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Showing 2 results for Forecast
Forecasting Frequency of Delivery using Poisson Hidden Markov Models
S Ghorbani Gholiabad , M Sadeghifar, R Ghorbani Gholiabad , O Hamidi,
Volume 14, Issue 1 (6-2018)
Abstract
Background and Objectives: Delivery is one of the most important services in the health systems, and increasing its effectiveness and efficiency are a health priorities. The aim of this study was to forecast the number of deliveries in order to design plans for using all facilities to provide patients with better services.
Methods: The data used in this study were the number of deliveries per month in Hakim Jorjani Hospital, Gorgan, Iran during the years 2010 to 2016. Due to the over-dispersion of the data and non-compliance with a Poisson distribution, the Poisson hidden Markov model was applied to predict the frequency of monthly deliveries. The model parameters were estimated using the maximum likelihood method and expectation maximization algorithm.
Results: The use of the Akaike criteria revealed the frequency of delivery in different months in the hospital followed a Poisson hidden Markov models with three hidden states, and the mean Poisson distribution in each component was 193.74, 236.05, and 272.61 labors, respectively.
Conclusion: The results of this study showed that government’s encouraging policies have had short-term, limited effects on increasing fertility with minimal effects on the results of the two-year forecast.
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.

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