Diffusion modeling of COVID-19 under lockdown

Social network analysis of tourism data: A case study of quarantine decisions in COVID-19 pandemic

Tourism is one of the most affected sector during the COVID-19 pandemic all over the world. Quarantine decisions are the leading measures taken in practice to reduce possible negative consequences of the COVID-19 pandemic. There is limited work in the literature on how to make the right quarantine decisions in a pandemic. Therefore, the aim of this study is to propose the use of social network analysis (SNA) based on tourism data to make the right quarantine decisions in the COVID-19 pandemic. A case study on quarantine decision is conducted based on data obtained from Turkish Statistical Institute to show how to perform SNA. Household domestic tourism survey is used as input data for SNA. The most critical region among 12 regions in Türkiye is Istanbul to decrease possible negative affect of COVID-19 pandemic on the tourism sector.

An Optical Modeling Framework for Coronavirus Detection Using Graphene-Based Nanosensor

The outbreak of the COVID-19 virus has faced the world with a new and dangerous challenge due to its contagious nature. Hence, developing sensory technologies to detect the coronavirus rapidly can provide a favorable condition for pandemic control of dangerous diseases. In between, because of the nanoscale size of this virus, there is a need for a good understanding of its optical behavior, which can give an extraordinary insight into the more efficient design of sensory devices. For the first time, this paper presents an optical modeling framework for a COVID-19 particle in the blood and extracts its optical characteristics based on numerical computations. To this end, a theoretical foundation of a COVID-19 particle is proposed based on the most recent experimental results available in the literature to simulate the optical behavior of the coronavirus under varying physical conditions. In order to obtain the optical properties of the COVID-19 model, the light reflectance by the structure is then simulated for different geometrical sizes, including the diameter of the COVID-19 particle and the size of the spikes surrounding it. It is found that the reflectance spectra are very sensitive to geometric changes of the coronavirus. Furthermore, the density of COVID-19 particles is investigated when the light is incident on different sides of the sample. Following this, we propose a nanosensor based on graphene, silicon, and gold nanodisks and demonstrate the functionality of the designed devices for detecting COVID-19 particles inside the blood samples. Indeed, the presented nanosensor design can be promoted as a practical procedure for creating nanoelectronic kits and wearable devices with considerable potential for fast virus detection.

NLRP-3 Inflammasome: A Key Target, but Mostly Overlooked following SARS-CoV-2 Infection

The last two years have shown many political and scientific debates during the current Coronavirus Disease 2019 (COVID-19) pandemic [...].

Psychological and Emotional Effects of Digital Technology on Digitods (14-18 Years): A Systematic Review

Background

The use of smartphones and other technologies has been increasing in digitods aged 14-18 years old. To further explain this relationship and explore the gap in research, this paper will appraise the available evidence regarding the relationship digital technology use and psychological/emotional outcomes and report on the strength of the associations observed between these variables.

Methodology

To select relevant studies, five separate computerized searches of online and electronic databases were performed. These included PubMed (MEDLINE, National Library of Medicine), ScienceDirect, Cochrane, Scopus, and Web of Science to attain literature from January 2017 to April 2022. The author independently reviewed studies for eligibility as per the inclusion/exclusion criteria and extracted the data according to a priori defined criteria. Risk of bias was assessed using the Agency for Healthcare Research and Quality (AHRQ) for healthcare studies and Cochrane Risk Of Bias In Non-randomized Studies of Interventions (ROBINS-I) assessment tool.

Results

Seven studies were included in this review. A positive relationship was found between excessive digital technology usage and negative psychological and emotional outcomes in digitods aged 14-18 (p ≤ 0.005). A statistically significant difference was found between girls and boys, with girls experiencing more negative outcomes than boys.

Conclusions

As the evidence in this review is distinctive, it is imperative that further research be conducted to investigate any synergistic relationships among these variables on a larger scale in order to better advise public health initiatives to specifically target heightened digital technology usage in adolescents.

Cities in the epidemic, the epidemic in cities: Reconstruction of COVID-19 development in Polish cities

The Covid-19 pandemic, with its epicentres in cities, came as the most severe social, economic and financial shock of the 21st century. The reconstruction of the pandemic spread in cities, the determination of factors conducive to and preventing from SARS-CoV-2 virus infections as well as searching for the ways to combat it and its effects have become the subject of many studies and analyses. The results presented in this article are part of this research. The study covered 20 large Polish cities with different functions, in the set of which: (1) the course of the infection process (by means of a rarely used trajectory method) was determined as well as its temporal variation (variance), (2) cities were classified in terms of the similarity of the epidemic process (correlation analysis), and (3) the factors conducive to infections presented in the literature (using a multivariate regression method) were verified. In this case the investigation was also carried out on the set of 66 large cities. Generally, the relative number of infections (per 10,000 inhabitants), i.e. the intensity of infections, was used as the basis for the analysis. The research has shown that the size, function and location within the country have no influence on the course and intensity of the epidemic in particular cities. Unfortunately, it was not possible to identify factors that could be responsible for infections, or at least that could determine the risk of infections (no confirmed impact on infections of population density, the level of poverty, the proportion of a post-working age population or the level of people's health). Thus, the obtained results testify to the individual nature of the spread of the epidemic in each city and to the possible influence of other explanatory features on the infection level than those considered in this investigation, or to the level of infections as the effect of the synergetic interaction of more than just socio-economic features. The solution to this issue remains open, as it seems, not only in the case of Polish cities.

Pre-conceptional and prenatal exposure to pesticides and pediatric neuroblastoma. A meta-analysis of nine studies

Neuroblastoma is primarily an embryonal tumor of infancy. Recently, some toxicological agents used as pesticides have been associated with an increased incidence of this tumor. We intended to determine the potential association between prenatal exposure to pesticides and the incidence of neuroblastoma in children. Studies targeting the link between neuroblastoma and pesticides were searched in PUBMED, SCOPUS, and Google Scholar from January 1, 1960, through December 2020. We performed a PRISMA-based systematic review and meta-analysis. In addition, we took into consideration the IARC evaluation on pesticides issued in recent monographs. Prenatal pesticide exposure is associated with an increased risk of neuroblastoma with an OR of 1.6 (1.1-2.3; p = 0.013), while the OR is 1.0 (0.8-1.3; p = 0.723) for pesticide exposure after birth. There is a significant association between prenatal pesticide exposure and neuroblastoma. We emphasize the IARC conclusions evaluating the carcinogenicity of diazinon, glyphosate, malathion, parathion, and tetrachlorvinphos.

Parental Pesticide Exposure and Childhood Brain Cancer: A Systematic Review and Meta-Analysis Confirming the IARC/WHO Monographs on Some Organophosphate Insecticides and Herbicides

BACKGROUND

Brain tumors are the second most common neoplasm in the pediatric age. Pesticides may play an etiologic role, but literature results are conflicting. This review provides a systematic overview, meta-analysis, and IARC/WHO consideration of data on parental exposure to pesticides and childhood brain tumors.

METHODS

We searched PubMed, SCOPUS, and Google Scholar for literature (1 January 1966-31 December 2020) that assessed childhood brain tumors and parental exposure to pesticides. We undertook a meta-analysis addressing prenatal exposure, exposure after birth, occupational exposure, and residential exposure. A total of 130 case-control investigations involving 43,598 individuals (18,198 cases and 25,400 controls) were included.

RESULTS

Prenatal exposure is associated with childhood brain tumors (odds ratio, OR = 1.32; 95% CI: 1.17-1.49; I2 = 41.1%). The same occurs after birth exposure (OR = 1.22; 95% CI: 1.03-1.45, I2 = 72.3%) and residential exposure to pesticides (OR = 1.31; 95% CI: 1.11-1.54, I2 = 67.2%). Parental occupational exposure is only marginally associated with CBT (OR = 1.17, 95% CI: 0.99-1.38, I2 = 67.0%).

CONCLUSIONS

There is an association between CBT and parental pesticides exposure before childbirth, after birth, and residential exposure. It is in line with the IARC Monograph evaluating the carcinogenicity of diazinon, glyphosate, malathion, parathion, and tetrachlorvinphos.

Multi-population analysis of the Cuban SARS-CoV-2 epidemic transmission before and during the vaccination process

In this work, several mathematical models for the spread of viruses and diseases are presented. In particular, the work focuses on the coronavirus disease 2019 (COVID-19) pandemic. A multi-population model is presented for the study of the interaction of various populations and the contagion of the virus between them. A second model on vaccination is presented, which allows analyzing the behavior of the disease taking into account the effectiveness of the vaccine and the speed of COVID-19 after the vaccination process. Finally, both models are applied to analyze the epidemic in Cuba. For this study, the official data reported by the Cuban Ministry of Health from March 2020 to August 2021 is used.