Call Center Operators Research Articles

Otologic symptoms and hearing thresholds among a cohort of call center operators in Lagos

BackgroundThe call center operation jobs are becoming a global phenomenon. The use of headphones for 7 to 9 h daily with varying noise level exposure is quite common among call center operators. This can cause structural and/or functional changes in the auditory system. Researchers have arrived at different conclusions regarding the risks associated with prolonged headphone usage. This study aimed to evaluate the risk of hearing changes and the range of otologic symptoms among call center operators in Lagos State, Nigeria.MethodsThis is a prospective cross-sectional study carried out on 90 call center operators (customer service staff) and 90 administrative staff (controls) aged 18 to 40 years working in two call centers affiliated to different private establishments in Lagos State. Their biographic data, work information, and otologic/non-otologic symptoms developed with the commencement of the job were obtained with a self-administered structured questionnaire. After otoscopic examination, diagnostic pure tone audiometry (PTA) was carried out before and after the work shift.ResultsThe most commonly reported symptoms among the call center operators were headache, tinnitus, and vertigo. Symptoms were noted as early as 3 months into the job in 20 (24.7%) call center operators. The pre-shift and post-shift mean PTA of the call center operators were normal bilaterally and comparable to the controls. There was an elevation of low frequency (500 Hz) mean PTA of > 30 dB in both the call center operators and the controls. The mean PTA average for the call center operators’ pre-shift and post-shift were 25.4 ± 8.2 and 25.6 ± 8.1 in the right ear, 24.8 ± 8.5 and 24.7 ± 8.9 in the left ear, 25.9 ± 7.8 and 24.7 ± 7.8 right and left ears for the control. There were no statistically significant differences between the call center operators’ pre-shift and the controls’ hearing thresholds, and the pre-shift and post-shift hearing thresholds of the call center operators at all frequencies and in both ears.ConclusionOtologic and non-otologic symptoms arise from prolonged headphones usage among call center operators. No hearing damage or headphone noise-induced hearing loss was recorded in the call center operators in this study.

Transfer rate prediction at self-service customer support platforms in insurance contact centers

Customer support constitutes the face of a brand and plays a critical role in shaping customers retention and loyalty. To facilitate customer contacts and to reduce the corresponding operating costs, organizations resort to self-service interaction channels. However, dealing with self-service customer support platforms has been identified to be one of the most frustrating aspects of a poor customer contact experience. This paper builds on real data from contact centers of a major U.S. insurance company, covering about 10 million calls, to study transfer rate at the interactive voice-response platform. We develop an empirical model to analyze features that exert significant impact on the likelihood that a call arrived to the platform is eventually transferred to a live agent. We find evidence that caller types, specific caller intents, trying distinct channels, and payment attempts can help predicting the transfer outcome. Our study confirms the importance of a caller’s location attribute and evinces that the size and composition of the set of effective features and their directions vary substantially across different states. Our results provide managers with several actionable insights to enhance the customer contact experience. For example, our feature selection analysis enables designing personalized interactive voice-response systems based on customer-contact features. Identifying those calls expected to be transferred at any time can guide recruiting and scheduling a workforce with appropriate skill sets. In addition, the transfer rate is a key input variable for various decision making problems arising in the management of call center operations.

АНАЛИЗ ОБРАЩЕНИЙ ГРАЖДАН НА ГОРЯЧУЮ ЛИНИЮ МИНИСТЕРСТВА ЗДРАВООХРАНЕНИЯ ЧЕЛЯБИНСКОЙ ОБЛАСТИ В ПЕРИОД ПАНДЕМИИ COVID-19

Abstract. The pandemic of coronavirus infection COVID-19, officially announced by WHO in March 2020, has had a direct impact on all segments of Russian society. Citizens of the Russian Federation, realizing their constitutional rights to health protection and information, with the development of the pandemic began to contact health authorities at the regional and federal levels more often. The authors, using generally accepted approaches, studied the dynamics of citizens' calls to the hotline of the Ministry of Health of the Chelyabinsk Region from January 2020 to March 2021, analyzed the calls received by topic and territorial affiliation. The dynamics of requests was tracked for 15 months; authors identified the main reasons for calls. The features of the work of call center operators and the awareness of citizens about the purpose and rules of the regional Ministry of Health hotline were also studied. The study showed that in the context of the COVID-19 pandemic, the needs of citizens for medical information are sharply increasing; the hotline has become an important point for registering cases of new infection and preventing its spread. Based on the data obtained, the authors made an attempt not only to describe the work with citizens' appeals during different periods of the coronavirus infection epidemic, but also to assess the effectiveness of the regional Ministry of Health hotline, as well as to offer recommendations for improving its recent work.

Noise exposure and hearing status among employees using communication headsets.

The objective of this study was to assess the hearing of employees using communication headsets with regard to their exposure to noise. The study group comprised 213 employees, including 21 workers of the furniture industry, 15 court transcribers and 177 call center operators, aged 19-55 years, working with headsets for a period of up to 25 years. All the participants underwent a standard puretone audiometry, extended high-frequency audiometry (EHFA) as well as transient-evoked otoacoustic emissions (TEOAEs) and distortion-product otoacoustic emissions (DPOAEs). Noise exposure from headsets was evaluated using the microphone in a real ear technique according to PN-EN ISO 11904-1:2008. Personal daily noise exposure levels ranged 57-96 dB and exceeded 85 dB only in 1.4% of the call center operators. Forty-two percent of the participants had bilateral normal hearing in the standard frequency range of 250-8000 Hz, and 33% in the extended highfrequency range of 9-16 kHz. It was found that DPOAEs were present bilaterally in 59% of the participants. Reproducibility of TEOAE at >70% and signal-to-noise ratio at >6 was exhibited by 42% and 17% of them, respectively. The 3 subgroups of workers differed in age, gender, noise exposure and type of headsets in use. However, after adjusting for age and gender, significant differences between these subgroups in terms of hearing were mostly visible in EHFA. A significant impact of age, gender, daily noise exposure level and current job tenure on hearing tests results was also noted among the call center operators and the transcribers. The most pronounced were the effects of age and gender, whereas the impact of the daily noise exposure level was less evident. It seems that EHFA is useful for recognizing early signs of noise-induced hearing loss among communication headset users. However, further studies are needed before any firm conclusions concerning the risk of hearing impairment due to the use of such devices can be drawn. Int J Occup Med Environ Health. 2022;35(5):585-614.

Impact of Motivation and Workload on Service Time Components: An Empirical Analysis of Call Center Operations

We study the joint effects of motivation and workload on human servers’ service time. Using operational and survey data from a call center with a pooled queue structure and limited financial incentives, we examine how individual differences between servers’ trait intrinsic motivation (IM) and extrinsic motivation (EM) impact their average offline, online, and total service times in response to changing workloads. We find significant differences in the patterns of workload and service time relationships across different stages of the service request between servers possessing different combinations of trait motivation. For example, servers with a combination of high IM and low EM were approximately 15% (161%) faster in processing the offline portion of service requests than their peers with the opposite combination (low and high) when workload levels were low (high), respectively. In contrast, servers with high IM-low EM were approximately 35% (5%) slower in processing the online portion of service requests than their low IM-high EM counterparts when workload levels were low (high), respectively. Our findings suggest important nuances in how servers with different trait motivation types respond to changing workload across different stages of the service request. The behavioral pattern shown by high IM-low EM servers is consistent with the preferences of productivity-seeking call center managers who favor speedup and slowdown at certain stages of the service request, conditional to workload. These findings underscore the importance of accounting for trait-based individual differences for a more complete understanding of the complex relationship between workload and service time. This paper was accepted by Charles Corbett, operations management.

Occupational diseases among call center operators needing vocal rehabilitation.

Work related diseases (WRDs) and occupational diseases (ODs) greatly affect call center operators (CCOs) who experience demanding work expectations and adverse working conditions in their workplace. The aim of this study was to evaluate the sociodemographic and job characteristics of CCOs diagnosed with OD, and to describe the changes in employment status after diagnosis. This descriptive study is based on the electronic data records of Istanbul Occupational Diseases Hospital available from February 2007 to March 2018. According to the health board reports, 122 of the 173 (70.5%) CCOs had a confirmed OD diagnosis, 85.2% were females and the mean age was 27.5 years. Vocal cord disorders were the most frequent ODs (64.8%), followed by hearing loss (12.5%), dysphonia (10.2%) and temporomandibular disorders (4.7%). Vocal cord nodules (VCN) were found to be more frequent among females compared to males (92.9% vs 62.4%, p<0.001). Although not statistically significant, the frequency of VCN was also higher in subjects working overtime (14.6% vs 6.3%), having gastroesophageal reflux disease (82.3% vs 73.9%) or thyroid nodules (100% vs 73.7%) and being current smokers (41.7% vs 13.3%). Following the OD diagnosis, 43.8% of the cases were dismissed, 18.7% quit their job, and 9.4% still held the same job position. Only 28.1% changed unit within the workplace. Including the CCOs who were diagnosed with an OD at a very young age and at an early stage of their working life into vocational rehabilitation programs and employing them under appropriate conditions is essential to proper health and safety protocol.

Virtualization and standardization of a health-system specialty pharmacy call center.

The coronavirus disease 2019 (COVID-19) pandemic provided an opportunity to change how health-system specialty pharmacy (HSSP) call center operations are organized. This article describes the steps taken to virtualize the current operations of a specialty pharmacy services call center and evaluate the impact. The onset of the COVID-19 pandemic and its impact on the normal provision of healthcare necessitated that HSSPs drastically modify existing procedures to both accommodate the expectations of staff and overcome the many barriers to care being experienced by patients. To fully understand and improve upon the workflow processes of an HSSP call center, a combination of qualitative feedback from patients, quantitative claims data, and quality metrics was evaluated. This project was divided into 3 phases: phase 1 (baseline) from July 2020 through August 2020, phase 2 (implementation) from September 2020 through December 2020, and phase 3 (analysis) from January 2021 through March 2021. Phase 1 included baseline review of workflow. Phase 2 encompassed development of new standard operating procedures (SOPs), making critical decisions to promote virtual capabilities of staff, and collaboration with team members to increase efficiency of current workflow. During phase 3, an evaluation of operational and service-related metrics was conducted to determine the impact of phase 2 workflow changes. Optimization of the specialty pharmacy call center allowed for staff members to transition to remote work to minimize exposure risk and prioritize the safety of patients and team members. The call center team was able to transition to fully remote operations, implement new SOPs, and undergo significant workflow changes to optimize performance while still maintaining all call center metric goals and without increased complaints from patients or errors. This approach allowed for added staff value and safety and improved organization during the COVID-19 pandemic.

Assuring safe artificial intelligence in critical ambulance service response: study protocol.

Early recognition of out-of-hospital cardiac arrest (OHCA) by ambulance service call centre operators is important so that cardiopulmonary resuscitation can be delivered immediately, but around 25% of OHCAs are not picked up by call centre operators. An artificial intelligence (AI) system has been developed to support call centre operators in the detection of OHCA. The study aims to (1) explore ambulance service stakeholder perceptions on the safety of OHCA AI decision support in call centres, and (2) develop a clinical safety case for the OHCA AI decision-support system. The study will be undertaken within the Welsh Ambulance Service. The study is part research and part service evaluation. The research utilises a qualitative study design based on thematic analysis of interview data. The service evaluation consists of the development of a clinical safety case based on document analysis, analysis of the AI model and its development process and informal interviews with the technology developer. AI presents many opportunities for ambulance services, but safety assurance requirements need to be understood. The ASSIST project will continue to explore and build the body of knowledge in this area.

Computer Modeling of Human Voice System Diagnostic Algorithms

Every year, people are faced with an increasing number of diseases that require timely detection and diagnosis without causing discomfort to the patient. Thus arose the systems of objective and subjective assessment of the quality of hearing, as well as the first systems of analysis of the state of the vocal tract. The problem of voice pathology is inherent in a fairly large risk group, which includes teachers, artists, call center operators. The specifics of the development of such systems is that the hardware and software complex developed by the engineer should be convenient for use by a doctor and relevant in terms of existing solutions to identify certain acoustic parameters of the voice. The study of the voice spectrum can be the main diagnostic test in the diagnosis of persistent voice disorders and, along with the study of the voice field and vibrometry, allows you to determine the form of voice disorders in professionals. Acoustic tests for the presence of high and low singing forms in the singing voice can be highly important in determining the singer's performance and professional prognosis, can serve as a criterion in the diagnosis of persistent voice disorders, and their use in early stages of occupational laryngeal diseases will help prevent preventive measures. MATLAB software comes with a large number of tools, which facilitates the implementation of many engineering, mathematical, computational issues of development and research of various processes related to any field of research. Based on these tools, there are a large number of basic functions of digital signal analysis, including audio signals. FFT - fast Fourier transform algorithms are chosen as a basis, which with a certain modification are divided into parametric and nonparametric. In this case, the nonparametric Welch method and the parametric Berg method are chosen. The user is given access to choose between the parameters required for their operation. For the first it is the dimension of the weight function, for the second it is the order of the autoregressive model. All this gives opportunity to analyze the spectrum of vowel phonemes. The AppDesigner package provides great opportunities for creating interfaces in software development. By manipulating the functions of Callback, you can bring the program to the finest settings, which at first may seem invisible, but generally create comfort when working. It is important to build a certain algorithm of action of each component. It often happens that it is necessary to take into account such details for which a certain component in itself is not responsible. For example, this could be changing the signatures of other components. To simplify code writing, it is important to create m-functions. However, this must be taken into account when editing them after entering them in the main script. Using the above toolbox, a software interface was developed, which is divided into two working areas: time and spectral parts. In addition, the interface is filled with controls for input data and spectrum analyzer parameters, as well as spectrum analysis tools.

Telephone Access Management in Primary Care: Cross-Case Analysis of High-Performing Primary Care Access Sites

ABSTRACTBackgroundPrimary care telephone access has been associated with patient satisfaction and emergency department utilization even after accounting for objective appointment wait times. However, relatively little is known about how to best structure and manage telephone access in primary care.ObjectiveAssess how primary care telephone access is structured and managed and explore how variation in telephone management may affect primary care teams and patients.DesignWe used 2016 administrative and patient survey data to select six Veterans Administration medical centers (VAMCs) with above-average primary care access (time to third next available appointment) but variable patient-reported access, geographic region, and urbanicity. Semi-structured interviews were conducted August –October 2017.ParticipantsForty-three key stakeholders knowledgeable about primary care, telephone management, and operational priorities nationally and/or within each VAMC.Key ResultsTelephone access was organized and managed differently across sites. Regional call centers were perceived as more efficient but less flexible in tailoring processes to meet local needs. Patient preferences for speaking with their own care teams were cited as a reason to manage telephone access locally rather than regionally, particularly in rural sites. Sites with high patient-rated access described call center functions as well-integrated with primary care team workflow, while those with low patient-rated access perceived telephone management practices as negatively affecting primary care team workload. Call center understaffing was a major barrier to optimal telephone access in all six sites, though rural sites reported greater challenges with provider recruitment and retention.ConclusionsIn VA, efforts to improve telephone access have focused on centralizing call center operations but current call center performance metrics do not account for the extent to which call center functions are integrated with primary care workflows or may impact patient experience. Efforts to improve primary care access should carefully consider impact of telephone management practices on providers and patients.

Noise Exposure, Headsets, and Auditory and Nonauditory Symptoms in Call Center Operators

This study evaluates the exposure of call center operators (CCOs) to occupational noise, its association with auditory and nonauditory symptoms, and the feasibility of monaural and binaural headsets. We measured the noise exposure sound pressure levels (SPLs) with the microphone-in-real-ear technique and administered a questionnaire on auditory/nonauditory symptoms and headset preference. We assessed 79 CCOs with normal hearing. Overall, 98.7% of the participants reported at least one auditory symptom, and 88.6% reported at least one nonauditory symptom after using the headset. We found significant associations between the headset volume setting and the number of auditory and nonauditory symptoms and between sharp increases in sound level and tinnitus. The microphone-in-real-ear diffuse-field-related SPLs with monaural headsets (85.5 dBA) were significantly higher than those with binaural headsets (83.1 dBA). Binaural headsets were the preference of 84.8% of the subjects. The SPLs of the binaural headsets were significantly lower than those of the monaural headsets in the subjects who preferred the binaural headsets. CCOs with normal hearing reported auditory and nonauditory symptoms, highlighting the need for attention and further investigation. The binaural headsets were preferable, as they were associated with a lower SPL and a higher call quality. https://doi.org/10.23641/asha.18361463.

Performance evaluation of an EMS system using queuing theory and location analysis: A case study.

In emergency medical services (EMS), response time is a key factor that shows the performance of the system. This factor is composed of two parts including activation time and travel time. The activation time of an emergency call is the time a call center spends on taking an incoming call for EMS and decides whether an ambulance should be dispatched or the emergency can be resolved by giving some medical advices. Having a good number of call center operators including call takers and dispatchers can help to reduce this time and thus the response time. However, this alone may not be enough to have a reasonable cycle time. In fact, having idle ambulances located in right places when emergency calls occur is an influential factor to reduce the travel time and thus have an optimal response time and save people's lives. Although many researchers have studied improving either the activation time or the travel time, to the best of our knowledge, there exists no study focusing on both. Motivated by this gap, in this study, a framework is proposed which uses queuing theory and location analysis to address both activation and travel times. In this regard, first, queuing theory is applied to evaluate the performance of an EMS call center and reduce the average activation time. Then, three mathematical models including mobile stations, MEXCLP and MECRP are applied to locate ambulances such that the average travel time is minimized. To shed light on the merits of using queuing theory and location models, computational results based on the real-world data from Tehran EMS Center are provided. The proposed methodology can reduce the average response time by approximately four minutes and increase the average coverage by 35%. This work is an example of the tremendous positive impact that the application of queuing theory and mathematical modeling can have. The proposed framework can significantly decrease the cycle time and increase the ambulance coverage level. The findings of this study help the policy makers of EMS centers with evaluating the performance of their systems and determining the optimal number of operators and locations of ambulances in a way that enhances the quality of emergency services.

The Speech Act of Apology by Filipino Call Center Agents

The Philippines is a global leader in business process outsourcing (BPO). Many foreign investors view the Philippines as a viable location for their call center operations due to the Filipinos' strength in English proficiency. This study focuses on inbound call center accounts that deal with a variety of call situations, ranging from information requests to difficult calls that require more time to handle, such as complaint calls. Since the goal of any business is customer satisfaction, this research aims to investigate how Filipino call center agents mitigate and reduce the liability and guilt towards customers. Results show that the 90 call center representatives have successfully produced 'perfect apologies' by providing all five strategies posited by Cohen et al. (1986) in most of their complaint calls. However, the sequence is distorted by emphasizing more on offering a repair. This leads to a recommendation that calls center training on apology be emphasized on building personal connections rather than a mechanical response to situations.

Impact of Outsourcing on Effectiveness of Call Center Services

Call center is the frontline of communicating with customers. This paper reports the findings of a survey on service effectiveness of call center operations of mobile communication service providers in Turkey that either use in-house or outsourcing method. The primary objective of this paper is to explore how the customers of mobile communications service provider companies perceive the inbound call center processes for speed, easiness of use, first call resolution, effective inquiry and in doing that what qualities they display. For this purpose a survey was conducted with the customers who use call centers either to make an inquiry or to complain about the services. The aims were: to specify the typical behavior of mobile communications service users; how the firms handle inquiries or complaints; if they solve the problems for good and in what time or how long it takes to get an answer practically useful; to reveal the speed and timeliness of the processes. The survey was conducted with the mobile phone users in a highly populated area of Istanbul.

Mediating Role of Stress at Work in the Relationship of Alexithymia and PTSD among Emergency Call Operators.

Aim: The main purpose of this research was to investigate the relationship between alexithymia, stress at work, and post-traumatic stress disorder (PTSD) in impact emergency call center operators working in Poland (province of Greater Poland). The risk of exposure to critical life events was also considered. Methods: Data were collected using self-report questionnaires administered after dispatchers’ shifts. The emergency call center operators (N = 66) completed the Impact of Event Scale—Revised, 20-item Toronto Alexithymia Scale, Workplace Perceived Stress Questionnaire, and a questionnaire measuring the frequency and intensity of potentially traumatic events faced by emergency operators (a questionnaire developed by the authors). Results: Twenty of the most frequent events (e.g., child sexual harassment, rape, etc.) were identified. Results indicated that post-traumatic stress positively correlated with (a) work-related stress and (b) one aspect of alexithymia: difficulty expressing feelings. Additionally, work-related stress was identified as a mediator for the relation between alexithymia and the intensity of post-traumatic stress. Conclusions: The results of this study confirm that emergency operators are a high-risk group for the development of PTSD. The study results suggest that performing the work of an emergency dispatcher is not only demanding but also inherently involves participation in potentially traumatic events (as encountered through emergency calls).

Incoming Call Forecasting Framework for a Network Service Provider Call Center during Mobile Expo Events

An accurate forecasting model for call center operations allows a company to optimize the number of staffs needed. However, when a special event is planned, the call volume and pattern during that event can be expected to be different from those reflected in the historical database, and consequently, the accuracy of current forecasting methods may degenerate. Thus, a framework that can help to provide a highly accurate forecasting model in such situations is needed. In this paper, a conceptual framework for forecasting incoming calls during mobile expo events is proposed. The framework comprises four main steps: defining data types, verifying time series forecasting methods based on the defined data types, defining the forecasting model and forecasting the incoming calls. This approach can assist in systematically selecting an appropriate forecasting model when a mobile expo event is arranged. Experimental results show that this framework helps to select the appropriate forecasting model for each mobile expo event organized over one year. For the first and third mobile expo event periods, a mixed-period model with an individual forecasting approach, provides the best result, whereas in the second period, a combined forecasting approach for nonevent and mobile expo event periods, is the most appropriate.

BGL Group: Artificial Intelligence (AI) Strategy

This research presents a detailed case analysis of BGL Group, a leading, international, distributor of insurance and household financial services. The AI strategy is described by analysing and evaluating a set of AI applications covering a variety of business areas: 1. Machine learning for pricing; 2. Chatbot AI technology to improve the customer experience in e-service; 3. Customer experience design thinking and a/b testing in new product development; 4. Voice recognition and Natural Language Processing (NLP) in call centre operations; 5. AI techniques for market segmentation. Each application is described in detail, and the concept of value creation in service markets is illustrated using data flow diagrams of customer interactions for different stages of the customer journey. A benefits matrix model is proposed that captures the principal AI benefits to both the supplier and the customer. The case discussion uses a new model, an AI systems map, to describe and explain the overall landscape of current AI applications, traditional Management Information Systems (MIS) and possible future application areas based on broad AI strategies and cognitive AI/thinking machines. Some concluding remarks are made on the importance of a digital first culture, up-to-date digital infrastructure and technology partnerships for successful implementation of AI systems, the crucial role of big data in AI strategies, and the growing importance of AI ethics in business applications. Finally, some propositions are offered regarding the future direction of AI in insurance markets.

Gender differences in vocal doses among occupational voice users: a systematic review of literature and meta-analysis

Background Occupational voice users such as teachers, singers, and broadcasters have high vocal demands increasing the risk for developing voice disorders. Among occupational voice users, the literature has report gender differences in vocal doses as part of vocal demands. However, these differences have not been quantified. Objective To determine differences per gender on vocal doses among different groups of occupational voice users. Methods A systematic review of literature and meta-analysis were conducted on publications about vocal dose among occupational voice users. In total, 242 potential articles were found. After screening of titles and abstracts, 16 papers were included for full revision in the systematic review of literature. For the meta-analysis, 7 out of 16 papers were included. Results Females had higher phonation time percentage compared with males (mean difference = 1.44, p value = .16). Nevertheless, this difference was not statistically significant. Among call centre operators, there was no difference in time doses associated with gender. Sport teachers had high values in time dose percentage, dissipation, and radiated energies. Conclusions The meta-analysis shows variations in time doses, which could be associated with the vocal demand responses for females compared with males in occupational voice settings. Future investigations are required for establishing safe limits criteria for vocal doses, as well as vocal functioning in different working context.

Značaj nacionalne koordinacije za brzi odgovor na COVID-19 u Crnoj Gori tokom prvog talasa pandemije

Introduction/Aim: The first detected case of SARS-CoV-2 infection in Montenegro was reported on March 17th, 2020. On March 20th, the National call center for COVID-19 started operating, with the main purpose to timely respond to the suspicion of COVID-19, as well as to provide support to local epidemiological services by involving a large number of previously trained volunteers as call center operators. The aim of this descriptive study was to present the results of the national coordination for a quick response to COVID-19 in Montenegro during the first wave of the pandemic. Methods: The data about the number of calls were taken from the contact application which enables detailed reporting on the status of calls, while data of interviewed people were taken from the database created by filling out an online questionnaire during the interview. Results: In period from March 20th to May 18th, 2020, 27,380 calls were realized, 16.130 of which were incoming calls, with daily variations (in relation to the daily number of reported cases, as well as in relation to whether it was a working day or weekend/state holiday). Also, in the same period, due to suspicion of COVID-19, 2,288 persons were interviewed and slightly more were men (50.5%). The largest number of respondents were from Podgorica (59.8%), and from the age group 60 or older (24.9%). During the study period, 40.4% of the total number of reported cases of SARS-CoV-2 infections in Montenegro were directly or indirectly related to the Call center. Conclusion: The national phone-line in coordinating for a quick response to COVID-19 met the primary goal, to be a "dam" until the health system consolidates, and to reduce pressure on limited human capacities. A notable percentage of detected cases through the line contributed to quicker detection of contacts of infected persons and helped quarantine them, which significantly contributed to the control of infection spreading.

Two-way communication retrial queue with unreliable server and multiple types of outgoing calls

Retrial queue under consideration is the model of call center operator switching between input and outgoing calls. Incoming calls form a Poisson point process. Upon arrival, an incoming call occupies the server for an exponentially distributed service time if the server is idle. If the server if busy, an incoming call joins the orbit to make a delay before the next attempt to take the server. The probability distribution of the length of delay is an exponential distribution. Otherwise, the server makes outgoing calls in its idle time. There are multiple types of outgoing calls in the system. Outgoing call rates are different for each type of outgoing call. Durations of different types of outgoing calls follow distinct exponential distributions. Unsteadiness is that the server crashes after an exponentially distributed time and needs recovery. The rates of breakdowns and restorations are different and depend on server state. Our contribution is to obtain the probability distribution of the number of calls in the orbit under high rate of making outgoing calls limit condition. Based on the obtained asymptotics, we have built the approximations of the probability distribution of the number of calls in the orbit.