A Brief Lesson on R0

Unless you’re an expert in public health, science, epidemiology or related field, chances are you hadn’t seen the term R0, until you started reading about the novel coronavirus pandemic. 

Pronounced “R-naught” or “R-zero,” R0 is an epidemiology term referred to as the basic reproduction number. As infection is transmitted to new people, it reproduces itself. Simply explained, R0 is a complex calculation that tells you the average number of people predicted to contract an infectious disease, from one person with that disease. For example, if R0 = 2, then one person with the disease is expected to infect, on average, 2 others. 

Image courtesy of The Conversation.

The R0 for any disease is built on hard science and complex mathematical models – however it is not a biological or mathematical constant for any pathogen. While it is calculated from innate features of a particular disease (such as, how easily it spreads from one person to the next), R0 is also affected by external factors, such as environmental conditions and human behavior of the infected population (i.e. how often sick or susceptible people are likely to come into contact). As a result, R0 for a particular disease can vary region to region. 

Yet, R0 still forms a centerpiece in most disease forecasting models, and is considered to to be an important compass – for both health and science experts studying a disease, as well as the leaders working to manage its spread. It has long been considered one of the fundamental and most often used metrics for the study of infectious disease dynamics. 

In most scenarios, the following possibilities exist: 

  • If R0 < 1, suggests the number of cases is in decline – and a potential outbreak may be likely to die out on its own.
  • If R0 = 1, the disease will likely remain alive and stable, without causing a pandemic. 
  • If R0 > 1, indicates the number of cases is growing – increasing the likelihood of a pandemic.

The below graphic illustrates the staggering impact of R0 = 2 versus R0 = 5. 

Image courtesy of Robert Roy Britt.

Ultimately, the closer to zero the R0 value, the better. 

The optimistic view? People have the ability to influence how environmental conditions (within a given region) impact the value of R0. Risk reduction measures such as wearing masks, social distancing, and implementing enhanced disinfection methods (such as hospital-grade UV-C) across indoor spaces, can all help reduce R0 (for COVID-19). 

As a company, R-Zero’s mission is to reduce the spread of all infectious diseases. As such, the name R-Zero is a reference to not only a key metric in the study of infectious disease (R0, itself), but to the best case scenario calculation for R0: Zero

Just as there isn’t a single calculation to predict pandemics, there’s no one silver bullet to prevent them. And just as there are multiple factors that contribute to calculating R0, every dynamic environment has multiple factors that must be accounted for when developing effective infection prevention protocols.

 R-Zero exists to provide the tools, technology and education to help every organization reduce R0 estimates in their community and environment, ultimately reducing the spread of all infectious disease. 

To learn more about R-Zero’s infection prevention platform, visit rzero.com.

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