Covid-19 Herd Immunity, Social Distancing’s Effect on Economics and Post-First Wave Considerations
By Stuart M. Caplen, MD
One of the biggest questions during this COVID-19 pandemic is when will it be safe to open up society again and allow people to go back to work and school. So far no “magic drug” that can significantly attenuate or rapidly cure the infection has been discovered or scientifically tested. A vaccine would certainly be helpful in that regard, but right now predictions of the time to actually develop an effective vaccine are 12 to 18 months. That leaves social distancing/isolation/quarantine and herd immunity as the only ways to effectively stop the virus spread.
Herd immunity is when enough people have had the disease that it no longer is passed within that group and provides protection for others who do not have antibodies. The percentage needed for herd immunity is varied. In diphtheria for example, the percentage is estimated to be 85%. A rough estimate for COVID-19 is that at least 60% of people need to be infected and have antibodies to produce effective herd immunity. How close are we to that? In New York City as of April 12th, 103,208 people had tested positive for COVID-19. With a population of 8.6 million, the case rate is 1.2% of people in New York City who are known to have had the disease. This does not count the asymptomatic cases, the people who could not or did not get tested and the close to 30% false negative rate of the current PCR (polymerase chain reaction) test. If the occult infection rate in New York City is even 20 times the known rate, that would mean only 24% of people had the disease, far less than needed for herd immunity. The actual number of infected will not be known for certain until there is wide-spread antibody testing available. However researchers have drawn blood samples on 500 people in Gangelt, one of the hardest hit cities with COVID-19 in Germany. They found only 15% of people had antibodies or were currently infected (14% had antibodies, 2% infected).[7,8] From that data you can predict that it would take about three more waves of infection to achieve herd immunity in that town. Thus the ability to achieve herd immunity in a short time frame without crippling the health care system is probably not achievable for COVID-19.
One other approach is that you do nothing to stop the spread, let as many people get infected as possible, regardless of the costs to the health care system or the number of deaths. Theoretically it would allow the economy to partially function and more quickly achieve herd immunity, which lets society move on much faster economically. For example, Sweden at the present time has not locked down its society in any significant manner, except for isolating confirmed cases. Will Sweden’s current policy of keeping society open lead to superior results economically during the recovery period? There are some lessons from the 1918 flu pandemic. A recent paper found that areas in the US that had a higher incidence of influenza during the 1918 pandemic experienced a sharp and persistent decline in economic activity. However it also found that cities that intervened earlier and more aggressively saw more rapid economic growth after the pandemic ended than cities that delayed intervention. It concluded that non-pharmaceutical interventions like distancing not only lowered mortality, but also mitigated the adverse economic disruption of the pandemic.
So what will happen after this first wave of disease lessens? No one really knows, as it is uncharted territory and there are a lot of unanswered questions. How long is the immunity good for? Are there people in whom the virus resides at low levels after feeling better who can get relapses? Can you reduce the level of disease to zero? How do you end the shutdown without creating more waves of this disease? Given how fast the virus spreads in high density areas and the lack of herd immunity, the case load in those areas may not go to zero. There will probably be recurring waves of COVID-19 disease as society opens up, similar to the 1918 flu pandemic, until a vaccine is available. It is also possible if the case load becomes too high, additional societal shutdowns may be needed temporarily to protect the healthcare system from being inundated.
Whatever the actual scenario turns out to be, the current situation is aptly described by Winston Churchill’s words during World War II; “Now this is not the end. It is not even the beginning of the end. But it is, perhaps, the end of the beginning.”
Addendum: On April 23rd the results of 3000 random antibody tests done throughout New York State were released. It found 13.9% of New York State residents had been infected with COVID-19. In New York City the percentage of people previously infected with COVID-19 was 21.2%.
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The effective reproductive number (R), the measure of transmissibility over time through the course of the Covid-19 epidemic, must be considered when calculating the effective minimum prevalence rate needed to secure our nation’s herd immunity. The following is useful in describing a measure of transmissibility: “The effective reproduction number, R, is defined as the average number of secondary cases that one index case generates over the course of its infectious period.” This can “then be estimated over time (ie, Rt) through the course of the epidemic.” The higher the effective R, the higher the minimum proportion (%) of the total population that must recover from COVID-19 to protect the population at large. Previous estimates of the effective R for the novel coronavirus might be as high as 6.0. If so, the required minimum percent needed to be infected rises to 80%.
Other factors that might also raise or lower this minimum number include:
the expected duration of immunity;
the extent of immunity in those previously infected: none, partial or complete;
the likelihood that previous immunity developed from other coronavirus infections will impart partial immunity to COVID-19.
Alimohamadi Y, Taghdir M, Sepandi M. The estimate of the basic reproduction number for novel coronavirus disease (COVID-19): a systematic review and meta-analysis. Journal of Preventive Medicine and Public Health. March 20, 2020. doi: https://doi.org/10.3961/jpmph.20.076.
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Cowling B, Lau M, Ho L, et al. The effective reproduction number of pandemic influenza: prospective estimation. Epidemiology. 2010;21:842–846. doi: 10.1097/EDE.0b013e3181f20977.
ABOUT THE AUTHOR
Stuart M. Caplen, MD, FACEP, MSM
Dr. Caplen is a former emergency physician and emergency department medical director, now retired from clinical practice. His current interests include how quality is produced and maintained in health care, and he recently achieved greenbelt certification in lean/six sigma.
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