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What do we know about controlling the spread of COVID-19 through hyper-local measures?

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Imposing restrictions at a hyper-local level, such as by postal code or zip code, can work to contain COVID-19, but is not without challenges and comes with a set of both pros and cons. The pros come into effect if individuals who are residents of that zip code or neighborhood a) follow the restrictions imposed and do not travel outside their neighborhood, especially at a mass level. The cons come into effect if individuals who are residents of that zip code or neighborhood either do not follow restrictions imposed, or travel outside their neighborhood, especially at a mass level. As a result, it’s crucial to communicate with residents so that they understand the expectations and what is at risk if local measures aren’t followed. To help ensure that they are followed, local public health officials and leaders must share information with residents on how to access the resources that they need hyper-locally, both for healthcare and otherwise, so that individuals are not pushed to seek resources outside of their affected area, and in turn potentially increasing positive rates in other neighborhoods, worsening the problem overall.  Of note is that hyperlocal surveillance of COVID-19 is also useful for tracking and ultimately controlling the spread of the virus, as the more local the data is, the more granular it is likely to be and the less gaps it is likely to have.

This article was published on
February 17, 2021

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What our experts say

Imposing restrictions at a hyper-local level, such as by postal code or zip code, can work to contain COVID-19, but is not without challenges and comes with a set of both pros and cons. The pros come into effect if individuals who are residents of that zip code or neighborhood a) follow the restrictions imposed and do not travel outside their neighborhood, especially at a mass level. The cons come into effect if individuals who are residents of that zip code or neighborhood either do not follow restrictions imposed, or travel outside their neighborhood, especially at a mass level.

As a result, it’s crucial to communicate with residents so that they understand the expectations and what is at risk if local measures aren’t followed. To help ensure that they are followed, local public health officials and leaders must share information with residents on how to access the resources that they need hyper-locally, both for healthcare and otherwise, so that individuals are not pushed to seek resources outside of their affected area, and in turn potentially increasing positive rates in other neighborhoods, worsening the problem overall. 

Of note is that hyperlocal surveillance of COVID-19 is also useful for tracking and ultimately controlling the spread of the virus, as the more local the data is, the more granular it is likely to be and the less gaps it is likely to have.

Context and background

There have been recent questions about hyper-local control measures in response to New York City’s announcement on October 4, 2020, to impose new restrictions in 20 COVID-19 hotspots in Brooklyn and Queens where the COVID-19 positivity rate has been higher than 3% for 7 consecutive days. 11 zip codes have lesser restrictions, such as banned indoor dining, and 9 zip codes with the highest positivity rates have major restrictions, which include closing schools, nonessential businesses, and day care centers, essentially reversing progress the city had made on fighting the outbreak in the spring. 

Given that zipcodes that fall into the three categories of 1) major hotspot, 2) minor hotspot, and 3) not a hotspot, in some cases, all neighbor each other or are closely nearby, questions have been raised as to how effective such hyper-local interventions such as these are towards the end of keeping the case count from increasing and, ideally, ultimately lowering the case count. 

Resources

  1. Fearing 2nd Wave, N.Y.C. Will Adopt Restrictions in Hard-Hit Areas (New York Times)
  2. Hyperlocal Postcode Based Crowdsourced Surveillance Systems in the COVID-19 Pandemic Response (Frontiers in Public Health)

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