Challenges for management of the COVID-19 epidemic in Iran

Lessons from COVID-19 Pandemic: A Successful Policy and Practice by Pasteur Institute of Iran

The present study aims to provide an insight to the comprehensive efforts of Pasteur Institute of Iran (PII) regarding COVID-19 management, research, achievements, and vaccine production, though there are many challenges. The relevant literature review was investigated through national and international database and also reports from the related research departments. Six strategies were taken by PII to manage the pandemic of COVID-19. While this pandemic has been hopefully controlled, SARS-CoV-2 could still be a potential threat. Therefore, COVID-19 data management and updated studies, as well as long-term safety and efficacy of the SARS-CoV-2 vaccines are still on the agenda.

Adjustment for collider bias in the hospitalized Covid-19 setting

Background

Causal directed acyclic graphs (cDAGs) are frequently used to identify confounding and collider bias. We demonstrate how to use causal directed acyclic graphs to adjust for collider bias in the hospitalized Covid-19 setting.

Materials and methods

According to the cDAGs, three types of modeling have been performed. In model 1, only vaccination is entered as an independent variable. In model 2, in addition to vaccination, age is entered the model to adjust for collider bias due to the conditioning of hospitalization. In model 3, comorbidities are also included for adjustment of collider bias due to the conditioning of hospitalization in different biasing paths intercepting age and comorbidities.

Results

There was no evidence of the effect of vaccination on preventing death due to Covid-19 in model 1. In the second model, where age was included as a covariate, a protective role for vaccination became evident. In model 3, after including chronic diseases as other covariates, the protective effect was slightly strengthened.

Conclusion

Studying hospitalized patients is subject to collider-stratification bias. Like confounding, this type of selection bias can be adjusted for by inclusion of the risk factors of the outcome which also affect hospitalization in the regression model.

The Dynamic Effective Reproductive Number of COVID-19 during the Epidemic in Iran

BACKGROUND

We aimed to determine the generation time, the best model for estimating reproduction number (R), and to estimate the basic reproduction number (R₀) and effective reproduction number (R_t) for COVID-19 in Iran.

METHODS

We used the daily incidence cases of COVID-19, hospitalized due to a probable diagnosis of COVID-19 from 19 February 2020 to 17 November 2020 in Iran. Four models, including maximum likelihood (ML), exponential growth (EG), time-dependent (TD), sequential Bayesian (SB) were evaluated. The weekly reproduction number with a 95% confidence interval (CI) was calculated.

RESULTS

TD model shows the best fit compared to other models for estimating reproduction number in Iran. The R₀ in Iran in the first week of the epidemic, leading up to 21 February 2020 was 7.19, 95% CI: 5.56, 9.00. The lowest value for the R_t was equal to 0.77 between 3 to 10 March 2020 and 4 to 11 December 2020. From 11 June 2020 up to13 August 2020, the R_t was more than one but after then to 24 September 2021 was less than one.

CONCLUSION

TD model was the best fit for estimating the R in Iran. The worst situation of the epidemic in Iran was related to the weeks leading up to 26 February 2020 and 28 October 2020, and better status was related to the weeks leading up to 10 March 2020 and 11 December 2020.

Evaluation of early complications, outcome, and mortality in Coronavirus Disease 2019 (COVID-19) infection in patients who underwent orthopedic surgery

BACKGROUND

A higher mortality and morbidity rate has been reported in COVID-19 patients undergoing surgery. To reduce the morbidity and mortality rate in COVID-19 patients undergoing orthopedic procedures, we aimed to increase the threshold for surgical planning.

METHODS

In a prospective cohort study, COVID-19 patients who underwent elective or emergent orthopedic surgery in three orthopedic surgery centers from February 2020 to September 2020 were included. In this period, 6751 patients were scheduled for orthopedic surgery. To increase surgical threshold planning, all patients with grade 5 of the American Society of Anesthesiologists (ASA) classification and patients with COVID-19 related moderate to severe pulmonary involvement were identified as high-risk patients and were excluded.

RESULTS

35 deaths occurred during the study. The frequency of deaths was significantly higher in patients with COVID-19, 6 (9.4%) than patients without COVID-19, 29 (0. 43%). The average hospitalization stay was 12.8 ± 12.1 days. The odds ratio (OR) for death was significantly higher in patients with COVID-19 than patients without COVID-19. [OR: 8.13, Confidence interval 95% (CI95%) (5.02-11.25), P: 0.001]. Four (6.3%) COVID-19-associated complications were recorded in this series that all were respiratory failure requiring unexpected postoperative ventilation. Twenty surgical complications (31.3%) were recorded. The odds ratio for ICU admission was significantly higher in patients with COVID-19 than patients without COVID-19. [OR: 5.46, CI 95% (2.68-8.68), P: 0.001].

CONCLUSIONS

An increased threshold for orthopedic surgery is suggested for COVID-19 patients with a mortality rate of 9.3%, which is less than the mortality rate in other studies. Level of evidence III.

Social Determinants of Adherence to COVID-19 Preventive Guidelines in Iran: A Qualitative Study

INTRODUCTION

Adherence to COVID-19 preventative guidelines may be influenced by a variety of factors at the individual, societal, and institutional levels. The current study sought to investigate the social factors of adherence to those preventive measures from the perspective of health professionals.

METHODS

In October 2020, we performed qualitative research in Tehran, Iran, using the directed content analysis method. For the preparation of our interview guide and data analysis, we employed the WHO conceptual framework of socioeconomic determinants of health. Semi-structured interviews were conducted with 15 health professionals and policymakers who were chosen using a purposive sampling approach. MAXQDA-18 software was used to analyze the data. The Goba and Lincoln criteria were used to assess the quality of the results.

RESULTS

There are 23 subcategories and 9 categories, which include socio-economic and political context (unstable macroeconomic environment, poor management of the pandemic, media and knowledge transfer), cultural and social values (fatalism, cultural norms, value conflicts, social customs), socio-economic positions (livelihood conditions), social capital (social cohesion, low trust), living conditions (housing conditions), occupational conditions (precarious employment), individual characteristics (demographic characteristics, personality traits, COVID-19 knowledge, and attitude), psycho-social factors (normalization of the disease, social pressure, and stigma), and health system leadership (health system problems, not taking evidence-based decisions, non-comprehensive preventive guidelines, non-operational guidelines, inadequate executive committee) were obtained.

CONCLUSION

To limit the new COVID-19 transmission, people must be encouraged to follow COVID-19 prevention instructions. Improving adherence to COVID-19 preventive guidelines necessitates dealing with the complexities of responding to social determinants of those guidelines. Increasing public health literacy and knowledge of COVID-19, informing people about the consequences of social interactions and cultural customs in the spread of COVID-19, strengthening regulatory lockdown laws, improving guarantees for adhering to preventive guidelines, providing easy access to preventive supplies, and strengthening financial support for households with precarious employment are all important.

Risk factors of developing critical conditions in Iranian patients with COVID-19

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.

Complete genome sequencing and molecular characterization of SARS-COV-2 from COVID-19 cases in Alborz province in Iran

Iran was among countries which was hard hit at the early stage of the coronavirus disease 2019 (COVID-19) pandemic and dealt with the second wave of the pandemic in May and June 2020; however, there are a very limited number of complete genome sequences of acute respiratory syndrome coronavirus 2 (SARS-CoV-2) from Iran. In this study, complete genome sequences of the virus in the samples obtained from three patients in Alborz province in May and June 2020 were generated and analyzed using bioinformatic methods. The sequenced genomes were positioned in a cluster with B.4 lineage along with the sequences from other countries namely, United Arab Emirates and Oman. There were seven single nucleotide variations (SNVs) in common in all samples and only one of the sequenced genomes showed the D614G amino acid substitution. Three SNVs, 1397 G > A, 28688T > C, 29742 G > T, which had already been reported in February, were found with high frequency in all the sequenced genomes in this study, implying that viral diversity reflected in the early stages of viral transmission in Iran were established in the second wave. Considering the importance of molecular epidemiology in response to ongoing pandemic, there is an urgent need for more complete genome sequencing and comprehensive analyses to gain insight into the transmission, adaptation and evolution of the virus in Iran.