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Your search keyword '"Hashemi Nazari, Seyed Saeed"' showing total 334 results
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334 results on '"Hashemi Nazari, Seyed Saeed"'

8. Side effects of COVID-19 vaccines among Iranian healthcare workers: a retrospective cohort study

Author

Roudgari, Hassan, primary, Etemad, Koorosh, additional, Karami, Manoochehr, additional, Mostafavi, Farideh, additional, Sotoodeh Ghorbani, Sahar, additional, Farhadi Babadi, Kosar, additional, Rahimi, Elham, additional, Taherpour, Niloufar, additional, Fattahi Masoom, Seyed Mahmood, additional, Habibi, Masoud, additional, Kermanpour, Hossein, additional, Laripour, Reza, additional, Manoochehri, Omid, additional, Raeeszadeh, Mohammad, additional, Salimi, Alireza, additional, Shekarchi, Babak, additional, Tajernia, Ali, additional, Zafarghandi, Mohammad Reza, additional, Zali, Alireza, additional, Zarghi, Afshin, additional, and Hashemi Nazari, Seyed Saeed, additional

Published
2024
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25. Intensive care unit admission and associated factors in patients hospitalised for COVID-19: A national retrospective cohort study in Iran

Author

Izadi, Neda, primary, Shahbazi, Fatemeh, additional, Mokhayeri, Yaser, additional, Seifi, Arash, additional, Taherpour, Niloufar, additional, Mehri, Ahmad, additional, Fallah, Saeid, additional, Sotoodeh Ghorbani, Sahar, additional, Farhadi-Babadi, Kosar, additional, Taherian, Mohammad Reza, additional, Rahimi, Elham, additional, Etemed, Koorosh, additional, and Hashemi Nazari, Seyed Saeed, additional

Published
2023
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32. Risk Factors Associated with Severity and Death from COVID-19 in Iran: A Systematic Review and Meta-Analysis Study

Author

Mehri, Ahmad, primary, Sotoodeh Ghorbani, Sahar, additional, Farhadi-Babadi, Kosar, additional, Rahimi, Elham, additional, Barati, Zahra, additional, Taherpour, Niloufar, additional, Izadi, Neda, additional, Shahbazi, Fatemeh, additional, Mokhayeri, Yaser, additional, Seifi, Arash, additional, Fallah, Saeid, additional, Feyzi, Rezvan, additional, Etemed, Koorosh, additional, and Hashemi Nazari, Seyed Saeed, additional

Published
2023
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38. A Bayesian approach to correct the under-count of cancer registry statistics before population-based cancer registry program.

Author

Barati, Hadis, Pourhoseingholi, Mohamad Amin, Roshandel, Gholamreza, Hashemi Nazari, Seyed Saeed, and Fattahi, Esmaeil

Subjects
CONFIDENCE intervals, DESCRIPTIVE statistics, TUMORS, DIFFUSION of innovations, PROBABILITY theory, SECONDARY analysis
Abstract

Aim: This study aims to correct undercounts in cancer data before initiating a population-based cancer registry program, employing an innovative Bayesian methodology. Background: Underestimation is a widespread issue in cancer registries within developing countries. Methods: This secondary study utilized cancer registry data. We employed the Bayesian approach to correct undercounting in cancer data from 2005 to 2010, using the ratio of pathology to population-based data in the Golestan province as the initial value. Results: The results of this study showed that the lowest percentage of undercounting belonged to Khorasan Razavi province with an average of 21% and the highest percentage belonged to Sistan and Baluchestan province with an average of 38%. The average age-standardized incidence rate (ASR) for all provinces of the country except Golestan province was equal to 105.72 (Confidence interval (CI) 95% 105.35-106.09) per 100,000 and after Bayesian correction was 137.17 (CI 95% 136.74-137.60) per 100,000. In 2010 the amount of ASR before Bayesian correction was 100.28 (CI 95% 124.39-127.09) per 100,000 for women and 136.49 (CI 95% 171.20-174.38) per 100,000 for men. Also, after implementing the Bayesian correction, ASR increased to 125.74 per 100,000 for women and 172.79 per 100,000 for men. Conclusion: The study demonstrates the effectiveness of the Bayesian approach in correcting undercounting in cancer registries. By utilizing the Bayesian method, the average ASR after Bayesian correction with a 29.74 percent change was 137.17 per 100,000. These corrected estimates provide more accurate information on cancer burden and can contribute to improved public health programs and policy evaluation. Furthermore, this research emphasizes the suitability of the Bayesian method for addressing underestimation in cancer registries. It also underscores its pivotal role in shaping the trajectory of future investigations in this field. [ABSTRACT FROM AUTHOR]

Published
2023
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49. Estimating COVID-19-Related Infections, Deaths, and Hospitalizations in Iran Under Different Physical Distancing and Isolation Scenarios

Author

Sharifi, Hamid, Jahani, Yunes, Mirzazadeh, Ali, Ahmadi Gohari, Milad, Nakhaeizadeh, Mehran, Shokoohi, Mostafa, Eybpoosh, Sana, Tohidinik, Hamid Reza, Mostafavi, Ehsan, Khalili, Davood, Hashemi Nazari, Seyed Saeed, Karamouzian, Mohammad, and Haghdoost, Ali Akbar

Subjects
SARS-CoV-2, Prevention, Physical Distancing, Modeling, COVID-19, Iran, Isolation, Hospitalization, Vaccine Related, Infectious Diseases, Emerging Infectious Diseases, Good Health and Well Being, Biodefense, Humans, Infection, Pandemics
Abstract

BackgroundIran is one of the first few countries that was hit hard with the coronavirus disease 2019 (COVID-19) pandemic. We aimed to estimate the total number of COVID-19 related infections, deaths, and hospitalizations in Iran under different physical distancing and isolation scenarios.MethodsWe developed a susceptible-exposed-infected/infectious-recovered/removed (SEIR) model, parameterized to the COVID-19 pandemic in Iran. We used the model to quantify the magnitude of the outbreak in Iran and assess the effectiveness of isolation and physical distancing under five different scenarios (A: 0% isolation, through E: 40% isolation of all infected cases). We used Monte-Carlo simulation to calculate the 95% uncertainty intervals (UIs).ResultsUnder scenario A, we estimated 5 196 000 (UI 1 753 000-10 220 000) infections to happen till mid-June with 966 000 (UI 467 800-1 702 000) hospitalizations and 111 000 (UI 53 400-200 000) deaths. Successful implantation of scenario E would reduce the number of infections by 90% (ie, 550 000) and change the epidemic peak from 66 000 on June 9, to 9400 on March 1, 2020. Scenario E also reduces the hospitalizations by 92% (ie, 74 500), and deaths by 93% (ie, 7800).ConclusionWith no approved vaccination or therapy available, we found physical distancing and isolation that include public awareness and case-finding and isolation of 40% of infected people could reduce the burden of COVID-19 in Iran by 90% by mid-June.

Published
2022

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