Seroprevalence and cumulative incidence of COVID-19 in Ravansar cohort study participants 2020: a cross-sectional study

Background and Objectives: Serological studies are based on the detection of antibodies. However, the produced antibodies decrease over time;therefore, such methods cannot provide a valid estimate of prevalence and incidence. The present study aimed to determine the serum prevalence and cumulative incidence in the Ravansar cohort population (Youth and RaNCD Cohort) in October 2020. Methods: A random sample of 716 people aged > 18 years old were selected from the participants in the Ravansar cohort study in October 2020. Euroimmun anti-SARS COV-2 IgG ELISA kits (Lubeck, Germany) were used to measure antibody levels. Seroprevalence was estimated with considering of cut-off = 1, and cumulative incidence (modified and modified based on test specificity) was determined using modeling. Results: In the present study, the serum prevalence of COVID-19 viral infection in the Ravansar cohort population from 22 October 2020 to 18 November 2020 was estimated to be %35.16 (95%CI: %31.64, %38.79). Modified Cumulative incidence and modified based on test characteristics from 20 February to 18 November 2020 were estimated to be %68.85 and %67.71, respectively. Conclusion: Although very high cumulative incidence may be a sign of approaching herd immunity, adherence to health protocols is still recommended due to the potential role of asymptomatic cases in transmitting the disease to other members of the community;and the presence of new variants of the virus and reduced antibody levels should be considered.

Seroprevalence of SARS-Cov-2 Virus Infection In Kermanshah, Iran: A Population-based Cross-Sectional Study

Background: The aim of this study was to estimate the seroprevalence of SARS-CoV-2 infection in a general population from Kermanshah province, Iran. Method(s): The present study was a population-based cross-sectional design conducted in Kermanshah province in 2020. Sampling was performed in a multi-stage process, and 1967 participants were considered, and also 174 interviewers were assigned to collect data online. Then, 5 mL of blood sample was taken from every participant. The blood samples were centrifuged with the ELISA method to detect SARS-CoV-2-specific IgG and IgM antibodies in serum samples. Seropositive prevalence was adjusted by means of survey analysis. Case fatality rate (CFR) and infection fatality rate (IFR) were estimated. Result(s): A total of 1967 people from 14 cities of the province participated in the study. The mean age of participants was 35.7+/-16.9, and 50.4% were female. The lowest and highest seroprevalence was found in the cities of Paveh (2.3% [0.3-4.2]) and Harsin (61.6% [54.7-68.5]), respectively. The CFR and IFR in men and women were 3.4 vs. 3.3 and 0.1 vs. 0.3. The aged 60 years or older had the highest CFR and IFR with 11.2 and 3.7%, respectively. Conclusion(s): The prevalence of SARS-CoV-2 infection and IFR among the general population of Kermanshah province was 18.3 and 0.3%, respectively. The results of this study can assist the policymaker in assessing risk factors, and transmission dynamics of SARS-CoV-2 in a population and implementing preventive and control interventions.Copyright © 2023 Shadmani et al.

Seroprevalence and Cumulative Incidence of COVID-19 in Ravansar Cohort Study Participants 2020: A Cross-Sectional Study.

Background and Objectives: Serological studies are based on the detection of antibodies. However, the produced antibodies decrease over time;therefore, such methods cannot provide a valid estimate of prevalence and incidence. The present study aimed to determine the serum prevalence and cumulative incidence in the Ravansar cohort population (Youth and RaNCD Cohort) in October 2020. Method(s): A random sample of 716 people aged > 18 years old were selected from the participants in the Ravansar cohort study in October 2020. Euroimmun anti-SARS COV-2 IgG ELISA kits (Lubeck, Germany) were used to measure antibody levels. Seroprevalence was estimated with considering of cut-off = 1, and cumulative incidence (modified and modified based on test specificity) was determined using modeling. Result(s): In the present study, the serum prevalence of COVID-19 viral infection in the Ravansar cohort population from 22 October 2020 to 18 November 2020 was estimated to be %35.16 (95%CI: %31.64, %38.79). Modified Cumulative incidence and modified based on test characteristics from 20 February to 18 November 2020 were estimated to be %68.85 and %67.71, respectively. Conclusion(s): Although very high cumulative incidence may be a sign of approaching herd immunity, adherence to health protocols is still recommended due to the potential role of asymptomatic cases in transmitting the disease to other members of the community;and the presence of new variants of the virus and reduced antibody levels should be considered.Copyright © 2022 The Authors.

A systematic review and meta-analysis on blood levels of cytokines/chemokines in COVID-19 cases

We assessed the blood levels of the most important factors such as cytokines/chemokines in Coronavirus disease-2019 (COVID-19). PubMed/Medline and Scopus as two important databases were searched up to March 26, 2020. To analyze the data, we used Review Manager 5.3 software. Out of forty-two records retrieved from two databases, 10 studies were involved in the analysis. Thirty-three cytokines/chemokines were checked. The levels of 27 cytokines/ chemokines in COVID-19 patients were higher than the healthy controls, and among 20 cytokines/chemokines;the levels of 10 cytokines/chemokines in severe COVID-19 patients were higher than non-severe COVID-19 patients. Also, out of three cytokines, one had a higher level in the intensive care unit (ICU) patients compared to the non-ICU patients. The findings showed the cytokine storm syndrome in COVID-19 patients, especially in patients with severe disease.

Seroprevalence and Cumulative Incidence of COVID-19 in Ravansar Cohort Study Participants 2020: A Cross-Sectional Study.

Background and Objectives: Serological studies are based on the detection of antibodies. However, the produced antibodies decrease over time;therefore, such methods cannot provide a valid estimate of prevalence and incidence. The present study aimed to determine the serum prevalence and cumulative incidence in the Ravansar cohort population (Youth and RaNCD Cohort) in October 2020. Method(s): A random sample of 716 people aged > 18 years old were selected from the participants in the Ravansar cohort study in October 2020. Euroimmun anti-SARS COV-2 IgG ELISA kits (Lubeck, Germany) were used to measure antibody levels. Seroprevalence was estimated with considering of cut-off = 1, and cumulative incidence (modified and modified based on test specificity) was determined using modeling. Result(s): In the present study, the serum prevalence of COVID-19 viral infection in the Ravansar cohort population from 22 October 2020 to 18 November 2020 was estimated to be %35.16 (95%CI: %31.64, %38.79). Modified Cumulative incidence and modified based on test characteristics from 20 February to 18 November 2020 were estimated to be %68.85 and %67.71, respectively. Conclusion(s): Although very high cumulative incidence may be a sign of approaching herd immunity, adherence to health protocols is still recommended due to the potential role of asymptomatic cases in transmitting the disease to other members of the community;and the presence of new variants of the virus and reduced antibody levels should be considered.Copyright © 2022 The Authors.

Modeling time to event for epicenters of the pandemic COVID-19

The epidemic of COVID-19 has been the most mathematically informative pandemic. The unprecedented information gives rise to some unprecedented models, problems, and discussions. One of these new matters is modeling the epicenters of a pandemic. The present paper is the first attempt to model the waiting time to introduce a new epicenter during a pandemic. This modeling is conducted in terms of time-to-event, the number of epicenters, and the normalized time. We model the waiting time data by an exponential distribution, therefore, the number of epicenters can be represented through a Poisson process. Then, the parameters are estimated by the method of moments and maximum likelihood method. All the simulations are the result of 10,000 runs conducted on MATLAB R2015b. It is expected to encounter 12 and 14 (with probability 95%, 3-24 and 7-23) epicenters from 15th May to 13th June and from June 14 to July 12, 2020, respectively. We forecast that the cumulative number of confirmed cases for coming epicenters is over 10,000 when they join the existing epicenters. The paper suggests that the time to epicenter is a suitable criterion to compare the spreading speed of an epidemic in different periods or even different epidemics. Highlights: The study aims to model the time to the next epicenters during the pandemic COVID-19. The study introduces the time to epicenter as a criterion to study of spreading speed of an epidemic in different periods or compare different epidemics. The study deals with the number of cumulative confirmed cases at the time that a region become epicenter. The study proposes the Poisson process as the model to describe the number of epicenters. The study suggests that exponential distribution can model the time to event for the epicenters of COVID-19.Copyright © 2023 International Biometric Society-Chinese Region.

Immune-mediated necrotizing myopathy following vaccination with the AstraZeneca (AZD1222) COVID-19 vaccine: A case report and brief review.

Immune-Mediated Necrotizing Myopathy (IMNM) after vaccination has been reported previously, however it is rare after COVID-19 vaccination. We report the first case of IMNM two weeks after vaccination with the AstraZeneca (AZD1222) COVID-19 vaccine. There was a probable temporal relationship between the COVID-19 vaccination and the development of IMNM due to lack of known causative factors for IMNM. This may have been due to 1) autoimmunity directly caused by the vaccine, 2) exacerbation of autoimmunity triggered by the vaccine or 3) autoimmune syndrome triggered by the vaccine adjutants. Further studies are needed to assess the underlying mechanisms.

Seroepidemiology of COVID-19 in high-risk occupational groups in west of Iran, November 2020

Background and purpose: The actual prevalence of Coronavirus Disease 2019 (COVID-19) can only be estimated by population-based serological examinations and individuals without clinical symptoms may not be identified or reported. In this sero-epidemiological study we aimed at exploring the serum prevalence of COVID-19 in highly exposed occupational groups in western Iran. Materials and methods: A total of 1106 people with jobs with a high potential for exposure to COVID-19 (excluding doctors) were selected in Sanandaj, Kermanshah, and Hamedan. Demographic information of all participants were recorded and venous blood samples (3 ml) were taken. IgG levels were measured to determine the serum prevalence of immunoglobulin using EUROIMMUN kit.

Associated factors with the mortality rate in patients with COVID-19 - decision trees vs. logistic regression

BACKGROUND: Given the global burden of COVID-19 mortality, this study intended to determine the factors affecting mortality in patients with COVID-19 using decision tree analysis and logistic regression model in Kermanshah province, 2020. METHODS: This cross-sectional study was conducted on 7799 patients with COVID-19 admitted to the hospitals of Kermanshah province. Data gathered from February 18 to July 9, 2020, were obtained from the vice-chancellor for the health of Kermanshah University of Medical Sciences. The performance of the models was compared according to the sensitivity, specificity, and area under the receiver operating characteristic (ROC) curve. RESULTS: According to the decision tree model, the most important risk factors for death due to COVID-19 were age, body temperature, admission to intensive care unit (ICU), prior hospital visit within the last 14 days, and cardiovascular disease. Also, the multivariate logistic regression model showed that the variables of age [OR = 4.47, 95% CI: (3.16 -6.32)], shortness of breath [OR = 1.42, 95% CI: (1.0-2.01)], ICU admission [OR = 3.75, 95% CI: (2.47-5.68)], abnormal chest X-ray [OR = 1.93, 95% CI: (1.06-3.41)], liver disease [OR = 5.05, 95% CI (1.020-25.2)], body temperature [OR = 4.93, 95% CI: (2.17-6.25)], and cardiovascular disease [OR = 2.15, 95% CI: (1.27-3.06)] were significantly associated with the higher mortality of patients with COVID-19. The area under the ROC curve for the decision tree model and logistic regression was 0.77 and 0.75, respectively. CONCLUSIONS: Identifying risk factors for mortality in patients with COVID-19 can provide more effective interventions in the early stages of treatment and improve the medical approaches provided by the medical staff.

Clinical effectiveness and safety of sofosbuvir-velpatasvir as add-on treatment for COVID-19 patients: Study protocol and preliminary data for the randomized controlled trial

Objectives: COVID-19 is a worldwide health problem. Although the most infected patients experience a mild-to-moderate disease, some patients (especially older people) develop pulmonary distress with fatal lung failure and multi-organ damage. There is currently no known effective treatment for this disease. Sofosbuvir, an FDA-approved drug for the treatment of hepatitis C virus, is also able to inhibit other members of positive strand RNA viruses with conserved polymerase and may be helpful for the treatment of SARS-CoV-2. The goal of the current trial is to determine the usefulness of 'standard of care (SOC) plus hydroxychloroquine and lopinavir/ritonavir' vs. 'SOC plus a combination of lopinavir/ritonavir hydroxychloroquine and sofosbuvir/velpatasvir' in patients hospitalized with COVID-19. The Design of Clinical Trial: In this randomized controlled trial, patients over 18 years who have been diagnosed with COVID-19 by the positive SARS-CoV-2 reverse transcriptase-polymerase chain reaction (RT-PCR) test or compatible chest computed tomography (CT) scan were candidates for the study. Eighty patients from Kermanshah province, West of Iran were allocated to treatment with SOC plus hydroxychloroquine and lopinavir/ritonavir (dual therapy) or SOC plus a combination of hydroxychloroquine and lopinavir/ritonavir and sofosbuvir/velpatasvir (triple therapy) for 10 days. Allocation was conducted using simple randomization. The primary outcomes were reducing mortality up to 28 days after hospitalization. Adverse events were handled and reported in accordance with the Good Clinical Practice guidelines. Participants: Patients who were hospitalized with COVID-19 (with positive SARS-CoV-2 RT-PCR test and/or compatible chest CT scan) were screened for eligibility at Farabi Hospital, Kermanshah University of Medical Sciences (KUMS), Kermanshah, Iran. Intervention and Comparator: Both arms received active treatment and none was given placebo. The intervention arm received hydroxychloroquine 400 mg single dose and lopinavir-ritonavir (400 and 100 mg) twice daily plus sofosbuvir-velpatasvir (400 and 100 mg) once daily orally, plus SOC for 10 days. The comparator arm received hydroxychloroquine 400 mg single dose and lopinavir-ritonavir (400 and 100 mg) twice daily orally, plus SOC for 10 days. SOC includes oxygen therapy, non-invasive and invasive ventilation, antibiotic agents, vasopressor support, renal-replacement therapy, and corticosteroids. Primary Outcomes: The main outcomes are reducing mortality until 28 days after hospitalization. Other outcomes can be found in full protocol file. Randomization: For the purpose of allocation sequence generation, using an Excel file (random-numbers table) and simple random allocation, 80 included patients entered to the study, 40 patients in each group (1:1 ratio). In order to maintain the allocation sequence concealment, the details of treatment for each patient were contained in a sealed envelope, labeled by the numbers from 1 to 80. In fact, our study was a randomized open label clinical trial in which all the physicians and nurses plus all patients were aware of the type of treatment. Blinding: Our study was a randomized open label clinical trial in which all the physicians and nurses plus all patients were aware of the type of treatment. Numbers to be Randomized (Sample Size): Eighty included patients entered to the study, 40 patients in each group using simple random allocation. Trial Status: The finalized protocol version 1.5 was used in the trial study and the recruitment/intervention process started on April 11, 2020, finished on May 11, and the related follow-up finished on June 8, 2020. Registry of Clinical Trial: This clinical trial has been registered on March 30, 2020 under IRCT number 46790, in the Iranian Registry of Clinical Trials (https://www.irct.ir/trial/46790) and by KUMS under Grant No. 990097. Full Protocol: The full protocol and other details are attached as a Supplementary File (full protocol), accessible from the journal website. Preliminary Data: The sofosbuvir/ve patasvir regimen does not improve survival, clinical improvement, and duration of hospitalization in hospitalized COVID-19 patients.

Mathematical modeling the epicenters of coronavirus disease-2019 (COVID-19) pandemic

In epidemiology, the modeling of epicenters is important both conceptually and mathematically. This paper is an attempt to model epicenters mathematically. We present an algorithm to find new epicenters. Applying our model for the data related to COVID-19 pandemic, we obtain epicenters in China, South Korea, Iran, Italy, France, Germany, Spain, the USA, and Switzerland, on the days 1, 35, 42, 42, 49, 50, 50, 50, and 56, respectively. Although the number of these epicenters is less than 5% of all contaminated countries across the globe, as of March 22, 2020, they make up 74% of new cases and over 80% of total confirmed cases. Finally, we conclude that we expect to face three new epicenters between March 22 and April 1, 2020.

Evaluation of angiotensin-converting enzyme 2 (Ace2) in covid-19: A systematic review on all types of studies for epidemiologic, diagnostic, and therapeutic purposes

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) uses the angiotensin-converting enzyme 2 (ACE2) receptor of SARS-CoV for cell entry. We aimed to check the association between ACE2 and COVID-19 (coronavirus disease 2019) in a systematic review. Two databases (PubMed/Medline and Scopus) and bioRxiv were checked for retrieving all types of studies in relation to ACE2 and COVID-19 until March 18, 2020. Forty-one studies were entered to the systematic review. These studies included nineteen original, eight reviews, four letters to the editor, three research papers, one correspondence, one commentary, one mini review, two reports, one opinion, and one perspective. In summary, the results showed that the ACE2 receptor for COVID-19 is similar to that of SARS-CoV. However, its expression was different in various populations as well as in the two genders. ACE2 may be used as a therapeutic target. Patients who take ACE inhibitors may have benefit in severe disease outcomes. Finally, pangolins and snakes and turtles may act as the potential intermediate hosts transmitting disease to humans. © 2020 Houshang Nemati, Mazaher Ramezani, Farid Najafi, Babak Sayad, Mehri Nazeri, Masoud Sadeghi.

The prediction of COVID-19 spread in Iran from 15 March to 15 April 2020

Background: Over 150,000 confirmed cases, around 140 countries, and about 6,000 death occurred owing to coronavirus disease 2019 (COVID-19) pandemic in China, Italy, Iran, and South Korea. Iran reported its first confirmed cases of COVID-19 in Qom City on 19 February 2020 and has the third-highest number of COVID-19 deaths after China and Italy and the highest inWestern Asia.

Serial interval and time-varying reproduction number estimation for COVID-19 in western Iran.

There is no report on the serial interval (SI) of coronavirus disease 2019 (COVID-19) in Iran, the present report aims to estimate the SI and time-varying R of COVID-19 in western Iran. In this study, there were 1477 confirmed, probable and suspected cases of severe acute respiratory syndrome coronavirus 2 for Kermanshah from 22 February to 9 April. The close contacts of the confirmed cases were identified using telephone follow up of patients and their contacts. The SI distribution was used as an alternative. We fitted different models using the clinical onset dates of patients with their close contact (infector-infectee). Also, we applied a 'serial interval from sample' approach as a Bayesian methodology for estimating reproduction number. From 22 February to 29 March, 247 COVID-19 cases were confirmed by RT-PCR. Close contact between 21 patients (21 infector-infectee pairs), including 12 primary cases and 21 secondary cases, was confirmed. The mean and standard deviation of the SI were estimated as 5.71 and 3.89 days. The R varied from 0.79 to 1.88 for a 7-day time-lapse and ranged from 0.92 to 1.64 for a 14-day time-lapse on raw data. Also, the R varied from 0.83 to 1.84 for 7-day time-lapse and from 0.95 to 1.54 for a 14-day time-lapse using moving average data, respectively. It can be concluded that the low reproduction number for COVID-19 in Kermanshah province is an indication of the effectiveness of preventive and interventive programmes such as quarantine and isolation. Consequently, continuing these preventive measures is highly recommended.