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The new coronavirus has given us all a rapid course in epidemiology, and scientists, the government and governments around the world are trying to understand how the infection should be managed and managed.
– There are some really big challenges. One, of course, is all the uncertainties about the biology of the virus that still remains. And we don’t know how different age groups contribute to the spread, or why people are so affected by the disease, says Sarah Cobey, head of the Cobey Laboratory in the Department of Ecology and Evolution at the University of Chicago.
His research group has long experience in mathematical models for the spread of influenza. In an article in the journal Science, Sarah Cobey writes about how past pandemic studies can be used to make some predictions about what might happen to covid-19.
– The way the United States copes with the outbreak has been extremely fragmented. There is a great need for epidemiological assistance at the local level. We try to offer that, says Sarah Cobey.
For the past 200 years At least 100 million people died when the world was hit by seven waves of cholera, four new strains of the influenza, tuberculosis and HIV viruses. This is the first time that a coronavirus is causing a pandemic, but there are still two lessons to be learned from history: the new coronavirus is here to stop, and because it is so contagious, we will have to keep choosing between the widespread spread of the virus. illness and serious illness. restrictions in society, at least until there is a vaccine, according to Sarah Cobey.
Another lesson is that it is difficult to compare the effects of infection control in different countries and areas. A rapid decrease in the number of cases detected or a small epidemic can be seen as evidence that a certain measure has been extra effective or that the herd’s immunity has been achieved. But relationships are very complex when the spread of infection can vary throughout the year and when people move between different groups and places.
– For example, we do not know if the infection is affected by the seasons. This is true for other respiratory tract viruses, which generally occur in winter in countries with temperate climates, but how exactly it works is an old unsolved problem. Now that we are in the midst of a pandemic, it is even harder to know what to expect, says Sarah Cobey.
An epidemic is disappearing. when the virus can no longer find new hosts to infect. It can happen when we have achieved herd immunity, that is, a sufficient number in a group is immune, either because they have already been sick or because they are vaccinated. The so-called R0 number, which indicates how many others an ill person infects on average, can be used to calculate both the proportion of a population that can become infected and the amount of the immune system that is needed to achieve herd immunity. As new children who can become infected are born, the herd’s immunity is constantly slackened and we will likely be able to live with the new coronavirus for many years.
The Asia and Hong Kong pandemics of 1957 and 1968 were eventually extinguished, as many were immune to other influenza viruses.
– The dynamics over time and the way in which the different age groups were affected were greatly influenced by the fact that there was immunity to the influenza virus that was circulating before, and that it took the initiative of the epidemics. But there is still no evidence to suggest that immunity to other coronaviruses provides protection now, says Sarah Cobey.
People’s behavior has consequences. for the spread of infection, and models should also take this into account. For example, semesters and school breaks affected how measles spread in England and Wales before there was a vaccine.
– Epidemics were governed by how many children came into contact with each other. Of course, it was easier to predict, since the measles center was run primarily by school-age children. With the new virus, children don’t seem to play the same role.
Despite all the uncertainties, it is still possible to make useful models.
– The problem here in the United States is that one of the worst models has received the most attention. It is a very, very, very bad model. At the White House, they went completely insane. It’s so stupid, because it really gives bad mathematical models a reputation, says Sarah Cobey.
The model comes from the Institute for Health Measurement and Assessment, IHME, University of Washington.
– It is a statistical model that does not make assumptions about the underlying biological processes. He’s just trying to find patterns. And then it cannot give an idea of the different possible scenarios, because we are in the midst of a pandemic that we have never experienced before.
Instead, models are needed According to Sarah Cobey, depending on how the virus can be transmitted and how different measures, such as increasing the physical distance, affect the spread of the infection.
“I think such models are really crucial if we want to make rational decisions in the future,” she says.
The fact that the results of different models can vary greatly is not a problem, and it is also quite natural in this situation.
– All researchers are working on this overtime, and we are in the midst of an avalanche of new data, and we often make slightly different assumptions. This is part of the process, where we learn how our assumptions affect the results. So precisely that the models do not match is really what we need now. We can only make good decisions by presenting different evidence and reasoning carefully based on it, says Sarah Cobey.
