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Herd Immunity: How Do we Know When it Might Happen?

Vaccines are starting to become widely available for the majority of the population. Each dose pushes us closer to herd immunity or community immunity, which is when enough of the people in the community are immune to the specific bacteria or virus (pathogen) that the disease cannot spread. How do doctors and scientists know when a population has reached herd immunity? The answer is scientific modeling, a process where scientists aim to take a phenomenon and make it easier to understand, so predictions can be made about the real world.
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 Good scientific models are: 

  1. Based on reliable observations, like clinical data;
  2. Able to explain the characteristics of the observations used to formulate it, just like analyzing the contact tracing information;
  3. Able to predict the future given different variables;
  4. Can be refined as new data arrives, such as a new genetic variant;
  5. Limited and specific to a concept, theory, or object; and,
  6. Constructed in a form that is relevant for the data. 

There are many types of models that can be used.  Some examples include physical (2D or 3D), mathematical, conceptual, and computer or physical simulations. Scientific models require a team of experts to construct, use, and share with the communities that are interested. Have you ever wondered how a doctor makes a model of the spread of a virus or how masks will affect the outcome of disease spread?

To make a great science (public health) model, an interdisciplinary team is required. We sat down with an infectious disease expert at Sanford Health to learn more about the group of people needed to create a model for a pandemic. According to the expert, modeling disease requires an interdisciplinary team.

1. Infectious disease specialist: An infectious disease specialist is a trained professional knowledgeable about diseases being transmitted through out a community being studied.  Their background helps them to diagnose and treat infectious diseases caused by microorganism including bacteria, viruses, fungi, and parasites.  

2. Data Scientist: Data scientists take large sets of data gathered by infectious disease specialists and help to make predictions through analytics. Analytics may include visualizing trends, exploring the data, or even statistical work. Data scientists may use the data in a descriptive (describing why an event happened) manner, or prescriptive (describing what action a person should take next).    

3. Mathematician/Statistician: Mathematicians are people with extensive knowledge in mathematics, enabling them to help to solve mathematical problems. Examples of a mathematical problem associated with infectious disease may ask how many people are currently infected or how quickly new people could become infected.  Statisticians work with in a specific branch of mathematics focusing on predictions related to a certain event. For example, how is mask-wearing associated with disease spread? 

At Sanford Research, we have an entire multidisciplinary team dedicated to helping our scientists with statistical work and creating models for disease.  They can help infectious disease experts understand if their question can be answered using statistical methods, or if the question might be better addressed by a mathematician.  

Learn more about COVID-19 and herd immunity by watching these videos from Sanford Health’s Dr. Paul Carson:

COVID-19 Compared to Risk of Vaccines

COVID-19 Herd Immunity

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