Face mask use and viral load in patients with mild symptoms of COVID-19.

Objective: Previous studies indicated that face masks reduce the probability of infection by SARS-CoV-2 but did not examine the relationship between SARS-CoV-2 viral load and mask usage. This study analyzed this relationship.

Methods: This cross-sectional study evaluated patients admitted to a public Emergency Care Unit in Belo Horizonte, MG, Brazil, between October 2020 and March 2021.

RT-qPCR-based pool testing for the diagnosis of COVID-19.

This study proposes a strategy for large-scale testing among a large number of people for the early diagnosis of COVID-19 to elucidate the epidemiological situation. Pool testing involves the analysis of pooled samples. This study aimed to discuss a reverse transcription technique followed by quantitative real-time polymerase chain reaction using pool testing to detect SARS-CoV-2 in nasopharyngeal swab samples.

Contributions to Dynamic Analysis of Differential Evolution Algorithms.

The Differential Evolution (DE) algorithm is one of the most successful evolutionary computation techniques. However, its structure is not trivially translatable in terms of mathematical transformations that describe its population dynamics. In this work, analytical expressions are developed for the probability of enhancement of individuals after each application of a mutation operator followed by a crossover operation, assuming a population distributed radially around the optimum for the sphere objective function, considering the DE/rand/1/bin and the DE/rand/1/exp algorithm versions.

Self-collected nasopharyngeal swab and molecular test using pool testing as strategies to detect severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2): feasibility in medical students at the Universidade Federal de Minas Gerais, Brazil, 2021.

Objective: To show the feasibility of the combined use of self-collected nasopharyngeal swab and pool testing to detect SARS-CoV-2 in epidemiological surveys.

Methods: This experience included a sample of 154 students at the Universidade Federal de Minas Gerais, who performed self-collected nasopharyngeal swab in individual cabins and without supervision. The molecular test was performed using the pool testing technique.

SARS-CoV-2 IgG Seroprevalence among Blood Donors as a Monitor of the COVID-19 Epidemic, Brazil.

During epidemics, data from different sources can provide information on varying aspects of the epidemic process. Serology-based epidemiologic surveys could be used to compose a consistent epidemic scenario. We assessed the seroprevalence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) IgG in serum samples collected from 7,837 blood donors in 7 cities of Brazil during March-December 2020.

Detection of SARS-CoV-2 through pool testing for COVID-19: an integrative review.

Introduction: The pool testing technique optimizes the number of tests performed and reduces the delivery time of results, which is an interesting strategy for the health crisis caused by the COVID-19 pandemic. This integrative review investigated studies in which pool testing was carried out for epidemiological or screening purposes to analyze its clinical or cost effectiveness and assessed the applicability of this method in high-, middle-, and low-income countries.

Methods: This integrative review used primary studies published in the MEDLINE, EMBASE, Literatura Latino-Americana e do Caribe em Ciências da Saúde (LILACS), and Cochrane Library databases.

Comparing community mobility reduction between first and second COVID-19 waves.

Background: In this paper, we conduct a mobility reduction rate comparison between the first and second COVID-19 waves in several localities from America and Europe using Google community mobility reports (CMR) data. Through multi-dimensional visualization, we are able to compare the reduction in mobility from the different lockdown periods for each locality selected, simultaneously considering multiple place categories provided in CMR. In addition, our analysis comprises a 56-day lockdown period for each locality and COVID-19 wave, which we analyze both as 56-day periods and as 14-day consecutive windows.

Application of Optimal Control of Infectious Diseases in a Model-Free Scenario.

Optimal control for infectious diseases has received increasing attention over the past few decades. In general, a combination of cost state variables and control effort have been applied as cost indices. Many important results have been reported.

Adjusting the Cut-Off and Maximum Pool Size in RT-qPCR Pool Testing for SARS-CoV-2.

Reverse transcription quantitative real-time polymerase chain reaction (RT-qPCR) to detect SARS-CoV-2 RNA is an essential test to monitor the occurrence of COVID-19. A methodology is proposed for the determination of maximum pool size and adjustments of cut-off values of cycle threshold (Ct in RT-qPCR pool testing, to compensate for the dilution caused by pooling. The trade-off between pool size and test sensitivity is stated explicitly.

Vertical social distancing policy is ineffective to contain the COVID-19 pandemic.

Considering numerical simulations, this study shows that the so-called vertical social distancing health policy is ineffective to contain the COVID-19 pandemic. We present the SEIR-Net model, for a network of social group interactions, as a development of the classic mathematical model of SEIR epidemics (Susceptible-Exposed-Infected (symptomatic and asymptomatic)-Removed). In the SEIR-Net model, we can simulate social contacts between groups divided by age groups and analyze different strategies of social distancing.

Data-driven inference for the spatial scan statistic.

Background: Kulldorff's spatial scan statistic for aggregated area maps searches for clusters of cases without specifying their size (number of areas) or geographic location in advance. Their statistical significance is tested while adjusting for the multiple testing inherent in such a procedure. However, as is shown in this work, this adjustment is not done in an even manner for all possible cluster sizes.

Multi-objective evolutionary optimization of biological pest control with impulsive dynamics in soybean crops.

The biological pest control in agriculture, an environment-friendly practice, maintains the density of pests below an economic injury level by releasing a suitable quantity of their natural enemies. This work proposes a multi-objective numerical solution to biological pest control for soybean crops, considering both the cost of application of the control action and the cost of economic damages. The system model is nonlinear with impulsive control dynamics, in order to cope more effectively with the actual control action to be applied, which should be performed in a finite number of discrete time instants.

The Q-norm complexity measure and the minimum gradient method: a novel approach to the machine learning structural risk minimization problem.

This paper presents a novel approach for dealing with the structural risk minimization (SRM) applied to a general setting of the machine learning problem. The formulation is based on the fundamental concept that supervised learning is a bi-objective optimization problem in which two conflicting objectives should be minimized. The objectives are related to the empirical training error and the machine complexity.

Local search with quadratic approximations into memetic algorithms for optimization with multiple criteria.

This paper proposes a local search optimizer that, employed as an additional operator in multiobjective evolutionary techniques, can help to find more precise estimates of the Pareto-optimal surface with a smaller cost of function evaluation. The new operator employs quadratic approximations of the objective functions and constraints, which are built using only the function samples already produced by the usual evolutionary algorithm function evaluations. The local search phase consists of solving the auxiliary multiobjective quadratic optimization problem defined from the quadratic approximations, scalarized via a goal attainment formulation using an LMI solver.