Comparative Epidemiological Assessment of Monkeypox Infections on a Global and Continental Scale Using Logistic and Gompertz Mathematical Models

The monkeypox virus (MPXV) has caused an unusual epidemiological scenario-an epidemic within a pandemic (COVID-19). Despite the inherent evolutionary and adaptive capacity of poxviruses, one of the potential triggers for the emergence of this epidemic was the change in the status of orthopoxvirus vaccination and eradication programs. This epidemic outbreak of HMPX spread worldwide, with a notable frequency in Europe, North America, and South America. Due to these particularities, the objective of the present study was to assess and compare cases of HMPX in these geographical regions through logistic and Gompertz mathematical modeling over one year since its inception. We estimated the highest contagion rates (people per day) of 690, 230, 278, and 206 for the world, Europe, North America, and South America, respectively, in the logistic model. The equivalent values for the Gompertz model were 696, 268, 308, and 202 for the highest contagion rates. The Kruskal-Wallis Test indicated different means among the geographical regions affected by HMPX regarding case velocity, and the Wilcoxon pairwise test indicated the absence of significant differences between the case velocity means between Europe and South America. The coefficient of determination (R2) values in the logistic model varied from 0.8720 to 0.9023, and in the Gompertz model, they ranged from 0.9881 to 0.9988, indicating a better fit to the actual data when using the Gompertz model. The estimated basic reproduction numbers (R0) were more consistent in the logistic model, varying from 1.71 to 1.94 in the graphical method and from 1.75 to 1.95 in the analytical method. The comparative assessment of these mathematical modeling approaches permitted the establishment of the Gompertz model as the better-fitting model for the data and the logistic model for the R0. However, both models successfully represented the actual HMPX case data. The present study estimated relevant epidemiological data to understand better the geographic similarities and differences in the dynamics of HMPX.

Mathematical Modeling of COVID-19 Cases and Deaths and the Impact of Vaccinations during Three Years of the Pandemic in Peru

The COVID-19 pandemic has caused widespread infections, deaths, and substantial economic losses. Vaccine development efforts have led to authorized candidates reducing hospitalizations and mortality, although variant emergence remains a concern. Peru faced a significant impact due to healthcare deficiencies. This study employed logistic regression to mathematically model COVID-19's dynamics in Peru over three years and assessed the correlations between cases, deaths, and people vaccinated. We estimated the critical time (tc) for cases (627 days), deaths (389 days), and people vaccinated (268 days), which led to the maximum speed values on those days. Negative correlations were identified between people vaccinated and cases (-0.40) and between people vaccinated and deaths (-0.75), suggesting reciprocal relationships between those pairs of variables. In addition, Granger causality tests determined that the vaccinated population dynamics can be used to forecast the behavior of deaths (p-value < 0.05), evidencing the impact of vaccinations against COVID-19. Also, the coefficient of determination (R2) indicated a robust representation of the real data. Using the Peruvian context as an example case, the logistic model's projections of cases, deaths, and vaccinations provide crucial insights into the pandemic, guiding public health tactics and reaffirming the essential role of vaccinations and resource distribution for an effective fight against COVID-19.

Physicochemical Evaluation of Cushuro (Nostoc sphaericum Vaucher ex Bornet & Flahault) in the Region of Moquegua for Food Purposes

The cyanobacterium Nostoc sp. contains considerable amounts of protein, iron, and calcium that could mitigate the problems of anemia and malnutrition in humans. However, the nutritional value of the edible species Nostoc sphaericum Vaucher ex Bornet & Flahault, which grows in the Moquegua region, is unknown. Descriptive research was developed, and samples were obtained from the community of Aruntaya, located in the region of Moquegua. Water samples were taken at two different points (spring and reservoir), and samples of the cyanobacteria were taken in the reservoir. The design used was completely randomized, with three repetitions. Sixteen characteristics associated with the water collected at two points were evaluated, and from the nutritional point of view, seven characteristics were evaluated in the collected algae. The physicochemical characteristics were determined using methods established in the Codex Alimentarius. For the morphological characterization at the macroscopic level, it was observed that the seaweed collected was spherical in shape, grayish-green in color, soft to the touch, and palatable. After carrying out the physicochemical and morphological characterization of the collected samples, it was verified that all were of N. sphaericum. When comparing the sixteen characteristics related to water at the two collection sites, highly significant differences (p < 0.01) were observed for most of the variables evaluated. The average data of the characteristics of the algae showed protein values of 28.18 ± 0.33%, carbohydrates of 62.07 ± 0.69%, fat of 0.71 ± 0.02%, fiber of 0.91 ± 0.02%, ash of 7.68 ± 0.10%, and moisture of 0.22 ± 0.01%. Likewise, calcium reported an average value of 377.80 ± 1.43 mg/100 g and iron of 4.76 ± 0.08 mg/100 g. High correlations (positive and negative) were obtained by evaluating seven characteristics associated with the reservoir water where the algae grew in relation to eight nutritional characteristics of the algae. In relation to the nutritional value, the amounts of protein, iron, and calcium exceed the main foods of daily intake. Therefore, it could be considered a nutritious food to combat anemia and malnutrition.