Showing 2 results for Gharibzadeh
Kazem Khalagi, Safoora Gharibzadeh, Davood Khalili, Siamak Mirab Samiee, Seyed Mahmoud Hashemi, Saeide Aghamohamadi, Maryam Mir-Mohammad-Ali Roodaki, Katayoun Tayeri, Hengameh Namdari Tabar, Keyhan Azadmanesh, Jafar Sadegh Tabrizi, Kazem Mohammad, Samira Goudarzi, Firoozeh Hajipour, Saeid Namaki, Alireza Raeisi, Afshin Ostovar,
Volume 35, Issue 1 (1-2021)
Abstract
Background: Serological surveillance of COVID-19 through conducting repetitive population-based surveys can be useful in estimating and monitoring changes in the prevalence of infection across the country. This paper presents the protocol of nationwide population-based surveys of the Iranian COVID-19 Serological Surveillance (ICS) program.
Methods: The target population of the surveys is all individuals ≥6 years in Iran. Stratified random sampling will be used to select participants from those registered in the primary health care electronic record systems in Iran. The strata are the 31 provinces of the country, in which sampling will be done through simple random sampling. The sample size is estimated 858 individuals for each province (except for Tehran province, which is 2574) at the first survey. It will be recalculated for the next surveys based on the findings of the first survey. The participants will be invited by the community health workers to the safe blood sampling centers at the district level. After obtaining written informed consent, 10 mL of venous blood will be taken from the participants. The blood samples will be transferred to selected reference laboratories in order to test IgG and IgM antibodies against COVID-19 using an Iranian SARS-CoV-2 ELISA Kit (Pishtaz Teb). A serologically positive test is defined as a positive IgG, IgM, or both. After adjusting for the measurement error of the laboratory test, nonresponse bias, and sampling design, the prevalence of COVID-19 will be estimated at the provincial and national levels. Also, the approximate incidence rate of infection will be calculated based on the data of both consecutive surveys.
Conclusion: The implementation of these surveys will provide a comprehensive and clear picture of the magnitude of COVID-19 infection and its trend over time for health policymakers at the national and subnational levels.
Leila Mounesan, Safoora Gharibzadeh, Mahboubeh Parsaeian, Mohammad Mehdi Gouya, Sana Eybpoosh, Ali Hosseini, Leila Haghjou, Aliakbar Haghdoost, Ehsan Mostafavi,
Volume 38, Issue 1 (1-2024)
Abstract
Background: To reduce the clinical burden of COVID-19, healthcare providers, and policymakers need a clear understanding of the illness severity during epidemic waves. This study aimed to identify the clinical severity of patients with COVID-19 during different stages of an epidemic wave (pre-peak, peak, post-peak) in four provinces in Iran.
Methods: We conducted a secondary analysis of the data on COVID-19 patients admitted to hospitals (25,382 cases), which were recorded in the Medical Care Monitoring Center. Data included adult patients (≥18 years) who were hospitalized due to COVID-19 infection, confirmed by a positive SARS-CoV-2 RT-PCR test. No exclusion criteria were applied. A pairwise comparison method was used to evaluate clinical severity. Then, based on univariable and multivariable linear regression models, the severity scores of patients were compared during various stages of an epidemic wave.
Results: The findings showed that the level of severity of the disease was higher during and after the peak in the total population. The means (SD) of severity scores were 0.16 (0.25), 0.18 (0.26), and 0.19 (0.26) before, during and after the peak, respectively. Besides, age and the underlying disease had a positive and significant relationship with disease severity.
Conclusion: During the middle and late phases of the COVID-19 epidemic wave, hospitals are seeing patients with more severe illnesses than in the early stages. Enhancing hospital preparedness is essential to avert excess deaths and critical cases. Moreover, it is important to maintain ongoing monitoring of clinical symptoms during the recovery phase to support individual patients, guide public health policy, and enhance scientific understanding of epidemic recovery processes.
