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Methodolgy and Data.Rmd
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Methodolgy and Data.Rmd
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---
title: "Methodology and Data"
description: |
Details of data sources and the methodology of analysis <ul class="list-inline title-nav">
<li class="list-inline-item-nav"><div class = "go-to-nav" >Go to: </div></li>
<li class="list-inline-item-nav">
<a href="providers.html"> <button type="button" class="btn btn-outline-light mb-2"> Providers </button>
</a>
</li>
<li class="list-inline-item-nav">
<a href="equity.html"> <button type="button" class="btn btn-outline-light mb-2"> Equity </button>
</a>
</li>
</ul>
output:
distill::distill_article:
toc: true
css: pace_header.css
---
```{r setup, include=FALSE}
knitr::opts_chunk$set(echo = TRUE)
library(kableExtra)
```
## General Notes on Methods
For our analysis we have relied on major public data sources which includes
* **[Texas Department of State Health Services (DSHS)](https://dshs.texas.gov/coronavirus/AdditionalData.aspx):** Texas state and county level data on COVID-19 cases, deaths and provision and administration of vaccine doses.
* **[Center of Disease Control](https://covid.cdc.gov/covid-data-tracker/#datatracker-home):** Covid-19 data of other states for comparison with Texas.
* **[American Community Survey (ACS)](https://covid.cdc.gov/covid-data-tracker/#datatracker-home):** State and County level estimates of population and demographics for year 2019 obtained through tidycensus R package.
Data from these sources has enabled us to construct graphical anaylsis of COVID-19 vaccine roll out and related areas of concern. Per-capita variables at county level are used to compare the progress across different counties which means Per 100,000 people whenever you see it mentioned. We use population and demographic estimates from ACS-2019, which gives us the most recent figures on population. All graphs and analysis has been done in R with the help of different packages.
## Equity
We use DSHS data on COVID-19 cases, deaths and vaccinations, which is published with demographic breakdowns like age, gender and race/ethnicity. A percentage analysis is shown in the first graph at the State level by dividing figures of each race by its own population estimates from ACS data for each category.
For example % of white people administered vaccines is calculated as
$$\scriptsize \frac{No.\space white \space people \space administered \space vaccine \space in \space Texas} {Total \space population \space of \space white \space people \space in \space Texas}$$
Administered doses contain number of people who have been given atleast one dose of vaccine. Similarly in the nexr graph we further split the demographics into gender and age group. We only include male and female gender and exclude unknown gender. A bar chart for each race shows the total number of people administered atleast one vaccine dose for each age group and each gender within that race. Same bar chart for the unknown gender category has also been created for all races that are mentioned in DSHS data.
To see the geographic accessability to vaccine sites, we take data on names and addresses of listed vaccine sites from DSHS. Using these addresses, we obtain the co-ordinates through [Mapbox](https://docs.mapbox.com/api/overview/) api. We take census block as our geographic unit which is the smallest possible population classification and map locations of vaccine sites. We then highlight the geographic areas which are 30 min drive away from each of vaccine sites by using Mapbox api. Using co-ordiantes of polygons that contained the area within 30 min drive of vaccine site, we calculate the number of 16 and above age people living in these areas. Similarly, we calculate the number of people living in areas which do not fall in any of those polygons to show how many Texans are more than 30 min away from vaccine sites.
## Provider
To allow people to check the availability of vaccines in their area, we provide the data obtained from DSHS website on vaccine sites locations and number of doses available at each site. Using this database, which is updated routinely, we provide a search option where people can search using name, street address or zip code for vaccine sites and the number of doses available at each site. Using [leaflet](https://leafletjs.com/) api, we provide an interactive map of the search area with vaccine sites highlighted on the map.
## Pace
We look at the pace of vaccination drive by taking data from DSHS which contains county wise information and is updated on daily basis to provide the following information:
```{r , include=TRUE , echo=FALSE, fig.width=12, layout= "l-body-outset"}
text_table <- data.frame(
Items = c('Total Doses Allocated',
'Vaccine Doses Administered',
'People Vaccinated with at least One Dose',
'People Fully Vaccinated',
'Population, 16+',
'Population, 65+',
'Population, Phase 1A Healthcare Workers',
'Population, Phase 1A Long-term Care Residents',
'Population, Phase 1B Any Medical Condition'),
Details = c("Total number of doses allocated to COVID-19 providers through the current week by provider county (all other measures are summed by recipient's county of residence). Includes doses that will be shipping and arriving at providers this week.",
"The number of vaccine doses administered, number of people vaccinated with one dose and number of people fully vaccinated are aggregated by the recipient’s county of residence. Health care providers have 24 hours after a dose is administered to enter information into ImmTrac2, the Texas Immunization Registry. The data comes from vaccination records submitted by health care providers as of 11:59 the previous night.",
"Number of people vaccinated with one dose is defined as the number of people who have received at least one dose of COVID-19 vaccine.",
"Number of people fully vaccinated is defined as the number of people who have completed the full series (2 doses of Moderna or Pfizer vaccine), as outlined by the CDC's Advisory Committee on Immunization Practices (ACIP).",
"2019 Population Estimates available from the Texas Demographic Center at https://demographics.texas.gov/Data/TPEPP/Estimates/.",
"2019 Population Estimates available from the Texas Demographic Center at https://demographics.texas.gov/Data/TPEPP/Estimates/.",
"Phase 1A healthcare workers estimates include people providing direct care in hospitals, EMS, long-term care facilities, home health and hospice and those providing direct care in Offices of Physicians, Other Healthcare providers like physical therapists and Mental Health Providers, Outpatient Care Centers, Medical and Diagnostic Laboratories, Freestanding ER and Urgent Care, Other Ambulatory Care, Pharmacies, Last responders who provide mortuary or death services, Public health and emergency response staff directly involved in administration of COVID testing and vaccinations, and school nurses. Data on frontline and vulnerable populations in Texas come from the 2018 Annual Survey of Hospitals (total number of employees), DSHS EMS Registry, Texas Pharmacy Board, Texas Education Agency, 2019 Quarterly Census of Employment and Wages (https://texaslmi.com/LMIbyCategory/QCEW), and the HHSC Directory of Long-term Care Providers (https://hhs.texas.gov/doing-business-hhs/provider-portals/long-term-care-providers).",
"Long-term care resident estimates include licensed capacity of Nursing Homes, Assisted Living, Adult Day Care and Activity Centers, and Intermediate Care for People with Intellectual Disabilities.",
"People 16 years of age and older with at least one chronic medical condition that puts them at increased risk for severe illness from the virus that causes COVID-19. The data are model-based estimates from CDC using self-reported data from the Behavioral Risk Factor Surveillance System and U.S. census population data. The methodology for generating these estimates are detailed in this MMWR: https://www.cdc.gov/mmwr/volumes/69/wr/mm6929a1.htm."
)
)
kbl(text_table)%>%
kable_paper(full_width = F)%>%
column_spec(1, bold=T, border_right = T) %>%
column_spec(2, width= "40em")
```
Using this data, we show the progress of vaccination against the available doses and the remaining population in different phases. A national comparison is showed by comparing Texas number of vaccines distribyted per 100,000 people and number of vaccines administered per 100,000 people with other states. The data on other states has been obtained through CDC and it allows us to rank Texas against other states in these two measures.
The distribution trends are shown through bar charts for total doses shipped to different provider types and total doses available at each provider types. The provider type is the classification of vaccine sites by State. Total doses shipped include total number of vaccine doses provided to each provider type uptil now. The available doses number gives us the current stock position of vaccine at each provider type.
The vaccine pace tracker provides a detail view of vaccination drive at the state and county level. Using the data from DSHS, which is provided on state and county level, we are able to construct a bar chart which provides information in percentage form, on a scale of 100, what percentage of population has been given at least one dose and what percentage of population has been fully vaccinated. The actual numbers can be seen by hovering the mouse over the bars. Some of the metrics used in these graphs are given as follow:
```{r , include=TRUE , echo=FALSE, fig.width=9, layout= "l-page"}
metric_table <-data.frame(
Metric = c("% of Population Partially vaccinated", "% of Population fully vaccinated", "Dose distribution", "Daily Average of vaccination", "When 70% of Pop is vaccinated"),
Equation = c("$$ \\frac{No. \\space of \\space people \\space given \\space one \\space dose}{No. \\space of \\space people \\space 16+ \\space age}*100$$","$$ \\frac{No. \\space of \\space people \\space fully \\space vaccinated}{No. \\space of \\space people \\space 16+ \\space age}*100 $$", "$$ \\frac{No. \\space of \\space Doses \\space administered}{No. \\space of \\space doses \\space supplied} $$", "$$ \\frac{Total \\space doses \\space administered}{No. \\space of \\space days \\space since \\space start \\space of \\space vaccination} $$","$$ Today + \\frac{No. \\space of \\space people \\space remaining \\space in \\space the \\space 70\\% \\space of \\space Eligible \\space Population}{Average \\space Daily \\space Vaccination} $$")
)
kbl(metric_table, escape= FALSE)%>%
kable_paper(full_width = F)%>%
column_spec(1, bold=T, border_right = T) %>%
column_spec(2, width= "30em")
```