Since the beginning of the pandemic, and especially the beginning of the measures of distancing and social isolation, we are seeing that more and more colleagues in the area of Ecology have started to participate in discussions about the expansion of the pandemic, in different degrees. Much information is beginning to circulate about the spread of the disease and many are using their knowledge of statistics and computing to analyze patterns and build models for complex systems, trying to understand what is happening.
The basic epidemiological models are based on the same principle, but the idea is that they are evaluating not the growth of the (human) population itself, but in fact the dynamics of “compartments” of this population, starting with the individuals who become infected. In the case of COVID-19 that we are dealing with, for example, as the virus spreads the number of infected people increases and some of them show symptoms and eventually some die. The most talked about parameter is the so-called R0, which is the average number of new people that each infected person is capable of contaminating, under "ideal" conditions of transmission. But, on the other hand, part of the population recovers and becomes immune, so that as the epidemic increases and more and more people become ill, the total number of people who can be infected is decreasing. This creates the logistical effect and, in fact, there comes a time when fewer and fewer people can become infected. In this way, the epidemic starts to subside quickly and tends to disappear. This is the general idea of the so-called "SIR" class compartment models (of Susceptible, Infected and Recovered) that have been so used to show the impact of social isolation measures in terms of "flattening" the epidemic curve. This flattening occurs because, with greater isolation and social distance, the R0 tends to be less, as the contagion is less. Thus, the epidemic advances more slowly, giving more time for health systems to organize and be able to receive sick patients in the best possible way.
Considering this scenario and their basic knowledge in Population Ecology, certainly many ecologists can assist, in different ways, in fighting an epidemic and help health professionals, managers and decision makers in times of crisis. There are certainly many ecologists and biologists working "on an emergency basis" on this issue. In fact, thinking in a historical context, this interest of ecologists in epidemiology and this strong potential for integration that we are seeing here is not something recent.
We therefore need to talk a lot with colleagues in the medical and health fields, epidemiologists and infectologists, as well as other health professionals, who will have a much better understanding of the phenomenon "itself". They better understand what the different compartments mean and in what situations people are “transferred” between them, for example, what leads a person to hospitalization, or in what conditions the disease gets worse and the patient needs an ICU .
This can certainly be put in a broader context and there is ample evidence that the pandemic is rapidly changing the way we do science. For years, we have discussed, mainly in Brazil, questions about collaborations between different areas of Science, in terms of multi, inter and transdisciplinarity. Despite the potential importance, I always thought that many of these discussions seemed distant reality and very difficult to implement, mainly due to the social structure of the academy.
This also brings us to another important point, as it is useless to build the models or do sophisticated statistical analysis if this is not in any way useful to decision makers in government agencies. The interaction between the academy and the public agencies involved in this issue is quite complex and goes through a series of problems. On the one hand, it is quite possible that the agencies are not interested in the analyzes carried out because the managers may not fully understand how they work, or because they do not trust the parameters used by the researchers. On the other hand, this clearly suggests that this scientific knowledge, in order to be applied, needs to be built collectively between researchers and people who will, in a second moment, use this information to make decisions.
This discussion about the collaboration between researchers and managers or decision makers takes us to the next level of need for integration, as it is not enough to think about public health and isolation and distance measures, it is necessary to evaluate a whole socioeconomic scenario and political in Government decisions (the discussion is not as simple and trivial as it has been done, in terms of "choosing" between "lives and the economy"). But that question so making decisions about complex scenarios and with a high degree of uncertainty is another matter, very complicated in itself.