Rapid evolution of SARS-CoV-2 challenges human defenses.

The race between pathogens and their hosts is a major evolutionary driver, where both reshuffle their genomes to overcome and reorganize the defenses for infection, respectively. Evolutionary theory helps formulate predictions on the future evolutionary dynamics of SARS-CoV-2, which can be monitored through unprecedented real-time tracking of SARS-CoV-2 population genomics at the global scale. Here we quantify the accelerating evolution of SARS-CoV-2 by tracking the SARS-CoV-2 mutation globally, with a focus on the Receptor Binding Domain (RBD) of the spike protein determining infection success. We estimate that the > 820 million people that had been infected by October 5, 2021, produced up to 1021 copies of the virus, with 12 new effective RBD variants appearing, on average, daily. Doubling of the number of RBD variants every 89 days, followed by selection of the most infective variants challenges our defenses and calls for a shift to anticipatory, rather than reactive tactics involving collaborative global sequencing and vaccination.

Optimal control of an SIR epidemic through finite-time non-pharmaceutical intervention.

We consider the problem of controlling an SIR-model epidemic by temporarily reducing the rate of contact within a population. The control takes the form of a multiplicative reduction in the contact rate of infectious individuals. The control is allowed to be applied only over a finite time interval, while the objective is to minimize the total number of individuals infected in the long-time limit, subject to some cost function for the control. We first consider the no-cost scenario and analytically determine the optimal control and solution. We then study solutions when a cost of intervention is included, as well as a cost associated with overwhelming the available medical resources. Examples are studied through the numerical solution of the associated Hamilton-Jacobi-Bellman equation. Finally, we provide some examples related directly to the current pandemic.

Assessing the age- and gender-dependence of the severity and case fatality rates of COVID-19 disease in Spain.

Background: The assessment of the severity and case fatality rates of coronavirus disease 2019 (COVID-19) and the determinants of its variation is essential for planning health resources and responding to the pandemic. The interpretation of case fatality rates (CFRs) remains a challenge due to different biases associated with surveillance and reporting. For example, rates may be affected by preferential ascertainment of severe cases and time delay from disease onset to death. Using data from Spain, we demonstrate how some of these biases may be corrected when estimating severity and case fatality rates by age group and gender, and identify issues that may affect the correct interpretation of the results. Methods: Crude CFRs are estimated by dividing the total number of deaths by the total number of confirmed cases. CFRs adjusted for preferential ascertainment of severe cases are obtained by assuming a uniform attack rate in all population groups, and using demography-adjusted under-ascertainment rates. CFRs adjusted for the delay between disease onset and death are estimated by using as denominator the number of cases that could have a clinical outcome by the time rates are calculated. A sensitivity analysis is carried out to compare CFRs obtained using different levels of ascertainment and different distributions for the time from disease onset to death. Results: COVID-19 outcomes are highly influenced by age and gender. Different assumptions yield different CFR values but in all scenarios CFRs are higher in old ages and males. Conclusions: The procedures used to obtain the CFR estimates require strong assumptions and although the interpretation of their magnitude should be treated with caution, the differences observed by age and gender are fundamental underpinnings to inform decision-making.