Industrial Engineering in the Digital Disruption Era

Experts forecast that 3D printing was a disruptive technology for conventional supply chains based on mass production, economies of scale, global transportation, and local inventories. However, 3D printing has many limitations in customers supply: Long operational times cause high manufacturing cost. 3D printing is not precise enough for functional surfaces and many parts and products have to be coated, assembled, or post-processed before they can be sold to customers. Spare parts could be ideal applications, but they must have the same abilities as original parts, and spare part business is too important to give away design data for 3D printing. So 3D printing is and will be limited to small volume production with new design options like the bionic design or lightweight design and for customer-configured products.

Disaster relief logistics is a critical part of humanitarian emergency operations. In this study, we develop integer programming models with a focus on the pre-disaster location selection for depots in which relief items would be stored and the post-disaster distribution of relief items to demand locations. The goal is to determine the optimal depot locations and depot-demand node allocations by minimizing the total transportation cost of delivering relief items. We incorporate performance measures that represent the efficiency, efficacy, and equity of the decisions in our models in terms of total transportation cost, total waiting time, and percent of unmet demand, respectively. We consider the uncertainties that would affect the decisions made in terms of demand and transportation times in our case study by analyzing the results under various scenarios. We provide observations regarding the performance of different objectives under different scenarios for demand and transportation network conditions.

An integrated employability aptitude survey-cognitive test is proposed to assess the retention threshold of students with the view of appraising the capabilities of engineering students in readiness for engineering positions. Numerical ability, space visualization, numerical reasoning, and symbolic reasoning responses are adapted into the model. One hundred six undergraduate students of the Department of Industrial Engineering at Eastern Mediterranean University selected across freshman, sophomore, junior and senior in the 2016–2017 academic years assessed their aptitudes through the proposed EAS cognitive tests. Analysis of variance is employed to analyze the model, and the results indicate a significant difference between students’ abilities in terms of raw scores and respective academic levels. Academic years and CGPA groups are found to have significant effects on the student’s percentile. Additionally, strong correlations between CGPA and the student’s percentile are found. However, space visualization ability is not affected by academic progression.

This paper extends the formula that derives the optimal order quantity for the risk-neutral newsvendor under stockout. Its objective is to maximize the mean-variance risk-averse profit utility function under the general demand probability distribution. The obtained formula is applied for the cases of the Uniform, Normal, and Exponential distributions. The obtained results confirmed earlier findings that the optimal order quantity for the risk-averse newsvendor problem with stockout using the mean-variance utility can either be less than or greater than the optimal quantity of the risk-neutral case.

The study examines university students’ attitudes toward sexual harassment and their perceptions of sexual harassment behaviors in a culturally diverse university in North Cyprus. Data is collected from 460 university students. The findings suggest that university students’ perceptions about what constitutes sexual harassment behavior were similar, regardless of their gender. However, women were more likely than men to perceive a wider range of verbal and non-verbal behaviors as sexual harassment. Furthermore, different perceptions of sexual harassment behavior were identified based on culture and age. When attitudes toward sexual harassment were compared, it was found that female students had lower tolerance levels and that age had an effect on attitudes toward sexual harassment.

Failure Mode and Effect Analysis (FMEA) is a widely used risk assessment approach for identification, quantification, and mitigation of potential failures in systems, products, processes, designs, and projects. Previous research efforts have focused on FMEA of Horizontal Axis Wind Turbines (HAWT)s, but there is a lack of application of FMEA for the failure analysis of Vertical Axis Wind Turbines (VAWT)s. This paper aims at the enhancement of reliability of VAWTs by applying system FMEA augmented with Fuzzy Logic (FL), and Dempster-Shafer (D-S) theory. A total of 12 probable failure modes have been identified, quantified and prioritized. The application of Fuzzy-FMEA and DS-FMEA approach based on three experts’ opinions accommodates the diversity of opinions and accounts for the uncertainty in decision making, due to any lack of knowledge and experience of the FMEA team.

Nowadays, sustainable manufacturing systems gain further awareness and importance because of considering economic, environmental, and social factors. This study presents a comprehensive evaluation to gain knowledge about sustainable manufacturing systems and related basic concepts such as circular economy, industrial symbiosis, eco-industrial parks, and life cycle assessment. Moreover, some suggestions for future research areas are presented to help to fill gaps in this field after many studies from the related literature are evaluated in detail.

The set covering problem (SCP) is one of the most studied NP-hard problems in the literature. To solve the SCP efficiently, this study considers a recently proposed bio-inspired meta-heuristic algorithm, called satin bowerbird optimizer (SBO). Since the SBO was first introduced for the global optimization problem, it works on a continuous solution space. To adapt the algorithm to the SCP, this study introduces a binary version of the SBO (BSBO). The BSBO simply converts real value coded solution vector of the SBO to binary coded solution vector by applying a binarization procedure. In addition to binarization procedures, a solution improving operator is employed in the BSBO to transform infeasible solutions into feasible solutions and remove redundant columns to reduce solution cost. The performance of the proposed BSBO is tested on a well-known benchmark problem set consists of 65 instances. With regards to the best-known solutions of the instances, efficient results are obtained by the proposed BSBO by finding near-optimal solutions. Furthermore, standard deviations of the runs demonstrate the robustness of the algorithm. As a consequence, it should be noted that the proposed solution approach is capable of finding efficient results for the SCP.

Population aging, rise in the prevalence of chronic diseases worldwide, and growing health care costs have substantially increased the demand for home health care (HHC) in recent years. To gain a competitive advantage in the market and lower public expenditure, HHC service providers and governmental institutions mainly focus on increasing service quality while decreasing their costs. These objectives have resulted in various challenging optimization problems that have been widely studied in the past few years, including routing and scheduling problems. In this paper, we study an HHC routing and scheduling problem with time windows, where service is provided to patients requesting different types of care using a limited crew. We first provide the mixed integer programming formulation of the problem. Then, we perform a computational study to investigate the benefits of allowing synchronized visits to patients. Our results show that synchronized visits guarantee HCC service to all patients in some instances which are otherwise infeasible, and may reduce the total travel distance in other cases.

The machine selection process has been an important issue for companies for many years. The wrong selection of the machine leaves a negative result on the efficiency, precision, flexibility, and sensitive production capacity of the company, and this leads to many problems. In this study, a real case application in a company that serves in the wood industry sector is carried out for the process of CNC woodworking machine selection. First, the main criteria and sub-criteria affecting machine selection are defined. For the decision-making process, 3 senior executives of the company are considered as decision-makers (DM). During the evaluation of alternatives under these criteria, the AHP method, one of the most popular Multi-Criteria Decision Making (MCDM) methods, is used. A sensitivity analysis is also conducted for a different scenario to see the change in the rankings of alternatives.

As a result of the product diversification, many types of components are used in the products’ bill-of-materials. Consequently, smaller quantities of many different types of components are needed to be distributed. All these factors complicated the part-feeding to the assembly lines. In this study, a mathematical model is developed for an in-plant milk-run material supply system that periodically distributes multiple parts by using multiple vehicles to the stations of the assembly lines. This model is called the Multi-Vehicle Milk-Run Model. As the proposed mathematical model is NP-hard, an Artificial Bee Colony Algorithm is developed to solve the large instances. The proposed ABC Algorithm is tested based on the optimum solutions (where available) and the best-known feasible solutions of different sized instances of a real washing machine assembly plant. Hence, the performance of the ABC Algorithm is validated.

There is an emerging need in understanding the trends and determinants of the medical tourism industry, which have a significant impact on the host country’s economy. Turkey’s popularity as an international tourism destination combined with the expertise of Turkish medical professionals and advanced technology available in the leading medical facilities make Turkey one of the most popular travel destinations for medical tourism. While the expanding literature on medical tourism offers conceptual and theoretical knowledge on this topic, the number of empirical studies is somewhat limited. Forecast of medical tourism demand is a critical input into decisions related to investments in healthcare, tourism, and transportation infrastructure. This study models Turkey’s medical tourism demand incorporating several factors. Due to the relatively high number of indicators and a small number of observations, Partial Least Squares Regression (PLSR) was employed to predict the response, and the results were compared with those of the Ordinary Least Squares (OLS) estimation. The empirical findings are expected to help policy makers and practitioners to deepen their understanding of medical tourism demand for Turkey.

Under recent circumstances such as globalization, edu-tourism and the privatization of institutions of higher education, the resultant competition in the higher education industry has forced universities to adopt an approach that is more business-oriented to compete in and overcome the challenges of the industry. One of the major challenges facing universities is student attraction and retention, as students face little or no barrier in transferring from one university to another. As a result, universities continue to seek effective ways to remain attractive to prospective students in addition to ensuring that their current students do not leave. While corporate social responsibility (CSR) is a means for firms to improve societal well-being, it likewise offers the opportunity to have a positive reputation and competitive advantage. Studies reporting the positive effect of CSR on stakeholders’ behavior are gradually increasing; thus, universities can use CSR as a part of their competitive strategy and positively influence the behavior of their students. However, for this strategy to be effective, attention has to be given to the significant role played by students’ understanding and awareness of the university’s CSR activities. This study investigates the association between students’ awareness of their university’s CSR initiatives and their intentions to recommend their university. This is particularly relevant primarily because studies that have explored the effect of CSR on stakeholders’ behavior have hardly considered the higher education sector thus leaving a void in literature this study seeks to fill. The primary data for this study is obtained from a structured questionnaire survey administered to students of Eastern Mediterranean University. Based on a conceptual model developed on the theory of planned behavior (TPB), this study investigates the causative relationships among awareness of CSR activities, perceived behavioral control, subjective norm, attitude and Word-of-Mouth intention using PROCESS macro. Theoretically, the present study contributes to the existing body of knowledge in this field by recommending and empirically analyzing an extended TPB model to predict students’ recommendation intentions as a result of being aware of their university’s CSR activities. This study is also relevant to the managers of higher education institutions as the findings suggest they can leverage on their CSR activities to build a reputation and gain competitive advantage.

Today, the increase in the sense of independence and developments in communication technology increase the importance of working from home. Working from home is not defined as bringing home the work that the employee cannot rise to the workplace, but rather working from home by the management at a certain frequency rather than going to work. Working from home has positive and negative effects on work-life. While some studies have positive findings that working from home will improve work performance, some studies have found that being away from the workplace will decrease team performance, create obstacles for progress and adversely affect business life. One hundred eighty employees, including 66 managers of the company to apply to work from home in the Turkish automotive sector, did take part in this study. As a result of the study, it has been concluded that the increase in transportation time and frequency of working from home reduces the level of communication between the manager and the employee and contributes positively to the establishment of work-family balance. It was obtained that working at home posed a barrier to progress at both the executive and employee levels and prevented teamwork. As a result, to increase the motivation of employees to work from home, it may be suggested that companies should place systems of teamwork in their enterprises, provide the necessary technological tools for remote teamwork and establish systems that closely monitor the results of the work of workers from home in their career plans.

An appropriate maintenance strategy can improve the availability and reliability levels of industries, while improper maintenance strategy can significantly reduce the effectiveness of companies. This paper aims to select the optimal maintenance strategy utilizing four decision-making techniques in a food company in Turkey. In this study, four multi-criteria decision making (MCDM) methods (Analytic Hierarchy Process (AHP), Technique for Order Preference by Similarity to Ideal Solution (TOPSIS), Simple Additive Weighting (SAW) and Weighted Product (WP)) are used to determine the optimal maintenance strategy. In this context, four main criteria (safety, cost, reliability, and added-value), twelve criteria and five alternatives (corrective maintenance, time-based preventive maintenance, opportunistic maintenance, condition-based maintenance, and predictive maintenance) are defined according to focus group meetings in the company and the literature review. The obtained results are compared with each other, and then the appropriate maintenance strategies are identified.

Small and medium-sized enterprises (SMEs) are important drivers of national economies, especially because of their employment-generating characteristics. In spite of this fact, SMEs are facing significant problems related to attracting and retaining a quality workforce, which is critical for organizational performance. This study aims to develop strategies that will attract high-quality employees in choosing SMEs as their workplace. For this purpose, the workplace preferences of employees are examined using conjoint analysis. A sample group was asked how attractive they find the alternative combinations of incentives (benefits) that will be provided by the government. According to the answers given, the impact of each alternative strategy proposed as state incentives were estimated. The results highlight the benefits the government should provide to employees to motivate them work in SMEs.

As university students spend a considerable part of their daily life studying in the library reading area, ensuring that the furniture dimensions used are agreeable with the principles of anthropometrics has become critical. The compatibility between dimensions of furniture and user anthropometrics is therefore important. This study was carried out to understand the anthropometric dimensions of the library users and juxtapose it with the observed dimensions of the furniture in the library. Two approaches were employed for data collection. Namely, measuring the students’ anthropometry and administration of questionnaires to the students using the university library. The questionnaire was focused on the musculoskeletal pain experienced by students. It was discovered that students feel more discomfort in the neck region. Also, shoulders and elbow regions are experiencing a considerable amount of pain. Results of the correlation analysis pointed out that there is a relationship between experienced musculoskeletal pain and variables like gender, age, degree level, and furniture design features. Comparison of furniture dimensions and anthropometric profile of the students highlights that there are mismatches in the paired dimensions. These mismatches are the precursor of the pains felt by the students that affect their well-being.

Digital twins (DT) are the key enablers for transformation to Industry 4.0 (I4.0), they are required and indispensable to the virtual design and optimization of smart manufacturing systems for I4.0. Recently many researchers have contributed to the development of Digital Twins for smart products processes and manufacturing systems. This paper presents a systematic literature review of recent developments in Digital Twins in I4.0 for Smart manufacturing, by examining the most researches related to DT, and classifying the existing publications according to the applications in various aspects of manufacturing i.e. product design, process design, manufacturing process (such as machining, cutting), additive manufacturing, 3D printing, plant layout design, production planning, ergonomics, maintenance and product lifecycle. This paper classifies, identifies, and analyzes the research on Digital Twin application to smart manufacturing systems for I4.0.

Computer-based models and simulations are critical to the design, development, and optimization of smart manufacturing systems required for Industry 4.0. Modeling and Simulation technologies are essential to address the challenges in the adoption of Industry 4.0 today, such as the creation of smart manufacturing systems. Recently many researchers have contributed to modeling and simulation of smart factories in Industry 4.0, also known as Factory 4.0. This paper presents a systematic literature review of recent developments in modeling, simulation, and optimization of Smart Factories. It indicates the most frequent contexts, problems, methods, tools, related to simulation and optimization of smart factories. This paper fills this gap by identifying and analyzing research on simulation of smart factories.

Industry 4.0 requires a paradigm shift from the traditional manufacturing practices and work environment to a dynamic workplace where humans and machines must work together as a human cyber-physical system for increased productivity and flexibility. It necessitates novel interactions between operators and machines, consequently leading to the transformation of a traditional operator to Operator 4.0 or Smart Operator. Improvement in operators and engineers’ cognitive skills is imminent to adapt to Industry 4.0 working environment. Wearable technology, sensors, or virtual reality equipment enhances cognitive capabilities of the Operator 4.0. Thus cognitive skills of the smart operators are required more rather than the physical strength. This paper presents a review of the recent developments in cognitive ergonomics of Smart Operator or Operator 4.0 in the context of Industry 4.0.

In this study, the adoption of smart home devices that offer comfort, security, and energy-saving to users has been examined. The technology acceptance model (TAM) is extended by integrating Domain Specific Innovativeness, Perceived Compatibility, Perceived Data Reliability, Perceived System Reliability, Variety Seeking and Laziness into the model. Different from the existing studies in the literature, the present study introduces the constructs Variety Seeking and Laziness the first time. In addition, Personal Innovativeness is replaced by the construct Domain Specific Innovativeness. Partial least squares structural equation modeling (PLS-SEM) is used to test the proposed model. This statistical technique does not require the data to be normally distributed and is well suited for testing large and complex models including moderating effects. According to the results, the relationship between Domain Specific Innovativeness and Perceived Usefulness is not supported. On the other hand, a positive weak relation is found between Domain Specific Innovativeness and Perceived Ease of Use. Although the analysis also reveals a weak positive relationship between Laziness and Attitude, the moderating effect of Laziness on the relationship between Attitude and Perceived Usefulness as well as Attitude and Perceived Ease of Use is not supported. Finally, a weak positive relationship between Variety Seeking and Attitude is found.

The use of social media has risen dramatically over the past few years, and companies are spending more dollars than ever on social media. It has created great opportunities for users in terms of social interaction, knowledge sharing, entertainment, and online shopping. At the same time, social media has generated a new set of capabilities for marketers to collect data, test propositions, understand consumer reactions and communicate more effectively. Therefore, a better understanding of the profiles and preferences of social media users becomes inevitable for developing effective marketing strategies. This requires a detailed analysis of meaningful differences among segments. Only a few studies have attempted to differentiate among users employing either a customer-based or product-based approach. To address this issue, this study applies the means-end approach along with the laddering technique and cluster analysis for data collection and analysis. The proposed approach can provide a deeper understanding of user perceptions and preferences. The constructed model presents the connections between preferred attributes of social media platforms, the benefits obtained from these attributes and the personal values satisfied by those benefits. The study identified four distinct groups that vary according to their motivations for using social media platforms.

This study aims to reveal the factors affecting the use of second-hand shopping through a mobile application. An extended Technology Acceptance Model (TAM), including economic advantage, natural conservation, sustainable consumption, trust, convenience, and subjective norms is constructed. A total of 318 questionnaires are collected from the users of one of the second-hand shopping application-Letgo. Regression analysis is used to reveal the relationships defined in the model. First, the results of the study confirm the relations defined in TAM in the context of second-hand shopping. Furthermore, behavioral intention to use is affected by perceived usefulness, subjective norms, convenience, and perceived ease of use. Perceived usefulness and subjective norms have a higher impact than others. Another result is that perceived ease of use, economic advantage, sustainable consumption, natural conservation, and subjective norms impact the feeling about the usefulness of second-hand shopping system. Among the factors, perceived ease of use and economic advantage have higher importance on perceived usefulness.

In this paper, the retail electricity supply to the end-user electricity customers is studied via cooperative game theory. There are two major players in the retail electricity market in Turkey: power plants and retailers. Players with retail licenses, who sell retail electricity directly to the end-user, operate with very low levels of profit margin due to high cost and competition in the market. On the other hand, power plants have a generation capacity, yet they lack sales and marketing know-how compared to retailers. We show that when power plants and retailers cooperate and integrate the market vertically, they can generate more profit compared to stand-alone. Accordingly, we investigate profit-sharing among these players using cooperative game theory. To this end, we choose Nash Bargaining, Kalai-Smorodinsky Bargaining, and weighted Shapley solutions and compare their results.

The purpose of this study is to explore the benefits of Open Data initiatives for the financial sector. The first approach is to take the financial activities, to consider their data needs (in terms of data kinds and characteristics) and consider if they are available, and in a suitable format for these goals. Even though it has been done for some cases and applied to the case of Luxembourg, we are the first and foremost group to suggest and explain a systematic method, based on an Open Data literature review, to assess the dimensions characterizing the availability (not only the data accessibility, but also the conditions around this accessibility) and the suitability of the data (not only their existence but other dimensions of their accessibility, like licenses). Although the accessibility of financial, economic and commercial information is highly dependent on contextual legal and political frameworks, this framework is adaptable enough to be used for different countries, and even beyond the case of financial data. The last part is showcasing the importance of the title of this study for financial data in Luxembourg. This contribution intends to be useful both for people in charge of the Open Data initiatives in the public and private sectors; for practitioners and researchers aiming at reusing these data; and for Open Data researchers.

National level innovation is one of the outstanding locomotive factors for both economic and business growth. Global Innovation Index (GII) is one of the most commonly used indices in this context. Furthermore, the innovation level of countries is affected by cultural dynamics. Hofstede’s Cultural Dimensions (HCD) is one of the prominent guidelines on cultural dynamics. In this study, human capital & research (HCR), business sophistication (BS) and knowledge & technology outputs (KTO) are addressed to analyze the relationships among them. Moreover, long-term orientation (LTO) factor from HCD is considered as a moderator variable. This study aims at examining the relationships between HCR-BS and BS-KTO and exploring the moderating effect of LTO on these relationships. For this purpose, a conceptual model was proposed to explore these relationships. Structural Equation Modelling (SEM) was performed to conduct path analysis by employing 86 data from official web sites. The results show that hypotheses related to GII factors are supported, and a moderating effect of LTO is observed on the relationship between BS and KTO. These findings pointed out that shortterm oriented countries are more successful in transforming knowledge into outputs. Furthermore, policymakers and innovation managers should consider time-oriented cultural values while planning to gain knowledge and technology outputs.

The purpose of this study is to question whether the level and dimensions of strategic management implementation affect the innovation level of the enterprise. Some situations created by strategic management (such as abundance, institutionalism) provide a healthy development environment in terms of innovation. Environmental scanning has been shown to support service innovation positively and powerfully. In this study, the level of strategic management applications not only impact on the type of innovation but also impact on all types of innovation were investigated. For this purpose, data obtained from 88 managers from various sectors were analyzed and interpreted by using survey method. As a result, a positive relationship was found between the strategic management level and innovation. It was found that the most important strategic management application level indicator affecting all types of innovation is environmental scanning intensity, planning horizon, and strategic control. Other indicators of the level of strategic management implementation, the flexibility of the strategic plan, and the level of participation in the preparation of strategic plans and innovation level of the enterprise could not be determined.

Today, the satisfaction of people who benefit from health systems and health systems are gaining importance. In this context, analyzing the basic concepts affecting customer satisfaction and analyzing the interactions of these concepts became essential for an accurate health system management. It is inevitable that the priorities of the customers are determined, and action is taken in line with these priorities. The concepts of Perceived Service Quality, Trust, and Organizational Image are the subjects of this study. The number of studies analyzing these four concepts together is deficient. The study was carried out in the district of Bakırköy. Sadi Konuk Research Hospital, Bakırköy. Sadi Konuk Hospital has 20 polyclinics, 359 beds and 800–1500 people in a day and it is the largest hospital in the region. The data of the study were collected from patients in these outpatient clinics. By using a convenience sampling method, polyclinic patients with at least two hospital visits responded to the questionnaire. Various demographic data were collected under the name of Age, Gender, Marital Status, Education Level, and Number of Arrival to Hospital. The questions were asked objectively, and the patients were asked to answer each question. According to the results obtained from the study, Perceived Service Quality is positively affected by Patient Satisfaction, Organizational Image, and Trust. Trust, Patient Satisfaction, and Organizational Image adversely affect Trust. Organizational Image also positively affects Patient Satisfaction.

The researchers have focused on device-aided rehabilitation systems for many years. Wearable, tangible devices, and virtual reality technologies have been used to rehabilitate impaired patients in rehabilitation centers since repetitive exercises induce neuroplasticity. Neuroplasticity is the capability of a neural network system to new situations or environmental and behavioral changes. During this adaptation stage, the brain forms new neural connections that cut off old injured ones, and it reorganizes itself. This lifelong process continues throughout a person’s life. The brain reshapes and rewires itself by synaptic pruning, deleting the neural connections that are no longer necessary and make the useful connections stronger. Some research studies have proved that intensive therapy sessions at hospital and rehabilitation centers improve the motor skills of patients. However, device-aided therapies applied in centers have expensive, time, and labor consuming issues. Additionally, some patients find repetitive exercises hard and boring. For this reason, home-based and gamified rehabilitation tools, devices, and robots have been becoming more attractive. Starting to use upper limb partially or completely is one of the most important issues makes the daily and business life of patients more comfortable. Games integrated to home-based, tangible-wearable rehabilitation devices designed for upper limb impairments, especially after stroke have been started to be used for motivating the patients to continue rehabilitation exercises. The design and manufacturing of wearable and tangible, game-based equipment is a subject of a multidisciplinary study and requires mainly engineering, medical, and education sciences. The purpose of this study is conducting a literature review to provide foundation knowledge on the topic and a picture about the research problem being studied clarifying what has been done until now and what is needed to be done.

Breast cancer is a widespread disease that can both be seen at males or females. According to so many different factors such as age, sex, genetics, the shape and size of the tumor, environmental situations, and so on, that affects cancer type directly. With so many alternative cancer types and thus, treatment preference changes, it is vital to make the diagnosis as soon as possible to decide and start the treatment process. Diagnosis time is dependent on both technological equipment and also medical personnel. This study aims to support medical personnel, radiologists, doctors, surgeons, via proposing a multi-criteria decision model to find out which factor is more effective on the breast cancer type. Fuzzy Analytic Hierarchy process is used to prioritize factors of breast cancer treatment alternatives and results are compared to another study which already used Analytic Hierarchy Process but in certain conditions.

HIV is one of the significant public health threats globally, with approximately 36.9 million people living with HIV and 1.8 million people becoming newly infected in 2017 (WHO fact sheet). To prevent HIV, to decrease its impact and to eventually eliminate this infectious disease; clinical, medical, epidemiological, economic, and modeling studies have been conducted in the last 30 years. In this study, we explore the mathematical modeling studies where HIV has been examined to understand the dynamics and spread of the disease as well as to improve HIV prevention. We surveyed HIV modeling literature, summarized primary modeling methodologies, and briefly discussed relevant studies. For each study included in this paper, we presented their modeling method, interventions included, target populations, implementation process, key results, and insights. Two most widely used modeling methodologies for HIV are Bernoulli process models and dynamic compartmental models similar to other infectious diseases. These methodologies have been discussed in detail in this paper. Other modeling methodologies included Markov models, agent-based simulation models, and discrete-event simulation models. Many studies focused on risk populations such as heterosexual (HET), men who have sex with men (MSM), people who inject drugs (PWID) and jail inmates. We included the cost-effectiveness studies where HIV prevention and treatment interventions and strategies are compared concerning their costs and benefits. In this survey, we provided a summary of existing modeling literature as well as suggestions for future studies. We concluded that application of modeling tools for HIV presents excellent opportunities for both decision-makers and public health policymakers while predicting the future of this disease, establishing the most cost-effective prevention strategies and evaluating possibilities for the elimination of HIV.

Hepatitis C (HCV) is one of the major infectious diseases in the world. Injection drug users (PWID) is a population who is at higher risk of acquisition of HCV due to risky behaviors such as needle sharing, and they are considered as an important factor in the spread of the disease. World Health Organization (WHO) aims to eliminate hepatitis C disease by 2030 with the help of approval and dissemination of newly developed direct-acting antiviral treatment regimes. In this study, we evaluated the cost-effectiveness of hepatitis C treatment among injected drug users in Turkey to observe whether it is possible to reach WHO targets. Purpose of our model is to determine the infected population in the future, and we simulated the injected drug user population with a time horizon of 20 years. We developed five scenarios to represent different levels of treatment coverage. We included treatment regimens that are available in Turkey and that are reimbursed by the government health care insurance policies, which roughly covers over 90% of the Turkish population. Our model objective is (i) to predict the spread of HCV in the next 20 years, (ii) to determine the cost of new treatment regimens available to Turkish PWID population and (iii) to estimate the cost-effectiveness of these regimes. Our results indicate that HCV infected PWIDs could significantly decrease with treatment while the lowest total cost of treatment could be achieved with Viekirax Exviera and Mavyret. Also, it is possible to reach WHO targets by 2030 in Turkey if the treatment coverage increases.