The counties that became hotspots were the ones already known to be at risk

The social vulnerability index was built in 2018 to identify the
communities that would need most help during a public health event. Two years
later there was an event, and the index could be checked against it.

Which counties became hotspots

Across all 3,142 US counties, comparing the most vulnerable quartile with
the rest for hotspot detection between 1 June and 25 July 2020:

Especially in less urban areas — the association was strongest where
population density alone would predict the least spread.

The second and third rows describe a mechanism anyone can picture: **a virus
that spreads indoors between people who share air**, in buildings with many
units and homes with more people than rooms. Distancing is a spatial
instruction, and it presumes you have the space.

And it did not end at detection

**Among hotspot counties, those with greater social vulnerability had higher
COVID-19 incidence during the 14 days after detection: 212–234 cases per
100,000 for the highest vulnerability quartile, versus 35–131 per 100,000 for
the other quartiles.**

Roughly two to six times the incidence in the fortnight after everyone
knew. Being identified as a hotspot triggers a response; the response did not
equalise what followed.

That is the finding with teeth. It is one thing for vulnerable communities to
be hit first — that could be about exposure. Remaining worse off two weeks
after the public health system has arrived says something about whether the
standard response fits the conditions it is being applied to. Advice to isolate
at home, stay off public transport and take time off work is not equally
available to everyone who receives it.

What the index is

The 2018 SVI scores every county on 15 population measures, in four parts:

1. Socioeconomic status
2. Household composition and disability
3. **Representation of racial and ethnic minority groups, and English
   proficiency**
4. Housing type and transportation

Scores are percentile rankings, grouped into quartiles, with urbanicity from
the NCHS urban-rural classification. Case counts came from USAFacts,
compiling state and local health department reports.

The conclusion is put in two halves, because they are different jobs:
prevent socially vulnerable communities from becoming hotspots, and
**decrease the persistently high incidence in the vulnerable counties that
already are.**

Source: Centers for Disease Control and Prevention, MMWR.