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The COVID-19 Report Card & Policymaker Playbook

A comprehensive overview of what we should be doing, what the data actually says, and how to move forward safely

Key Findings

  • Oklahoma takes the top spot in our super spreader rankings and the top 15 states are predominantly Republican, with only two swing states and one democratic state featured
  • Alabama tops our intracity spreaders ranking with Colorado coming in second and swing state Georgia in third.
  • Oklahoma and Alabama rank 1 and 2 in terms of out of home activity. Of the top 15 states listed, 13 are Republican, one is democratic and another is a swing state
  • The bad behavior of close proximity encounters has, unfortunately, clear bi-partisan support, yet Republican states have higher infection rates, indicating that mask wearing measure in blue states have been effective in curtailing the spread.

With more than 1,000,000 deaths globally and over 40,000,000 confirmed infections worldwide, COVID-19 has become a global pandemic the likes of which hasn’t been experienced since the 1918 Spanish Flu. Under such conditions, continued loss of life is inevitable and no completely effective “solution” will be found until a vaccine is widely administered.

Yet, in the absence of a vaccine, policymakers and businesses both have critical roles to play in terms of saving lives and economic livelihoods. Those roles involve implementing smart policy measures such as mask-wearing, local lockdowns, faster testing, and identification of high-risk areas that should be avoided or better managed.

This report looks at population behavior within the context of actions taken by state governments in the United States and leverages cutting edge behavioral intelligence data to assess how states are doing in terms of critical factors driving COVID-19’s spread. These include:

  • Identifying the most at-risk states for super-spreaders
  • Where the most travel is taking place in terms of encounters between people from different neighborhoods
  • Showing where residents are most likely to leave their homes
  • Which states have the most visitors from COVID-19 hotspots
  • What the data means when it comes to future infection

The Status Quo

Contact Tracing: It wasn’t until August, nearly 8 months after coronavirus became widespread, that the first contact tracing program was rolled out by the state of Virginia. The initiative relies on Bluetooth technology to notify users of contact with someone who reports a positive test. Versions of this same program are rolling out in three more states as part of a joint Google-Apple initiative.

Issues: Individuals may not report a positive test, Bluetooth may be disabled, slow testing makes the tracing reactive, and adoption of the app has been lagging.

Testing: Current testing options are PCR lab testing which is highly accurate and Antigen testing is poised to be deployed widely as a faster and cheaper option.

Issues

According to a survey from August carried out by four universities, more than 63 percent of U.S. residents are waiting longer than one to two days to get their coronavirus test results. One of the authors of that report said of the delay, “This is definitely a case of closing the barn doors after the horses have escaped.” By the time of the test the spread has already occurred and everyone is forced to simply play catchup instead of breaking the chain of infection.

Rapid testing is a great improvement in terms of speed, but the sensitivity of those tests is not as good as PCR tests and if deployed widely could result in millions of false positives. The antigen tests may also not be fast enough to preempt the spread because by the time a test reaches the threshold to be picked up a day or two has passed.

Ranking: Super-spreaders

What it means: Individuals who participate in many daily encounters in multiple areas and who are often amongst groups. The behavior could be due to either social choice, or profession.

Why it’s important: Superspreaders constitute one of the biggest drivers of the pandemic and can even turn relatively stable rates of infection into out of control outbreaks that strain medical systems.

There is a clear correlation between Republican leaning states and super-spreader behavior, it’s those same republican states that have the amongst the highest infection rates despite population densities well below their democratic counterparts.

  • The super-spreader behavior could be influenced by peers (see the Asch conformity experiment)
  • Socioeconomic status could also play a role, as all of the states (with the exception of North Dakota or Wyoming depending how you’re measure) where super-spreader behavior is common are in the bottom half of states in terms of median income and income per capita) (Source: 2010 US Census)
  • It’s not because of a disparity in testing numbers. With the exception of Texas, Ohio, and Florida which have high test numbers because of their size, the rest either fall within or below the average number of tests. (Source)

Ranking: Intra-city spreaders

What it means:  People that go out of their neighborhood and have multiple encounters with individuals based on constant movement visiting high foot traffic areas and visits to homes of known acquaintances.

Why it’s important: Provides insights into lockdown and social distancing adherence. Understanding frequency and duration of encounters occurs along with travel patterns can also serve as a clear indicator of outbreak risk and where transmission hotspots are located and where they are most likely to occur in the future.

See full chart: https://public.flourish.studio/visualisation/4074505/

  • The bad behavior of close proximity encounters has, unfortunately, clear bi-partisan support.
  • Not all states that top the list for encounters have a high infection rate, particularly the Democratic states. That discrepancy most likely indicates that although all those states have high numbers of social encounters, Democratic states have a higher adherence to preventive guidelines such as mask wearing.

Insights into: Who’s Leaving Their Home?

What it means? People who leave their home (100 meters)

Why it’s important? It’s an indicator of adherence to stay at home restrictions, or in the case of those states below, largely an indication of active behavior outside the home being strongly correlated with high rates of transmission.

South Dakota, Louisiana, Alabama, Tennessee, Nebraska, Mississippi, Louisiana, and Kansas are doing particularly badly based on this measurement. Typically we would expect people to leave their homes, but the aforementioned states have amongst the worst infection rates in the United States, rates that would normally trigger a lockdown of selected areas at a minimum. All of those states with a high infection rate and residents routinely leaving their homes, are Republican. (Source)

Insights into: Visitors from Other States

What it means: How many visitors coming in from out of state

Why is it important? A population inflow from high risk areas has created serious outbreaks in states and cities that were previously under control. Movement from New York kicked off Florida’s first wave and movement from Texas led to a spike in Atlanta.

  • Only Florida and Montana rank amongst the top US states for second homes (Source)
  • The only state to have quarantine for incoming travelers or returning residents (coming from states with a positive testing rate of 15% or more) is Kentucky, where it is simply a recommendation to self-quarantine for 14 days.
  • Lack of restrictions combined with interstate travel have spurred on outbreaks in areas such as Georgia, Tennessee, and Oklahoma, as we’ll see thanks to Neura data below.

Many of the snapshots of COVID-19’s spread illustrated below are based on the very real issue of mass population movement from highly infected areas. Below, we’ve included a map of 5 of the nation’s most infected areas, along with their outflow trends. The case of Atlanta, Georgia, which we will delve into below is clearly indicated by outflows from Texas, as is Oklahoma’s outbreak.

When looking at the 5 most infected states, and where people travel to in one month from those States (5 most popular destinations per location source)

Inter-State Spreaders from Highest Infected States

Case 1: Atlanta, Georgia

We see most people travelled to Atlanta Georgia, over 11% of all travel, in this one month period.

We also see that people from 3 states travelled to Atlanta, so it’s not just one in stream

See full chart: https://public.flourish.studio/visualisation/4073979/

 

In Atlanta, Georgia which had the highest amount of these travelers in July, we see a continuation of cases into August.

Source: https://dph.georgia.gov/covid-19-daily-status-report

The highest amount of deaths that occurred in the State was 4 weeks after the influx of travelers

On August 12 Georgia reported its highest death toll since the start of the pandemic.

Shown here is the onset of those cases, which presented in July when the travel was at its peak.

Source: https://dph.georgia.gov/covid-19-daily-status-report

Atlanta, Georgia is at a critical crossroads. If they ease restrictions and don’t look at specific areas of transmission for selective guidelines the city will see a return to an unsustainable trajectory of new cases.

Gov. Brian Kemp on Wednesday extended the state’s coronavirus restrictions an additional two weeks, signing an order that relaxes rules for restaurant and bar employees exposed to the disease.

The influx of travelers from high infectious states shows no sign of abating, and by opening the city, Atlanta risks the virus being reintroduced and spread for another outbreak.

Case 2: Tennessee & Indiana

We see the exact same pattern with Indiana & Tennessee. A large number of people 7.4% and 6% respectively traveling into these States the latter seeing multiple highly infectious points of origins.

See full chart: https://public.flourish.studio/visualisation/4074505/

Death rates peaked 4 weeks after inbound travelers from highly infected states arrived in both instances, and continued to climb.

 

Case 3: Oklahoma

Oklahoma ranked the worst in terms of accumulated risk score criteria during this period, as seen in the stacked comparison of data

The graph above illustrates a peak in death rate four weeks after the initial influx of out of state visitors.

Oklahoma Governor Kevin Stitt, who eventually tested positive for Covid, treated Covid in a similar fashion to Georgia early on.

In a now deleted tweet Stitt posted a photo sitting with his family at a packed restaurant with the caption “’Eating with my kids and all my fellow Oklahomans at the @CollectiveOKC. It’s packed tonight!”

And on July 15th, when Oklahoma was clearly identified as a “red” state the governor issued the following statement, ““We respect people’s rights to stay home if they want, to run their businesses, and not wear a mask.”

Case 4: South Dakota

South Dakota demonstrated the same dangerous pattern as Oklahoma, with numbers continuing to rise.

  

 

During a special session of the South Dakota Legislature on October 5, Noem stated that a “very prominent national reporter” had told her that they would not have had proof of how “useless” lockdowns were if she had not “stood against” them.[48] On October 7, President Trump posted a clip of the session on Twitter captioned “Great job South Dakota!”; Noem replied, arguing that he had given them “the flexibility to respect Freedom and personal responsibility”, and claimed that they made decisions “based on science, facts, and data”. This praise came despite South Dakota having recently set new records for active cases and hospitalizations.

Noem has faced criticism from residents, as well as other city and county leaders, for her lack of state-wide action

Beginning August 16 and spanning to September 26, the seven-day moving average quadrupled from an average of 95.6 cases per-day to 384 cases per-day.[3] On September 16, a single-day record was reached when eight new deaths were reported.[3] And, by September 23, a new peak had been reached when the state’s number of new, active, and hospitalized cases reached an overwhelming high.[32] Along with North Dakota, South Dakota has seen the largest per-capita increases in new cases nationwide.[5] On October 1, this state reported 13 new deaths, which was the highest single-day record for new deaths to date.[1][3]

Behavioral Intelligence must play a prominent role in the fight to contain Covid-19 and future outbreaks.

The status quo of containment methods has shown varying degrees of effectiveness, but all remain woefully insufficient to address the spread of Covid-19 and future national and global events. Testing remains – both in the case of PCR and antigen tests – far too slow and ineffective to do anything except more accurately track spreading well after it has occurred.

Policymakers and businesses meanwhile rely almost entirely on outdated test results and self-reported information, along with flawed blue-tooth dependent measures of proximity.

The current behavioral intelligence insights from the United States demonstrate startling trends:

  • The strong link between Republican policies and rhetoric that minimized the risk of Covid-19 even after its danger was widely known and bad behavior acted as a catalyst for its spread.
  • 12 of 15 states with the most super spreaders with Republican, including all of the top 10
  • A bi-partisan list of states with high social encounters, yet a discrepancy is case numbers suggests higher levels of adherence when it comes to preventative measures such as mask wearing in democratic states
  • Some of the most infected states: South Dakota, Louisiana, Alabama, Tennessee, Nebraska, Mississippi, Louisiana, and Kansas are those most likely to leave their homes. That indicates that even those Republican states that are most hard hit are refusing to consider lockdowns and their residents aren’t taking it upon themselves to change their behavior either
  • Out of state visitors continue to visit Republican states (and Joe Biden’s home state of Delaware) with astonishing frequency and no restrictions.
  • Visitors from the most highly infected areas in the country are responsible for outbreaks in Georgia, Tennessee, Oklahoma, and several additional states. They must be dissuaded from traveling.

Plotting a Way Forward For COVID-19 and Beyond

  • Deploying behavioral intelligence capabilities to testing has already shown promising results, increasing testing capacity by 6x and enabling test pooling of PCR tests that produced 98% accuracy and results within a matter of hours.
  • Behavioral intelligence is the only method currently available to take reactive tracking methods and transform them into accurate and predictive.
  • Policies will always be up to those in power and varying levels of restrictions and approaches based on considerations beyond the behavioral will be common.
  • However, the implementation of behavioral intelligence is the single method that can pre-empt an outbreak and lead to meaningful preventative actions beyond general guidelines, or full lockdowns.
  • All states should consider adopting behavioral intelligence technology to pinpoint superspreaders, encounter rates, high risk areas, restriction adherence and more.
  • Adopting a fact based approach that saves lives should be non-partisan

*Each State’s Party Affiliation is From Pre-2020 Elections

US COVID Report Data
State Name Cross Zip Rank Out of Home Rank Unique Places Visited Rank Super Spreader Rank Out of State Visitors Rank New Weekly Cases (Updated) New Cases Per % of Population Rank
Alabama 1 2 14 13 11 7284 28
Colorado 2 23 25 25 29 6841 38
Georgia 3 20 19 21 23 9149 8
Illinois 4 19 17 18 35 25447 42
Oklahoma 5 1 1 1 21 8242 34
Tennessee 6 11 18 17 8 14027 36
Nevada 7 42 44 45 26 4486 27
Louisiana 8 13 21 19 30 4282 47
Indiana 9 5 7 4 20 12601 7
West Virginia 10 29 31 31 4 1953 9
Michigan 11 15 26 26 43 9655 30
Ohio 12 10 15 12 33 13038 26
Minnesota 13 16 27 27 40 11000 46
Nebraska 14 3 2 3 18 5686 33
Pennsylvania 15 32 33 34 37 9996 21
Missouri 16 22 22 23 17 12466 11
Arizona 17 40 37 37 44 5574 18
Kentucky 18 12 20 20 7 7315 49
Arkansas 19 6 5 6 10 6233 23
Virginia 20 33 32 33 25 7258 32
South Carolina 21 21 16 16 9 6584 29
New Mexico 22 18 12 14 19 3805 22
Maryland 23 45 42 42 28 4293 20
Mississippi 24 7 10 11 15 5660 16
North Carolina 25 26 23 22 27 14557 41
Kansas 26 14 9 10 6 5048 48
New Hampshire 27 34 36 36 24 551 44
Utah 28 35 35 35 34 8550 25
Washington 29 39 41 41 46 4339 40
Wisconsin 30 24 29 29 32 16912 31
New Jersey 31 46 47 47 41 6385 5
Delaware 32 36 30 30 5 1066 35
California 33 50 49 49 48 20738 13
Rhode Island 34 41 39 39 31 1397 17
Florida 35 31 11 15 2 20077 10
New York 36 49 46 46 47 10206 14
Iowa 37 30 24 24 16 7437 3
Massachusetts 38 47 43 43 45 4479 2
Texas 39 28 6 8 13 31301 6
Oregon 40 37 38 38 39 2277 4
Connecticut 41 48 45 44 42 2792 12
Idaho 42 25 28 28 22 5026 24
South Dakota 43 4 3 2 3 4705 1
Maine 44 38 40 40 38 239 15
Vermont 45 43 48 48 36 61 39
North Dakota 46 8 8 7 12 4900 37
Wyoming 47 9 4 5 1 1414 19
Montana 48 17 13 9 14 4121 43
Alaska 49 27 34 32 49 1294 50
Hawaii 50 44 50 50 50 456 45

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