COVID-19 Epidemiology 2

COVID-19 – The END GAME

covid-19

It has been 3 weeks since our last post discussing the initial round of SARS-CoV-2 literature and information is evolving faster than most of us can keep up. Data continues to flow out of nearly every academic institution on a global scale and it is difficult to know how to interpret this massive flow of data, and more importantly, what to trust. This article is “Part 2” in an open-ended series discussing what we currently know about the novel coronavirus. 

What has changed in our knowledge of how infectious this disease really is?

In our last post, we discussed the basic reproduction number (R0), which is the number that measures how contageous a particular pathogen is. Initial data out of Wuhan estimated this number to be about 2.5 with a doubling time of 6-7 days. This means that each person infected with the virus would infect another 2.5 people and the number of infections would double about every week. A new model published by the CDC looking at early data out of Wuhan suggests that the R0 was actually more likely in the range of 3.8 to 8.9, with an average of 5.7 (95% CI) and a doubling time of 2.3 to 3.3 days.

Source: CDC and WHO

Why is this important to know?

Simply put, when the R0 is > 1, the infection will spread in a population and if it is < 1, it will not.

Further, it allows us to determine the number of people that need to be immunized (by vaccine or develop immunity through infection) to prevent sustained spread. We call this herd immunity and is calculated by the equation 1-1/R0.

I know what you are thinking…not math!!! Stick with me…

So, for an R0 of 5.7 (quickly does math)…82% of the population would need to get immunity to stop the spread of illness.

According to the World Health Organization (WHO), the overall fatality rate of COVID-19 is around 3.5%. This rate is largely dependent on region, and influenced largely by how thin the healthcare system is spread, the quality of healthcare, and the likely large number of undiagnosed cases. The case fatality rate was around 4.4% for patients in Wuhan, 4.0% for patients in Hubei, and 0.92% for patients in Chinese territories outside of Hubei, for example. Regardless, without a vaccine, that is putting a whole lot of susceptible people at risk of death if we just let it happen naturally and we have seen over and over again how easy it is for a healthcare system to be overwhelmed during peaks in cases. Remember, just 25% of patients who died in Wuhan had access to a ventilator.

If we could decrease the R0 to 1.3 (the average for seasonal influenza), just 23% of the population would need to get immunity to stop the spread of illness.

R0 is not constant and is influenced by factors such as the environment and behavior of the population infected. There have historically been large ranges in calculated R0 values of different diseases depending on location where it was calculated. Therefore, we cannot simply use an R0 calculated in China and apply it to a population two months later in the United States, for example. The true contagiousness of SARS-CoV-2 in other countries is yet to be determined. It is nearly impossible to calculate an R0 while an epidemic is spreading as it is based on the assumption that all members of the community are susceptible to the virus. We can influence the portion of the population that is susceptible to a disease through measures such as vaccination or natural immunity. Without a vaccine, we rely on contact tracing, case isolation, and quarantine protocols, travel restrictions, social distancing, and widespread use of face masks to decrease the portion of the population susceptible to the disease. With these measures, we can estimate what is known as the “effective” reproductive number (R). Just as with R0, when the R is > 1, the infection will continue to spread.

The University of Hong Kong keeps a dynamic dashboard where they keep a real-time effective reproductive number ticker:

What is contact tracing?

Contact tracing, in a nutshell, is finding each sick person and figuring out who they recently had interactions with. People are interviewed by public health officials and all potential exposures are quarantined. It is difficult detective work and takes a concerted effort. Can you see how this could be time consuming and difficult? 

In a feasibility study looking to determine if COVID-19 can be controlled by contact tracing, researchers found that during an outbreak involving a virus with an R0 of 2.5, more than 70% of all contacts needed to be traced to successfully contain the spread. With an R0 of 3.5, more than 90% of contacts had to be traced. At an R0 of 5.7, this seems unlikely to solve the problem alone without more widespread regional quarantine and social distancing.

Well, then how the heck did we even contain the 2003 SARS outbreak?

The 2003 SARS is strikingly similar to COVID-19. They are 86% similar in their genomes. They both have incubation periods of about 5 days. They are both spread by respiratory droplets and both can shed virus in stool. The progression to severe disease follows a similar pattern in both viruses as well with an ARDS like appearance 8-20 days after first symptom onset and CT scan of the chest showing the most severe infiltrates around day 10. The ACE2 receptor in the lungs serves as a point of entry for both viruses, as well. However, according to a recent study of viral structure, SARS-CoV-2 has a much higher affinity to the receptor needed for cell entry than the 2003 SARS virus.

The 2003 SARS outbreak was contained by interrupting human-to-human interaction through strict surveillance, prompt isolation, strict quarantine, and in some areas, large community quarantine. This has been a difficult task for COVID-19 for many reasons. Firstly, Wuhan is a densely populated major transport and industrial center that is home to the largest train station, deep-water port, and airport in China. Secondly, hospitals were initially overwhelmed because of a shortage of hospital beds, causing seeding in the community and a total of 5 million people left Wuhan in the few days just before the lockdown. Many of whom could have been incubating the virus. 

Finally, there was not a single documented case of asymptomatic transmission by the 2003 SARS-CoV-1 virus and early communication from the World Health Organization inaccurately tweeted that this was unlikely to drive transmission of COVID-19. Unfortunately, we now know that the incubation period has been described to average from 2-14 days, but case reports document ranges from 0-24 days, if not longer. Further, there have been numerous documented case reports that the COVID-19 causing virus can be spread from person-to-person before the person even knows they have the illness. In the case of the Diamond Princess cruise, nearly 50% of all patients had no symptoms at the time they tested positive and 16% of patients who tested positive never developed symptoms. 

In Deagu, South Korea, 1,900 Shincheonji Church members were exposed to a man found to have COVID-19. All 1,900 church members were then tested for the virus. 1,300 had symptoms and 600 did not. Out of those tested with symptoms, an incredible 87.5% tested positive. More shockingly, out of the 600 without any symptoms, 70% tested positive. In fact, numerous studies have shown that up to 80% of patients who test positive may have minimal to no symptoms at all.  

Contact tracing is starting to seem nearly impossible now, isn’t it?

Well, how far are we from a vaccine?

From these numbers, it seems our only real way out of this mess is with widespread vaccinations. But nobody truly knows when one will be available. It typically takes years to safely manufacture a vaccine given a typical vaccine testing and approval process with the largest hurdle for development being manufacture and distribution at scale. In a global push for vaccines, this could still take 12-18 months to accomplish. Further hindering vaccine development appears to be the fact that COVID-19 has mutated into two major strains. Further significant mutations could be catastrophic to this timeline. Fortunately, at the time of writing this, there are at least 70 vaccines in development and at least four of those currently in or just starting clinical trials.

But then we have to ask ourselves if there are enough citizens willing to get an expedited vaccine to offer immunity to the number of people necessary to reach herd immunity. In a 2015 survey, 9% of Americans felt vaccines were unsafe for children. In a 2018 survey of Americans, less than half of people got an influenza vaccine that year with half of those claiming their choice not to vaccinate was because they felt vaccines were unsafe. 

What if we re-open the economy now and attempt natural herd immunity?

According to models from the CDC, if we did nothing, we could expect between 160-214 million people infected in the United States with as many as 200,000 to 1.7 million deaths.

Widespread testing would certainly be a key factor in allowing us to determine a safe time to fully re-open the economy. As of April 13th, the United States has only tested 8.5 per 1,000 citizens. We are several months into this and the window for accurate population-based testing of those with no or mild symptoms will be inaccurate for many U.S. cities. Large scale population-based testing done in Iceland revealed a prevalence of just 0.86% of the virus in the general population. That’s not nearly enough for herd immunity. In a population-based sampling study of the San Francisco Bay Area conducted out of Stanford, they also found community prevalence was low with only 2 of the 3,000 patients tested before February 28th were positive for the virus. This number increased to 9% with more widespread testing in March. Estimates of population prevalence based on mortality data of disease in Italy suggest rates varying from 0.35% in Sicily to 13.3% in Lombardy. Overall, there has been limited published data of measured prevalence, and those that have been published show a shockingly low prevalence. Nowhere near what would be needed for herd immunity.

Further, immunity isn’t a sure thing. We do not yet know if those who recover will determine long-term immunity. We can infer from prior pandemics, that at least some immunity will occur, but the verdict is still out on this. There are multiple documented cases where people who appear to recover from the virus test positive again, which calls even short-term immunity into question. At this point, it’s really just a guessing game. There just isn’t enough known to safely recommend intentionally contracting the disease as a way to attempt immunity. Young and healthy people are not immune to bad outcomes and the long-term health effects of the virus is unknown as otherwise healthy people in their ‘20s and ‘30s may be looking at long term heart, kidney, and lung issues even after they recover. 

Antibody testing would allow us to determine if we have enough of the population who have been unknowingly exposed and have at least some level of immunity. The first FDA approved antibody test was just released last week. A new study has begun recruiting at the National Institutes of Health using antibody testing to determine the prevalence of undetected coronavirus cases. But even having antibodies does not guarantee immunity. Regardless, antibody testing is very important for us to get a better understanding on how much this virus has penetrated society.

Widespread lockdown certainly doesn’t seem like a viable long-term solution. At some point, we have to weigh the risks and benefits of the percent of deaths in a population and the long-term downstream effects of driving the country, if not the world, into a deep economic depression. Not to mention the long-term health repercussions on individuals by delaying non-COVID related care.

How are we doing with stay-at-home recommendations?

In my home state of Michigan, social distancing and school cancellations began on March 16th. Tracking cell phone movement data, we can see that roughly 30% of the population was staying at home at that time in self-quarantine. On March 23rd, Michigan adopted a rather radical “shelter in place” order. Since that time, roughly 50% of the population has remained in self-quarantine. That means nearly 50% of the population, assuming most are essential workers, are still cohabitating in the community. Regardless, we see that even with radical widespread lockdowns, it seems improbable that we will be able to completely stop the spread. 

Well, that's just Michigan. How are we doing as a nation?

…eh, about the same…

Image source: safegraph.com

So, is social distancing even working?

This graph has been getting some attention representing a similar outcome in progress between the states of Kentucky and Tennessee. Both states appear to have started seeing confirmed COVID-19 cases at relatively the same time. Kentucky declared a state of emergency nearly immediately and began strict social distancing practices. Tennessee delayed similar response by one week, and the differences in the number of positive cases is hard not to notice…

Some caveats to keep in mind when looking at this graph. First, Tennessee has 6.8 million residents to Kentucky’s 4.5 million. Second, testing per capita was 20 per 100,000 residents higher in Tennessee. Finally, Nashville alone had more cases than the entire state of Kentucky during the sample periods.

If we follow the daily cases and the timeline in which measures were initiated, we can see how different regions around the glove are flattening the curve. It is important to keep in mind that the average incubation period of 2-14 days means that when you see a spike in cases, you are really looking at what was going on in the population a week or two in the past.

Source: graph adapted from the University of Hong Kong

The United States is a little difficult to assess as a whole as quarantine measures vary wildly from state-to-state and many of the epicenters are just now starting to peak. In Michigan, we are just now starting to see a plateau in COVID-19 related deaths in the southeastern part of the state.

According to CDC Europe, the global cases have begun to show downward trends.

Source: ECDC

At this time, the total number of case numbers is not quite as helpful in determining the real-time effectiveness of social distancing as is other measures. As testing continues to become more prevalent, the number of cases identified will certainly continue to increase. But this doesn’t mean our situation is getting worse. In this graph, we see that despite an increase in tests obtained across the state of Michigan, the overall percentage of daily positive tests appears to have hit a plateau.

Image source: Infogram

An even better measure of flattening the curve is looking at the amount of time in between an observed doubling of deaths. This is known as the doubling time. The national average doubling time for the week of March 16th was 2.3. On March 23rd, 10 days after a national state of emergency was announced, this increased to 3.8. Since that time, 44 states have issued “shelter in place” orders and doubling times are starting to lengthen…

If we simply look at the number of deaths related to COVID-19, it seems apparent that we are starting to see some progress…

Image source: ECDC

What does history tell us?

In our first part of the series, we discussed the historical example of St. Louis and Philadelphia during the Spanish flu pandemic of 1918. St. Louis practiced social distancing and saw only 1,703 deaths, while Philadelphia did not and suffered the worst outcomes nationally with over 16,000 dead in just half a year.

A 2007 study published in JAMA evaluated the effects of social distancing measures during the 1918 Spanish flu across 43 cities over 24 weeks. These measures included school closures, public gathering bans, and quarantine. The cities that adopted school closure and banned public gatherings with a median duration of 4 weeks (range of 1-10 weeks) saw the greatest reduction in deaths. The earlier these measures were implemented, the greatest delay in reaching peak mortality and the lowest peak mortality rates were observed. Further, the longer these measures were implemented, the lower the total mortality was.

Image source: National Geographic

So, how do we know when it’s safe for states to lift pandemic restrictions?

The American Enterprise Institute offers a road map to reopening, co-written by former U.S. Food and Drug Administration (FDA) commissioner Scott Gottlieb. In the piece, they offer a 4-step strategy:

Phase I: Slow the spread

We are currently in this phase through the measures we have already extensively discussed. These measures will need to be in place until each state is able to demonstrate a downward trend in cases over a 2-week period.

Phase II: State-by-state reopening

States should have extensive diagnostic testing capabilities, be able to offer testing to anyone with symptoms and have results in the same day. They should have sufficient PPE within the state to cover current and anticipated needs to handle a potential increase in cases when social distancing measures are relaxed. During this phase, schools and businesses re-open, but some physical distancing measures and limitations on gatherings would still be needed to prevent accelerated transmission.

Phase III: Establish immune protection and lift physical distancing

Social distancing restrictions can be lifted when effective mitigation tools are in place such as rapid contact tracing, case isolation, and effective treatments are established, or there is a safe and effective vaccine.

Phase IV: Rebuild our readiness for the next pandemic

This will require increased research and development initiatives to make sure we are never under-prepared again.

Bottom line: There is no safe shortcut to immunity. Social distancing is buying us time. Specifically, it is buying researchers time to learn what we are up against. It is buying scientists time to develop testing and treatment strategies and it is buying healthcare workers time to determine fast, efficient, and effective treatments without jeopardizing the health and safety of front-line workers.

Behind the scenes, there are literal armies of individuals across the globe undertaking the monumental task through sleepless nights and never-ending days to normalize life again. Policy makers, researchers, scientists, physicians, nurses, and other clinical and nonclinical staff are attempting to understand what could be considered a lifetime worth of knowledge in just a few short weeks and they are doing it at the expense of their own health and safety in many cases. There are many that are suffering the economic impacts of population-based quarantine and we must continue to work hard and fast to find a balance to preserve our economy and minimize the collateral damage of loss of human life.

The communication and comradery across specialties around the globe have been a humbling experience for me as a clinician and I have never been prouder to be a member of this profession. I don’t know the perfect formula, but I do believe we are on the right track. We are saving lives, and we are learning daily. It is going to take a global effort, from every individual who breaths air on this earth, to accomplish this goal. I have no doubt we will succeed in our combined efforts. My only hope is that we can hold onto the values of humility and sacrifice that we learn from this and better our world in other aspects moving forward.  

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Nicholas McManus
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