A comparison of online and face-to-face teaching of economically oriented master's degree university studies

PurposeThe aim of this paper is to evaluate the influence of distance learning of the subject Operational Research in terms of the impact of the COVID-19 pandemic on the quality of teaching and the success of this course, to find out the satisfaction of students with the online learning, and the impact on the performance.Design/methodology/approachGrades of students from the subject were collected from the Faculty of Business and Economics of Mendel University in Brno between 2009 and 2021. A questionnaire concerning the views of students on online teaching of the subject and its comparison with face-to-face teaching was conducted, and the data obtained from 94 respondents were statistically processed by cluster analysis and the K-means method.FindingsA comparison of the results of examinations from the years taught in classical face-to-face form and from the period when teaching took place only online showed no significant effect on the final grades of the students. The results show that the students were basically divided into two-halves: one-half that preferred online teaching and the other that supported a more face-to-face form of teaching. Most of the students highly appreciated the tutorial videos provided because of the possibility of repeated viewing.Originality/valueThe paper shows that online teaching may be a suitable replacement for standard teaching. The paper answers the question whether some online elements can be integrated in the standard form of teaching.

Hybridizing adaptive large neighborhood search with kernel search: a new solution approach for the nurse routing problem with incompatible services and minimum demand

The average age of the population has grown steadily in recent decades along with the number of people suffering from chronic diseases and asking for treatments. Hospital care is expensive and often unsafe, especially for older individuals. This is particularly true during pandemics as the recent SARS-CoV-2. Hospitalization at home has become a valuable alternative to face efficiently a huge increase in treatment requests while guaranteeing a high quality of service and lower risk to fragile patients. This new model of care requires the redefinition of health services organization and the optimization of scarce resources (e.g., available nurses). In this paper, we study a Nurse Routing Problem that tries to find a good balance between hospital costs reduction and the well-being of patients, also considering realistic operational restrictions like maximum working times for the nurses and possible incompatibilities between services jointly provided to the same patient. We first propose a Mixed Integer Linear Programming formulation for the problem and use some valid inequalities to strengthen it. A simple branch-and-cut algorithm is proposed and validated to derive ground benchmarks. In addition, to efficiently solve the problem, we develop an Adaptive Large Neighborhood Search hybridized with a Kernel Search and validate its performance over a large set of different realistic working scenarios. Computational tests show how our matheuristic approach manages to find good solutions in a reasonable amount of time even in the most difficult settings. Finally, some interesting managerial insights are discussed through an economic analysis of the operating context. © 2022 The Authors. International Transactions in Operational Research published by John Wiley & Sons Ltd on behalf of International Federation of Operational Research Societies.

Empanelment of the Population to the Primary Medical Care Institution of Sri Lanka: A Mixed-Methods Study on Outcomes and Challenges.

The registration of individuals with designated primary medical care institutions (PMCIs) is a key step towards their empanelment with these PMCIs, supported by the Primary Health Care System Strengthening Project in Sri Lanka. We conducted an explanatory mixed-methods study to assess the extent of registration at nine selected PMCIs and understand the challenges therein. By June 2021, 36,999 (19.2%, 95% CI-19.0-19.4%) of the 192,358 catchment population allotted to these PMCIs were registered. At this rate, only 50% coverage would be achieved by the end of the project (December 2023). Proportions of those aged <35 years and males among those registered were lower compared to their general population distribution. Awareness activities regarding registration were conducted in most of the PMCIs, but awareness in the community was low. Poor registration coverage was due to a lack of dedicated staff for registration, misconceptions of health care workers about individuals needing to be registered, reliance on opportunistic or passive registration, and lack of monitoring mechanisms; these were further compounded by the COVID-19 pandemic. Moving forward, there is an urgent need to address these challenges to improve registration coverage and ensure that all individuals are empaneled before the close of the project for it to have a meaningful impact.

Predicting the outbreak of epidemics using a network-based approach

The spread of epidemics is a common societal problem across the world. Can operational research be used to predict such outbreaks? While equation-based approaches are used to model the trajectory of epidemics, can a network-based approach also be used? This paper presents an innovative application of epidemic modelling through the design of both approaches and compares between the two. The network-based approach proposed in this paper allows implementing heterogeneity at the level of individuals and incorporates flexibility in the variety of situations the model can be applied to. In contrast to the equation-based approach, the network-based approach can address the role of individual differences, network properties, and patterns of social contacts responsible for the spread of epidemics but are much more complex to implement. In this paper, we simulated the spread of infection at the beginning of Covid-19 (Coronavirus disease 2019) using both approaches. The results are showcased using empirical data for eight countries. Sophisticated measures, including partial curve mapping, are used to compare the simulated results with the actual number of infections. We find that the plots generated by the network-based approach match the empirical data better than the equation-based approach. While both approaches can be used to predict the spread of infections, we conclusively show that the proposed network-based approach is better suited with its ability to model the spread of epidemics at the level of an individual. Hence, this can be a model of choice for epidemiologists who are interested to model the spread of an epidemic. © 2023 Elsevier B.V.

Capacity building in operational research on obstetric fistula: Experience in the Democratic Republic of Congo, 2017-2021.

OBJECTIVE: To implement a Flexible Operational Research Training (FORT) course within the Fistula Care Plus Project, Democratic Republic of Congo, from 2017 to 2021. METHODS: A descriptive study using design and implementation (process and outcome) data. Two to four members of medical teams from three supported sites were selected for the training based on their research interests and level of involvement in the program. RESULTS: Two courses (13-14 months each) involving nine facilitators and 17 participants overall were conducted between 2017 and 2021. Most participants in both courses were medical doctors (67% and 71%, respectively) from the supported hospitals (83% and 77%, respectively). About half were women. In addition to classic face-to-face didactic modules, the courses integrated online platforms to cope with the changing contexts (Ebola virus and COVID-19). Most participants reported having gained new skills in developing research protocols, collecting, managing, and analyzing data, and developing research manuscripts. The two courses resulted in six scientific manuscripts and three presentations at international conferences. Participants subsequently published five papers from their research after the first course. The total direct costs for both courses were representing a cost of $3669 per participant trained. CONCLUSION: The FORT model proved feasible, efficient, and successful. However, scaling up will require more adaptation efforts from programs and participating sites.

Outcomes and Challenges in Noncommunicable Disease Care Provision in Health Facilities Supported by Primary Health Care System Strengthening Project in Sri Lanka: A Mixed-Methods Study.

The Primary Healthcare System Strengthening Project in Sri Lanka focuses on improving noncommunicable disease (NCD) care provision at primary medical care institutions (PMCIs). We conducted an explanatory mixed-methods study to assess completeness of screening for NCD risk, linkage to care, and outcomes of diabetes/hypertension care at nine selected PMCIs, as well as to understand reasons for gaps. Against a screening coverage target of 50% among individuals aged ≥ 35 years, PMCIs achieved 23.3% (95% CI: 23.0-23.6%) because of a lack of perceived need for screening among the public and COVID-19-related service disruptions. Results of investigations and details of further referral were not documented in almost half of those screened. Post screening, 45% of those eligible for follow-up NCD care were registered at medical clinics. Lack of robust recording/tracking mechanisms and preference for private providers contributed to post-screening attrition. Follow-up biochemical investigations for monitoring complications were not conducted in more than 50% of diabetes/hypertension patients due to nonprescription of investigations by healthcare providers and poor uptake among patients because of nonavailability of investigations at PMCI, requiring them to avail services from the private sector, incurring out-of-pocket expenditure. Primary care strengthening needs to address these challenges to ensure successful integration of NCD care within PMCIs.

Audit of Clinical Care Received by COVID-19 Patients Treated at a Tertiary Care Hospital of Nepal in 2021.

Like the world over, Nepal was also hard hit by the second wave of COVID-19. We audited the clinical care provided to COVID-19 patients admitted from April to June 2021 in a tertiary care hospital of Nepal. This was a cohort study using routinely collected hospital data. There were 620 patients, and most (458, 74%) had severe illness. The majority (600, 97%) of the patients were eligible for admission as per national guidelines. Laboratory tests helping to predict the outcome of COVID-19, such as D-dimer and C-reactive protein, were missing in about 25% of patients. Nearly all (>95%) patients with severe disease received corticosteroids, anticoagulants and oxygen. The use of remdesivir was low (22%). About 70% of the patients received antibiotics. Hospital exit outcomes of most (>95%) patients with mild and moderate illness were favorable (alive and discharged). Among patients with severe illness, about 25% died and 4% were critically ill, needing further referral. This is the first study from Nepal to audit and document COVID-19 clinical care provision in a tertiary care hospital, thus filling the evidence gap in this area from resource-limited settings. Adherence to admission guidelines was excellent. Laboratory testing, access to essential drugs and data management needs to be improved.

Prioritization of operational research questions on COVID-19 vaccination in the African Region.

Introduction: a year after the start of COVID-19 vaccination, coverage remains very low in the African Region. Different challenges and operational barriers have been documented, but countries will need to supplement the available information with operational research in order to adequately respond to practical questions regarding how best to scale up COVID-19 vaccination. We conducted a survey among immunisation program staff working in the African Region, in order to identify the high priority operational research questions relevant to COVID-19 vaccination. Methods: proposed operational research questions categorized into six topic areas were sent to resource persons, asking them to rate according to the relevance, urgency, feasibility, and potential impact of the research questions on the progress of COVID vaccination. Results: a total of 25 research questions have been given an average weighted rating of 75% or more by the respondents. Nine of these top priority research questions were in the area of demand generation, risk communication and community engagement while 8 questions covered the area of service delivery. Conclusion: countries should plan for and coordinate stakeholders to ensure that relevant operational research is done to respond to the top priority research questions, with a view to influence policies and implementation of strategies.

The system-wide effects of dispatch, response and operational performance on emergency medical services during Covid-19.

In this paper, we analyze the Fire Department of New York City's pre-hospital emergency medical services dispatch data for the period of March 20, 2019-June 13, 2019, and the corresponding Covid lockdown period of March 20, 2020-June 13, 2020. A fixed effects negative binomial model is used to estimate the heterogeneity effects of average ambulance travel or response times on the daily volume of emergency calls, year, day of the week, dispatcher-assigned medical emergency call type, priority rank, ambulance crew response, borough and an offset for missing calls. We also address the limitations of other non-parametric Covid studies or parametric studies that did not properly account for over-dispersion. When our model is estimated and corrected for clustered standard errors, fixed effects, and over-dispersion, we found that Wednesday was the only day of the week that was most likely to increase travel response time with an odd ratio of 6.91%. All grouped call types that were categorized showed significant declines in average travel time, except for call types designated as allergy and an odds ratio of 21.81%. When compared to Manhattan, Staten Island ambulance response times increased with an odds ratio of 19.05% while the Bronx showed a significant decline with an odds ratio of 31.92% advanced life support (ALS) and BLS ambulances showed the biggest declines in travel time with the exception of BLS assigned ambulance types and emergency priority rank of 6. Surprisingly, in terms of capacity utilization, the dispatch system was not as overwhelmed as previously predicted as emergency call volume declined by 8.83% year over year.

Originating multiple-objective portfolio selection by counter-COVID measures and analytically instigating robust optimization by mean-parameterized nondominated paths

The COVID-19 pandemic is unleashing crises of humanity, economy, and finance. Portfolio selection is widely recognized as the foundation of modern financial economics. Therefore, it is naturally crucial and inviting to utilize portfolio selection in order to counter COVID-19 in stock markets. We originate a counter-COVID measure for stocks, extend portfolio selection, and construct multiple-objective portfolio selection. Because of the uncertainty in measuring counter-COVID, we perform robust optimization. Specifically, we analytically compute the optimal solutions as a trail of an optimal portfolio due to the change of counter-COVID. We call the trail as mean-parameterized nondominated path. Moreover, the path is a continuous function of the change, so the portfolio relatively mildly varies for the change. In contrast, researchers typically still focus on 2-objective robust illustrations and infrequently explicitly compute the optimal solutions for multiple-objective portfolio optimization. To the best of our knowledge, there is limited research for multiple-objective portfolio selection of COVID and for the robust optimization of multiple-objective portfolio selection. In such an area, this paper contributes to the literature. The implications to fight COVID are that investors minimize risk, maximize return, and maximize counter-COVID in stock markets and that investors ascertain the multiple-objective portfolio selection as relatively robust.

Achieving Minimum Standards for Infection Prevention and Control in Sierra Leone: Urgent Need for a Quantum Leap in Progress in the COVID-19 Era!

INTRODUCTION: Good Infection prevention and control (IPC) is vital for tackling antimicrobial resistance and limiting health care-associated infections. We compared IPC performance before (2019) and during the COVID-19 (2021) era at the national IPC unit and all regional (4) and district hospitals (8) in Sierra Leone. METHODS: Cross-sectional assessments using standardized World Health Organizations IPC checklists. IPC performance scores were graded as inadequate = 0-25%, basic = 25.1-50%, intermediate = 50.1-75%, and advanced = 75.1-100%. RESULTS: Overall performance improved from 'basic' to 'intermediate' at the national IPC unit (41% in 2019 to 58% in 2021) and at regional hospitals (37% in 2019 to 54% in 2021) but remained 'basic' at district hospitals (37% in 2019 to 50% in 2021). Priority gaps at the national IPC unit included lack of: a dedicated IPC budget, monitoring the effectiveness of IPC trainings and health care-associated infection surveillance. Gaps at hospitals included no assessment of hospital staffing needs, inadequate infrastructure for IPC and lack of a well-defined monitoring plan with clear goals, targets and activities. CONCLUSION: Although there is encouraging progress in IPC performance, it is slower than desired in light of the COVID-19 pandemic. There is urgent need to mobilize political will, leadership and resources and make a quantum leap forward.

Introduction to the special issue on the role of operational research in future epidemics/ pandemics.

In this special issue, 23 research papers are published focusing on COVID-19 and operational research solution techniques. First, we detail the process from advertising the call for papers to the point where the best papers are accepted. Then, we provide a summary of each paper focusing on applications, solution techniques and insights for practitioners and policy makers. To provide a holistic view for readers, we have clustered the papers into different groups: transmission, propagation and forecasting, non-pharmaceutical intervention, healthcare network configuration, healthcare resource allocation, hospital operations, vaccine and testing kits, and production and manufacturing. Then, we introduce other possible subjects that can be considered for future research.

Optimal Models for Distributing Vaccines in a Pandemic

Distributing vaccines among a massive population is one of the challenging tasks in a pandemic. Therefore, health care organizations need to optimize the assignment of vaccination appointments for people while considering their priorities and preferences. In this paper, we propose two optimal vaccine distribution models as Integer Linear Programming (ILP) models;namely, Priority-based Model (PM) and Priority & Preference-based Model (PPM), to maximize the distribution of vaccines among a given population. In PM, we divide the people among several priority groups and ensure maximum vaccine distribution among the higher priority groups. However, along with the priority groups, PPM also considers a list of preferred vaccine distribution centers and time slots for each person. Thus, this model maximizes vaccine distribution among the higher priority groups by assigning appointments in their desired location and time. We analyzed the performance of our proposed models on a randomly generated dataset. In addition, we also performed a case study for our proposed models on the COVID-19 vaccination dataset from Thunder Bay, Canada. In both experiments, we show that PPM outperforms PM in full-filling people's preferences while maximizing the distribution of vaccines among the higher priority groups.

Trends in Influenza Infections in Three States of India from 2015-2021: Has There Been a Change during COVID-19 Pandemic?

The COVID-19 pandemic and public health response to the pandemic has caused huge setbacks in the management of other infectious diseases. In the present study, we aimed to (i) assess the trends in numbers of samples from patients with influenza-like illness and severe acute respiratory syndrome tested for influenza and the number and proportion of cases detected from 2015-2021 and (ii) examine if there were changes during the COVID-19 period (2020-2021) compared to the pre-COVID-19 period (2015-2019) in three states of India. The median (IQR) number of samples tested per month during the pre-COVID-19 period was 653 (395-1245), compared to 27 (11-98) during the COVID-19 period (p value < 0.001). The median (IQR) number of influenza cases detected per month during the pre-COVID-19 period was 190 (113-372), compared to 29 (27-30) during the COVID-19 period (p value < 0.001). Interrupted time series analysis (adjusting for seasonality and testing charges) confirmed a significant reduction in the total number of samples tested and influenza cases detected during the COVID-19 period. However, there was no change in the influenza positivity rate between pre-COVID-19 (29%) and COVID-19 (30%) period. These findings suggest that COVID-19-related disruptions, poor health-seeking behavior, and overburdened health systems might have led to a reduction in reported influenza cases rather than a true reduction in disease transmission.

Compliance with Medication amongst Persons with Diabetes Mellitus during the COVID-19 Pandemic, Kerala, India: A Cross Sectional Study.

Compliance with medication in persons with diabetes mellitus (DM) has been a challenge during the COVID-19 pandemic, leading to poor glycemic control and higher risk of complications. In the state of Kerala, India, 20-25% of adults have DM. Our cross-sectional study aimed to assess medication compliance and factors associated with poor compliance in DM persons attending selected primary care government facilities in Kerala during the COVID-19 pandemic. Persons registered with DM for >6 months were consecutively interviewed between August and September 2021. Poor compliance was defined as answering "No" to one or more of three questions related to access and intake of medication two weeks prior to and the day before the interview. Factors independently associated with poor compliance were assessed using adjusted prevalence ratios (aPr) and 95% confidence intervals. Of the 560 DM persons included, 209 (37%) exhibited poor compliance. Factors associated with poor compliance were age 19-45 years (aPr 1.4, 1.1-1.9); inability to be blood glucose tested during the COVID-19 pandemic (aPr 3.6, 2.9-4.3); not having COVID-19 (aPr 1.4, 1.0-1.9); and being double vaccinated against COVID-19 (aPr 1.4, 1.1-2.0). Focused attention must be paid to these groups to improve medication compliance and prevent DM complications and severe COVID-19-related disease.

COVID-19 Amongst Travelers at Points of Entry in Nepal: Screening, Testing, Diagnosis and Isolation Practices.

WHO recommends surveillance for COVID-19 among travelers at Points of Entry (POE) to countries. At 13 selected POE at the Nepal-India border, between March 2021 and July 2021, we describe the screening, testing, diagnosis and isolation practices of COVID-19 amongst travelers. Those who stayed in India or elsewhere for > one day and those who did not have a negative RT-PCR result within the last 72 h of travel were tested for COVID-19 with rapid antigen diagnostic tests. Daily surveillance reports maintained at POE were used for analysis. Of 337,338 travelers screened, 69,886 (21%) were tested and 3907 (6%) were diagnosed with COVID-19. The proportions tested averaged 15% during April-May when screened numbers were high and increased to 35% in July when screened numbers had decreased. The proportions diagnosed positive peaked at 10% in April-May, but decreased to below 1% in June and July. Testing coverage varied from 0-99% in the different POE. Most COVID-19 cases were Nepalese, male, <60 years of age, migrant workers and presented with fever. Of COVID-19 cases, 32% had home-based isolation, 64% underwent community-based isolation and the remainder either went to hospital or returned to India. In conclusion, about one fifth of travelers overall were tested, with coverage varying considerably over time and among different POE. Strengthening surveillance processes at POE is needed.

Pesticide Importation in Sierra Leone, 2010-2021: Implications for Food Production and Antimicrobial Resistance.

There are no previous studies reporting the type and quantity of pesticides for farming from Sierra Leone and the impact of Ebola or COVID-19 on importation. This study reviewed imported farming pesticides by the Sierra Leone, Ministry of Agriculture and Forestry (MAF), between 2010-2021. It was a descriptive study using routinely collected importation data. We found the MAF imported pesticides for farming only during 2010, 2014 and 2021, in response to growing food insecurity and associated with Ebola and COVID-19 outbreaks. Results showed insecticide importation increased from 6230 L in 2010 to 51,150 L in 2021, and importation of antimicrobial pesticides (including fungicides) increased from 150 kg in 2010 to 23,560 kg in 2021. The hazard class risk classification of imported pesticides decreased over time. Increasing amounts of imported fungicides could increase the risk of future fungal resistance among humans. We found that in responding to escalating food insecurity, the government dramatically increased the amount of pesticide importation to improve crop production. Further support is necessary to decrease the risk of worsening food shortages and the possible threat of emerging antimicrobial resistance. We recommend continued monitoring and surveillance, with further studies on the most appropriate response to these multiple challenges.

Assessment of Infection Prevention and Control Measures at Points of Entry in Sierra Leone in 2021: A Cross-Sectional Study

Implementing and monitoring infection prevention and control (IPC) measures at immigration points of entry (PoEs) is key to preventing infections, reducing excessive use of antimicrobials, and tackling antimicrobial resistance (AMR). Sierra Leone has been implementing IPC measures at four PoEs (Queen Elizabeth II Quay port, Lungi International Airport, and the Jendema and Gbalamuya ground crossings) since the last Ebola outbreak in 2014–2015. We adapted the World Health Organization IPC Assessment Framework tool to assess these measures and identify any gaps in their components at each PoE through a cross-sectional study in May 2021. IPC measures were Inadequate (0–25%) at Queen Elizabeth II Quay port (21%;11/53) and Jendema (25%;13/53) and Basic (26–50%) at Lungi International Airport (40%;21/53) and Gbalamuya (49%;26/53). IPC components with the highest scores were: having a referral system (85%;17/20), cleaning and sanitation (63%;15/24), and having a screening station (59%;19/32). The lowest scores (0% each) were reported for the availability of IPC guidelines and monitoring of IPC practices. This was the first study in Sierra Leone highlighting significant gaps in the implementation of IPC measures at PoEs. We call on the AMR multisectoral coordinating committee to enhance IPC measures at all PoEs.

Achieving Minimum Standards for Infection Prevention and Control in Sierra Leone: Urgent Need for a Quantum Leap in Progress in the COVID-19 Era!

Introduction: Good Infection prevention and control (IPC) is vital for tackling antimicrobial resistance and limiting health care-associated infections. We compared IPC performance before (2019) and during the COVID-19 (2021) era at the national IPC unit and all regional (4) and district hospitals (8) in Sierra Leone. Methods: Cross-sectional assessments using standardized World Health Organizations IPC checklists. IPC performance scores were graded as inadequate = 0–25%, basic = 25.1–50%, intermediate = 50.1–75%, and advanced = 75.1–100%. Results: Overall performance improved from ‘basic’ to ‘intermediate’ at the national IPC unit (41% in 2019 to 58% in 2021) and at regional hospitals (37% in 2019 to 54% in 2021) but remained ‘basic’ at district hospitals (37% in 2019 to 50% in 2021). Priority gaps at the national IPC unit included lack of: a dedicated IPC budget, monitoring the effectiveness of IPC trainings and health care-associated infection surveillance. Gaps at hospitals included no assessment of hospital staffing needs, inadequate infrastructure for IPC and lack of a well-defined monitoring plan with clear goals, targets and activities. Conclusion: Although there is encouraging progress in IPC performance, it is slower than desired in light of the COVID-19 pandemic. There is urgent need to mobilize political will, leadership and resources and make a quantum leap forward.

Infection Prevention and Control in Three Tertiary Healthcare Facilities in Freetown, Sierra Leone during the COVID-19 Pandemic: More Needs to Be Done!

Infection Prevention and Control (IPC) measures are critical to the reduction in healthcare-associated infections, especially during pandemics, such as that of COVID-19. We conducted a hospital-based cross-sectional study in August 2021 at Connaught Hospital, Princess Christian Maternity Hospital and Ola During Children's Hospital located in Freetown, Sierra Leone. We used the World Health Organization's Infection Prevention and Control Assessment Framework Tool to assess the level of IPC compliance at these healthcare facilities. The overall IPC compliance score at Connaught Hospital was 323.5 of 800 points, 313.5 of 800 at Ola During Children's Hospital, 281 of 800 at Princess Christian Maternity Hospital, implying a 'Basic' IPC compliance grade. These facilities had an IPC program, IPC committees and dedicated IPC focal persons. However, there were several challenges, including access to safe and clean water and insufficient quantities of face masks, examination gloves and aprons. Furthermore, there was no dedicated budget or no healthcare-associated infection (HAI) surveillance, and monitoring/audit of IPC practices were weak. These findings are of concern during the COVID-19 era, and there is an urgent need for both financial and technical support to address the gaps and challenges identified.