But innate immunity can also go awry. The reason why some patients have bad outcomes, including death, when they are suffering from COVID-19 is because of misregulation of innate immunity. This leads to something called a cytokine storm, which is characterized by uncontrolled secretion of cytokines that just does not turn off. SARS-CoV-2 infects organs in the respiratory tract, like the lungs. An overly exuberant immune reaction is especially perilous in the lung, where oxygen transfer into the blood occurs across thin membranes that can be damaged by cytokines. Some reports even suggest that SARS-CoV-2 does something very insidious. It turns off the production of interferons, the cytokines that block viral replication, while promoting the production of cytokines that cause other effects of inflammation, leading to a cytokine storm. As we learn more, we hope we will develop good therapeutics to help with such conditions. Common autoimmune diseases, such as rheumatoid arthritis, lupus, or inflammatory bowel disease, are also exacerbated by an overexuberant innate immune system. Drugs that try to block these effects have been developed, and indeed cytokine blockers are among the best-selling drugs on the market.
Putting It All Together
Our first line of defense against infectious microbes is our innate immune system. Cells of the innate immune system destroy microbes by ingesting them and by secreting chemicals such as cytokines. The innate immune system is remarkably efficient, and many viral invasions are eliminated by innate immunity. When patients are infected with SARS-CoV-2, which causes COVID-19, there are no symptoms for a few days. Up to 50 percent of those infected are either asymptomatic or have mild symptoms. Most likely, for the first few days after infection, and in those with mild or no symptoms, the innate immune system is able to largely control the virus through secretion of cytokines. For example, interferons can suppress viral replication.
The onset of symptoms is a sign that the innate immune system is fully activated, and this begins mobilization of the adaptive immune system. Many different cytokines are produced at this stage and patients feel very ill. Because SARS-CoV-2 infects the lungs, there is inflammation in the lung and this impairs the ability to transfer oxygen from the air to the blood, leading to respiratory distress. Around 5 to 7 days after the beginning of symptoms, patients appear to either get better or get much worse. The timing is consistent with the adaptive immune system kicking in.
B cells are a key component of adaptive immunity. Each B cell displays a receptor, its BCR, on its surface. The BCR on one B cell is likely to be distinct from the BCR on another B cell. If the BCR on a particular B cell can bind sufficiently strongly to a part of the spike proteins of a particular virus, then it begins to multiply. A Darwinian evolutionary process then takes place, which ultimately leads to the secretion of soluble forms of the BCR that bind even more avidly to the virus. These are antibodies. Antibodies migrate to tissues and bind to the infecting virus, preventing them from infecting cells. Phagocytic cells of the innate immune system also ingest and digest the antibody-bound viruses. There are many kinds of antibodies that arise during different stages of infection, and they combat the virus in different ways. These processes lead to IgM and then IgG antibodies becoming detectable in blood about 5–7 days after the beginning of symptoms.
But antibodies principally combat virus particles in blood or in the spaces between cells in tissues. T cells wage war against infected cells. Most T cells have a distinct receptor (TCR). Infected cells display protein fragments derived from the virus bound to our HLA proteins. If the TCR on a particular T cell can bind sufficiently strongly to the HLA-bound viral protein fragment on an infected cell, it gets activated and multiplies. The activated progeny migrate to tissues. In tissues, one class of activated T cells, killer T cells, kill infected cells that display the same viral protein fragment that originally activated the parent T cell. They do so by secreting chemicals that punch holes in the infected cell. Because the SARS-CoV-2 virus infects cells that have the ACE2 receptor, successful clearance of the virus likely involves killer T cells. In addition to killer T cells, there are other subtypes of activated T cells that perform functions like secreting cytokines and assisting B cells in the production of high-affinity antibodies.
Why do some patients infected with SARS-CoV-2 do more poorly than others? It is possible that in some patients, the immune response is defective or is activated too late to control the widespread growth and spread of the virus. Sometimes when the immune response senses incorrectly that the infection is out of control, it mounts an immune response that is out of proportion to the threat. Cytokines send out a general alert of infection. But when the immune system senses the potential that the body is in grave danger, immune cells can start to produce levels of cytokines that are too high, leading to a cytokine storm. This is especially precarious for respiratory infections, as inflammation due to cytokines causes swelling and fluids to leak into the air spaces in the lung, making it difficult to breathe. A cytokine storm can also cause the blood pressure to drop, putting the body into shock. In such a condition, uncontrolled blood clotting occurs and multiple organs begin to fail. While it may be possible to treat this condition by suppressing the immune system, in practice, it is difficult to do so with precision. This is because it is difficult to distinguish between the parts of the immune system that are fighting the virus from the parts that are threatening the survival of the patient.
If and when a person successfully clears an infection, most of the T and B cells that multiplied in response to the causative virus die. But a few remain as memory T and B cells, and antibody levels are elevated for some time. These ready and waiting warriors allow a rapid and robust response upon reinfection. This virus-specific immunological memory is the basis for vaccination. A vaccine aims to elicit memory T and B cells, and antibodies that are specific for the virus against which one wishes to protect the population. We will say much more about vaccines in chapter 7.
5 Spread and Mitigation of Pandemics
In Boccaccio’s famous novel, The Decameron, seven women and three men flee to a villa outside Florence to wait out the bubonic plague epidemic in 1348. To pass their time, they devise a system of storytelling, each being assigned to tell a story five nights a week for 2 weeks. Boccaccio ends the novel without telling us whether 2 weeks was enough time to let them return to their homes and resume normal lives. As weeks of lockdown continued during the COVID-19 pandemic, many of us felt as if we had just finished the Decameron, as we were left wondering when we could return safely to our normal lives.
How do we know how quickly a viral infection will spread? What steps do we need to take to mitigate the spread? When do we know that the peril has either passed or can be managed? These questions are very difficult to answer. In this chapter, we will describe the most important factors that influence the answers to these questions. We will also describe the essence of mathematical models that are used by epidemiologists to help guide public policy decisions during pandemics such as the COVID-19 crisis. These models can be useful for qualitative comparisons of the effect of different epidemic mitigation strategies on future outcomes. It is difficult, however, for these models to make numerically precise projections, especially in the early stages of an ongoing pandemic when the data are sparse and noisy.
The most important factors that influence whether a virus will cause a frightening infectious disease pandemic are how infectious the virus is and how fatal is the disease it causes. Let’s explore these concepts.
Mortality Rate
In February 2003, a Chinese medical professor from Guangdong Province traveled to Hong Kong. After checking into his hotel, he began to feel ill. He was admitted to a hospital, where he died two weeks later. Unknowingly, he infected up to 23 other individuals in the hotel, who later traveled to Singapore, Toronto, and Hanoi and initiated new rounds of infections. The person who traveled to Hanoi was an American businessman who was urgently hospitalized soon after arrival. Concerned that he might be infected with a new virus, his doctors in Vietn
am contacted the World Health Organization (WHO). The WHO sent an Italian physician, Carlo Urbani, to examine the patient. Urbani, who received the Nobel Peace Prize when he worked for Doctors without Borders, was alarmed by what he saw, and alerted the WHO of the possibility that a new virus might be circulating. Unfortunately, Urbani contracted the disease and died in Bangkok on March 29. In April 2003, the US CDC and Canadian authorities announced that they had isolated and identified a new virus. Thus began the SARS pandemic, which is caused by SARS-CoV, a coronavirus closely related to SARS-CoV-2. This virus was frighteningly deadly. SARS had a mortality rate of 10 percent—that is, 10 percent of infected people died. Another related coronavirus, MERS, which emerged in 2012, has a mortality rate of about 35 percent. One of the most lethal viruses is Ebola, which circulates in Central and Western Africa and has a mortality rate of more than 50 percent.
Viruses that cause diseases with a high mortality rate place a tremendous burden on the healthcare system. This is because almost everyone these viruses infect becomes seriously ill and requires hospitalization, often in the intensive care unit. The demand for care can overwhelm the capacity of the healthcare system, which, combined with the high mortality rate, results in a frightening situation. This problem is exacerbated by healthcare workers being especially at risk. This is because the virus’s lethality is not known in the beginning, and the need for special protective equipment for the safety of healthcare workers is not yet recognized. Early warning about the mortality rate of a viral infection is critical for protecting healthcare workers and taking steps to mitigate the spread of the disease.
Even though highly lethal viruses are frightening, they usually do not spread widely and cause global pandemics. This is because infected people quickly become too sick to move around and infect others. The spread of the virus is thus mostly limited to healthcare workers and family members. So, the outbreak is usually easily contained. At the other end of the spectrum are viruses that cause only a mild illness and almost no deaths. Because infected individuals do not feel terribly sick, they go about their daily lives and can spread the virus to many with whom they interact. But since almost no one falls very ill, these viruses are just nuisances, and not a public health hazard. Four common coronaviruses that cause about 30 percent of common colds are examples.
SARS-CoV-2 is a virus with multiple features that are ideal for causing a global pandemic. It has a low to moderate average mortality rate, estimated to be roughly 0.3–1 percent. This is much lower than the mortality rate for SARS, MERS, and Ebola, but higher than for seasonal flu (roughly 0.1 percent). Most infected people have mild to moderate symptoms or none at all, and the onset of symptoms of illness occurs several days after being exposed to the virus. This makes SARS-CoV-2 tricky because infected people can transmit the virus to others before exhibiting any symptoms. Since many infected people do not feel very sick when they are transmitting the virus, they go about their normal lives and spread the infection to others. With many people infected, even if a fraction of patients require hospitalization, the capacity of healthcare systems can be overwhelmed, even in well-resourced countries. In the period between 2010 and 2019, the number of people who died of influenza in the United States ranged from 12,000 to 61,000 people each year. Since the mortality rate for the COVID-19 is perhaps ten times higher than that for influenza, if a comparable number of people are infected, the relatively moderate mortality rate for COVID-19 can still cause a frighteningly large number of deaths. To know how many people will be infected by a virus, we need to know how infectious it is.
Infectiousness of a Virus
The Concept of R0
How quickly a viral infection can spread in a population is measured by a quantity called the basic reproductive number, which is abbreviated as R0 (pronounced “R naught”). After a person is infected with a virus, there is a period of time over which they can transmit the infection to others. R0 is equal to the average number of people an infected person infects during the infectious period when the entire population is susceptible to the virus. Suppose the infectious period of a virus is 10 days. To measure R0, we could follow 100 infected individuals around for 10 days after each got infected, determine who they were in contact with, and find out how many of them became infected. For each person, the number of people they infected would be somewhat different because of differences in social networks (how many people they interact with), differences in types of interactions (e.g., outdoors versus inside a restaurant), random chance, and many other factors. We can, however, take the total number of people infected by the people we followed and divide it by 100 to get the average value of R0. Why do we care about the value of R0?
Suppose a particular viral infection is associated with a value of R0 that is greater than 1—say, 2. So, one person infects two people, who then infect two others, and so on. How quickly the number of cases can grow in such a circumstance is illustrated by the likely apocryphal story of an Indian king who loved to play chess. He often challenged wise people and traveling sages to play with him, and offered them financial incentives. One day, such a person, who was an expert chess player, accepted the challenge. He told the king that, if he won, he would like only some grains of rice. The amount of rice would be determined by the king placing one grain of rice on the first square of the chessboard, two on the second square, four on the third square and so on—just like the growing number of infected people in our example. After the king lost, he ordered a bag of rice and started putting rice grains on the chessboard. Very soon, he realized that he had been duped. By the time he got to square number 64, the chessboard would be covered by more than 18,000,000,000,000,000,000 grains of rice! This type of growth is called exponential growth. So, if R0 is greater than 1, a viral infection can expand explosively and can quickly overwhelm the capacity of the healthcare system and cause a lot of deaths. Many common childhood diseases are highly infectious. Measles has an estimated R0 between 12-18, mumps has an estimated R0 between 10 and 12, and chicken pox has an estimated R0 between 10 and 12. In contrast, the 1918 pandemic-causing influenza virus had an estimated R0 of about 2, smallpox an R0 of roughly 5, polio between 5 and 7, and seasonal influenza about 1.5.
When R0 = 1, the virus does not spread rapidly across the population. One infected person can spread the virus to only one other person during the infectious period. So, once the first person recovers, the total number of infectious individuals does not change. This stable situation is referred to as an endemic infection. When R0 = 1, while the number of infectious people does not increase, the number of people who have been infected grows with time.
When R0 is less than 1, one individual can, on average, pass the virus to less than one other individual. Since partial individuals don’t exist, this means that one person may or may not pass the virus to another individual. For example, if we have a situation where the R0 is one half, there are 50 percent fewer infected people per infectious cycle. So, when R0 is less than 1, the number of infected people declines over time and eventually goes to zero, and the virus dies out.
The length of the infectious period is another factor that is important in estimating how quickly a virus spreads. If, for example, R0 is 2 and the infectious period is 100 days, an infected person transmits the virus to one other person every 50 days. For the same R0, if the infectious period is 10 days, a new person would be infected every 5 days. A virus characterized by a high value of R0 and a short infectious period spreads frighteningly fast.
R0 Is Not an Absolute Number
While R0 is often discussed as if it is an absolute number for a given virus, it is not. Its value depends on many factors. A virus that is spread by human-to-human contact will have a higher R0 in a city where people live close together than in a rural area where much less human contact occurs. This is why respiratory infections spread more rapidly in cities like New York, Paris, and London compared with rural areas. Social customs in different countries can also influence the value of R0. In Italy,
where multiple generations of families live together, R0 will likely be higher in comparison to countries where nuclear families are the norm. R0 can vary with the time of the year. For example, it could be higher in the winter because the virus is more stable in cool dry weather, and/or because people are confined indoors in the winter leading to more social contact in confined environments. This is true for influenza and the viruses that cause the common cold.
How quickly a virus spreads also depends on the stage of a disease epidemic. In early stages, most people have not been infected and so are susceptible to the disease. This is the stage when the number of infected people grows exponentially. As the infection progresses, an increasing number of people become infected, and some recover and are usually immune. So, the number of people susceptible to infection keeps declining. If an infected person typically meets 100 people during the infectious period, in the early stages of an epidemic all are susceptible. If R0 for a particular virus in this social setting is 4, this person would infect four people. Now suppose that in the late stages of an infection 97 percent of people have recovered from the infection. Then, an infected person who encounters 100 people in the infectious period would interact with only three susceptible people, and would certainly not infect four new people. So, the virus would spread more slowly. While this example is contrived to make a point, you can see how the growth in the number of new cases changes with the stage of an epidemic by just looking at data for the COVID-19 pandemic. You can find this data on the website of the Institute for Health Metrics and Evaluation or the similar site maintained by Johns Hopkins University. The growth in the number of cases is exponential only for the first few hundred cases in any US county or any nation. After that the growth rate is slower because a newly infected person encounters fewer susceptible people. For example, if one person starts to spread the infection to their social network and another person does the same, soon their social networks overlap. The two people cannot both infect a common person in their social network.
Viruses, Pandemics, and Immunity Page 9