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Objectives This study aimed to evaluate the performance of vaccine logistics management information systems at public health facilities in Amhara Region, Ethiopia. Methods An institution-based concurrent explanatory mixed design was used at public health facilities in Amhara Region, Ethiopia. In total, 102 health facilities were selected using the multi-stage, stratified, random-sampling proportionate-to-size method. Data were collected using a structured data abstraction checklist from vaccine logistics management information system records. Additionally, experiences of Expanded Program for Immunization focal persons were gathered through interviewer-administered questionnaires. Results Among the 102 health facilities surveyed, 99 (97.1%) provided vaccination services during the study period. On the day of the visit, the average availability and utilization rates of 15 vaccine logistics management information system forms were 44.1% and 40.5%, respectively. The mean inventory accuracy for tracer vaccines stood at 58.3% ± 45.1%. The overall average accuracy percentages for urban and rural vaccine request form reports were 73.4% and 69.6%, respectively. Conclusions The performance of vaccine logistics management information systems in these public health facilities was suboptimal. Key issues identified include inconsistent use of recording forms, shortages of reporting forms, lack of digitalization, poor data quality, and a shortage of qualified staff. These findings underscore the urgent need for standardization of the vaccine logistics management information system and enhancement of data quality.

The study aimed to systematically analyze published articles on the challenges, impacts, and prospects of the global health commodities' supply chain in the era of the COVID-19 pandemic. Methods: A standard searching strategy was conducted in seven research databases to retrieve pertinent articles. Finally, 459 articles were retrieved for further screening, and only 13 articles were selected for final synthesis. Results: Almost 38.5% of the studies targeted the supply chain of health commodities used to treat HIV, TB, and malaria. Lockdown policies, travel restrictions, lack of transportation, low manufacturing capacity, and rising costs were the significant challenges indicated for the supply interruption of essential health commodities and COVID-19 vaccines. Findings indicated that the supply interruption of essential health commodities leads to a devastating impact on global health. Conclusion: Global medicine shortages due to the pandemic crisis can have a devastatingly harmful impact on patient outcomes and might result in a devastatingly long-lasting effect on the health of the world community. Supply-related challenges of the COVID-19 vaccine affect countries' ambitions for achieving herd immunity quickly. Monitoring the pandemic's effect on the health commodities' supply system and designing a short-term and long-term resilient health supply chain system that can cope with current and future health catastrophes is pivotal. [ABSTRACT FROM AUTHOR]

Student class schedules often involve significant scheduling conflicts and can be challenging to resolve. Three scheduling problems common to students, advisors, and deans at universities include building a schedule, changing schedules for multiple students due to a course cancelation, and finding seats for students on waitlists for multiple courses. This paper presents binary integer programs to solve each, building in complexity. [ABSTRACT FROM AUTHOR]

Abstract Background Breast cancer represents a significant public health concern in India, accounting for 28% of all cancer diagnoses and imposing a substantial economic burden. This study introduces a novel approach to forecasting the number of breast cancer cases (based on prevalence rates) and estimating the associated economic impact in India using the autoregressive integrated moving average (ARIMA) model. Methods Data on the prevalence of breast cancer in India from 2000 to 2021 were obtained from the Global Burden of Disease (GBD) database. This dataset provided annual estimates of the number of patients with breast cancer, serving as the basis for modeling future prevalence and estimating the economic burden. The ARIMA (Auto-Regressive Integrated Moving Average) model was employed to analyze and predict breast cancer prevalence in India up to the year 2030 (time-series forecasting). Data were visualized and checked for stationarity using the Augmented Dickey-Fuller (ADF) test. Using the autocorrelation function (ACF) and partial autocorrelation function (PACF) plots, the appropriate parameters (p, d, q) were determined. Several ARIMA configurations were tested to identify the model with the best fit. The goodness-of-fit of the model was assessed using standard metrics such as the Akaike Information Criterion (AIC) and Bayesian Information Criterion (BIC). The residuals were tested using the Box-Ljung test to confirm the absence of autocorrelation and verify that they followed a white noise distribution. Using the fitted ARIMA model, prevalence rates were forecasted from 2022 to 2030, with 95% confidence intervals to capture prediction uncertainty. Direct costs were calculated based on medical expenses for breast cancer patients, such as hospital visits, diagnostic tests, treatment costs, and follow-up care. A bottom-up approach was applied, which involves aggregating individual cost components from each stage of care to estimate the total direct burden of disease. A bottom-up approach was applied, which involves aggregating individual cost components from each stage of care to estimate the total direct burden of disease. Indirect costs were estimated using the human capital approach, which assesses productivity losses due to morbidity and premature mortality. The Disability-Adjusted Life Years (DALY) associated with breast cancer were also predicted using the ARIMA model. Results The results of coefficient of determination (0.99), mean absolute percentage error (69%), mean absolute error (5229), and root mean squared error (6451.2) showed that the ARIMA (0,2,0) model fitted well. Coefficient of determination (0.99) indicated that 99% of the variance in the data was explained by the model. Akaike information criterion (411.54) and Bayesian information criterion (412.53) indicated the ARIMA (0,2,0) model was reliable when analysing our data. The result of the relative error of prediction (2.76%) also suggested that the model predicted well. The number of patients with breast cancer from 2021 to 2030 was predicted to be about 1.25 million, 1.1.29 million,, 1.34 million, 1.39 million, 1.44 million, 1.48 million, 1.53 million, 1.58 million, 1.63 million, 1.68 million, and respectively. The total economic burden of breast cancer from 2021 to 2030 was estimated to be $8 billion, $8.72 billion, $9.05 billion, $9.84 billion, $10.20 billion, $11.07 billion, $11.49 billion, $12.44 billion, $12.91 billion, $13.95 billion, respectively is estimated to rise significantly. Conclusion Breast cancer prevalence and its economic impact are projected to grow substantially in India. Between 2021 and 2030, the number of breast cancer patients is expected to increase by approximately 0.05 million annually, with an annual increase rate of about 5.6%. The associated economic burden will also rise, averaging an additional $19.55 billion per year, underscoring the need for intensified healthcare and economic strategies to manage this growing challenge.

Cardiovascular diseases (CVDs) are the leading cause of death globally and the prevention and control of these diseases tend to entail longer and larger social and economic commitments on the part of governments. This systematic review (SR) aims to understand the quantum, diversity, and quality of implementation research (IR) done in the field of CVDs in India with a view to maximizing the utility of the efforts made by the government. The evidence was collated on IR on CVDs in India conducted in the past 20 years (2001–2021) using a SR approach. The SR was drafted using Preferred Reporting Items for SRs and Meta-analyses guidelines. Academic databases (PubMed, Embase, and Science Direct) and nonacademic databases (Google Scholar and ProQuest) were chosen, along with repositories of gray literature. Retrieved articles were screened for titles and abstracts and assessed by two independent reviewers. The articles also underwent a concomitant risk of bias assessment utilizing checklists (STARI, STROBE, CONSORT, etc.,) and a narrative summary was drafted using SwiM guidelines. In the final analysis, 10 articles that fitted the inclusion criteria of IR for CVD in India were included, of which seven were directed at IR on hypertension, and three were related to coronary artery disease, myocardial infarction, and stroke. Acceptability, adoption, and feasibility were the only attributes of IR that were explored in these studies.

This paper explores the development of the method of partial fraction decomposition from elementary number theory through calculus to its abstraction in modern algebra. This unusual perspective makes the topic accessible and relevant to readers from high school through seasoned calculus instructors.

Abstract Background Health guideline developers engage with interested people and groups to ensure that guidelines and their recommendations are relevant and useful to those who will be affected by them. These ‘interest‐holders’ include patients, payers/purchasers of health services, payers of health research, peer review editors, product makers, programme managers, policymakers, providers, principal investigators, and the public. The Guidelines International Network (GIN) and McMaster University Guideline Development Checklist describes 146 steps of the guideline process organized into 18 topics. While one topic focuses on engagement, it does not describe how to engage with interest‐holders. In addition, interest‐holder input could be sought throughout the guideline development process. This scoping review is part of a series of four related reviews. The three other reviews address barriers and facilitators to engagement in guideline development, managing conflicts of interest in guideline development, and assessing the impact of interest‐holder engagement on guideline development. The four reviews will inform the development of guidance for multi‐interest‐holder engagement in guideline development; the GIN‐McMaster Guideline Development Checklist Extension for Engagement. Objectives The objective of this scoping review is to identify, describe, and summarise existing guidance and methods for multi‐interest‐holder engagement throughout the health guideline development process. Search Methods We conducted one comprehensive search for studies of engagement in guidelines to meet the inclusion criteria of one or more of the four systematic reviews in this series. We searched MEDLINE (OVID), CINAHL (EBSCO), EMBASE (OVID), PsycInfo (OVID) and SCOPUS databases up to September 2022. We did not include limits for date, study design, or language. We searched websites of agencies and organizations that engage interest‐holder groups, such as the Agency for Healthcare Research and Quality (AHRQ), CIHR Strategy for Patient‐Oriented Research (SPOR), National Institute for Health and Care Research (NIHR) Be Part of Research, Guidelines International Network (G‐I‐N), the National Institute for Health and Care Excellence, and the PatientCentred Outcomes Research Institute (PCORI). We handsearched the websites of guideline producing agencies. We solicited additional grey literature from the members of the MuSE Consortium. Selection Criteria Studies were included in this review if they reported on engagement of any of our identified groups, patients, payers/funders of research, payers/purchasers of health services, policymakers, programme managers, providers, principal investigators/researchers, peer review editors, product makers in the development of a health guideline. Titles and abstracts of identified citations were screened independently, in duplicate. The full text of potentially relevant papers were screened for eligibility into one or more of the four reviews in the series. Screening was done independently, by two reviewers. The team held weekly meetings with all reviewers involved in screening to discuss and resolve conflicts. Data Collection and Analysis Two reviewers extracted relevant data into a pilot‐tested data extraction form using Excel. We used the GIN‐McMaster guideline development checklist as a framework for extracting the available guidance for each of our identified interest‐holder groups throughout the development process. We presented descriptive statistics of the number of papers reporting guidance for each groups across the steps of the guideline process. We synthesized the relevant text using a qualitative meta‐summary approach. Main Results We included 16 papers (from 17 reports). These papers were from Australia, Denmark, the Netherlands, the UK, and the USA, and eight papers were international (countries not specified). The papers provided guidance for at least one of our interest‐holder groups for at least one stage of guideline development. We mapped this guidance to the GIN‐McMaster Guideline Development Checklist to identify the available guidance for each of our interest‐holder groups across all stages of the guideline development process. Guidance was available for patient engagement in 15 of the 16 papers. At least two papers provided guidance for each of the 18 topics of the GIN‐McMaster Guideline Development Checklist. For healthcare providers, 9 papers provided guidance for their engagement across 10 of the 18 guideline development topics. Guidance for engaging with the public was provided for 14 of the 18 topics and reported in 4 of our included papers. For payers/purchasers of health services, policymakers, product makers, programme managers, and principal investigators, 2–3 papers provided guidance for these groups across 4–7 topics of the GIN‐McMaster checklist. We did not identify any specific guidance for payers of health research or for editors of peer‐reviewed journals. Authors' Conclusions Guidance for interst‐holder engagement in guidelines is available but has focused primarily on patients. We will utilize the guidance identified in this scoping review to inform the GIN‐McMaster Guideline Development Checklist Extension for engagement. Combined with the information obtained from the other systematic reviews in this series, we will address the gaps in guidance for the other identified interest‐holder groups.

Lung ischemia-reperfusion injury (IRI), a common complication after lung transplantation (LTx), plays a crucial role in both primary graft dysfunction (PGD) and chronic lung allograft dysfunction (CLAD) thereby adversely impacting the clinical outcomes in these patient cohorts. Lung IRI is characterized by several molecular events including immune cell infiltration, reactive oxygen species (ROS) generation, calcium overload, inflammation and various forms of cell death pathways. Currently, no therapeutic agents are available to clinically prevent lung IRI. While animal and cell culture models are highly valuable in understanding the pathophysiology of lung IRI, they may not completely recapitulate the complexity of human lung tissue pathology. This limitation necessitates the requirement for developing innovative preclinical human research tools that can supplement available scientific modalities. Emerging evidence suggests that precision-cut lung slices (PCLS) have become an indispensable tool in scientific research to study lung biology in an ex vivo tissue system. Recent studies using PCLS have investigated lung diseases including asthma, chronic obstructive pulmonary disease (COPD), and lung cancer. Although PCLS can be successfully employed to determine the deleterious events in the pathogenesis of lung IRI, including cell-cell interactions as well as hallmarks of inflammation and oxidative stress-dependent pathways, detailed studies employing PCLS to decipher these molecular events in post-LTx injury are currently limited. This review focuses on the applicability and unexplored potential of PCLS as a powerful tool in lung IRI research for understanding the pathophysiology and consequent development of new therapeutic modalities.