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Objective: Given its effects on long-term illnesses, like heart problems and diabetes, air pollution may be among the reasons that led COVID-19 to get worse and kill a larger number of people. Experiments have shown that breathing in polluted air weakens the immune system, making it easier for viruses to enter the body and grow. Viruses may be able to survive in the air by interacting in complex ways with particles and gases. These interactions depend on the air's chemical makeup, the particles' electric charges, and environmental conditions like humidity, UV light, and temperature. Moreover, exposure to UV rays and air pollution may reduce the organism's production of antimicrobial molecules, thus supporting viral infections. More epidemiological studies are needed to determine what effects air pollution has on COVID-19. In this review, we will discuss how air pollutants such as PM2.5 and PM10 contribute to the transmission of COVID-19., Materials and Methods: We have used nine target cities in the Tuscany region to verify this certainty, and in all these cases, the air pollution factors were found to be strongly correlated with COVID-19 cases. For each city, we applied a multivariate analysis and found an appropriate model that better fits the data., Results: This review underlines that both short-term and long-term exposure to air pollution may be crucial exasperating factors for SARS-CoV-2 transmission and COVID-19 severity and lethality. The statistical analysis concludes that air pollution should be accounted for as a possible risk factor in future COVID-19 investigations, and it should be avoided as much as possible by the general population., Conclusions: Our research highlighted the correlation between COVID-19 and air pollution. Reducing air pollution exposure should be one of the first measures against COVID-19 spread.

Objective: Long-COVID is a clinical syndrome characterized by the presence of symptoms related to SARS-CoV-2 infection that persist for at least four weeks after recovery from COVID-19. Genetics have been proposed to play an important role in long-COVID syndrome onset. This study aimed to identify genetic pathogenetic and likely pathogenetic causative variants of Mendelian genetic diseases in patients with Long-COVID syndrome. Additionally, we aimed to establish an association between these genetic variants and the clinical symptoms manifested during long-COVID syndrome., Patients and Methods: 95 patients affected by long-COVID syndrome were analyzed with a Next-Generation Sequencing (NGS) panel comprising 494 genes. The analyzed genes and the symptoms of the patients collected with an ad-hoc questionnaire were divided into four groups (cardiological, respiratory, immunological, and neurological). Finally, a statistical analysis comprising descriptive statistics, classification based on reported symptoms, and comparative analysis against a control group of healthy individuals was conducted., Results: 12 patients resulted positive for genetic testing with an autosomal dominance (8) or autosomal recessive (4) inheritance, showing a higher prevalence of cardiovascular genetic diseases (9) in the analyzed cohort compared to the normal population. Moreover, the onset of the long-COVID syndrome and its cardiovascular manifestations was compliant with the onset reported in the literature for the identified genetic diseases, suggesting that COVID-19 could manifest late-onset genetic diseases associated with their appearance. Apart from the 12 positive patients, 57 were healthy carriers of genetic diseases. Analyzing the whole cohort, a statistical correlation between prevalent symptomatology and the gene class was established, suggesting an association between the genetic susceptibility of an individual and the possibility of developing specific long-COVID syndrome symptoms, especially cardiovascular symptoms. Furthermore, 17 genetic variants were identified in CFTR. Finally, we identified genetic variants in IFNAR2 and POLG, supporting their respective involvement in inflammation and mitochondria mechanisms, correlated with long-COVID syndrome according to literature data., Conclusions: This study proposed COVID-19 to act as a manifest of underlying late-onset genetic diseases Mendelian associated with carrier status. Moreover, according to our results, mutations in cardiological genes are more present in patients who show cardiological symptoms during the syndrome. This underscores the necessity for cardiological investigation and genetic screening in long-COVID patients to address existing or potential clinical implications.

Background: Infectious diseases are disorders caused by microorganisms such as bacteria, viruses, fungi, or parasites. Many organisms live in and on our bodies. They are normally harmless or even helpful. However under certain conditions, some organisms may cause disease. Infectious diseases are also called contagious diseases due to the fact that they can be passed from person to person. Some are transmitted by insects or other animals. COVID-19 is an infectious disease that has "pervaded" the whole world during the last three years. The World Health Organization (WHO) has declared COVID-19 a Public Health Emergency of International Concern., Methods: In this paper, we will study the outbreak of this pandemic in Albania based on some mathematical models, such as SIR, SIRD, and SEIRD. We will present a detailed analysis of these models and also demonstrate how they can be used to predict the spread of infectious diseases. More precisely, we will see the spread of COVID-19 in our country, Albania. Software such as MATLAB and RStudio will be used to do this. The data that we will use when working with these programs is taken from the Institute of Public Health, Tirana, Albania., Results: We've developed an application utilizing actual data to estimate SEIRD model parameters. It's able to compute the basic reproduction number and, more significantly, provides forecasts on the disease's progression., Conclusions: Our aim is to calculate the Basic Reproduction Number, using the Next Generation Matrix, and use it to see the future of the disease. This is the average number of new infections generated by an infected individual. A large value indicates that the infection is transmitted very quickly. We will try to calculate what the values of Basic Number Reproduction have been over different time periods.

Abstract: The global COVID-19 outbreak, started in December 2019, resulted in severe financial losses and extraordinary health crises. Finding a potent and secure medication candidate to treat SARS-CoV-2 infection and its symptoms is still an urgent global need. After reviewing previous studies, olive leaves, being rich in polyphenolic compounds (a large class of bioactive substances naturally found in plants), were proposed as a viable co-therapy supplement to treat and improve clinical symptoms in COVID-19 patients. It has long been known that olive tree polyphenols-such as oleuropein, hydroxytyrosol, verbascoside, as well as triterpenoids like maslinic, ursolic, and oleanolic acids-have anti-inflammatory and multitarget antiviral effects on several virus families, and they could be one of the reasons of the beneficial effects of the Mediterranean diet against COVID-19. Thus, olive tree poly-phenols were tested in silico and in vitro for preventing SARS-CoV-2 infection, claiming that they have beneficial effects. Nevertheless, there is still a small number of research studies on this topic. The aim of this scoping review is to provide more information and offer an opinion on the feasibility of using olive tree polyphenols as a springboard for the creation of innovative natural remedies against this viral illness, ultimately planning future relevant studies.

Background. Infectious diseases are disorders caused by microorganisms such as bacteria, viruses, fungi, or parasites. Many organisms live in and on our bodies. They are normally harmless or even helpful. However under certain conditions, some organisms may cause disease. Infectious diseases are also called contagious diseases due to the fact that they can be passed from person to person. Some are transmitted by insects or other animals. COVID-19 is an infectious disease that has "pervaded" the whole world during the last three years. The World Health Organization (WHO) has declared COVID-19 a Public Health Emergency of International Concern. Methods. In this paper, we will study the outbreak of this pandemic in Albania based on some mathematical models, such as SIR, SIRD, and SEIRD. We will present a detailed analysis of these models and also demonstrate how they can be used to predict the spread of infectious diseases. More precisely, we will see the spread of COVID-19 in our country, Albania. Software such as MATLAB and RStudio will be used to do this. The data that we will use when working with these programs is taken from the Institute of Public Health, Tirana, Albania. Results. We've developed an application utilizing actual data to estimate SEIRD model parameters. It's able to compute the basic reproduction number and, more significantly, provides forecasts on the disease's progression. Conclusions. Our aim is to calculate the Basic Reproduction Number, using the Next Generation Matrix, and use it to see the future of the disease. This is the average number of new infections generated by an infected individual. A large value indicates that the infection is transmitted very quickly. We will try to calculate what the values of Basic Number Reproduction have been over different time periods. [ABSTRACT FROM AUTHOR]