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Investigating the Challenges of Death Registration and Classification Program and Providing a Solution: A Qualitative Study
M Gholamhoseinzadeh, L Ghadirian Marnani, E Ehsani-Chimeh, F Rajabi,
Volume 18, Issue 1 (5-2022)
Abstract
Background and Objectives: The distribution of causes of death indicates the distribution of risk factors for death, and is a basis of planning and intervention to reduce risk factors. The quality of the registered information has problems due to the weakness of the processes of completing and issuing the death certificate or the coding method. The purpose of this study was to explain the challenges of death registration and to provide a solution in this regard.
Methods: This qualitative study was conducted in the second half of 2019 in Guilan University of Medical Sciences. The target population was the directors and experts of the death registration program. Sampling was done purposefully by counting. Data was collected through in-depth interviews using a questionnaire and simultaneous contractual content analysis to identify key themes. To ensure the validity and acceptability of the data, the participants and two research colleagues reviewed the data frequently.
Results: According to the content analysis of 24 interviews, the main challenges of death registration included manpower, organizing the death registration system in the country, and death registration software system and its implementation. These themes were abstracted from 45 subcategories and 13 main categories.
Conclusion: Considering the challenges described by death registration managers and experts, the main proposed interventions to improve the death registration system include recruiting appropriate staff, empowering and motivating various human resources departments, developing internal and external cooperation, increasing public participation, monitoring and continuous assessment to identify the strengths and weaknesses of the death registration system and adressing them, attention to the development of death registration software and its required infrastructure such as Internet access and equipment, attention to the multiplicity of systems, and efforts to integrate them.
 

An Overview of Epidemiology Education in Iran
Kiumarss Nasseri,
Volume 18, Issue 2 (9-2022)
Abstract
Epidemiology is generally defined as the basic science and art of disease prevention and health promotion. Historically, it began with the accounting of death in major epidemics in the Middle Ages. Over the years, it has evolved into the basic science and art of dealing with mass phenomena of disease occurrence and public health. It is now gaining eminence in dealing with all kinds of mass phenomena beyond disease and public health.
Prior to the 1970s when teaching of epidemiology became a distinct training in academia, most epidemiologists were highly experienced practitioners of infectious and parasitic diseases and drew from their vast experiences in suggesting interventions for infectious disease control. With the prominence of non-infectious and chronic diseases, the need for special training with particular emphasis on biostatistics became apparent and has extensively developed to the present state. In Iran, epidemiological practice and training began with the national efforts in combating the main scourges of Malaria, Trachoma, Schistosoma infestation, cholera, and other diseases that impacted the country with high endemicity and regular epidemic outbreaks. This brief paper describes the development of epidemiology training in Iran in more detail.
 

Identification Symptoms and Underlying Diseases Related to COVID-19 And Prediction of Death Status Using Artificial Neural Network and Logistic Regression: A Data Mining Approach
Nasrin Talkhi, Nooshin Akbari Sharak, Zahra Rajabzadeh, Maryam Salari, Seyed Masoud Sadati, Mohammad Taghi Shakeri,
Volume 18, Issue 3 (12-2022)
Abstract
Background and Objectives: Due to the high prevalence of COVID-19 disease and its high mortality rate, it is necessary to identify the symptoms, demographic information and underlying diseases that effectively predict COVID-19 death. Therefore, in this study, we aimed to predict the mortality behavior due to COVID-19 in Khorasan Razavi province.
Methods: This study collected data from 51, 460 patients admitted to the hospitals of Khorasan Razavi province from 25 March 2017 to 12 September 2014. Logistic regression and Neural network methods, including machine learning methods, were used to identify survivors and non-survivors caused by COVID-19.
Results: Decreased consciousness, cough, PO2 level less than 93%, age, cancer, chronic kidney diseases, fever, headache, smoking status, and chronic blood diseases are the most important predictors of death. The accuracy of the artificial neural network model was 89.90% in the test phase. Also, the sensitivity, specificity and area under the rock curve in this model are equal to 76.14%, 91.99% and 77.65%, respectively.
Conclusion: Our findings highlight the importance of some demographic information, underlying diseases, and clinical signs in predicting survivors and non-survivors of COVID-19. Also, the neural network model provided high accuracy in prediction. However, medical research in this field will lead to complementary results by using other methods of machine learning and their high power.

Exploring Prospective Job Opportunities for Epidemiologists in Public and Non-Governmental Sectors and Projecting the Required Workforce in Iran Until 2027
Shoboo Rahmati, Reza Goujani, Zahra Abdolahinia, Naser Nasiri, Sakineh Narouee, Amir Hossein Nekouei, Hamid Sharifi, Ali Akbar Haghdoost,
Volume 19, Issue 3 (12-2023)
Abstract
Background and Objectives: The influential role of epidemiologists in improving health outcomes and conducting pertinent research becomes apparent  when they are strategically positioned and available in sufficient numbers within a nation. This study aims to identify potential job positions in epidemiology within both governmental and non-governmental sectors while estimating the necessary workforce of epidemiologists in the country until 2027.
Materials and Methods: The present study was conducted as a combination in two quantitative and qualitative parts. In the qualitative part, interviews were conducted with experts, policy makers, graduates and students of this field in the field of job opportunities. In the quantitative part, the number of epidemiologists needed was estimated using modeling and parameters obtained from the review of the literature and the opinions of experts in this field. In this study, the current and near future needs up to 1406 have been considered.
Results: Based on the interviewes, job opportunities for epidemiologists in the country encompass diverse domains, including problem management and analysis, conducting applied research, data analysis, dashboard development, teaching, training, and future-oriented work (forecasting). Acounting for lost job opportunities, the estimated number of epidemiologists required in the country until 2027 is 1122 individuals, that most of them contribute to the country's health system if job opportunities are created. The highest demand for epidemiologists was identidied in units of the Ministry of Health, medical universities, research centers, and hospitals.
Conclusion: Estimating the number of epidemiologists needed using modeling in the country and paying attention to the current number of graduates, reveals that the growth of this field and the increase in graduates can only occur if job opportunities are clearly defined, created, and implemented across proposed job levels.

Challenges of the Field of Epidemiology and the Reasons for the Migration of Epidemiologists in Iran: A Qualitative Study
Shoboo Rahmati, Zahra Abdolahinia, Sakineh Narouee, Naser Nasiri, Reza Goujani, Ali Akbar Haghdoost,
Volume 19, Issue 4 (3-2024)
Abstract
Background and Objectives: Given the significant migration of educated individuals, particularly epidemiologists, throughout the country, it is crucial to investigate the underlying causes. This article presents the findings of an extensive study that sought to explore this issue by gathering insights from experts in the field.
Methods: The study was conducted using qualitative methods, employing content analysis. Data were collected between summer and autumn 2023 through semi-structured interviews with 32 epidemiologists in the country. Analysis followed the steps outlined by Lundman and Graneheim, with coding facilitated by MAXQDA software.
Results: The main challenges of epidemiology in Iran were divided into six main categories. In the field of graduate students, problems in recruitment and employment due to the lack of suitable careers, infrastructure and structural problems of the system, research problems and insufficient knowledge about the performance of this field are the most important challenges, and in the field of students, education problems, structural and infrastructure problems were reported. Also, the main reasons for the migration of epidemiologists were the lack of meritocracy and specialization, inappropriate privileges (including the application of unconventional recruitment quotas), lack of a job market and opportunities for graduates, and inadequate compensation and benefits.
Conclusion: Based on the results of this study, it seems that the migration of epidemiologists as a valuable human resource abroad is a serious concern and problem. The lack of a suitable job position and ambiguity in the path to career advancement due to non-adherence to the meritocracy and skill-building system have increased the motivation to migrate in this group.

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