Six Tips to Navigating the COVID-19 Landscape from an Epidemiologist

As the pandemic progresses, more and more people are getting a glimpse into the world of public health. Epidemiology is one public health discipline that is getting a lot of attention and happens to be my chosen field of study.

Epidemiology is an applied field of biostatistics, and beyond the numbers is the study of humans. Social norms, individual behaviors, health, wealth, emotions – any facet of life with a discernible pattern. The combination of numbers and practical application allow us to understand current trends and predict future ones. We can identify points of interaction with individuals that will yield the highest probability of action and influence behavior using subtle human cues to elicit an action

It’s important to remember that many factors influence both sides of the equation – human and mathematical. Social determinants of health, sociodemographic disparities, or differences that can only be explained by factors that would be irrelevant in a world that was fair. The numbers you see on the screen, the dots that make up every graph a human life. On the mathematical side, numbers are only as good as the quality of their measurement and data management.

As an epidemiologist and public health professional, I’d like to share answers to six common questions I’ve been asked during the COVID-19 pandemic. I’m grateful that I can dissect the information bombarding me at every turn and hope to share useful information for others to do the same.

1) Should I wear a mask? 

Yes. I’ve been asked this question more than any other. If you are to be in public, it may help slow the spread of the virus by preventing you from spreading it to others. If you know you are infected or if you have been in contact with someone who may be infected, it is best to stay home.

2) What is flatten the curve? 

Most people are familiar with this one. It’s been used to describe the intended effects of social distancing, which appear to be working. With a flatter curve, the Area Under the Curve (AUC) is the same, but the duration of the outbreak is longer. In other words, the same number of people will be exposed to and get the virus – just stretched out so that the healthcare system isn’t overwhelmed.

3) What do all these numbers mean? 

We’ve all heard ‘flatten the curve’, but there are other common metrics that are useful for understanding the virus. These numbers won’t stay the same and will vary depending on the population studied – a key epidemiologic concept.

• R0 or R-naught represents how many people one infected individual infects on average. Social distancing efforts can lower this number and slow the spread of the disease and prevent new incidence.

• Incidence or number of new cases of a disease. This can aid in resource allocation, such as healthcare utilization. The number of new cases, duration of disease, and rate of spread taken together may predict what is needed two weeks from now.

• Case Fatality Rate represents fatalities relative to confirmed cases. In the current climate, testing is limited and often flawed. People will contract the virus and have no symptoms. Similarly, patients die before they test positive.

• All-Cause Fatality Rate is the fatality rate for all causes which can be monitored year-over-year to estimate the total fatalities related to the disease and account for gaps in incidence and prevalence monitoring.

• Infection Mortality Rate represents fatalities relative to all people infected. This number is not known without universal or widespread testing.

4) How does COVID-19 compare to other well-known viruses? 

It’s twice as infectious as H1N1 or the typical seasonal flu. The mortality rate is 10-30x higher than the seasonal flu. The H1N1 mortality rate was much lower than either COVID-19 or the seasonal flu.

The H1N1 virus was deadlier to younger ages because many people over age 65 had been exposed to a similar strain of virus earlier in life. This immunity helped keep them from contracting not only cases but severe cases. Because this is a novel or new virus, no one has immunity. That is why social distancing may play an important role in containing the virus until a vaccine is available.

5) Why do the numbers keep changing?

The numbers listed above can change depending on the population of people you are examining. A few examples are shown below.

With #flattenthecurve, we take social distancing seriously, decrease new cases and decrease the rate of spread. The mortality rate could go either way depending on how it is calculated. If it is only confirmed cases, it may go up as more people are staying home if they have mild or asymptomatic cases and will not be tested. They survive but aren’t counted toward lowering the mortality rate.

Examples of how the numbers could change. Up indicates an increase. Down a decrease. Arrows that point to the side indicate it could go either way depending on other circumstances.

6) Why is testing such a big deal? 

Testing is important because it gives us a fuller picture of the virus, how it behaves, who it affects and how intensely, what treatments are effective for easing symptoms and shortening duration of illness, and what points of intervention we can employ to prevent or stop the spread of the virus. Testing also allows us to understand who has the virus and has built up antibodies. It could determine whether people are safe to return to work and a more integrated form of society. Testing enables a more accurate measurement of metrics for informed decision-making.

If you are unsure of something you read or want more information, as a trusted friend or colleague to help decipher the information. Use your social media networks to find people you trust who share information from vetted sources. I’m happy to do this for my sources and know many others who do the same.

I’m not sure what the other side of COVID-19 looks like, but the news I read every day makes me hopeful for the ingenuity, intelligence, compassion, and humanity I’ve witnessed in-person and through social media in the past several weeks. I am grateful that my life has not much changed, yet I worry for the world, vulnerable populations, and those I love. Despite the uncertainty, I am sure of one thing – Epidemiologists around the world are at far lesser risk than ever before of being asked if they study the skin.