Abstract:The COVID-19 pandemic has had a major impact on a global scale. Understanding the innate and lifestyle-related factors influencing the rate and severity of COVID-19 is important for making evidence-based recommendations. This cross-sectional study aims at establishing a potential relationship between human characteristics and vulnerability/resistance to SARS-CoV-2. We hypothesize that the impact of the virus is not the same due to cultural and ethnic differences. A cross-sectional study was performed using an … Show more
“…To date, there have been in excess of 550 million confirmed cases and over six million deaths in more than 200 countries [ 1 ]. The COVID-19 pandemic dramatically affected the world’s economy [ 2 , 3 ] and impacted all aspects of the socioeconomic spectrum. The global response to the pandemic, in terms of government policy, vaccination development and availability, slowed the spread of COVID-19 and its effects [ 4 , 5 , 6 ].…”
Background: One-third of patients who recover from COVID-19 present with long COVID. Their symptoms are broad, affecting their physical functioning and, ultimately, their quality of life. Many of those individuals who develop long COVID, possibly from a mild COVID-19 infection, are in the 18–65 age group. This prolongation of malaise directly influences national workforce economies. Objectives: To summarise the commonly reported physical symptoms of long COVID in order to inform potential adjustments in healthcare for the employable population. Methods: The Embase, CINAHL, Medline, SCOPUS, and WHO COVID-19 databases were searched. The study selection process was based on the PRISMA guidelines. The extracted data were synthesised and presented narratively. Results: 7403 studies were accessed, comprising 60 cohort studies and 10 case series/studies, representing 289,213 patients who met our criteria. The most frequently reported physical symptoms were fatigue (92%), shortness of breath (SOB) (81.8%), muscle pain (43.6%), and joint pain (34.5%). Conclusions: The range of reported physical symptoms was broad and varied; the main ones being fatigue, breathlessness/SOB, and pain. Similarities observed between long COVID and other post-acute infection syndromes may help formulate protocols to manage and promote recovery for long COVID patients. Inconsistencies were evident, particularly with a lack of adherence to the standardised definitions of long COVID.
“…To date, there have been in excess of 550 million confirmed cases and over six million deaths in more than 200 countries [ 1 ]. The COVID-19 pandemic dramatically affected the world’s economy [ 2 , 3 ] and impacted all aspects of the socioeconomic spectrum. The global response to the pandemic, in terms of government policy, vaccination development and availability, slowed the spread of COVID-19 and its effects [ 4 , 5 , 6 ].…”
Background: One-third of patients who recover from COVID-19 present with long COVID. Their symptoms are broad, affecting their physical functioning and, ultimately, their quality of life. Many of those individuals who develop long COVID, possibly from a mild COVID-19 infection, are in the 18–65 age group. This prolongation of malaise directly influences national workforce economies. Objectives: To summarise the commonly reported physical symptoms of long COVID in order to inform potential adjustments in healthcare for the employable population. Methods: The Embase, CINAHL, Medline, SCOPUS, and WHO COVID-19 databases were searched. The study selection process was based on the PRISMA guidelines. The extracted data were synthesised and presented narratively. Results: 7403 studies were accessed, comprising 60 cohort studies and 10 case series/studies, representing 289,213 patients who met our criteria. The most frequently reported physical symptoms were fatigue (92%), shortness of breath (SOB) (81.8%), muscle pain (43.6%), and joint pain (34.5%). Conclusions: The range of reported physical symptoms was broad and varied; the main ones being fatigue, breathlessness/SOB, and pain. Similarities observed between long COVID and other post-acute infection syndromes may help formulate protocols to manage and promote recovery for long COVID patients. Inconsistencies were evident, particularly with a lack of adherence to the standardised definitions of long COVID.
“…Figure 3 , Figure 6 and Figure 7 provided a more accurate and detailed view of the level of mortality risks by province. The provinces of Batna and Tizi Ouzou showed higher risks, and this means that besides the population density component already demonstrated [ 20 ], there are other factors related to the distribution of the number of deaths in the country [ 10 ]. The three provinces with the largest population density (Algerirs, Oran, and Constantine) were at the forefront of the ranking with the provinces of Tizi Ouzou, Setif, and Batna.…”
Section: Resultsmentioning
confidence: 99%
“…Therefore, studying the pandemic is essential for acquiring comprehensive analytical knowledge about the new phenomenon and finding appropriate measures to control the spread of the disease [ 9 , 10 ], also based on previous experience in infectious diseases control [ 11 ]. Global efforts have resulted in identifying several antiviral drugs, and a few vaccines have been developed [ 12 , 13 ], however, no clinically approved treatments have been identified, despite many trials of drug repurposing [ 14 , 15 ].…”
COVID-19 causes acute respiratory illness in humans. The direct consequence of the spread of the virus is the need to find appropriate and effective solutions to reduce its spread. Similar to other countries, the pandemic has spread in Algeria, with noticeable variation in mortality and infection rates between regions. We aimed to estimate the proportion of people who died or became infected with SARS-CoV-2 in each provinces using a Bayesian approach. The estimation parameters were determined using a binomial distribution along with an a priori distribution, and the results had a high degree of accuracy. The Bayesian model was applied during the third wave (1 January–15 August 2021), in all Algerian’s provinces. For spatial analysis of duration, geographical maps were used. Our findings show that Tissemsilt, Ain Defla, Illizi, El Taref, and Ghardaia (Mean = 0.001) are the least affected provinces in terms of COVID-19 mortality. The results also indicate that Tizi Ouzou (Mean = 0.0694), Boumerdes (Mean = 0.0520), Annaba (Mean = 0.0483), Tipaza (Mean = 0.0524), and Tebessa (Mean = 0.0264) are more susceptible to infection, as they were ranked in terms of the level of corona infections among the 48 provinces of the country. Their susceptibility seems mainly due to the population density in these provinces. Additionally, it was observed that northeast Algeria, where the population is concentrated, has the highest infection rate. Factors affecting mortality due to COVID-19 do not necessarily depend on the spread of the pandemic. The proposed Bayesian model resulted in being useful for monitoring the pandemic to estimate and compare the risks between provinces. This statistical inference can provide a reasonable basis for describing future pandemics in other world geographical areas.
“…An example is a study by Aouissi et al, which showed that strong immunity due to healthy lifestyle measures was associated with a reduced probability of contracting the COVID-19 virus. They also demonstrated that eating healthy, sleeping well, and regular physical activity can better enhance multiple disease prevention and outcomes [ 18 , 19 ]. Another study on children by Scapaticci et al discussed that being able to consume enough vitamins and minerals, which have antiviral properties and may lessen the intensity of symptoms, is essential for enhancing immune responses [ 20 ].…”
(1) Background: Body mass index (BMI) was observed to affect COVID-19 outcomes; however, the complete spectrum of clinical outcomes concerning BMI remains unexplored. The current study aimed to investigate the correlation between BMI and the severity and mortality of COVID-19, as well as ICU admission, radiological findings, clinical presentation, and time to viral clearance. (2) Methods: This retrospective study included 1796 multiethnic patients with COVID-19 treated at NMC Royal Hospital, Abu Dhabi, UAE. (3) Results: COVID-19’s adjusted odds of severity increased by 3.7- and 21.5-fold in classes I and III, respectively (p = 0.001). The odds of mortality were not significantly different after adjustment for age, sex, and race. The adjusted odds of ICU admission increased significantly by 3-fold and non-significantly by 4-fold in obesity classes I and II, respectively. Pneumonia was significantly higher in patients who were overweight and class I, II, and III obese. Furthermore, class III obese patients had a greater risk of presenting with combined respiratory and gastrointestinal manifestations (p < 0.001). The median time to viral clearance with a BMI > 40 kg/m2 was moderately higher than that with a BMI < 40 kg/m2. (4) Conclusions: High BMI was associated with pneumonia, ICU admission, severity, and mortality due to COVID-19.
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