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dcyphr | Evaluating the Effectiveness of Social Distancing Interventions to Delay or Flatten the Epidemic Curve of Coronavirus Disease

Evaluating the Effectiveness of Social Distancing Interventions to Delay or Flatten the Epidemic Curve of Coronavirus Disease

Endorsers
Daniel Amuedo
  I am a premedical student at Missouri State studying Cellular and Molecular Biology with a minor in Chemistry and a dist...
Jeffrey Ma
  B.S. in Computer Science and Mathematics from Yale University in 2022. Founder of dcyphr. ...

APA citation: Matrajt, L., and Leung, T. (2020). Evaluating the effectiveness of social distancing interventions to delay or flatten the epidemic curve of coronavirus disease. Emerging Infectious Diseases, 26(8). doi: 10.3201/eid2608.201093

DOI: 10.3201/eid2608.201093

dcyphr-d by Daniel Amuedo on 2020-06-18

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Contributors
Daniel Amuedo

I am a premedical student at Missouri St...

Leanna Zelle

I am a pre medical student at Missouri S...

Abstract

This study looks at how effective social distancing is in a mid sized city. 20% of deaths were avoided in real cities that carried out social distancing. When the social distancing ended these rates went back up. This study suggests that social distancing allows hospitals to increase their capacity. It is necessary to have enough testing and self isolation to slow the spread of the virus.

Introduction

On January 21st, Washington had the first confirmed case of COVID-19 in the US. On March 12th, the first set of social restrictions began in Washington. By March 25th, a stay at home order was put into place for 6 weeks. Researchers used Seattle, Washington as a model. This study predicts cases, hospitalizations rate, deaths prevented, and how effective social distancing is.

Methods

This study used a model that separated their population into age groups. In each age group, there were several subcategories: susceptible, exposed, infectious, and removed. Susceptible people could get the virus. Exposed people had come into contact with the virus but were asymptomatic. Infectious were people who were positive for the virus. Removed people were those who had recovered or died. This study found that only 20% of cases were discovered, because 80% of cases were mild. This prevented those patients from being tested.

In Washington, there were six weeks of time for SARS-CoV-2 to circulate between the first and second positive case. Then the social distancing period started. This reduced the contact rate for three age groups: less than 19, 20 to 59, and 60 or more. There were four models of social distancing used.

Model 1 - Only adults over 60 years of age reduced social contact by 95%. This model was used in some countries. When people tried to protect the elderly from harm.

Model 2 - Adults over 60 reduced their contact by 95% and children both reduced their contact by 85%. This model represents social distancing of the elderly and of school closures. As most contact for a child is done during the school day.

Model 3 - Adults over 60 reduced their contact by 95%. Adults 20 to 59 have either 25%, 75%, or 95% reduced contact. The child contact is not reduced. This model represents the elderly are social distancing. The adults have mixed distancing. As this model accounts for the essential frontline workers and people who are able to work from home. However, some countries did not close their schools. This model accounts for this by having the children not social distance.

Model 4 - Adults over 60 reduced their contact by 95%. Adults 20 to 59 have either 25%, 75%, or 95% less contact. Children have 85% less contact. This model is similar to the US. As The elderly social distance the most, the adults are medium, and the schools are closed.

Results

Infection Period

First the infectious period of this model was set to only 5 days. In this case, the epidemic peaked after 85 days. When the infectious period increased to 8 days, the epidemic took 110 days to peak. Raising the infectious period lowers the infectious rate. Decreasing the infectious rate early on delays the peak. However, it fails to change the size of the pandemic.

Models 1-4

The study then looks at models 1 through 4 mentioned in the methods section, for an 8 day infectious period. Model 1 delayed the peak by 5 days. Model 2 delayed the peak by 23 days. Model 3 delayed the peak by 24 days. Model 4 delayed the peak by over 40 days. This study looked at other lengths of infectious periods. When the infectious period was shorter, social distancing was more effective. But still, this did not impact the height of the peak.


Execution


Next, they looked at how long social distancing was executed after the first case was identified. When social distancing started at day 50, the epidemic was delayed under every percent isolation condition. But the height of the curve did not change. When the social distancing was executed mid pandemic at day 80, all models did somewhat flatten the curve.


Hospitalization and Fatality Rates


Here, the children group had the most impact by reducing hospitalizations by 75% and the total death rate by 80%. This is because children might not need to be hospitalized. Despite this, the virus will spread to people 60 or older. Model 2 averted 87% of cases and model 1 averted 77% of cases, but models 1 and 2 still had similar hospitalizations and fatalities to each other. No matter the social distancing put into place, every model suggested that the epidemic would spike again after the social distancing orders were lifted.


Discussion


Many people are familiar with the term “flatten the curve” and this study addresses that. This study concludes several things about social distancing. Such as:


1) Social distancing too soon after the first case will delay the pandemic, not flatten the curve. In order to flatten the curve social distancing must be executed during the “growth” phase of the pandemic.

2) The effectiveness of social distancing is reliant on the ratio of susceptible, infected, and recovered people at the very start of the intervention. To predict the effects of social distancing  accurate data on these factors is necessary

3) As of April 2nd, the US was testing less people per million for COVID-19 than some other countries, like Italy.The future of social distancing relies on expanded testing.

4) It is still unclear how long immunity to COVID-19 lasts after having the virus. This will continue to play a role in social distancing regulations in the US. If we have long term immunity, recovered people can go back work. If the immunity is lasting for a couple of weeks, they should continue to social distance.


These results should be handled with caution because this model is simplified. Social distancing can give communities vital time to prepare for the pandemic. And it can avert deaths for a small period of time. But it will likely not decrease the number of cases long term. Social distancing is also not helping economically or socially, and therefore not sustainable long term. So, it would be best to not rely entirely on social distancing. Rather implement a collection of methods to combat the pandemic. Interventions should be made globally because any imported cases could lead to a new outbreak. More aggressive measures should be taken to decrease as many deaths as possible.


The limitations of this study include mathematics and information about COVID-19. Current research estimates of the infectious period of COVID range from 5 to 20. This is a wide range and leads to different results in the models of this study. Secondly, we cannot confirm that people of the same age group have the same ability to infect others. This study considered all all age groups had the same ability to infect others. Different countries have different population structures and health care systems. This could change the results in some countries. Finally, probability and mathematics can predict well, but also have the opportunity to over or under predict some factors in this study.