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Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection is a global health problem; this has caused thousands of deaths around the world. This infection induces hematologic alterations, and it is necessary to recognize predictive biomarkers to address the need for hospitalization or the severity of the disease. This study aimed to analyze different parameters in outpatients and hospitalized patients infected with SARS-CoV-2 and determine whether hematic biometry can be used for prognosis rapidly. We analyzed 689 patients, of whom 355 were outpatients (162 women and 193 men) and 334 required hospitalization (197 men and 137 women). The average age of the hospitalized patients was 46 years (men, 49 years; women, 52 years), whereas the average age of the outpatients was 49 years (men, 51 years; women, 44 years). Hematologic parameters were analyzed and compared between the outpatients and hospitalized patients. The patients were divided into groups by age and sex. We found that in the hospitalized patients, the erythrocyte, hematocrit, and hemoglobin levels decreased, whereas the outpatients did not experience changes in the erythroid series. In leukocytes, these increased significantly, as they did in neutrophils; however, lymphocytopenia was observed. In the outpatients, we observed normal levels of neutrophils and lymphopenia. We can conclude that hematic biometry can be used as a biomarker, and the relation between neutrophils and lymphocytes is indicated for understanding the development and prognosis of the disease., Competing Interests: Conflict of Interest Disclosure The authors do not have any conflicts of interest to declare in relation to this work., (Copyright © 2023. Published by Elsevier Inc.)

Governments have implemented measures to minimize SARS-CoV-2 spread. However, these measures were relaxed, and the appearance of new variants has prompted periods of high contagion known as waves. In Mexico, four waves distributed between July and August 2020, January and February 2021, August and September 2021, and January and February 2022 have appeared. Current health policies discourage mass sampling, preferring to focus on the corrective treatment of severe cases. Outpatients are only advised to undergo brief voluntary confinement and symptomatic treatment, with no follow-up. Therefore, the present study aimed to analyze sex, age, and viral load in outpatients during the four waves in a medium-sized city in Mexico. For each wave, the date of peak contagion was identified, and data were collected within ±15 days. In this regard, data from 916 patients (434 men and 482 women) were analyzed. The age range of positive patients (37-45 years) presented a higher frequency during the first and third waves, while 28-36 years was the most frequent age range during the second and fourth waves, while the viral load values were significantly higher, for both sexes, during the fourth wave. Obtained data of COVID-19 prevalence in population segments can be used for decision-making in the design of effective public health policies.

The COVID-19 pandemic highlighted health systems vulnerabilities, as well as thoughtlessness by governments and society. Due to the nature of this contingency, the use of geographic information systems (GIS) is essential to understand the SARS-CoV-2 distribution dynamics within a defined geographic area. This work was performed in Tepic, a medium-sized city in Mexico. The residence of 834 COVID-19 infected individuals was georeferenced and categorized by viral load (Ct). The analysis took place during the maximum contagion of the first four waves of COVID-19 in Mexico, analyzing 158, 254, 143, and 279 cases in each wave respectively. Then heatmaps were built and categorized into five areas ranging from very low to very high risk of contagion, finding that the second wave exhibited a greater number of cases with a high viral load. Additionally, a spatial analysis was performed to measure urban areas with a higher risk of contagion, during this wave this area had 19,203.08 km 2 (36.11% of the city). Therefore, a kernel density spatial model integrated by meaningful variables such as the number of infected subjects, viral load, and place of residence in cities, to establish geographic zones with different degrees of infection risk, could be useful for decision-making in future epidemic events.

Introduction: Former studies have shown that hematologic parameters are affected by the SARS-CoV-2 infection which has caused a global health problem. Therefore, this research aims to identify the most frequent symptoms and comorbidities in SARS-CoV-2 infected outpatients; besides, to analyze hematological parameters and their correlation with cycle threshold (Ct) values., Methods: We analyzed a total of sixty outpatients with SARS-CoV-2 infection. They were divided according to sex. Afterward, a questionnaire was carried out to find out their symptoms and comorbidities. Additionally, blood biometry data were correlated with the Ct value, respectively., Results: Sixty patients were analyzed; the mean age was 43 years. All patients were from Nayarit, Mexico. The frequency index showed that the main symptoms were headache and anosmia, and the comorbidities were obesity and smoking. The analysis of blood biometry showed a clear increase in red blood cells (RBC) related parameters in women. In both sexes an increase in the number of white blood cells (WBC) was observed. Also, all the hematological alterations correlated with the grade of infection., Conclusion: Headache and anosmia are the most common symptoms according to the frequency index, the main comorbidities were obesity and smoking. Also, there is a Ct value correlation with hematological parameters (WBC, mean corpuscular volume, mean corpuscular hemoglobin, hemoglobin); they can be used as a prognostic marker of infection., (© 2021 John Wiley & Sons Ltd.)

Objective: To perform an improved large-scale SARS-CoV-2 detection on pooled tests of asymptomatic workers., Methods: qRT-PCR validation of the SARS-CoV-2 detection in salivae samples and saliva pools and working-group saliva pooling and testing for SARS-CoV-2., Results: We found a high Cycle threshold correlation (r = 0.9099) between swabs and saliva samples. Then, through the pooling strategy, we detected that 18/360 (5%) of individual saliva samples were SARS-CoV-2 positive. Saliva-pooling efficiency (360 of test sample/30 individual PCR) was higher (5.45) than the reported for swabbing group-testing and we spared 82% of the PCR reagents as well as sampling and personal protection equipment., Conclusion: Through this simplified and less expensive procedure, we detected in a short time asymptomatic-infected SARS-CoV-2-carriers that were isolated from their co-workers, thus, this methodology can be implemented in different workplaces to ensure consumers that employees are not infectious., Competing Interests: MI Giroń-Pérez, DA Giroń-Pérez, Ruiz-Manzano, Benitez-Trinidad, Ventura-Ramoń, Covantes-Rosales, Ojeda-Durań, Mercado-Salgado, Toledo-Ibarra, and Díaz-Reséndiz have no relationships/conditions/circumstances that present potential conflict of interest., (Copyright © 2021 American College of Occupational and Environmental Medicine.)