Census Visitation record all de jure household members were counted by sex, in addition, persons present in St Lucia at the time of the census who were not usual residents were also counted to produce the de facto population of St Lucia on census day May 10, 2010.

Kind of data

Census/enumeration data [cen]

Mode of data collection

Face-to-face [f2f]

Research instrument

The questionnaires were bound together into booklets. Each booklet contained a cover page (for identification and the Record of Visits), page 2 for Listing the names of the members of the Household and for any comments needed concerning any member of the household or any part of the enumeration. NATIONAL ARCHIVES, INTERNATIONAL MIGRATION and HOUSING spread over pages 3 to 5.

After these sections, three individual questionnaires (6 pages each) complete the booklet. These booklets provide for three (3) persons and are to be used for households consisting of three (3) or fewer persons. If the household comprises more than three persons, the main booklet plus the number of additional person questionnaires were required. For example,

For a 1, 2, 3-person household, use one booklet;

For a 4-person household, use one booklet plus one additional person questionnaire.

For a 5-person household, use one booklet plus two additional person questionnaires and so on.

The ED Number and the Household number contained on the front cover page of the main questionnaire was transferred to the top of the front page of EVERY person questionnaire whether or not it was an individual questionnaire within the main booklet or whether it was an individual questionnaire applicable to a household with more than three persons.

STRUCTURE OF THE INDIVIDUAL QUESTIONNAIRE

The individual questionnaire starts at Section 3. The questions are divided into eleven groups, each having a central theme and given a section number as follows:

Section 3: Personal Characteristics (for all persons) Section 4: Birthplace & Residence (for all persons) Section 5: Disability (for all persons) Section 6: Health (for all persons) Section 7: Education and Internet Access (for all persons) Section 8: Professional, Technical & Vocational Training (for persons 15 years and over) Section 9: Economic Activity (for persons 15 years and over) Section 10: Income and Livelihood (for females 15 years and over) Section 11: Marital Status and Union Status (for persons 15 years and over) Section 12: Fertility (for persons 15 years and over) Section 13: Where Spent Census Night (for all persons)

Cleaning operations

Data editing took place at a number of stages throughout the processing, including (See External Resource for more information on this item):

a) Field Editing by interviewers and field supervisors The guidelines for the conduct of these edits were laid out in PART IX: Checking Your Questionnaires for Errors in the Enumerators Manual. These instructions are repeated in the supervisors manual and also stated in the contract for payment of enumerators and supervisors. A number of elements of the edits outlined formed the basis for the payment of enumerators and supervisors.

b) Office editing and questionnaire re-numbering When a full set of questionnaires from a completed ED was recieved by the office, persons assigned as census evaluators had the responsibility to review the content of each Questionnaire to check for completeness. They were required to perform checks on the questionnaires and the visitation records for the key geographic variables and perform other checks in line with the requirements of a Census Evaluation form which laid out quality standards for the approval of a completed ED for payment. The Census evaluation form is provided as an external resource for information.

c) Data Capture, Editing and Coding during scanning and data verification The data was captured using TELEform V10.4.1 and the data from the forms was exported to a SQL Server 2005 database as was all other census related information captured on forms, such as the census 2010 Evaluation form, referred to previously, the census visitation record etc.

The names of the SQL Server Databases are as follows: 1) Census2010 containing Tables: Census2010Persons, Census2010House, Census2010Visit, Census2010Evaluation, Census2010ApplicationForms, CensusTestScores, Census2010Institutions 2) Census2010_Validated contained data which was validated on several metrics outline in a VBA program built into the TELEform v10.4 software used to capture the data after scanning.

The correction of geographic variables was completed during this process. The scanner operator would manually enter the ED code for the batch being scanned, he would also enter the first and last household for the batch manually. Later the verifier would independantly verify the ED and the household number entered by the enumerator against the values entered by the scanner operator to ensure that they were either the same as in the case of the ED number or within the range of households expected in the batch as in the case of the household number. This was done using VBA validation code written within the TELEform 10.4.1 software used for the scanning and capture of the data from the Census.

Computer Assisted Coding was built into the TELEform template, this method assisted the enumerator using keywords to identify the code for the entry of the appropriate settlement, industry or occupation code. A listing of the codes used is attached to this document as an external resource. Occupation codes are in the international format of ISCO-08 while the industry code applied is based on ISIC Rev4.

d) Structure checking and completeness in Foxpro

The data was exported to MS Access and then on to MS Foxpro where some basic editing was done.

1) This involved the conversion of descriptions of settlement, ISCO and ISIC data collected in fields to codes 2) Standardizing the lenghts and format of all fields in the dataset in preparation for conversion to CSPRO ASCII data format 3) Transposing data on Migration, deaths, disability and births in the last 12 months to variables in the household and person files 4) Removal of blank and very incomplete records 5) Removal of all duplicates and the cleaning of all inconsistent records between the household and the person file. 6) Creation of CSPRO 4.0 compatible format data file for use in further editing and cleaning

e) Detailed variable level editing using CSPRO 4.0 and hotdecking Detailed programs were developed to clean census data on critical variables in the housing section of the questionnaire such as Type of Dwelling, household assets etc, demographic variables such as age, sex, education and economic activiity variables were cleaned in the first version of the CSPRO 4.0 *.bch program file developed. After the first version of the cleaning program was complete the Statistical Office published the Preliminary Census 2010 Report (Updated April 2010). The first version of this publication released in January contained only data on population counts from the census visitation records. The updated April 2010 Preliminary Census report contained information on all the main variables cleaned in the first version of the cleaning program. The CSPRO 4.0 program employed the use of many 3-dimensional hotdecking programs to correct for items not stated or recorded.

f) Checking of data files using the Tabulation Features of CSPRO 4.0 and SPSS 19 Crosstabulations of variables were used to identify inconsistent data and improve CSPRO 4.0 editing programs

Detailed documentation of