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Mostafavi E, Eybpoosh S, Karamouzian M, Khalili M, Haji-Maghsoudi S, Salehi-Vaziri M, Khamesipour A, Jalali T, Nakhaeizadeh M, Sharifi H, Mansoori Y, Keramat F, Ghodrati S, Javanian M, Doroud D, Omrani MD, Asadi H, Pouriayevali MH, Ghasemian R, Farshidi H, Pourahmad M, Ghasemzadeh I, Mounesan L, Darvishian M, Mirjalili MR, Toledo-Romani ME, Valenzuela-Silva C, Verez-Bencomo V, Gouya MM, Emadi-Koochak H, Haghdoost AA, Biglari A. Efficacy and Safety of a Protein-Based SARS-CoV-2 Vaccine: A Randomized Clinical Trial. JAMA Netw Open 2023; 6:e2310302. [PMID: 37133864 PMCID: PMC10157429 DOI: 10.1001/jamanetworkopen.2023.10302] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 05/04/2023] Open
Abstract
Importance The protein-based SARS-CoV-2 vaccines FINLAY-FR-2 (Soberana 02) and FINLAY-FR-1A (Soberana Plus) showed good safety and immunogenicity in phase 1 and 2 trials, but the clinical efficacy of the vaccine remains unknown. Objective To evaluate the efficacy and safety of a 2-dose regimen of FINLAY-FR-2 (cohort 1) and a 3-dose regimen of FINLAY-FR-2 with FINLAY-FR-1A (cohort 2) in Iranian adults. Design, Setting, and Participants A multicenter, randomized, double-blind, placebo-controlled, phase 3 trial was conducted at 6 cities in cohort 1 and 2 cities in cohort 2. Participants included individuals aged 18 to 80 years without uncontrolled comorbidities, coagulation disorders, pregnancy or breastfeeding, recent immunoglobulin or immunosuppressive therapy, and clinical presentation or laboratory-confirmed COVID-19 on enrollment. The study was conducted from April 26 to September 25, 2021. Interventions In cohort 1, 2 doses of FINLAY-FR-2 (n = 13 857) or placebo (n = 3462) were administered 28 days apart. In cohort 2, 2 doses of FINLAY-FR-2 plus 1 dose of FINLAY-FR-1A (n = 4340) or 3 placebo doses (n = 1081) were administered 28 days apart. Vaccinations were administered via intramuscular injection. Main Outcomes and Measures The primary outcome was polymerase chain reaction-confirmed symptomatic COVID-19 infection at least 14 days after vaccination completion. Other outcomes were adverse events and severe COVID-19. Intention-to-treat analysis was performed. Results In cohort 1 a total 17 319 individuals received 2 doses and in cohort 2 5521 received 3 doses of the vaccine or placebo. Cohort 1 comprised 60.1% men in the vaccine group and 59.1% men in the placebo group; cohort 2 included 59.8% men in the vaccine group and 59.9% in the placebo group. The mean (SD) age was 39.3 (11.9) years in cohort 1 and 39.7 (12.0) years in cohort 2, with no significant difference between the vaccine and placebo groups. The median follow-up time in cohort 1 was 100 (IQR, 96-106) days and, in cohort 2, 142 (137-148) days. In cohort 1, 461 (3.2%) cases of COVID-19 occurred in the vaccine group and 221 (6.1%) in the placebo group (vaccine efficacy: 49.7%; 95% CI, 40.8%-57.3%) vs 75 (1.6%) and 51 (4.3%) in cohort 2 (vaccine efficacy: 64.9%; 95% CI, 49.7%-59.5%). The incidence of serious adverse events was lower than 0.1%, with no vaccine-related deaths. Conclusions and Relevance In this multicenter, randomized, double-blind, placebo-controlled, phase 3 trial of the efficacy and safety of FINLAY-FR-2 and FINLAY-FR-1A, 2 doses of FINLAY-FR-2 plus the third dose of FINLAY-FR-1A showed acceptable vaccine efficacy against symptomatic COVID-19 as well as COVID-19-related severe infections. Vaccination was generally safe and well tolerated. Therefore, Soberana may have utility as an option for mass vaccination of the population, especially in resource-limited settings, because of its storage condition and affordable price. Trial Registration isrctn.org Identifier: IRCT20210303050558N1.
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Affiliation(s)
- Ehsan Mostafavi
- Department of Epidemiology and Biostatistics, Research Centre for Emerging and Reemerging Infectious Diseases, Pasteur Institute of Iran, Tehran, Iran
| | - Sana Eybpoosh
- Department of Epidemiology and Biostatistics, Research Centre for Emerging and Reemerging Infectious Diseases, Pasteur Institute of Iran, Tehran, Iran
| | - Mohammad Karamouzian
- HIV/STI Surveillance Research Center, and WHO Collaborating Center for HIV Surveillance, Institute for Futures Studies in Health, Kerman University of Medical Sciences, Kerman, Iran
- School of Public Health, Brown University, Providence, Rhode Island
- Centre on Drug Policy Evaluation, St. Michael's Hospital, Toronto, Ontario, Canada
| | - Malahat Khalili
- The Michael G. DeGroote Institute for Pain Research and Care, McMaster University, Hamilton, Ontario, Canada
| | - Saiedeh Haji-Maghsoudi
- Modeling in Health Research Center, Institute for Futures Studies in Health, Kerman University of Medical Sciences, Kerman, Iran
- Department of Biostatistics and Epidemiology, School of Public Health, Kerman University of Medical Sciences, Kerman, Iran
| | | | - Ali Khamesipour
- Center for Research and Training in Skin Diseases and Leprosy, Tehran University of Medical Sciences, Tehran, Iran
| | - Tahmineh Jalali
- COVID-19 National Reference Laboratory, Pasteur Institute of Iran, Tehran, Iran
| | - Mehran Nakhaeizadeh
- Department of Biostatistics and Epidemiology, School of Public Health, Kerman University of Medical Sciences, Kerman, Iran
| | - Hamid Sharifi
- HIV/STI Surveillance Research Center, and WHO Collaborating Center for HIV Surveillance, Institute for Futures Studies in Health, Kerman University of Medical Sciences, Kerman, Iran
- Department of Biostatistics and Epidemiology, School of Public Health, Kerman University of Medical Sciences, Kerman, Iran
| | | | - Fariba Keramat
- Brucellosis Research Center, Hamadan University of Medical Sciences, Hamadan, Iran
| | - Samad Ghodrati
- Internal Medicine Department, Zanjan University of Medical Sciences, Zanjan, Iran
- Zanjan Metabolic Diseases Research Center, School of Medicine, Zanjan University of Medical Sciences, Zanjan, Iran
| | - Mostafa Javanian
- Infectious Diseases and Tropical Medicine Research Center, Health Research Institute, Babol University of Medical Sciences, Babol, Iran
| | - Delaram Doroud
- Quality Control Department, Production and Research Complex, Pasteur Institute of Iran, Tehran, Iran
| | - Mir Davood Omrani
- Department of Genetics, School of Medicine, Urogenital Stem Cell Research Center, Shahid Beheshti University of Medical Sciences, Tehran, Iran
- Pasteur Institute of Iran, Tehran, Iran
| | - Hassan Asadi
- Pasteur Institute of Iran, Tehran, Iran
- Department of Health Information Management, School of Health Management and Information Sciences, Iran University of Medical Sciences, Tehran, Iran
| | | | - Roya Ghasemian
- Department of Infectious Diseases, Antimicrobial Resistance Research Center, Mazandaran University of Medical Sciences, Sari, Iran
| | - Hossein Farshidi
- Cardiovascular Research Center, Hormozgan University of Medical Sciences, Bandar Abbas, Iran
| | - Morteza Pourahmad
- Department of Infectious Diseases, Infectious Diseases and Tropical Medicine Research Center, Isfahan University of Medical Sciences, Isfahan, Iran
| | - Iman Ghasemzadeh
- Research Center of Tropical and Infectious Diseases, Kerman University of Medical Sciences, Kerman, Iran
| | - Leila Mounesan
- Department of Epidemiology and Biostatistics, Research Centre for Emerging and Reemerging Infectious Diseases, Pasteur Institute of Iran, Tehran, Iran
| | - Maryam Darvishian
- Cancer Control Research, BC Cancer Research Centre, Vancouver, British Columbia, Canada
| | | | | | | | | | - Mohammad Mehdi Gouya
- Centre for Communicable Disease Control, Ministry of Health and Medical Education, Tehran, Iran
- Department of Infectious Disease and Tropical Medicine, School of Medicine, Iran University of Medical Sciences, Tehran, Iran
| | - Hamid Emadi-Koochak
- Department of Infectious Disease, School of Medicine, Imam Khomeini Hospital, Tehran University of Medical Sciences, Tehran, Iran
| | - Ali Akbar Haghdoost
- Modeling in Health Research Center, Institute for Futures Studies in Health, Kerman University of Medical Sciences, Kerman, Iran
| | - Alireza Biglari
- Pasteur Institute of Iran, Tehran, Iran
- School of Medicine, Tehran University of Medical Sciences, Tehran, Iran
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2
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Hadifar S, Kargarpour Kamakoli M, Eybpoosh S, Nakhaeizadeh M, Kargarpour Kamakoli MA, Ebrahimifard N, Fateh A, Siadat SD, Vaziri F. The shortcut of mycobacterial interspersed repetitive unit-variable number tandem repeat typing for Mycobacterium tuberculosis differentiation. Front Microbiol 2022; 13:978355. [PMID: 36160200 PMCID: PMC9493315 DOI: 10.3389/fmicb.2022.978355] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/25/2022] [Accepted: 08/18/2022] [Indexed: 11/16/2022] Open
Abstract
The 24-loci mycobacterial interspersed repetitive unit-variable number tandem repeat (MIRU-VNTR) genotyping has been used as an international standard method for Mycobacterium tuberculosis (Mtb) genotyping. However, different optimized VNTR loci sets for improving the discrimination of specific Mtb genotypes have been proposed. In this regard, we investigated the efficacy of accumulation of the percentage differences (APDs) compared with the least absolute shrinkage and selection operator (LASSO) regression strategy to identify a customized genotype-specific VNTR loci set which provides a resolution comparable to 24-loci MIRU-VNTR in divergent Mtb populations. We utilized Spoligotyping and 24-loci MIRU-VNTR typing for genotyping 306 Mtb isolates. The APD and LASSO regression approaches were used to identify a customized VNTR set in our studied isolates. Besides, the Hunter-Gaston discriminatory index (HGDI), sensitivity, and specificity of each selected loci set were calculated based on both strategies. The selected loci based on LASSO regression compared with APD-based loci showed a better discriminatory power for identifying all studied genotypes except for T genotype, which APD-based loci showed promising discriminative power. Our findings suggested the LASSO regression rather than the APD approach is more effective in the determination of possible discriminative VNTR loci set to precise discrimination of our studied Mtb population and may be beneficial to be used in finding reduced number loci sets in other Mtb genotypes or sublineages. Moreover, we proposed customized genotype-specific MIRU-VNTR loci sets based on the LASSO regression and APD approaches for precise Mtb strains identification. As the proposed VNTR sets offered a comparable discriminatory power to the standard 24 MIRU-VNTR loci set could be promising alternatives to the standard genotyping for using in resource-limited settings.
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Affiliation(s)
- Shima Hadifar
- Department of Mycobacteriology and Pulmonary Research, Pasteur Institute of Iran, Tehran, Iran
- Microbiology Research Center, Pasteur Institute of Iran, Tehran, Iran
| | - Mansour Kargarpour Kamakoli
- Department of Mycobacteriology and Pulmonary Research, Pasteur Institute of Iran, Tehran, Iran
- Microbiology Research Center, Pasteur Institute of Iran, Tehran, Iran
| | - Sana Eybpoosh
- Department of Epidemiology and Biostatistics, Research Centre for Emerging and Reemerging Infectious Diseases, Pasteur Institute of Iran, Tehran, Iran
| | - Mehran Nakhaeizadeh
- Modeling in Health Research Center, Institute for Futures Studies in Health, Kerman University of Medical Sciences, Kerman, Iran
- Department of Biostatistics and Epidemiology, School of Public Health, Kerman University of Medical Sciences, Kerman, Iran
| | | | - Nasim Ebrahimifard
- Department of Mycobacteriology and Pulmonary Research, Pasteur Institute of Iran, Tehran, Iran
- Microbiology Research Center, Pasteur Institute of Iran, Tehran, Iran
| | - Abolfazl Fateh
- Department of Mycobacteriology and Pulmonary Research, Pasteur Institute of Iran, Tehran, Iran
- Microbiology Research Center, Pasteur Institute of Iran, Tehran, Iran
| | - Seyed Davar Siadat
- Department of Mycobacteriology and Pulmonary Research, Pasteur Institute of Iran, Tehran, Iran
- Microbiology Research Center, Pasteur Institute of Iran, Tehran, Iran
| | - Farzam Vaziri
- Department of Mycobacteriology and Pulmonary Research, Pasteur Institute of Iran, Tehran, Iran
- Microbiology Research Center, Pasteur Institute of Iran, Tehran, Iran
- *Correspondence: Farzam Vaziri, ,
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Nakhaeizadeh M, Eybpoosh S, Jahani Y, Ahmadi Gohari M, Haghdoost AA, White L, Sharifi H. Impact of Non-pharmaceutical Interventions on the Control of COVID-19 in Iran: A Mathematical Modeling Study. Int J Health Policy Manag 2022; 11:1472-1481. [PMID: 34273920 PMCID: PMC9808365 DOI: 10.34172/ijhpm.2021.48] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/16/2020] [Accepted: 04/19/2021] [Indexed: 01/12/2023] Open
Abstract
BACKGROUND During the first months of the coronavirus disease 2019 (COVID-19) pandemic, Iran reported high numbers of infections and deaths. In the following months, the burden of this infection decreased significantly, possibly due to the impact of a package of interventions. We modeled the dynamics of COVID-19 infection in Iran to quantify the impacts of these interventions. METHODS We used a modified susceptible-exposed-infected-recovered (SEIR) model to model the COVID-19 epidemic in Iran, from January 21, 2020 to September 21, 2020. We estimated the 95% uncertainty intervals (UIs) using Markov chain Monte Carlo simulation. Under different scenarios, we assessed the effectiveness of non-pharmaceutical interventions (NPIs) including physical distancing measures and self-isolation. We also estimated the time-varying reproduction number (Rt ), using our mathematical model and epidemiologic data. RESULTS If no NPIs were applied, there could have been a cumulative number of 51 800 000 (95% UI: 1 910 000- 77 600 000) COVID-19 infections and 266 000 (95% UI: 119 000-476 000) deaths by September 21, 2020. If physical distancing interventions, such as school/border closures and self-isolation interventions had been introduced a week earlier than they were actually launched, 30.8% and 35.2% reduction in the number of deaths and infections respectively could have been achieved by September 21, 2020. The observed daily number of deaths showed that the Rt was one or more than one almost every day during the analysis period. CONCLUSION Our models suggest that the NPIs implemented in Iran between January 21, 2020 and September 21, 2020 had significant effects on the spread of the COVID-19 epidemic. Our study also showed that the timely implementation of NPIs showed a profound effect on further reductions in the numbers of infections and deaths. This highlights the importance of forecasting and early detection of future waves of infection and of the need for effective preparedness and response capabilities.
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Affiliation(s)
- Mehran Nakhaeizadeh
- Modeling in Health Research Center, Institute for Futures Studies in Health, Kerman University of Medical Sciences, Kerman, Iran
- Department of Biostatistics and Epidemiology, School of Public Health, Kerman University of Medical Sciences, Kerman, Iran
| | - Sana Eybpoosh
- Department of Epidemiology and Biostatistics, Research Centre for Emerging and Reemerging Infectious Diseases, Pasteur Institute of Iran, Tehran, Iran
| | - Yunes Jahani
- Modeling in Health Research Center, Institute for Futures Studies in Health, Kerman University of Medical Sciences, Kerman, Iran
- Department of Biostatistics and Epidemiology, School of Public Health, Kerman University of Medical Sciences, Kerman, Iran
| | - Milad Ahmadi Gohari
- Modeling in Health Research Center, Institute for Futures Studies in Health, Kerman University of Medical Sciences, Kerman, Iran
- Department of Biostatistics and Epidemiology, School of Public Health, Kerman University of Medical Sciences, Kerman, Iran
| | - Ali Akbar Haghdoost
- Modeling in Health Research Center, Institute for Futures Studies in Health, Kerman University of Medical Sciences, Kerman, Iran
- HIV/STI Surveillance Research Center, and WHO Collaborating Center for HIV Surveillance, Institute for Futures Studies in Health, Kerman University of Medical Sciences, Kerman, Iran
| | - Lisa White
- Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, Nuffield Department of Medicine, University of Oxford, Oxford, UK
| | - Hamid Sharifi
- Department of Biostatistics and Epidemiology, School of Public Health, Kerman University of Medical Sciences, Kerman, Iran
- HIV/STI Surveillance Research Center, and WHO Collaborating Center for HIV Surveillance, Institute for Futures Studies in Health, Kerman University of Medical Sciences, Kerman, Iran
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Nakhaeizadeh M, Khalooei A. Psychometric Properties of the Persian Version of the Diabetes Self-Management Questionnaire for Patients with Type 2 Diabetes in Iran. Int J Prev Med 2021; 12:120. [PMID: 34760131 PMCID: PMC8551775 DOI: 10.4103/ijpvm.ijpvm_241_19] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/09/2019] [Accepted: 06/10/2020] [Indexed: 11/04/2022] Open
Abstract
Background: Diabetes self-management questionnaire (DSMQ) is among the relatively new tools with comprehensive structure measuring various dimensions of self-care behaviors in diabetic patients. This study was carried out to evaluate psychometric properties of Persian version of DSMQ. Methods: A cross-sectional study was carried out from January to March 2017 among patients with type 2 diabetes mellitus (T2DM) referred to urban health centers, in Kerman, southeastern Iran. Data were collected from 589 patients using DSMQ. The DSMQ was translated into Persian by forward and backward translation method. Cronbach's alpha method and intraclass correlation coefficient (ICC) were used to measure internal consistency and test-retest reliability, respectively. In addition, construct validity was assessed by confirmatory factor analysis and exploratory factor analysis (EFA). Results: The sum-scale Cronbach's α of DSMQ was equal to 0.82 for 30 participants. The mean inter-item correlation and mean item-total correlation of “Sum Scale” (SS) were equal to 0.21 (standard deviation (SD) = 0.22) and 0.53 (SD = 0.19), respectively. All items had item-total correlations higher than 0.30 except items 7, 11, and 15. For “SS,” ICC was obtained as 0.93. EFA revealed a four-factor model accounting for 62.5% of the total variance. All indices were acceptable for the modified DSMQ with four factors (χ2 = 134.33, degrees of freedom = 89, P = 0.001, comparative fit index = 0.97, root mean square error of approximation = 0.044, Tucker-Lewis index = 0.96, and normal fit index = 0.92). Conclusions: The Persian version of DSMQ was found to have acceptable reliability and validity for assessing self-management among patients with T2DM.
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Affiliation(s)
- Mehran Nakhaeizadeh
- Department of Biostatistics and Epidemiology, School of Public Health, Kerman University of Medical Sciences, Kerman, Iran.,HIV/STI Surveillance Research Center, and WHO Collaborating Center for HIV Surveillance, Institute for Futures Studies in Health, Kerman University of Medical Sciences, Kerman, Iran
| | - Ali Khalooei
- Social Determinants of Health Research Center, Institute for Futures Studies in Health, Kerman University of Medical Sciences, Kerman, Iran
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Azimi SS, Koohi F, Aghaali M, Nikbakht R, Mahdavi M, Mokhayeri Y, Mohammadi R, Taherpour N, Nakhaeizadeh M, Khalili D, Sharifi H, Hashemi Nazari SS. Estimation of the basic reproduction number (𝑅0) of the COVID-19 epidemic in Iran. Med J Islam Repub Iran 2020. [DOI: 10.47176/mjiri.34.95] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022] Open
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Azimi SS, Koohi F, Aghaali M, Nikbakht R, Mahdavi M, Mokhayeri Y, Mohammadi R, Taherpour N, Nakhaeizadeh M, Khalili D, Sharifi H, Hashemi Nazari SS. Estimation of the basic reproduction number (𝑅0) of the COVID-19 epidemic in Iran. Med J Islam Repub Iran 2020; 34:95. [PMID: 33315980 PMCID: PMC7722950 DOI: 10.34171/mjiri.34.95] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/15/2020] [Indexed: 11/28/2022] Open
Abstract
Background: Estimation of the basic reproduction number of an infectious disease is an important issue for controlling the infection. Here, we aimed to estimate the basic reproduction number (𝑅0) of COVID-19 in Iran. Methods: To estimate 𝑅0 in Iran and Tehran, the capital, we used 3 different methods: exponential growth rate, maximum likelihood, and Bayesian time-dependent. Daily number of confirmed cases and serial intervals with a mean of 4.27 days and a standard deviation of 3.44 days with gamma distribution were used. Sensitivity analysis was performed to show the importance of generation time in estimating 𝑅0. Results: The epidemic was in its exponential growth 11 days after the beginning of the epidemic (Feb 19, 2020) with doubling time of 1.74 (CI: 1.58-1.93) days in Iran and 1.83 (CI: 1.39-2.71) in Tehran. Nationwide, the value of 𝑅0 from February 19 to 29 using exponential growth method, maximum likelihood, and Bayesian time-dependent methods was 4.70 (95% CI: 4.23-5.23), 3.90 (95% CI: 3.47- 4.36), and 3.23 (95% CI: 2.94-3.51), respectively. In addition, in Tehran, 𝑅0 was 5.14 (95% CI: 4.15-6.37), 4.20 (95% CI: 3.38-5.14), and 3.94 (95% CI: 3.45-4.40) for exponential growth, maximum likelihood, and Bayesian time-dependent methods, respectively. Bayesian time dependent methods usually provide less biased estimates. The results of sensitivity analyses demonstrated that changes in the mean generation time affect estimates of 𝑅0. Conclusion: The estimate of 𝑅0 for the COVID-19 ranged from 3.94 to 5.14 in Tehran and from 3.23 to 4.70 in nationwide using different methods, which were significantly larger than 1, indicating the potential of COVID-19 to cause an outbreak.
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Affiliation(s)
- Seyyedeh Sara Azimi
- Student Research Committee, Department of Epidemiology, School of Public Health and Safety, Shahid Beheshti University of Medical Sciences, Tehran, Iran
| | - Fatemeh Koohi
- Department of Epidemiology, School of Health, Qom University of Medical Sciences, Qom, Iran
| | - Mohammad Aghaali
- Department of Epidemiology, School of Health, Qom University of Medical Sciences, Qom, Iran
- Department of Epidemiology, School of Public Health and Safety, Shahid Beheshti University of Medical Sciences, Tehran, Iran
| | - Roya Nikbakht
- Department of Biostatistics, Faculty of Health, Mazandaran University of Medical Sciences, Sari, Iran
| | - Maryam Mahdavi
- Obesity Research Center, Research Institute for Endocrine Sciences, Shahid Beheshti University of Medical Sciences, Tehran, Iran
| | - Yaser Mokhayeri
- Department of Epidemiology and Biostatistics, School of Public Health and Nutrition, Lorestan University of Medical Sciences, Khorramabad, Iran
| | - Rasool Mohammadi
- Department of Epidemiology and Biostatistics, School of Public Health and Nutrition, Lorestan University of Medical Sciences, Khorramabad, Iran
| | - Niloufar Taherpour
- Department of Epidemiology, School of Public Health and Safety, Shahid Beheshti University of Medical Sciences, Tehran, Iran
| | - Mehran Nakhaeizadeh
- Modeling in Health Research Center, Institute for Futures Studies in Health, Kerman University of Medical Sciences, Kerman, Iran
| | - Davood Khalili
- Prevention of Metabolic Disorders Research Center, Research Institute for Endocrine Sciences, Shahid Beheshti University of Medical Sciences, Tehran, Iran
| | - Hamid Sharifi
- HIV/STI Surveillance Research Center, and WHO Collaborating Center for HIV Surveillance, Institute for Futures Studies in Health, Kerman University of Medical Sciences, Kerman, Iran
| | - Seyed Saeed Hashemi Nazari
- Prevention of Cardiovascular Disease Research Center, Department of Epidemiology, School of Public Health and Safety, Shahid Beheshti University of Medical Sciences, Tehran, Iran
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Sharifi H, Jahani Y, Mirzazadeh A, Ahmadi Gohari M, Nakhaeizadeh M, Shokoohi M, Eybpoosh S, Tohidinik HR, Mostafavi E, Khalili D, Hashemi Nazari SS, Karamouzian M, Haghdoost AA. Estimating COVID-19-Related Infections, Deaths, and Hospitalizations in Iran Under Different Physical Distancing and Isolation Scenarios. Int J Health Policy Manag 2020; 11:334-343. [PMID: 32772007 PMCID: PMC9278464 DOI: 10.34172/ijhpm.2020.134] [Citation(s) in RCA: 12] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/07/2020] [Accepted: 07/14/2020] [Indexed: 11/09/2022] Open
Abstract
Background: Iran 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.
Methods: We 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).
Results: Under 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).
Conclusion: With 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.
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Affiliation(s)
- Hamid Sharifi
- HIV/STI Surveillance Research Center, and WHO Collaborating Center for HIV Surveillance, Institute for Futures Studies in Health, Kerman University of Medical Sciences, Kerman, Iran.,Department of Biostatistics and Epidemiology, School of Public Health, Kerman University of Medical Sciences, Kerman, Iran
| | - Yunes Jahani
- Modeling in Health Research Center, Institute for Futures Studies in Health, Kerman University of Medical Sciences, Kerman, Iran.,Department of Biostatistics and Epidemiology, School of Public Health, Kerman University of Medical Sciences, Kerman, Iran
| | - Ali Mirzazadeh
- Department of Epidemiology and Biostatistics, Institute for Global Health Sciences, University of California San Francisco, San Francisco, CA, USA.,HIV/STI Surveillance Research Center, and WHO Collaborating Center for HIV Surveillance, Institute for Futures Studies in Health, Kerman University of Medical Sciences, Kerman, Iran
| | - Milad Ahmadi Gohari
- Modeling in Health Research Center, Institute for Futures Studies in Health, Kerman University of Medical Sciences, Kerman, Iran
| | - Mehran Nakhaeizadeh
- Modeling in Health Research Center, Institute for Futures Studies in Health, Kerman University of Medical Sciences, Kerman, Iran.,Department of Biostatistics and Epidemiology, School of Public Health, Kerman University of Medical Sciences, Kerman, Iran
| | - Mostafa Shokoohi
- HIV/STI Surveillance Research Center, and WHO Collaborating Center for HIV Surveillance, Institute for Futures Studies in Health, Kerman University of Medical Sciences, Kerman, Iran.,Dalla Lana School of Public Health, University of Toronto, Toronto, ON, Canada
| | - Sana Eybpoosh
- Department of Epidemiology and Biostatistics, Research Centre for Emerging and Reemerging Infectious Diseases, Pasteur Institute of Iran, Tehran, Iran
| | - Hamid Reza Tohidinik
- HIV/STI Surveillance Research Center, and WHO Collaborating Center for HIV Surveillance, Institute for Futures Studies in Health, Kerman University of Medical Sciences, Kerman, Iran.,Department of Biostatistics and Epidemiology, School of Public Health, Kerman University of Medical Sciences, Kerman, Iran
| | - Ehsan Mostafavi
- Department of Epidemiology and Biostatistics, Research Centre for Emerging and Reemerging Infectious Diseases, Pasteur Institute of Iran, Tehran, Iran
| | - Davood Khalili
- Prevention of Metabolic Disorders Research Center, Research Institute for Endocrine Sciences, Shahid Beheshti University of Medical Sciences, Tehran, Iran
| | - Seyed Saeed Hashemi Nazari
- Prevention of Cardiovascular Disease Research Center, Department of Epidemiology, School of Public Health and Safety, Shahid Beheshti University of Medical Sciences, Tehran, Iran
| | - Mohammad Karamouzian
- HIV/STI Surveillance Research Center, and WHO Collaborating Center for HIV Surveillance, Institute for Futures Studies in Health, Kerman University of Medical Sciences, Kerman, Iran.,School of Population and Public Health, Faculty of Medicine, University of British Columbia, Vancouver, BC, Canada
| | - Ali Akbar Haghdoost
- Modeling in Health Research Center, Institute for Futures Studies in Health, Kerman University of Medical Sciences, Kerman, Iran.,HIV/STI Surveillance Research Center, and WHO Collaborating Center for HIV Surveillance, Institute for Futures Studies in Health, Kerman University of Medical Sciences, Kerman, Iran
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Nakhaeizadeh M, Abdolahinia Z, Sharifi H, Mirzazadeh A, Haghdoost AA, Shokoohi M, Baral S, Karamouzian M, Shahesmaeili A. Opioid agonist therapy uptake among people who inject drugs: the findings of two consecutive bio-behavioral surveillance surveys in Iran. Harm Reduct J 2020; 17:50. [PMID: 32698875 PMCID: PMC7373839 DOI: 10.1186/s12954-020-00392-1] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/20/2020] [Accepted: 06/26/2020] [Indexed: 11/15/2022] Open
Abstract
BACKGROUND Opioid agonist therapy (OAT) uptake has been associated with multiple positive health outcomes among people who inject drugs (PWID). This study evaluated the pattern of OAT uptake among PWID in two consecutive national bio-behavioral surveillance surveys (2010 and 2014) in Iran. METHODS Data were obtained from two national bio-behavioral surveillance surveys (N2010 = 1783 and N2014 = 2166) implemented using convenience sampling at the harm reduction facilities and street venues in 10 geographically diverse urban centers across Iran. Multivariable logistic regression models were built to determine the correlates of OAT uptake for the 2014 survey, and adjusted odds ratios (AORs) along with 95% confidence intervals (CI) were reported. RESULTS The prevalence of OAT uptake decreased from 49.2% in 2010 to 45.8% in 2014 (P value = 0.033). OAT uptake varied across the studied cities ranging from 0.0 to 69.3% in the 2010 survey and 3.2 to 75.5% in the 2014 survey. Ever being married (AOR = 1.40; 95% CI 1.12, 1.75), having a history of incarceration (AOR = 1.56; 95% CI 1.16, 2.09), and human immunodeficiency virus (HIV) sero-positivity (AOR = 1.63; 95% CI 1.08, 2.50) were associated with OAT uptake. Conversely, PWID who reported using only non-opioid drugs (AOR = 0.43; 95% CI 0.26, 0.71) and those who reported concurrent use of opioid and non-opioid drugs (AOR = 0.66; 95% CI 0.51, 0.86) were less likely to uptake OAT. CONCLUSIONS Although OAT uptake among PWID in Iran is above the 40% threshold defined by the World Health Organization, there remain significant disparities across urban settings in Iran. Importantly, the OAT services appear to be serving high-risk PWID including those living with HIV and those with a history of incarceration. Evaluating service integration including mental health, HIV and hepatitis C virus care, and other harm reduction services may support the optimization of health outcomes associated with OAT across Iran.
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Affiliation(s)
- Mehran Nakhaeizadeh
- HIV/STI Surveillance Research Center, and WHO Collaborating Center for HIV Surveillance, Institute for Futures Studies in Health, Kerman University of Medical Sciences, Kerman, Iran, Haftbagh Highway, Kerman, 7616913555, Iran
- Department of Biostatistics and Epidemiology, School of Public Health, Kerman University of Medical Sciences, Kerman, 7616913555, Iran
- Modeling in Health Research Center, Institute for Futures Studies in Health, Kerman University of Medical Sciences, Kerman, 7616913555, Iran
| | - Zahra Abdolahinia
- HIV/STI Surveillance Research Center, and WHO Collaborating Center for HIV Surveillance, Institute for Futures Studies in Health, Kerman University of Medical Sciences, Kerman, Iran, Haftbagh Highway, Kerman, 7616913555, Iran
- Department of Biostatistics and Epidemiology, School of Public Health, Kerman University of Medical Sciences, Kerman, 7616913555, Iran
| | - Hamid Sharifi
- HIV/STI Surveillance Research Center, and WHO Collaborating Center for HIV Surveillance, Institute for Futures Studies in Health, Kerman University of Medical Sciences, Kerman, Iran, Haftbagh Highway, Kerman, 7616913555, Iran
| | - Ali Mirzazadeh
- HIV/STI Surveillance Research Center, and WHO Collaborating Center for HIV Surveillance, Institute for Futures Studies in Health, Kerman University of Medical Sciences, Kerman, Iran, Haftbagh Highway, Kerman, 7616913555, Iran
- Department of Epidemiology and Biostatistics, University of California San Francisco, San Francisco, CA, USA
| | - Ali Akbar Haghdoost
- HIV/STI Surveillance Research Center, and WHO Collaborating Center for HIV Surveillance, Institute for Futures Studies in Health, Kerman University of Medical Sciences, Kerman, Iran, Haftbagh Highway, Kerman, 7616913555, Iran
- Modeling in Health Research Center, Institute for Futures Studies in Health, Kerman University of Medical Sciences, Kerman, 7616913555, Iran
| | - Mostafa Shokoohi
- HIV/STI Surveillance Research Center, and WHO Collaborating Center for HIV Surveillance, Institute for Futures Studies in Health, Kerman University of Medical Sciences, Kerman, Iran, Haftbagh Highway, Kerman, 7616913555, Iran
- Department of Epidemiology & Biostatistics, Schulich School of Medicine & Dentistry, The University of Western Ontario, London, Canada
- Division of Social and Behavioural Health Sciences, Dalla Lana School of Public Health, University of Toronto, Toronto, Canada
| | - Stefan Baral
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
| | - Mohammad Karamouzian
- HIV/STI Surveillance Research Center, and WHO Collaborating Center for HIV Surveillance, Institute for Futures Studies in Health, Kerman University of Medical Sciences, Kerman, Iran, Haftbagh Highway, Kerman, 7616913555, Iran
- School of Population and Public Health, Faculty of Medicine, University of British Columbia, Vancouver, BC, Canada
| | - Armita Shahesmaeili
- HIV/STI Surveillance Research Center, and WHO Collaborating Center for HIV Surveillance, Institute for Futures Studies in Health, Kerman University of Medical Sciences, Kerman, Iran, Haftbagh Highway, Kerman, 7616913555, Iran.
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Nakhaeizadeh M, Khalooei A. Psychometric Properties of Persian Version of the 8-item Morisky Medication Adherence Scale in Type 2 Diabetes Patients. J Clin Diagn Res 2019. [DOI: 10.7860/jcdr/2019/41408.13076] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/24/2022]
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