: Sentinel surveillance in the early stage of the COVID-19 pandemic in Mexico represented a significant cost reduction and was useful in estimating the population infected with SARS-CoV-2. However, it also implied that many patients were not screened and therefore had no accurate diagnosis. In this study, we carried out a population-based SARS-CoV-2 screening in Mexico to evaluate the COVID-19-related symptoms and their weighting in predicting SARS-CoV-2 infection. We also discuss this data in the context of the operational definition of suspected cases of COVID-19 established by the Mexican Health Authority's consensus. : One thousand two hundred seventy-nine subjects were included. They were screened for SARS-CoV-2 using RT-PCR. The weighting of COVID-19 symptoms in predicting SARS-CoV-2 infection was evaluated statistically. : Three hundred and twenty-five patients were positive for SARS-CoV-2 and 954 were negative. Fever, asthenia, dysgeusia, and oxygen saturation predicted SARS-CoV-2 infection (odds ratios ranged from 1.74 to 4.98; < 0.05). The percentage of asymptomatic COVID-19 patients was 36% and only 38.15% met the Mexican operational definition. Cq-values for the gene N of SARS-CoV-2 were significantly higher in asymptomatic subjects than in the groups of COVID-19 patients with neurological, respiratory, and/or musculoskeletal manifestations ( < 0.05). : Dysgeusia, fever, and asthenia increased the odds of a positive result for COVID-19 1.74-4.98-fold among the study population. Patients with neurological, respiratory, and/or musculoskeletal manifestations had higher viral loads at COVID-19 diagnosis than those observed in asymptomatic patients. A high percentage of the participants in the study (61.85%) did not meet the operational definition for a suspected case of COVID-19 established by the Mexican Health Authority's consensus, representing a high percentage of the population that could have remained without a COVID-19 diagnosis, so becoming a potential source of virus spread.
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http://dx.doi.org/10.3390/medicina57040363 | DOI Listing |
Sci Rep
December 2024
College of Mechanical and Electronic Engineering, Dalian Minzu University, Dalian, 116650, Liaoning, China.
The novel coronavirus (COVID-19) has affected more than two million people of the world, and far social distancing and segregated lifestyle have to be adopted as a common solution in recent years. To solve the problem of sanitation control and epidemic prevention in public places, in this paper, an intelligent disinfection control system based on the STM32 single-chip microprocessor was designed to realize intelligent closed-loop disinfection in local public places such as public toilets. The proposed system comprises seven modules: image acquisition, spraying control, disinfectant liquid level control, access control, voice broadcast, system display, and data storage.
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December 2024
Department of Mathematics, GC University, Lahore, Pakistan.
In this article, a nonlinear fractional bi-susceptible [Formula: see text] model is developed to mathematically study the deadly Coronavirus disease (Covid-19), employing the Atangana-Baleanu derivative in Caputo sense (ABC). A more profound comprehension of the system's intricate dynamics using fractional-order derivative is explored as the primary focus of constructing this model. The fundamental properties such as positivity and boundedness, of an epidemic model have been proven, ensuring that the model accurately reflects the realistic behavior of disease spread within a population.
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December 2024
Division of Rheumatology and Clinical Immunology, Department of Medicine, University of Pittsburgh, Pittsburgh, PA, USA.
Antibody-mediated protection against pathogens is crucial to a healthy life. However, the recent SARS-CoV-2 pandemic has shown that pre-existing comorbid conditions including kidney disease account for compromised humoral immunity to infections. Individuals with kidney disease are not only susceptible to infections but also exhibit poor vaccine-induced antibody response.
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December 2024
State Key Laboratory of Quality Research in Chinese Medicine, Institute of Chinese Medical Sciences, University of Macau, Macau, China.
Lipid nanoparticles (LNPs) have proven effective in mRNA delivery, as evidenced by COVID-19 vaccines. Its key ingredient, ionizable lipids, is traditionally optimized by inefficient and costly experimental screening. This study leverages artificial intelligence (AI) and virtual screening to facilitate the rational design of ionizable lipids by predicting two key properties of LNPs, apparent pKa and mRNA delivery efficiency.
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December 2024
Laboratory of Aging Research and Cancer Drug Target, National Clinical Research Center for Geriatrics, West China Hospital, Sichuan University, Chengdu, China.
The immune escape capacities of XBB variants necessitate the authorization of vaccines with these antigens. In this study, we produce three recombinant trimeric proteins from the RBD sequences of Delta, BA.5, and XBB.
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