COVID State-tistics
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A DATA-DRIVEN NARRATIVE oN
policy, mobility, and mortality
of coronavirus in the U.S.
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R Shiny Dashboard
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Written by UCLA statistics students at the height of the pandemic season in Spring 2020.
Last updated June 3rd, 2020. Data and information provided may not be up to date.
Our QUESTION
We want to investigate the effects of legally
easing restrictions on certain states in the US.
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How does a state’s policy regarding coronavirus affect citizen mobility?
u.s. timeline
January 20
First confirmed case on American soil (Washington).
March 13
US declares national emergency.
March 21- April 7
States begin enforcing
stay-at-home orders.
March 26
US records highest reported cases globally.
April 6
Coronavirus becomes leading cause of death in the US.
April 28
US hits past 1 million positive cases.
May 27
The number of COVID-19
deaths tops 100,000.
50 States dashboard
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INTERPRETATION
The boxes at the top shows the values associated with the later date in the date range. For example as of May 5th, Alabama had 15,396 total tests in which 666 cases were from that day.
The three graphs at the bottom of the dashboard will adjust depending on the state and date range.
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DAILY TESTS:
Across all the states, the blue lines represent the number of people that tested for the virus for every day up to date. The black line follows the rate at which the numbers are moving, or the average number of tests administered over a five day period.
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DAILY CASES:
Across all the states, the yellow lines represent the number of people that tested positive for the virus for every day up to date. The black line follows the rate at which the numbers are moving, or the average number of positive test cases discovered in a five day interval.
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DAILY DEATHS:
Across all the states, the red lines represent the number of people that have died from the virus every day up to date. The black line follows the rate at which the numbers are moving, or the average number of deaths measured over a five day period.
MapPING THE VIRUS
Having a per 100k metric is a way to standardize the values for daily testing, confirmed cases, and confirmed deaths per state.
At the beginning of Q3 2020, New York has the 2nd highest average daily testing per citizen. This is not surprising due to the fact that it was the hardest hit state at the beginning of March. The policies and infrastructure set in place are set in place such that everyday, there are around 60 thousand New Yorkers getting tested
reopening policies
Note: The states that only have a reopening stage (e.g. Wyoming,Nebraska,Iowa, Arkansas) never officially enacted a stay home order with full restrictions. These state reopen areas that were either closed privately or county-wide.
During the latter half of March, a majority of states began implementing stay-at-home orders in attempts to flatten the curve. California, New York, and Washington were among the earliest to enforce these policies. However, states like Arkansas, Iowa, Nebraska, Utah, and Wyoming chose to forgo these measures. Some states, such as Texas, Nevada, and Missouri, implemented orders later, during the first week of April.
After identifying the states as a blue or red state based on the results of the 2016 presidential election, we noticed that Democratic states typically had later reopening dates in early to mid-May while most Republican states had reopening dates in the latter half of April.
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Currently, all states are in the process of transitioning to their second phase. For example, Texas is in its second phase of its Open Texas Plan, reopening bars, recreational establishments, childcare programs, and in-person summer schooling while increasing restaurant capacities to 50%. Several counties in Washington, where the first confirmed US case occurred, are also in the second phase of its Safe Start Washington plan. Several counties in California are in the second phase of its Resilience Roadmap plan and are reopening retail, childcare, and places of worship at limited capacity.
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While states have taken certain precautions to reduce the spread of the virus in the midst of reopening, it may have been too early for some to take this step. States reopening earlier increases the likelihood of a second wave of the pandemic occurring in the future. Although the nation is in the process of reestablishing regularity, there should be caution when stepping out in public.
INsights
A main component of our project is the mobility dashboard. Using Google Mobility Reports as its data source, this dashboard provides an aggregated view of movement trends over time by region across different categories of places. Having an interactive dashboard allows anyone to visualize trends over time across a state of interest.
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The Google Mobility Reports provides insights into six categories of places:
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Retail and recreation
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Groceries and pharmacies
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Parks
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Transit stations
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Workplaces
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Residential
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For states with lockdown policies, we expect mobility to decrease in these categories:
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Retail and recreation
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Transit stations
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Workplaces
For states with less restrictive policies, we expect mobility to increase in residential areas.
For the other two categories, groceries/pharmacies and parks, the dashboard can provide some interesting insights.
Across all 50 states, workplace mobility was most affected while parks experienced a 75% increase in mobility overall. States with no lockdown (Arkansas, Iowa, Nebraska, North Dakota, Oklahoma, South Dakota, Utah, Wyoming) had less drastic changes in mobility particularly in the retail and recreation category (-3.5%) and transit stations (-2.5%). To see more details, check out the dashboard here.
red vs. blue states
It’s interesting to note that Democratic states had less mobility in areas that were affected by lockdowns, such as grocery & pharmacy, retail and recreation, transit stations, and workplaces, in comparison to Republican states. This could imply that Democratic states are more strict with their lockdown policies.
MOVEMENT TRENDS
OVER TIME
Looking at mobility trends over time, the Mobility Index line graph measures changes in movement from the baseline mobility patterns at the beginning of the year. A sharper decrease in the line graph indicates a more dramatic adherence to the lockdown policy. For example, let’s look at California. Around March 8th when news about the Coronavirus began to spread rapidly, mobility trends shifted towards what we would expect. (source) Trends in most categories dropped, with the exception of residential areas and grocery stores which experienced a rapid increase over a few days. By mid-March right around when California enforced stay home orders state-wide, we see a drastic decrease in overall mobility and an increase in mobility around residential areas.