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Financial analysis plays a major role in investing the disposable income of various economic agents. Stock markets are predominantly made up of small investors with limited information and low capabilities for a suitable analysis. Researchers, as well as practitioners, are divided over the findings on the adequacy of technical analysis in investing. This paper examines the Markov chain process in the stock market to discover the essential links and probabilities for the stocks’ transition through three states of stagnation, growth, and decline (i.e., stagnant, bull, and bear markets). The subject of analysis is a randomly selected portfolio of 20 shares traded on the New York Stock Exchange. The data suggest that the portfolio relatively quickly, in four trading days, achieves equilibrium probabilities that allow a certain amount of predictability of future movements. At the same time, when analyzing the expected time intervals for the first transition, we found that the portfolio returns to a state of growth much faster than a decline. In addition, the results negate the basic habits of frequent trading, herding, and taking a short position in events of negative price fluctuations. Our research contributes towards observing regularities and stock market efficiency with a clear goal of improving expectations and technical analysis for small individual investors.

This paper presents an overview of recent advances for the Nurse Rostering Problem (NRP) based on methodological papers published between 2012 to 2021. It provides a comprehensive review of the latest solution methodologies, particularly computational intelligence (CI) approaches, utilized in benchmark and real-world nurse rostering. The methodologies are systematically categorised (Heuristics, Meta-heuristics, Hyper-heuristics, Mathematical Optimisation, Matheuristics and Hybrid Approaches). The NRP benchmark repositories and the respective state-of-the-art methods are also presented. A distinctive feature of this survey is its focus on the emerging trends in terms of solution methodologies and benchmark datasets. Meta-heuristics are the most popular choices in addressing NRP. Matheuristics, one of most popular methodologies in addressing the NRP, has been an emerging trend in recent years (2018 onwards). The INRC-I dataset is the most popular benchmark currently in use by researchers to test their algorithms. An in-depth discussion on the challenges and research opportunities is provided. The summary and analysis of the recently published NRP methodological papers in this survey is valuable for the CI and Operational Research (OR) communities especially early career researchers seeking to find gaps and identify emerging trends in this fast-developing, important research area.

Introduction: Non-communicable diseases (NCDs) have contributed to almost half of the global disease burden. Many countries have experimented with Community Health Volunteers (CHVs) to provide necessary care for NCDs. We aimed at evaluating the contribution of CHVs in mobilizing adults for the Diabetes and Hypertension screening in a selected Primary Health Centre (PHC) of Puducherry, India. Methodology: A community-based operational research study was conducted, where five volunteers from each of the 13 anganwadis functioning under the PHC were chosen as study participants. They were interviewed before enrolment for willingness. Four batches of sensitization and training sessions were conducted to provide the necessary training. CHVs were then given 3 months to mobilize the individuals for NCD screening. This model was evaluated using the Theoretical underpinning technique. Results: Of the total 85 CHVs suggested, around 65 (76.5%) showed willingness for rendering services. Approximately 32 (49.2%) discontinued during the initial weeks of the intervention due to various reasons. The remaining CHVs could reach 363/1470 (24.7%), eligible individuals, among them, 303 (83.5) were convinced to visit the health centre for screening. From the total members who were screened, approximately 52 (17%) and 31 (10%) were diagnosed to have diabetes and hypertension respectively and were initiated on treatment as per national guidelines. Conclusion: About half of the CHVs who volunteered, remained till the end and effectively contributed to a screening of NCDs. The involved volunteers aided in improvising the NCD coverage under the PHC.

The paper investigates the efficiency of serving high demand transit corridors with connected semi-autonomous bus platoons in both bus and BRT services. Platooning facilitates higher capacity than conventional buses by forming virtual long buses out of multiple smaller vehicles, which may be particularly relevant in scenarios with large demand variations between peak and off-peak hours. The problem is formulated as a constrained optimization problem to minimize total system cost, which includes waiting cost, access cost, riding cost, operating cost and capital cost. For a single period with fixed demand, both analytical solutions and numerical examples are provided. Sensitivity analysis is carried out with regard to demand levels and capacity upper bound. The problem is generalized to a two-period problem considering peak and off-peak demand. Numerical results are provided with sensitivity analysis regarding demand level and ratio of peak/off-peak demand. Furthermore, the impact of a lower bound on service headway is investigated. The result shows that semi-autonomous vehicle platooning is competitive in medium and high-demand scenarios, with the potential of reduced user costs and operating costs at the expense of additional rolling stock costs. Minimum headway constraint, restricted vehicle size, and higher demand ratio all make semi-autonomous platooning more advantageous.

IntroductionDigital technologies can improve adherence to tuberculosis (TB) treatment. We studied the impact of digitizing TB treatment monitoring on adherence among TB patients in Wuhan, China, during 2020-2021.MethodsWe compared an electronic system introduced to monitor TB medication adherence (e-Patient Service System; e-PSS) with the p paper-based standard of care (TB Control Information System; TCIS) in terms of prescribed TB treatment doses taken by patients and patient outcome after six months of follow up. We designed a cross sectional study using retrospective data for all drug susceptible pulmonary TB patients recorded on both systems. The main indicators were: compliant first follow up visit (within 3 days of start of treatment); medication adherence (80% or more of monthly doses taken); and end of treatment success ratio.ResultsA total of 1,576 TB patients were recorded in TCIS in July September, 2020 and 1,145 TB cases were included in e-PSS in January March, 2021. The distribution of patient demographic and clinical features was similar between the two groups. A larger proportion from the e-PSS group visited the community doctor in the first three days compared with the TCIS group (48.91 versus 29. 76 % respectively). Medication adherence was also higher in the e-PSS group during the 6 months of treatment than in the TCIS group (84. 28 versus 80.3 3 % respectively). Treatment success was 92.52% in the e-PSS group and 92.07% in the TCIS group. Multivariate logistic regress ion analysis demonstrated that adjusted odds ratios for compliant first follow up visit, medication adherence and favorable treatment outcome in the e-PSS versus TCIS groups were 2.94 (95% 2.47 3.50), 1.33 (95% 1.08 1.63), and 1. 12 (95% CL: 0.79 1.57) respectively.DiscussionThis study revealed improvements in TB care following an intervention to monitor treatment digitally in patients in Wuhan, China.

A wide range of disciplines are directing their methods and tools to help address the challenges of healthcare. Chief among these are design and operational research (OR). Though they have much in common, these two disciplines have existed in isolation for most of their history and there is currently a gulf between the two research communities. In this position paper, we rapidly review the contributions of design and OR in healthcare. We then identify similarities and complementarities between the two disciplines and communities when they consider healthcare systems. Finally, we propose practical steps to enable better collaboration. Our focus is on finding ways in which the two disciplines complement each other. When applying design to healthcare services, designers may wish to learn from OR, which has a long history of supporting improvements in healthcare organisation and services, particularly using quantitative data and analysis and modelling methods. In return, design has distinctive qualities that could augment the OR approach, such as its emphasis on wide and creative search for potential solutions, and iterative co-production and prototyping of solutions with clients. Better collaboration will require a coordinated effort but could yield a more comprehensive and effective approach to improving healthcare systems.

Background National tuberculosis (TB) programmes in high-burden countries do not systematically assess severity at diagnosis followed by referral for inpatient care. Due to limited capacity, comprehensive assessment of all TB patients is not practical. In three districts of Gujarat (West India) in June 2021, we determined the feasibility of screening for severe illness by paramedical staff of public facilities and the burden of 'high risk for severe illness' at notification among adults (≥15 y of age) with TB. Methods In this cross-sectional study, the screening criteria for high risk for severe illness was the presence of any one of the following: body mass index (BMI) ≤14.0 kg/m2, BMI ≤16.0 kg/m2 with bilateral leg swelling, respiratory rate >24/min, oxygen saturation <94% or inability to stand without support. We summarized the feasibility indicators and burden using proportion (95% confidence interval [CI]) and median, as applicable. Results Of 626 notified adults, 87% were screened. The median time interval for screening was 3 d from notification and all indicators were collected in 97% of patients. The burden of high risk for severe illness was high, at 41.6% (95% CI 37.5 to 45.8). Conclusions High burden and feasibility (high coverage, acceptable time interval and minimal missing data) makes a strong case for routine screening of severe illness. [ABSTRACT FROM AUTHOR]

As an important research direction, operational research (OR) has always attracted scholars worldwide. We study the structure, trend and prospect in the OR field by conducting a bibliometric analysis of publications in the period of 1952–2020, which are included in the Web of Science (WoS) database. Using three effective bibliometric tools, namely, VOS viewer, CiteSpace, and Bibliometrix, a total of 5,353 publications were retrieved to show clear visual results using a series of scientific analyses. First, a performance analysis revealed the basic characteristics of publications considering the type distribution, annual trend, quantity and quality. Then, a cooperation analysis presented the influential countries/regions and showed the relationships among countries/regions, institutions and authors during different periods based on bibliometric indicators and co-authorship networks. Moreover, a keyword analysis was conducted to investigate the hot topics and development of the OR field, using co-occurrence analysis, timeline view analysis and evolution analysis. Finally, we discussed the implications and limitations, and summarized the main findings. This study hopes to provide important and valuable references for future research on the OR field. [ABSTRACT FROM AUTHOR]

Operational research is the scientific discipline — widespread in sciences like engineering, economics, sociology, politics — that applies advanced analytical methods to assist in decision-making. The aim of this study was to demonstrate the value of such methods to the research of the carbon footprint produced by vertical farms, in specific its decrease in regard to the pre- and post-operational energy consumption and cost that occurs throughout their lifecycle. A logistic structure was designed, dependent on specific parameters, such as the space, location, and fuel of the hydroponic unit that change during the research. This way, multiple possible scenarios could be studied. The results of each scenario were analysed and compared via a linear multi-criteria model. The results demonstrated strong dependencies (and softer links) between particular parameters, such as the choice of space and the food miles required for the product. [ABSTRACT FROM AUTHOR]

The companies increasingly need to adopt strategies that improve their decision-making, and Operational Research is one of them. Operational Research aims to represent, through mathematical models, real-life problems offering viable solutions and for this it has numerous techniques that provide organizations to achieve economies of significant scales. This article aims to present a practical application of one of these techniques, the linear programming, applied in the making of Christmas food parcel. The article aims to maximize the sales revenue of the food parcel by controlling the items that compose them and performing the possible resupplies if there were missing items in stock. This study is justified by the fact that companies working in this segment do not have an academic reference in this subject. From its construction, it was noticed that the model presented concrete results, its use and interpretation of easy understanding to the employee of the supply sector, and mainly by its daily monitoring and financial result. [ABSTRACT FROM AUTHOR]

Complex environments, conflicting criteria, uncertainties, and inaccurate information are some characteristics of many nowadays real-world decision-making problems. The Multi-Criteria Decision-Making (MCDM) methodology is one of the most used, perhaps because it drives decision-making processes to be more rational, efficient, and effective. Thus, the Armed Forces of several countries have used MCDM methods in the Life Cycle Management of Defense Systems (LCM-DS) to deal with military systems' complexity, breadth, and sensitivity. However, despite the rich and vast literature available on several MCDM methods applied to LCM-DS problems, there is a lack of a recent bibliometric study on this relevant subject. This paper presents an analysis of a quantitative approach based on bibliometric metrics to evaluate the application of MCDM methods in LCM-DS. By using the Scopus and Web of Science databases as references, this study focuses on the identification of the following aspects related to the research in this field: distribution of scientific publications, most relevant sources, interaction dynamics among these sources, most prominent subjects in recent research (trend topics), and application of MCDM methods in LCM-DS. Regarding the latter, this study identified the Analytic Hierarchy Process (AHP) as the most used method in the LCM-DS since almost a quarter of the analyzed works applied it in the original, adapted, or hybrid (combined with other methods) format. Finally, our results show that MCDM methods are commonly applied to LCM-DS problems in all life cycle stages, mainly in development, utilization, and support. [ABSTRACT FROM AUTHOR]

A Primary Healthcare-System-Strengthening Project (PSSP) is implemented by the Ministry of Health, Sri Lanka, with funding support from the World Bank for providing quality care through primary medical care institutions (PMCIs). We used an explanatory mixed-methods study to assess progress and challenges in human resources, drug availability, laboratory services and the health management information system (HMIS) at PMCIs. We conducted a checklist-based assessment followed by in-depth interviews of healthcare workers in one PMCI each in all nine provinces. All PMCIs had medical/nursing officers, but data entry operators (44%) and laboratory technicians (33%) were mostly not available. Existing staff were assigned additional responsibilities in PSSP, decreasing their motivation and efficiency. While 11/18 (61%) essential drugs were available in all PMCIs, buffer stocks were not maintained in >50% due to poor supply chain management and storage infrastructure. Only 6/14 (43%) essential laboratory investigations were available in >50% of PMCIs, non-availability was due to shortages of reagents/consumables and lack of sample collection–transportation system. The HMIS was installed in PMCIs but its usage was sub-optimal due to perceived lack of utility, few trained operators and poor internet connectivity. The PSSP needs to address these bottlenecks as a priority to ensure sustainability and successful scale-up. [ABSTRACT FROM AUTHOR]

Human resources (HR) have a key impact on the creation and implementation of modern products, solutions and concepts. Relatively new and rarely undertaken research challenge in enterprise is optimization of HR in the context of their location and requirements for working conditions. A great challenge here is the transparency and reliability of the collected data. In the article, we present a modern approach to knowledge extraction based on Artificial Intelligence (AI) and Multivariate Adaptive Regression Splines optimizing the availability of HR with a high innovation rate, taking into account their availability time and location. This study was conducted on a group of 5095 young people from the Z generation. A total of 11 variables were analyzed in the context of innovation and presented in this article. The effect of research using machine learning methods is the analysis of the characteristics of generation Z representatives, whose desire is to work in innovative companies. Research results indicate that some regions offer candidates with a higher level and commitment to innovation, and thus make HR more available for the development of innovative products. Chosen models designed by using AI and Operational Research Analytics were presented in the graphic visualization, which is a novelty in the presentation of similar issues in relation to HR. [ABSTRACT FROM AUTHOR]

Background: Operational research (OR) is a process to improve health system capacity by evaluating interventions to improve health delivery and outcomes. The World Health Organization (WHO) Structured Operational Research Training Initiative (SORT-IT) programme promotes how OR contributes to improved health care delivery and health outcomes. A partnership project between the International Institute of Primary Health Care (IPHCE) in Ethiopia and The University of Queensland (UQ) in Australia modified the SORT-IT programme to deliver a hybrid Training of Trainers programme and improve OR capacity., Objective: This study was performed to develop and evaluate the effectiveness of Train-the Trainers approach in building capability to expand the capacity of the IPHCE to deliver the SORT-IT programme., Methods: Recruitment of participants and training were aligned with the principles of the SORT-IT programme. Training was face-to-face for the first session with subsequent training sessions delivered via Zoom over a 13-week period. Participants were required to complete all activities in line with SORT-IT deliverables. Slide decks supporting the SORT-IT training videos were developed and adapted to the Ethiopian context., Results: Participants had diverse experience from programme directors to research officers. All training sessions were recorded and available for participants to watch and review when required. All participants completed OR protocols to the draft stage. Course evaluation revealed participants found the content and format of the training useful, pertinent, and interesting., Conclusion: A hybrid model (face-to-face and video platform) for OR training was implemented. Managing contextual challenges such as information technology were managed easily by programme staff. Translating course requirements at a management level proved challenging with data collection for the protocols but provided insight into potential future challenges. This OR Training of Trainers course demonstrated that sharing of skills and knowledge can occur through a hybrid delivery model and contribute to developing capacity.

Background: Sustaining a 'fit-for-purpose' health workforce requires a better understanding of the health care worker cadres that are affected during pandemics and their outcomes. In hospitalized health care workers with confirmed COVID-19 between March 2020 and May 2023 in Liberia, we determined the hospitalization and case fatality rates, type of health care worker cadres affected, their demographic and clinical characteristics and hospital exit outcomes., Methods: This was a cohort study using routine data extracted from hospitalization forms for health care workers in 24 designated COVID-19 treatment facilities., Results: Of the 424 health care workers with COVID-19, hospitalization rates progressively declined between 2020 and 2023, (P<0.001) with the highest rates in 2020 (24/1,000 health care workers) and 2021 (14/1,000 health care workers). Case fatality was 2% in both 2020 and 2021 with no deaths thereafter. Among those hospitalized, the highest proportions were nursing cadres with 191(45%), physicians with 63 (15%) and laboratory technicians with 42 (10%). The most frequent reported site for COVID-19 infection was the health facility (326, 89%). COVID-19 vaccination coverage in health care workers was 20%. The majority (91%) of hospitalizations were for mild symptomatic infections. Even in referral centres (n-52), 18 (35%) were for mild infections. Of the 424 who were hospitalized, 412 (97%) recovered, 9 (2%) died and 3 (1%) either left against medical advice or absconded. Of the nine deaths, none were vaccinated, seven had moderate-to-severe disease but were not referred to specialized COVID-19 treatment centers., Conclusions: The hospitalized health care workers for COVID-19 were predominantly clinical and laboratory personnel who were mostly unvaccinated, and health facilities were hot-spots for contracting infections. The triage and referral system was weak with unnecessary hospitalization of mild infections. This study provides useful insights for outbreak preparedness including priority vaccination and improving health care worker safety in Liberia., Competing Interests: No competing interests were disclosed., (Copyright: © 2024 Lehyen DB et al.)

In 2021, an operational research study in two tertiary hospitals in Freetown showed poor hand hygiene compliance. Recommended actions were taken to improve the situation. Between February–April 2023, a cross-sectional study was conducted in the same two hospitals using the World Health Organization hand hygiene tool to assess and compare hand hygiene compliance with that observed between June–August 2021. In Connaught hospital, overall hand hygiene compliance improved from 51% to 60% (p < 0.001), and this applied to both handwash actions with soap and water and alcohol-based hand rub. Significant improvements were found in all hospital departments and amongst all healthcare worker cadres. In 34 Military Hospital (34MH), overall hand hygiene compliance decreased from 40% to 32% (p < 0.001), with significant decreases observed in all departments and amongst nurses and nursing students. The improvements in Connaught Hospital were probably because of more hand hygiene reminders, better handwash infrastructure and more frequent supervision assessments, compared with 34MH where interventions were less well applied, possibly due to the extensive hospital reconstruction at the time. In conclusion, recommendations from operational research in 2021 contributed towards the improved distribution of hand hygiene reminders, better handwash infrastructure and frequent supervision assessments, which possibly led to improved hand hygiene compliance in one of the two hospitals. These actions need to be strengthened, scaled-up and guided by ongoing operational research to promote good hand hygiene practices elsewhere in the country.

An operational research study was conducted in 2019 to assess the quality of data submitted by antimicrobial resistance (AMR) surveillance sites in the Bagmati Province of Nepal to the National Public Health Laboratory for Global Antimicrobial Resistance and Use Surveillance System (GLASS). Measures were implemented to enhance the quality of AMR surveillance by strengthening capacity, improving infrastructure, implementing data sharing guidelines, and supervision. The current study examined reports submitted by surveillance sites in the same province in 2022 to assess whether the data quality had improved since 2019. The availability of infrastructure at the sites was assessed. Of the nine surveillance sites in the province, seven submitted reports in 2022 versus five in 2019. Completeness in reporting improved significantly from 19% in 2019 to 100% in 2022 (p < 0.001). Timely reports were received from two sites in 2019 and only one site in 2022. Specimen–pathogen consistency in accordance with the GLASS guidelines for urine, feces, and genital swab specimens improved, with ≥90% consistency at all sites. Overall, the pathogen–antibacterial consistency improved significantly for each GLASS priority pathogen. The study highlights the importance of dedicated infrastructure and institutional arrangements for AMR surveillance. Similar assessments covering all provinces of the country can provide a more complete country-wide picture.

In Sierra Leone, two operational research (OR) studies in 2019 and 2021 showed deficiencies in the data being captured by the Integrated Animal Disease Surveillance and Reporting (IADSR) system. This third OR study was conducted in 2023 to assess whether the second OR study’s results and recommendations were disseminated with the key stakeholders, the uptake of the recommendations, improvements in data capture in the IADSR system, and to describe the data on livestock disease and antimicrobial use. In 2022, on seven occasions, the authors of the second OR study disseminated the study’s findings. Of the four recommendations, the one on improving laboratory infrastructure for confirmation of animal disease was not implemented. The district animal health weekly surveillance reports received through the IADSR system were sustained at 88% between the second (2021) and third (2023) studies. In both studies, the proportion of sick animals receiving antibiotics (25%) remained the same, but the use of “critically important antimicrobials for veterinary use” declined from 77% (in 2021) to 69% (in 2023). The IADSR system has improved considerably in providing information on animal health and antibiotic use, and sequential OR studies have played a key role in its improvement.

Cutaneous leishmaniasis (CL) is common in Ethiopia, but the national guideline does not offer specific treatment recommendations. Consequently, different treatment regimens are used in the country, without quality evidence. In Boru Meda Hospital, sodium stibogluconate (SSG) is routinely used in combination with allopurinol for systemic CL treatment, although evidence on its effectiveness is limited. An observational cohort study was carried out to document clinical treatment outcomes in patients receiving SSG/allopurinol at the end of each 28-day treatment cycle and after 180 days. Patient-reported outcomes were assessed by asking patients to rate lesion severity, and by the dermatological life quality index. A total of 104 patients were included. After one treatment cycle, only four patients were clinically cured, although patient-reported outcomes significantly improved. The majority (88) of patients were appointed for a second treatment cycle, of whom only 37 (42%) attended. Among the 36 patients who came for final outcome assessment, 50% were cured. Follow-up and treatment were severely affected by conflict; drug stock-outs and insufficient ward capacity for treatment were additional challenges. The treatment outcomes of SSG/allopurinol were relatively poor, and most patients required more than one cycle of treatment. Shortages of drugs and beds indicate the existing gaps in providing CL treatment in Ethiopia.

(1) Background: Surgical antibiotic prophylaxis (SAP) is important for reducing surgical site infections. The development of a dedicated hospital SAP guideline in the Dhulikhel Hospital was a recommendation from a baseline study on SAP compliance. Compliance with this new guideline was enhanced through the establishment of a hospital committee, the establishment of an antibiotic stewardship program and the funding and training of healthcare professionals. Using the baseline and a follow-up study after introducing dedicated hospital SAP guidelines, we compared: (a) overall compliance with the SAP guidelines and (b) the proportion of eligible and non-eligible patients who received initial and redosing of SAP; (2) Methods: A before-and-after cohort study was conducted to compare SAP compliance between a baseline study (July 2019–December 2019) and a follow-up study (January 2023–April 2023); (3) Results: A total of 874 patients were in the baseline study and 751 in the follow-up study. Overall SAP compliance increased from 75% (baseline) to 85% in the follow-up study (p < 0.001). Over 90% of those eligible for the initial dose of SAP received it in both studies. Inappropriate use for those not eligible for an initial dose was reduced from 50% to 38% (p = 0.04). For those eligible for redosing, this increased from 14% to 22% but was not statistically significant (p = 0.272); (4) Conclusions: Although there is room for improvement, introduction of dedicated SAP guidelines was associated with improved overall SAP compliance. This study highlights the role of operational research in triggering favorable interventions in hospital clinical care.

Concerning the development of computational tools and solutions as a decision-making aid, this paper presents the results of the waspasWEB project, which strives to provide decision-makers with a readily accessible mechanism to employ the weighted aggregated sum product assessment (WASPAS) method. The social contribution of the project encompasses the development of a user-friendly and publicly accessible internet tool, as well as a package launched on the Comprehensive R Archive Network (CRAN) to serve the community of users of the R language. The use of operational research methodologies is crucial to justify decisions, and this effort seeks to advance the adoption of such methodologies, offering managers, researchers, and the general public an intuitive and easily accessible multi-criteria decision-making tool. In this way, we present the technical specifications, usability, and interactivity of the user with the computational platform, being validated its viability through a hypothetical case study. At the end of the research, it exposes the limitations and feasibility of the proposed computational model along with future research.

Implementing infection prevention and control (IPC) programmes in line with the World Health Organization’s (WHO) eight core components has been challenging in Sierra Leone. In 2021, a baseline study found that IPC compliance in three tertiary hospitals was sub-optimal. We aimed to measure the change in IPC compliance and describe recommended actions at these hospitals in 2023. This was a ‘before and after’ observational study using two routine cross-sectional assessments of IPC compliance using the WHO IPC Assessment Framework tool. IPC compliance was graded as inadequate (0–200), basic (201–400), intermediate (401–600), and advanced (601–800). The overall compliance scores for each hospital showed an improvement from ‘Basic’ in 2021 to ‘Intermediate’ in 2023, with a percentage increase in scores of 16.9%, 18.7%, and 26.9% in these hospitals. There was improved compliance in all core components, with the majority in the ‘Intermediate’ level for each hospital IPC programme. Recommended actions including the training of healthcare workers and revision of IPC guidelines were undertaken, but a dedicated IPC budget and healthcare-associated infection surveillance remained as gaps in 2023. Operational research is valuable in monitoring and improving IPC programme implementation. To reach the ‘Advanced’ level, these hospitals should establish a dedicated IPC budget and develop long-term implementation plans.

The stock exchange, despite being dynamic and considered to be a risky asset, is capable way of yielding great financial gains to its investors. In this sense, this article presents methods developed through the mathematical models of Multivariate Markov Chains (CMM) and Multiple Linear Regression (MRL), to predict oscillations in the IBOVESPA index as a function of the indices of the American stock exchanges NYSE and NASDAQ. In order to maximize gains and reduce losses in the purchase and sale of shares held on the Brazilian stock exchange, a database of daily variation of the indices was used, covering the years 2019 and 2020, which were later applied to develop the transition matrices of CMM and the linear equation of RLM. Then, through the proposed models, the precision of each method was evaluated, as well as a simulation of financial return obtained based on the predicted results. It was found that the Multivariate Markov Chain method obtained greater precision and greater simulated profit, with an average of hits greater than 50% and 19% of financial return throughout the delimited period. [ABSTRACT FROM AUTHOR]

Objective: We sought to document outcomes and factors associated with surgical success in hospitals supported by the Fistula Care Plus Project in the Democratic Republic of Congo (DRC), 2017-2019.Methods: This was a retrospective cohort study analysing routine repair data on women with Female Genital Fistula. Univariate and multivariate analyses were conducted to determine factors associated with successful fistula repair.Results: A total of 895 women were included in this study, with a mean age of 34 years (±13 years). The majority were married or in union (57.4%) and living in rural areas (82.0%), while nearly half were farmers (45.9%). The average duration living with fistula was 8 years (±7). Vesicovaginal (70.5%) and complex (59.8%) fistulas were the most common fistula types. Caesarean section (34.7%), obstructed labour (27.0%) and prolonged labour (23.0%) were the main aetiologies, with the causal deliveries resulting in stillbirth in 88% of cases. The vaginal route (74.9%) was the primary route for surgical repair. The median duration of bladder catheterization after surgery was 14 days (interquartile range [IQR] 7-21). Multivariate analysis revealed that Waaldijk type I fistula (adjusted odds ratio [aOR]:2.71, 95% confidence interval [CI]:1.36-5.40), no previous surgery (aOR:2.63, 95% CI:1.43-3.19), repair at Panzi Hospital (aOR: 2.71, 95% CI:1.36-5.40), and bladder catheterization for less than 10 days (aOR:13.94, 95% CI: 4.91-39.55) or 11-14 days (aOR: 6.07, 95% CI: 2.21-15.31) were associated with better repair outcomes.Conclusion: The Fistula Care Plus Project in the DRC recorded good fistula repair outcomes. However, further efforts are needed to promote adequate management of fistula cases. [ABSTRACT FROM AUTHOR]

In 2020 the European Commission approved the GND (Green New Deal), a strategic plan aimed at the decarbonization of the EU by 2050. In this scenario, the diffusion of alternative renewable energy sources (RESs) play a key role, particularly electric energy production from wind and photovoltaic power plants. Regardless, the nonprogrammable nature of these power sources led recent studies to focus the interest on the power-to-gas solution (PtG), consisting of the electrolytic transformation of excesses of unused electric energy into hydrogen. The complexity of this technology requires the development of strategic optimization models aimed at finding the best locations for new PtG plants in specific territorial scenarios. This paper presents the development of a GIS-based optimization model that combines an operational research approach with territorial services based on geographic information system (GIS) data. The study is located in Sicily (Italy), considering the large renewable energy penetration in the larger Mediterranean island. The developed model allows us to find the best location for new PtG installations in the considered area by combining GIS automated processing with cost function resolution. The results of this work could be useful in the years to come in light of the rapid spread of hydrogen energy production in Italy. [Display omitted] [ABSTRACT FROM AUTHOR]

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Francisella tularensis is a virulent bacterium which hijacks the host's immune response, turning cells usually tasked with killing foreign organisms as nutrient-rich receptacles for rapid multiplication. It is designated a Tier 1 Select Agent by the US CDC due to its potential to cause widespread mortality upon deliberate release. In this study, the key biological mechanisms of host infection are modelled as a continuous-time Markov chain (CTMC) and solved via discrete event simulation (DES). The efficacy of various medication strategies at the behest of public health authorities are investigated. Without treatment, the median lethal dose – not previously considered in humans – is estimated at approximately 1,000 organisms. Results suggest that fatality can be averted if antibiotics are administered for at least 7 days, no later than 10 days post exposure. In a mass casualty setting, this can reduce symptomatic cases by 18% from the baseline involving no medication. Reductions of 59% are possible if medication can be disseminated no later than 5 days post exposure, mitigating otherwise severe pressure on healthcare services. Novel use of CTMC and DES highlight the potential for OR in the field of immunology, where further opportunities may present in a post COVID-19 world. [ABSTRACT FROM AUTHOR]