Models suggest how to get to herd immunity
In a survey our biochemistry class distributed, we asked Addison County residents to share their concerns about COVID-19 vaccines. Interestingly, 57% of the 349 respondents indicated that a vaccine would not be effective at ending the pandemic because not enough people will get the vaccine.
When asked whether or not they would get the vaccine, 58% of the respondents said yes, 32% were not sure, and 10% said they would not get a vaccine. Are numbers like these sufficient to end the pandemic, if applied on a global scale?
When an individual is vaccinated and becomes immune to a virus, the virus can’t use that individual as host to make many copies of itself. With enough people immune, the disease will stop spreading because there will be far fewer copies of the virus around that can infect people and viruses without a host will ultimately die.
In this article, we explore what percentage of the population needs to be immune in order to decrease the number of total cases over time. This phenomenon, known as herd immunity, can only be achieved if enough people elect to receive a vaccine or obtain immunity through infection. So then, how many people must become immune? Fortunately, there are mathematical models that can predict just that.
The percentage of the population that needs to be immune to shut down any specific disease can be approximated mathematically using a series of values. Epidemiologists who have studied the transmission of disease have determined just how many people need to be infected in a given population in order for an infection to spread through it. By looking at past outbreaks, they have created models with certain variables that can tell us how likely it is for a virus to spread.
The most important value is R0, or the average number of individuals one diseased individual will infect over the course of their illness. Another important value to consider is Rt. This value expands upon the aforementioned R0 by taking a few further considerations into account. These considerations include, but are not limited to, the fact that individuals over the age of 80 have far fewer contacts than younger individuals and the fact that children under the age of 10 are less susceptible to getting the disease (in the case of COVID, at least) and passing the disease onto other individuals.
With knowledge of the Rt value, one can calculate the minimum percentage of the population that must be immune to prevent the spread of infection using the equation 1 – (1/ Rt). Although it is not definitive and predictions vary, the Rt of COVID-19 is thought to be up to about 3, which, when plugged into the equation 1 – (1/ Rt), yields a value of 0.67. This means approximately 67% of people might need to be immune to COVID-19 in order to reach herd immunity.
Modeling what it will take to curb the spread of COVID-19 is a delicate practice, but previous research suggests that these predictions can be quite accurate. Estimates using this equation have shown that the spread of a typical flu can be limited with a population immunity of about 25%. So far, this has been quite accurate in a typical year.
However, there are limitations to modeling. For example, unexpected mutations in a virus can increase transmissibility (i.e. R0), as may be the case for a recently identified coronavirus strain in the United Kingdom. Another limitation is that R0 can vary across different environments depending on factors such as population density, birth rate, and cultural practices. For example, the R0 may be smaller in a rural area like Vermont compared to New York City because people are able to physically distance better. In all, the model presented provides a strong estimate for what level of immunity is required, but it does not provide a definitive answer.
NATURAL HERD IMMUNITY
Now that we’ve explored approximately what percent immunity it will take to achieve herd immunity, it is important to think about how to obtain herd immunity. Is it best for everyone to receive a vaccine or can we simply allow enough people to be infected and become naturally immune? The response in Scandinavian countries provides one example why natural immunity may not be an effective response to curbing the spread of COVID-19.
While Denmark, Finland, and Norway implemented severe restrictions in order to curb the spread of COVID-19, Sweden took a more hands-off approach. As of June 23, 2020, Sweden had more total COVID-19 deaths per million people than the other three Scandinavian countries combined (511 versus 208). One reason why natural immunity is not a good solution is due to the high fatality rate of COVID-19 (0.6%). Therefore, vaccination is the way to go.
In fact, many companies have striven to develop vaccines, which is evidenced by the fact that there were 193 vaccines in development, with 42 of these in clinical trials at the start of October. Two standout examples are Pfizer and Moderna’s vaccines, which are approximately 95% effective against COVID-19 and have recently been approved by the FDA.
Current vaccines are very promising, as will be touched upon throughout our collection of articles, and they continue to be our main hope for resolving the COVID-19 pandemic. The herd immunity modeling emphasizes the need for a vaccine to be distributed to as many people as possible. Predicted threshold immunity levels are quite high, and they may be even higher than expected as we don’t know everything about the virus, and the spread of disease varies greatly in different communities.
• Expert comments about herd immunity | Science Media Centre. (n.d.). Retrieved December 7, 2020, from https://www.sciencemediacentre.org/expert-comments-about-herd-immunity/
• Fontanet, A., & Cauchemez, S. (2020). COVID-19 herd immunity: Where are we? Nature Reviews Immunology, 20(10), 583–584. https://doi.org/10.1038/s41577-020-00451-5
• Kwok, K. O., Lai, F., Wei, W. I., Wong, S. Y. S., & Tang, J. W. T. (2020). Herd immunity – estimating the level required to halt the COVID-19 epidemics in affected countries.
Journal of Infection, 80(6), e32–e33. https://doi.org/10.1016/j.jinf.2020.03.027
• Orlowski, E. J. W., & Goldsmith, D. J. A. (2020). Four months into the COVID-19 pandemic, Sweden’s prized herd immunity is nowhere in sight. Journal of the Royal Society of Medicine, 113(8), 292–298. https://doi.org/10.1177/0141076820945282
• Randolph, H. E., & Barreiro, L. B. (2020). Herd Immunity: Understanding COVID-19. Immunity, 52(5), 737–741. https://doi.org/10.1016/j.immuni.2020.04.012
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