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1.
Prev Med ; : 107127, 2022 Jul 01.
Article in English | MEDLINE | ID: covidwho-1915097

ABSTRACT

It is well known that the statistical analyses in health-science and medical journals are frequently misleading or even wrong. Despite many decades of reform efforts by hundreds of scientists and statisticians, attempts to fix the problem by avoiding obvious error and encouraging good practice have not altered this basic situation. Statistical teaching and reporting remain mired in damaging yet editorially enforced jargon of "significance", "confidence", and imbalanced focus on null (no-effect or "nil") hypotheses, leading to flawed attempts to simplify descriptions of results in ordinary terms. A positive development amidst all this has been the introduction of interval estimates alongside or in place of significance tests and P-values, but intervals have been beset by similar misinterpretations. Attempts to remedy this situation by calling for replacement of traditional statistics with competitors (such as pure-likelihood or Bayesian methods) have had little impact. Thus, rather than ban or replace P-values or confidence intervals, we propose to replace traditional jargon with more accurate and modest ordinary-language labels that describe these statistics as measures of compatibility between data and hypotheses or models, which have long been in use in the statistical modeling literature. Such descriptions emphasize the full range of possibilities compatible with observations. Additionally, a simple transform of the P-value called the surprisal or S-value provides a sense of how much or how little information the data supply against those possibilities. We illustrate these reforms using some examples from a highly charged topic: trials of ivermectin treatment for Covid-19.

2.
Clin Nutr ESPEN ; 48: 1-4, 2022 04.
Article in English | MEDLINE | ID: covidwho-1767995

ABSTRACT

SARS-CoV-2 and some other members of Coronaviridae family have recently forced a great deal of health, social, and economic issues globally. To that end, investigations have been oriented towards finding ways for reducing the burden of COVID-19. One of the occurrences which stands in the way of making the treatment of this disease less complicated is the way coronaviruses involve a variety of cells, tissues, organs, and even systems. This action is possible as a result of viral attachment to the angiotensin-converting enzyme 2 or ACE2. Thus, any kind of cell expressing ACE2 is prone to be affected by both SARS-COV and SARS-COV-2. Endocrine system is one of these at-risk systems. In this review, we have considered the relation between coronaviruses and one of the most essential organs of endocrine system: thyroid gland. This relation can be probed from two aspects: how underlying thyroid dysfunction can increase the risk of being infected by these viruses and how these viruses can alter the function of thyroid gland.


Subject(s)
COVID-19 , SARS Virus , Humans , Peptidyl-Dipeptidase A , SARS-CoV-2 , Thyroid Gland
3.
Clin Microbiol Infect ; 27(12): 1762-1771, 2021 Dec.
Article in English | MEDLINE | ID: covidwho-1433091

ABSTRACT

BACKGROUND: With limited vaccine supplies, an informed position on the status of SARS-CoV-2 infection in people can assist the prioritization of vaccine deployment. OBJECTIVES: We performed a systematic review and meta-analysis to estimate the global and regional SARS-CoV-2 seroprevalences around the world. DATA SOURCES: We systematically searched peer-reviewed databases (PubMed, Embase and Scopus), and preprint servers (medRxiv, bioRxiv and SSRN) for articles published between 1 January 2020 and 30 March 2021. STUDY ELIGIBILITY CRITERIA: Population-based studies reporting the SARS-CoV-2 seroprevalence in the general population were included. PARTICIPANTS: People of different age groups, occupations, educational levels, ethnic backgrounds and socio-economic status from the general population. INTERVENTIONS: There were no interventions. METHODS: We used the random-effects meta-analyses and empirical Bayesian method to estimate the pooled seroprevalence and conducted subgroup and meta-regression analyses to explore potential sources of heterogeneity as well as the relationship between seroprevalence and socio-demographics. RESULTS: We identified 241 eligible studies involving 6.3 million individuals from 60 countries. The global pooled seroprevalence was 9.47% (95% CI 8.99-9.95%), although the heterogeneity among studies was significant (I2 = 99.9%). We estimated that ∼738 million people had been infected with SARS-CoV-2 (as of December 2020). Highest and lowest seroprevalences were recorded in Central and Southern Asia (22.91%, 19.11-26.72%) and Eastern and South-eastern Asia (1.62%, 1.31-1.95%), respectively. Seroprevalence estimates were higher in males, persons aged 20-50 years, in minority ethnic groups living in countries or regions with low income and human development indices. CONCLUSIONS: The present study indicates that the majority of the world's human population was still highly susceptible to SARS-CoV-2 infection in mid-2021, emphasizing the need for vaccine deployment to vulnerable groups of people, particularly in developing countries, and for the implementation of enhanced preventive measures until 'herd immunity' to SARS-CoV-2 has developed.


Subject(s)
COVID-19 , SARS-CoV-2 , Seroepidemiologic Studies , Bayes Theorem , COVID-19/epidemiology , Global Health , Humans
4.
Clin Microbiol Infect ; 27(11): 1666-1671, 2021 Nov.
Article in English | MEDLINE | ID: covidwho-1284003

ABSTRACT

OBJECTIVES: This study aims to estimate the prevalence of coronavirus disease 2019 (COVID-19) in the general population of Iran. METHODS: The target population was all Iranian people aged 6 years and older in the country. A stratified random sampling design was used to select 28 314 people from among the individuals registered in the electronic health record systems used in primary health care in Iran. Venous blood was taken from each participant and tested for the IgG antibody against COVID-19. The prevalence of COVID-19 was estimated at provincial and national levels after adjusting for the measurement error of the laboratory test, non-response bias and sampling design. RESULTS: Of the 28 314 Iranians selected, 11 256 (39.75%) participated in the study. Of these, 5406 (48.0%) were male and 6851 (60.9%) lived in urban areas. The mean (standard deviation) participant age was 35.89 (18.61) years. The adjusted prevalence of COVID-19 until 20 August 2020 was estimated as 14.2% (95% uncertainty interval 13.3%-15.2%), which was equal to 11 958 346 (95% CI 11 211 011-12 746 776) individuals. The adjusted prevalences of infection were 14.6%, 13.8%, 16.6%, 11.7% and 19.4% among men, women, urban population, rural population and individuals aged 60 years or more, respectively. Ardabil, Golestan and Khuzestan provinces had the highest prevalence and Alborz, Hormozgan and Kerman provinces had the lowest. CONCLUSIONS: Based on the study results, a large proportion of the Iranian population had not yet been infected by COVID-19. The observance of hygienic principles and social restrictions should therefore continue until the majority of the population has been vaccinated.


Subject(s)
COVID-19 , Adolescent , Adult , Antibodies, Viral/blood , COVID-19/epidemiology , Female , Humans , Immunoglobulin G/blood , Iran/epidemiology , Male , Middle Aged , Prevalence , Seroepidemiologic Studies , Young Adult
5.
European Journal of Integrative Medicine ; : 101356, 2021.
Article in English | ScienceDirect | ID: covidwho-1263263

ABSTRACT

Introduction Physical activity-enhancing websites have created a new accessible and cost-effective method to increase the level of physical activity. The purpose of this study was to assess the impact of an individualized internet-based physical activity program on improving physical activity level. Methods This study conducted May-Dec 2018 was a single blind parallel group randomized controlled trial. Participants were recruited by distributing advertisements on popular Persian websites. Participants meeting eligibility criteria were randomly assigned to individualized (N=91) or non-individualized internet-based physical activity (N=93) intervention groups. The designed website for the study included an interactive computer-tailored exercise program that generated progressing physical activity recommendations for individualized intervention group based on the progression process for 10 weeks and a fixed exercise program for non-individualized group. Results Drop outs in the individualized group were 15 and in the non-individualized group were 14. Following the ten-week exercise program, the individualized group's physical activity level according to GPAQ questionnaire assessments was significantly improved in the travel section (p-value <0.001), recreational activities (p-value: 0.036), and total physical activity (p-value <0.001) compared to the beginning of the study. The physical activity level in the travel section (p-value <0.001) and total physical activity (p-value: 0.009), were significantly improved in the individualized group (N=76) compared to the non-individualized group (N=79). No adverse effects were reported. Conclusions Based on the current study, an individualized internet-based physical activity intervention might be effective in improving the level of physical activity. Conducting future studies during the COVID-19 pandemic is mandated to assess the impact.

6.
J Cardiovasc Thorac Res ; 13(1): 15-22, 2021.
Article in English | MEDLINE | ID: covidwho-1170607

ABSTRACT

Recently, coronavirus disease 2019 (COVID-19) has been considered as a major health problem around the globe. This severe acute respiratory syndrome has a bunch of features, such as high transmission rate, which are adding to its importance. Overcoming this disease relies on a complete understanding of the viral structure, receptors, at-risk cells or tissues, and pathogenesis. Currently, researches have shown that besides the lack of a proper anti-viral therapeutic method, complications provided by this virus are also standing in the way of decreasing its mortality rate. One of these complications is believed to be a hematologic manifestation. Commonly, three kinds of coagulopathies are detected in COVID-19 patients: disseminated intravascular coagulation (DIC), pulmonary embolism (PE), and deep vein thrombosis (DVT). In this paper, we have reviewed the relation between these conditions and coronavirus-related diseases pathogenesis, severity, and mortality rate.

8.
Emerg Infect Dis ; 27(2): 636-638, 2021 02.
Article in English | MEDLINE | ID: covidwho-993266

ABSTRACT

We determined the seroprevalence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in an affected area in northern Iran in April 2020. Antibodies to SARS-CoV-2 were detected in 528 persons by using rapid tests. Adjusted prevalence of SARS-CoV-2 seropositivity was 22.2% (95% CI 16.4%-28.5%).


Subject(s)
Antibodies, Viral/blood , COVID-19 Serological Testing/statistics & numerical data , COVID-19/epidemiology , SARS-CoV-2/immunology , Antibodies, Viral/immunology , COVID-19/blood , COVID-19/immunology , Cross-Sectional Studies , Family Characteristics , Female , Humans , Iran/epidemiology , Male , Seroepidemiologic Studies
10.
Glob Epidemiol ; 3: 100046, 2021 Nov.
Article in English | MEDLINE | ID: covidwho-965367

ABSTRACT

COVID-19 due to novel Coronavirus was first reported in Wuhan, China. Nowadays, the Islamic Republic of Iran stands among countries with high COVID-19 prevalence and high burden of disease. Since the medical resources are limited, we aimed to identify the risk factors for patients developing critical conditions. This can help to improve resource management and treatment outcomes. In this retrospective study, we included 12,677 patients who were from 26 hospitals, supervised by Tehran University of Medical Sciences with signs and symptoms of COVID-19, until April 12. University integrated IT system was adopted to collect the data. We performed Logistic regression to evaluate the association between death in COVID-19 positive patients and other variables. Cough, respiratory distress and fever were the most common symptoms in our patients, respectively. Cancer, chronic lung diseases and chronic neurologic diseases were the strongest risk factors for death in COVID-19 patients.

14.
Microb Pathog ; 147: 104390, 2020 Oct.
Article in English | MEDLINE | ID: covidwho-650874

ABSTRACT

INTRODUCTION: In the current time where we face a COVID-19 pandemic, there is no vaccine or effective treatment at this time. Therefore, the prevention of COVID-19 and the rapid diagnosis of infected patients is crucial. METHOD: We searched all relevant literature published up to February 28, 2020. We used Random-effect models to analyze the appropriateness of the pooled results. RESULT: Eighty studies were included in the meta-analysis, including 61,742 patients with confirmed COVID-19 infection. 62.5% (95% CI 54.5-79, p < 0.001) of patients had a history of recent travel endemic area or contact with them. The most common symptoms among COVID-19 infected patients were fever 87% (95% CI 73-93, p < 0.001), and cough 68% (95% CI 55.5-74, p < 0.001)), respectively. The laboratory analysis showed that thrombocytosis was present in 61% (95% CI 41-78, p < 0.001) CRP was elevated in 79% (95% CI 65-91, p < 0.001), and lymphopenia in 57.5% (95% CI 42-79, p < 0.001). The most common radiographic signs were bilateral involvement in 81% (95% CI 62.5-87, p < 0.001), consolidation in 73.5% (95% CI 50.5-91, p < 0.001), and ground-glass opacity 73.5% (95% CI 40-90, p < 0.001) of patients. Case fatality rate (CFR) in <15 years old was 0.6%, in >50 years old was 39.5%, and in all range group was 6%. CONCLUSIONS: Fever and cough are the most common symptoms of COVID-19 infection in the literature published to date. Thombocytosis, lymphopenia, and increased CRP were common lab findings although most patients included in the overall analysis did not have laboratory values reported. Among Chinese patients with COVID-19, rates of hospitalization, critical condition, and hospitalization were high in this study, but these findings may be biased by reporting only confirmed cases.


Subject(s)
Coronavirus Infections/diagnosis , Pneumonia, Viral/diagnosis , Betacoronavirus , COVID-19 , Coronavirus Infections/mortality , Coronavirus Infections/physiopathology , Cough/virology , Fever/virology , Hospitalization , Humans , Pandemics , Pneumonia, Viral/mortality , Pneumonia, Viral/physiopathology , SARS-CoV-2 , Travel
15.
Prehosp Disaster Med ; 35(4): 438-441, 2020 Aug.
Article in English | MEDLINE | ID: covidwho-604157

ABSTRACT

Studies have reported a sex bias in case fatalities of COVID-19 patients. Moreover, it is observed that men have a higher risk of developing a severe form of the disease compared to women, highlighting the importance of disaggregated data of male and female COVID-19 patients. On the other hand, other factors (eg, hormonal levels and immune functions) also need to be addressed due to the effects of sex differences on the outcomes of COVID-19 patients. An insight into the underlying causes of sex differences in COVID-19 patients may provide an opportunity for better care of the patients or prevention of the disease. The current study reviews the reports concerning with the sex differences in COVID-19 patients. It is explained how sex can affect angiotensin converting enzyme-2 (ACE2), that is a key component for the pathogenesis of COVID-19, and summarized the gender differences in immune responses and how sex hormones are involved in immune processes. Furthermore, the available data about the impact of sex hormones on the immune functions of COVID-19 cases are looked into.


Subject(s)
Coronavirus Infections/epidemiology , Coronavirus Infections/immunology , Pneumonia, Viral/epidemiology , Pneumonia, Viral/immunology , Angiotensin-Converting Enzyme 2 , Betacoronavirus , COVID-19 , Coronavirus Infections/mortality , Female , Gonadal Steroid Hormones/immunology , Humans , Male , Pandemics , Peptidyl-Dipeptidase A/physiology , Pneumonia, Viral/mortality , SARS-CoV-2 , Severity of Illness Index , Sex Factors
16.
Arch Iran Med ; 23(4): 244-248, 2020 04 01.
Article in English | MEDLINE | ID: covidwho-48277

ABSTRACT

BACKGROUND: The rapid spread of COVID-19 virus from China to other countries and outbreaks of disease require an epidemiological analysis of the disease in the shortest time and an increased awareness of effective interventions. The purpose of this study was to estimate the COVID-19 epidemic in Iran based on the SIR model. The results of the analysis of the epidemiological data of Iran from January 22 to March 24, 2020 were investigated and prediction was made until April 15, 2020. METHODS: By estimating the three parameters of time-dependent transmission rate, time-dependent recovery rate, and timedependent death rate from Covid-19 outbreak in China, and using the number of Covid-19 infections in Iran, we predicted the number of patients for the next month in Iran. Each of these parameters was estimated using GAM models. All analyses were conducted in R software using the mgcv package. RESULTS: Based on our predictions of Iran about 29000 people will be infected from March 25 to April 15, 2020. On average, 1292 people with COVID-19 are expected to be infected daily in Iran. The epidemic peaks within 3 days (March 25 to March 27, 2020) and reaches its highest point on March 25, 2020 with 1715 infected cases. CONCLUSION: The most important point is to emphasize the timing of the epidemic peak, hospital readiness, government measures and public readiness to reduce social contact.


Subject(s)
Betacoronavirus , Coronavirus Infections , Disease Outbreaks , Models, Statistical , Pandemics , Pneumonia, Viral , COVID-19 , China/epidemiology , Coronavirus Infections/epidemiology , Coronavirus Infections/transmission , Forecasting , Humans , Iran/epidemiology , Mortality , Pneumonia, Viral/epidemiology , Pneumonia, Viral/transmission , SARS-CoV-2 , Time Factors
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