Local Facilities Research Articles

Season-dependent characteristics of shock-related injuries in the Arctic zone of the Arkhangelsk region

Relevance. Studying the dynamics of injury rates, injury types and severity, as well as the treatment quality across various country regions, in particular the Arctic, is a prerequisite for managerial, healthcare, and strategic efficiency prior to and during hospital stay, taking into account the climate, geography, social and economic characteristics of every Russian Federation constituent.The objective is to analyse shock-related injuries in the Arctic zone of the Arkhangelsk region to understand season-related injury dynamics.Methods. Retrospective case series description parameters were used to study 140 patients with traumatic shock admitted to the Arkhangelsk Regional Clinical Hospital (ARCH) - a tier 1 trauma center. The analysed medical registration records included patient ambulance record and token (form 114/u), inpatient medical record (form 003/u), surgery logbook (form 008/u), patient radiographs, CT and nuclear MRI reports, as well as laboratory results. The study was conducted in accordance with ethical standards of the Declaration of Helsinki and European Community Directives (8/906 EC) and was approved by the local ethics committee of the Northern State Medical University of the Russian Ministry of Healthcare, Arkhangelsk (protocol no. 02/4-15 dated 04/08/2015). Statistical application package STATA ver.12 was used for statistical data processing.Results and discussion. The research demonstrated that the incidence of shock trauma is 4 times higher in men than in women. The vast majority of the injured are of working age. Seasonal distribution analysis per type of injuries and shock severity, including due to alcohol abuse, was carried out. The number of shock injuries is highest in winter, mainly due to road accidents which constitute 75.6 % of all injuries in winter. Throughout the year, over 50 % of shock injuries are combined injuries, that outperform isolated and multiple injuries in number. In particular, numerous combined injuries occur in winter with a responsible for almost 60 % among all other injuries. The majority the injured with shock-related trauma presented with stage 2 shock (49.3 %), whereas stage 1 and stage 3 shock was diagnosed in 27.9 % and in 21.4 % respectively. In winter, one in four patients with a shock-related injury presented with stage 3 shock. Alcohol-associated shock injuries are more numerous in summer (35.3 %), showing almost the same incidence as road traffic, domestic, and street injuries.Conclusion. The analysis of various types of injuries and season-related incidence of shock injuries in the Arctic territory of the Arkhangelsk region provides evidence to justify preventive measures to reduce the injury rates. Intensified efforts are required to minimise road traffic accidents in winter and combat alcohol abuse responsible for most injuries in summer. Since the vast majority of shock injuries occur in winter, in cold months ambulances must be equipped with local heating facilities, such as evacuation thermal bags with autonomous electric heating, thermal blankets, infusion warmers for blood transfusion and infusion sets.

Spatial-Temporal Distribution of 12-Year Periodontal Disease Prevalence in a Large Population Using Geographical Information Systems: A Longitudinal Study.

Periodontal diseases, commonly linked to dental biofilm and affecting adults, were studied using Geographic Information Systems (GIS) and Kernel Analyses with epidemiological data. This paper presents a hybrid method for use in epidemiological studies by evaluating the spatiotemporal distribution of disease prevalence. This study analy ed 47,757 patients from the Department of Periodontology out of 662,351 visitors to University Faculty of Dentistry (2012 to July 2023). The central districts of Kayseri in Turkey were selected as the study areas. Periodontitis prevalence was assessed through radiographic evidence and clinical examination. Point-based location data, including gender, age, and disease type, matched household data, creating building-based spatial data. Kernel Density (KD) and Average Nearest Neighbor (ANN) analyses examined patient concentration and disease types in specific regions. Accordingly, standard deviation ellipses were prepared by year to assess the spatial changes in the regions where patients resided. The study found higher periodontitis prevalence in males, increasing with age, while gingivitis decreased. After 2017, periodontitis prevalence notably declined. Location-based data exhibited clustering in patient distribution. KD maps showed similar patient distributions over the years, with more applications from areas closer to the Faculty of Dentistry. The spatial distribution of the patients applying has remained consistent over the last 5 years. Through GIS, KD maps reveal the spatial-temporal distribution of periodontitis patients. This aids in identifying high-prevalence regions and guiding strategic healthcare facility placement. Implementing preventive programs in high-demand areas, particularly in family health centers (local health facilities), can reduce community-wide periodontal disease prevalence.

Community responses and adaptations following the closure of a rural pharmacy and primary care facility.

This study investigates the experiences of one rural community in Central Pennsylvania following the closure of its singular pharmacy and primary health care facility. It aims to understand community members' responses and adaptations to declining health care accessibility and broader implications for rural health policy and practice. Employing a qualitative case study design, researchers conducted 26 in-depth interviews from May to December 2022. Interviews were grounded in a phenomenological approach and focused on participants' perceptions of their community and experiences accessing health care. Data were analyzed thematically following a coding reliability approach. The closure of the health care facilities resulted in significant social and economic impacts, particularly among vulnerable groups, such as older adults, people with disabilities, and working-class families. Participants reported increased reliance on their social support networks to access care, delays in seeking care due to the strain from longer travel distances, and loss of familiar and trusted care providers. We also found an over-reliance on local emergency medical services for routine care. Although the community demonstrated resilience through the use of social networks, some adaptations carried health risks, including delayed care and unmonitored use of alternative remedies. This study highligths theneed for health care policies that address the immediate loss of services and support the social networks and economic stability that rural communities rely on in the absence of local health care facilities. This research contributes insights for policymakers, health care providers, and community leaders working to support rural communities facing similar health care losses.

Impact of Long COVID symptoms on individuals in Hong Kong: Implications for occupational therapy practices

Introduction: From occupational therapy perspective, this study investigates the nature and impact of Long COVID symptoms on individuals in Hong Kong according to their gender, age, and occupation and to understand their treatment needs Method: A total of 193 participants with an acute COVID-19 episode 3 months ago and having recovered from it who were experiencing subjective symptoms of Long COVID were recruited through snowball sampling from local COVID-19 support groups and healthcare facilities to participate in a cross-sectional design via an online survey assessing their symptoms and the impact on daily activities, and exploring their treatment preferences. Findings: Respiratory, systemic, sleep, and cognitive symptoms were found to be the most prevalent, with significant variations in symptom severity and impact on daily life across different age and occupational status groups. The treatment preference was quite strongly inclined to traditional Chinese medicine. Conclusion: This study has uncovered the critical and yet recognized roles of occupational therapy in managing Long COVID impact by identifying the potential gaps of occupational therapy in its management and calling for advocating promotion in the community and interdisciplinary collaboration with traditional Chinese medicine. Implications about occupational therapy management and the healthcare policies for tailoring treatment programs are discussed.

Epidemiological Investigation of a Cholera Outbreak in Nepal-India Border Communities: Public Health Implications

ObjectivesOn October 4, 2021, a cholera outbreak was reported in Kapilvastu district, one of the 26 districts in Nepal bordering India. This study examined the outbreak's characteristics, response efforts, and the challenges faced. MethodsA descriptive cross-sectional design was applied for the outbreak investigation. Data was gathered through a review of cases registered in three local health facilities and community-based active case searching. Descriptive analysis was conducted for data analysis. ResultsBetween 4 October and 2 December 2021, 1,570 cases were reported across 10 municipalities in Kapilvastu, with 84% of cases occurring in communities bordering India. Most affected were females (55%) and children aged 5-14 years (32%). A total of 39% cases were confirmed to have Vibrio cholerae O1 Ogawa serotype, which showed resistance to cotrimoxazole. Additionally, 453 cases of acute watery diarrhea were identified in the community, with 23% showing the signs of dehydration. Of 29 water samples, 17 (59%) were contaminated with fecal coliform. ConclusionCommunities along the Nepal-India border are highly vulnerable to cholera outbreaks, highlighting the urgent need for improved water, sanitation and hygiene practices. A coordinated approach to cholera surveillance and preparedness is crucial to prevent future outbreaks.

Keeping birth at home: community and service provider visions for perinatal wellness and continued Inuit childbirth in Nunavik

Childbirth on traditional territories is unattainable for many Indigenous peoples living in remote communities in Canada. In Nunavik, Inuit territory in northern Quebec, rapid population growth risks exceeding local midwifery capacity. This poses challenges to community-based childbirth in a region recognized for reclaiming Inuit midwifery and local birthing. To explore community views on protective factors of maternal and family perinatal wellness and continued local birthing. In ten communities, Inuit families and perinatal service providers created a total of 54 fuzzy cognitive maps on protective factors for (1) birth in a good way in Nunavik, (2) maternal and family perinatal wellness, and (3) community-based birthing in Nunavik. We used fuzzy transitive closure to examine direct and indirect connections and collated individual factors into categories using inductive thematic analysis. Well-equipped local medical facilities and services, community birthing centres run by Inuit midwives, and Inuit perinatal traditions had the strongest influence on experiencing birth in a good way in Nunavik. Inuit youth perspectives featured instrumental and emotional support for mothers and families, along with health and self-care in pregnancy as the most influential factors on maternal and family perinatal wellness. Prominent protective factors for community birth in Nunavik included maternal-infant health and wellness, local Inuit midwifery services, and well-resourced medical facilities. Fuzzy cognitive mapping was helpful in informing community visioning of local childbirth and maternal and family perinatal wellness in Nunavik. Inuit-led midwifery services are essential to continued local childbirth in the region.

Egyptian pediatric kidney transplantation: highlights on post-transplant follow-up and management of complications by the Egyptian Pediatric Clinical Practice Guidelines Committee (EPG) Nephrology Group

BackgroundPediatric kidney transplantation is unique when compared to adults. They need optimum post-transplant care to achieve longer graft and patient survival. Infections, rejection, recurrence, malignancy, bone problems, hypertension, and surgical complications are the most important challenges that require prevention, early detection, and management. Chronic allograft nephropathy needs different approaches based on its related causes, allograft pathology, graft function, and availability of re-transplantation.Aim/objectivesThis national adapted guideline aims to frame evidence-based post-transplant recommendations adopted or adapted from EB source guidelines to optimize post-transplant patient care.MethodsOur guideline is evidence based adapted from four national and international source guidelines with permissions [KDIGO 2020, RA/BTS 2022–2018, EAU 2018] that were appraised with AGREE II instrument tool. We followed the “adapted ADAPTE” CPG formal adaptation methodology that consists of 3 phases and 24 steps and tools. Virtual monthly meetings all through the year 2023 were activated for reviewing and validation of final adaptation of evidence-based guideline draft, considering all comments of external reviewers. This guideline was registered in the practice guideline registration for transparency (PREPARE), number: PREPARE-2023CN364.ResultsRecommendation statements in guidelines stand for results in articles. Discussion of important recommendations and the rationale behind selection of adopted statements and tailoring of others to suit our local facilities, expertise, and renal native disease profile was presented in the text with reasons and references.ConclusionThe provided guidelines aim to improve graft and patient outcome through prevention and early management of complications and suggest research areas lacking validated research recommendations.

The role of sociodemographic factors on herpes zoster vaccine uptake among hard-to-reach populations

Abstract Background The anti-Herpes Zoster (HZ) vaccination program was expanded with the adjuvated recombinant vaccine (HZR) in the Lazio Region, Italy, in 2022, restricting its use only to certain categories at risk due to pathological conditions, such as dialysis patients or immunocompromised individuals. This study focuses on the role of clinical and socio-demographic factors on HZR vaccine uptake within the fragile resident population of the Local Health Authority Rome 2 (ASL RM2). Methods This population-based, retrospective cohort study leveraged data from various registries and databases. The study population comprised 835,779 individuals aged ≥18 years who were both RM2 residents and registered with an RM2 general practitioner (GP). Among these, 143,242 individuals with at least one chronic condition were assessed for vaccination uptake using a multivariate logistic model, exploring associations with gender, age, nationality, marital status, household size, and level of deprivation. Results At the conclusion of the study period, a small fraction (1.5%) of the fragile subjects had received at least one dose of the HZR vaccine, and a majority (78%) completed the vaccination course of two doses. The analysis indicated that vaccine adherence was significantly higher in males (OR = 1.15) and individuals aged 65 + (OR = 1.13) while lower among residents in areas of medium (OR = 0.61) and high deprivation (OR = 0.44) and with specific living arrangements - widowed people living alone (OR = 0.66) and families ≥ 6 people (OR = 0.63). Conclusions The ASL RM2 vaccination strategy for hard-to-reach individuals includes an integrated approach, with the engagement of local healthcare facilities and hospitals. Despite these efforts, lower adherence in socioeconomically disadvantaged fragile patients suggests a pressing need for targeted communication strategies and interventions to ensure equitable access to the HZ vaccine, as these groups are more vulnerable to developing chronic diseases. Key messages • Socio-demographic factors significantly influence Herpes Zoster vaccine uptake in hard-to-reach populations, with lower adherence in socially deprived groups. • Tailored, equity-driven approaches are essential for enhancing vaccine coverage among hard-to-reach fragile individuals, mitigating the higher disease risks in these communities.

Method for Enhancing AI Accuracy in Pressure Injury Detection Using Real and Synthetic Datasets

Pressure injuries pose significant health risks, especially for the elderly, immobile individuals, and those with sensory impairments. These injuries can rapidly become chronic, making initial diagnosis important. Due to the difficulty of transporting patients from local health facilities to higher-level general hospitals for treatment, it is essential to utilize telemedicine tools, such as chatbots, to ensure rapid initial diagnosis. Recent advances in artificial intelligence have demonstrated potential for medical imaging and disease classification. Ongoing research in the field of dermatological diseases focuses on disease classification. However, the assessment accuracy of artificial intelligence is often limited by unequal class distributions and insufficient dataset quantities. In this study, we aim to enhance the accuracy of artificial intelligence models by generating synthetic datasets. Specifically, we focused on training models for Pressure Injury assessment using both real and synthetic datasets. We used PI data at a domestic medical university. As part of our supplementary research, we established a chatbot system to facilitate the assessment of pressure injuries. Using both constructed and synthetic data, we achieved a top-1 accuracy of 92.03%. The experimental results demonstrate that combining real and synthetic data significantly improves model accuracy. These findings suggest that synthetic datasets can be effectively utilized to address the limitations of small-scale datasets in medical applications. Future research should explore the use of diverse synthetic data generation methods and validate model performance on a variety of datasets to enhance the generalization and robustness of AI models for Pressure Injury assessment.

Rise of the robots: implementing robotic surgery into the acute care surgery practice.

Acute Care Surgery (ACS) admissions and procedures are substantially increasing. ACS disproportionally accounts for a majority of morbidity and mortality among surgical patients. Minimally invasive techniques are associated with improved outcomes and shorter hospital length of stay within the ACS population. While laparoscopy is widespread, ACS surgeons have been slower to adopt the use of robotics. We aimed to evaluate the feasibility of incorporating robotic surgery within ACS practice. Robotic General Surgery operations performed by 8 Acute Care Surgeons from 5 local facilities within a large integrated healthcare system were queried over a 15 month period. Patients who underwent emergent, urgent, sub-acute, and elective robotic operations by ACS staff were identified. Demographics collected included age, gender, BMI, and ASA score. Outcomes recorded included procedure classification, total supply and implant charges (TSI), conversion to open, hospital length of stay (LOS), 30 day readmission, and 30 day mortality. Of 200 operations, the most common were Cholecystectomy (43.5%), Inguinal hernia repair (26.0%), Ventral hernia repair (18.0%), Appendectomy (5.0%), and Sigmoid Colectomy (3.5%). The median (± std dev) age was 48 ± 16.66years and BMI was 29.9 ± 8.79kg/m2. 46% of cases were sub-acute (n = 92), 33.5% were elective (n = 67), 14% were emergent (n = 28), and 6.5% were urgent (n = 13). Most patients were ASA 2 (107, 46.1%) or ASA 3 (71, 45.9%). The median (IQR) TSI and LOS were $1,770 (889.50) USD and 0.1 (0.9) days. Forty-one inpatient procedures were performed. Median LOS was 3days and expected LOS was 3.1days (O:E = 0.96). Five patients were readmitted within 30days, and there were no deaths within 30days. Robotic techniques may be safely implemented by ACS surgeons, potentially benefitting both patient and surgeon. LOS was similar between laparoscopic and robotic cases and only two cases required conversion to an open procedure. Next steps include a multi-center prospective trial comparing robotic to laparoscopic cases.

Feasibility, Acceptability, Satisfaction, and Challenges of an mHealth App (e-ASCov) for Community-Based COVID-19 Screening by Community Health Workers in Rwanda: Mixed Methods Study.

Although at the base of the pyramid-shaped organization of the Rwandan health system, community health workers (CHWs) are central to the community-based management of disease outbreaks. This mixed methods study aimed to explore the feasibility, acceptability, satisfaction, and challenges of a mobile health (mHealth) tool for community-based COVID-19 screening in Rwanda. Two urban (Gasabo and Nyarugenge) and 2 rural (Rusizi and Kirehe) districts in Rwanda participated in the project (smartphone app for COVID-19 screening). A mixed methods approach was used to inform the feasibility (awareness and expectation), acceptability (use and perceived benefits), satisfaction, and challenges of the mHealth intervention. At the end of the project, CHWs were asked to complete a quantitative questionnaire on the use of and satisfaction with the app. Then, in-depth interviews and focus group discussions were organized with CHWs. A content analysis was performed on the transcripts. Overall, 383 CHWs were recruited and trained; 378 CHWs participated in the study. The mean age of CHWs was 36.7 (SD 6.6) to 45.3 (SD 9.9) years and most were women (237/378, 62.7%). More than 7000 people were registered with the use of the app and 20% were referred to a local COVID-19 testing facility. According to CHW reporting, the median number of people screened by each CHW ranged from 152 (IQR 70-276) for Nyarugenge to 24 (IQR 16-90) for Rusizi. COVID-19 positivity rates were higher in urban than rural districts: more than half of the CHWs in Gasabo reported a confirmed positive case versus only 2.4% for Kirehe and 15.4% for Rusizi. Despite the app being a novel tool, CHWs were well aware of the use of such a tool and had appropriate expectations. Acceptability and satisfaction were very high, with differences between urban and rural districts. Satisfaction was higher in Nyarugenge (72.8/100) and Gasabo (80.7/100) than in Kirehe (61.6/100) and Rusizi (64.5/100). More than 80% of the CHWs were willing to continue using the e-ASCov app, with the exception of CHWs in Kirehe (56.7%). The app was perceived as a tool to generate information on COVID-19, inform on the status of the pandemic, and help curb the spread of the pandemic in Rwanda. CHWs were satisfied with the app at all stages of its implementation in their districts. In this proof-of-concept study, a smartphone app for screening COVID-19 was useful as an mHealth tool to be used by CHWs, with the potential to increase health system efficiency in an epidemic context. The context should be analyzed for generalization on a country-wide scale, both in case of an epidemic and to take into account certain conditions at the community level. Information is needed on the conditions of generalization and transferability of this type of app to other health conditions so that CHWs can be given their full place in a pyramidal health system.

Geometric and dosimetric evaluation for breast and regional nodal auto-segmentation structures.

The accuracy of artificial intelligence (AI) generated contours for intact-breast and post-mastectomy radiotherapy plans was evaluated. Geometric and dosimetric comparisons were performed between auto-contours (ACs) and manual-contours (MCs) produced by physicians for target structures. Breast and regional nodal structures were manually delineated on 66 breast cancer patients. ACs were retrospectively generated. The characteristics of the breast/post-mastectomy chestwall (CW) and regional nodal structures (axillary [AxN], supraclavicular [SC], internal mammary [IM]) were geometrically evaluated by Dice similarity coefficient (DSC), mean surface distance, and Hausdorff Distance. The structures were also evaluated dosimetrically by superimposing the MC clinically delivered plans onto the ACs to assess the impact of utilizing ACs with target dose (Vx%) evaluation. Positive geometric correlations between volume and DSC for intact-breast, AxN, and CW were observed. Little or anti correlations between volume and DSC for IM and SC were shown. For intact-breast plans, insignificant dosimetric differences between ACs and MCs were observed for AxNV95% (p=0.17) and SCV95% (p=0.16), while IMNV90% ACs and MCs were significantly different. The average V95% for intact-breast MCs (98.4%) and ACs (97.1%) were comparable but statistically different (p=0.02). For post-mastectomy plans, AxNV95% (p=0.35) and SCV95% (p=0.08) were consistent between ACs and MCs, while IMNV90% was significantly different. Additionally, 94.1% of AC-breasts met ΔV95% variation<5% when DSC>0.7. However, only 62.5% AC-CWs achieved the same metrics, despite AC-CWV95% (p=0.43) being statistically insignificant. The AC intact-breast structure was dosimetrically similar to MCs. The AC AxN and SC may require manual adjustments. Careful review should be performed for AC post-mastectomy CW and IMN before treatment planning. The findings of this study may guide the clinical decision-making process for the utilization of AI-driven ACs for intact-breast and post-mastectomy plans. Before clinical implementation of this auto-segmentation software, an in-depth assessment of agreement with each local facilities MCs is needed.

Assessing Business Viability for a Production Joint Venture in the Indonesian Medical Device Industry

Research Aims: This study examines the viability of a joint venture between Daenamic Health Inc., a South Korean medical device manufacturer, and PT. Kenari Jaya Perkasa, an Indonesian medical device importer, to establish a local production facility for high-end medical devices in Indonesia. Design/methodology/approach: The research follows a structured approach involving the analysis of business model compatibility, external market dynamics, and the financial and operational viability of the joint venture. Employing qualitative analysis from discussions, VRIO Framework, and quantitative analysis from Analytic Hierarchy Process (AHP), the study evaluates market conditions and strategic fit between the partners. Research Findings: Findings indicate that Daenamic Health Inc. and PT. Kenari possess complementary strengths, forming a synergistic partnership poised to become a leading local brand for high end medical technology, as well as enabling access to more export market. Motivated by the need to reduce Indonesia's dependency on import, especially highlighted during the COVID-19 pandemic, this venture aligns with government policies to enhance local manufacturing and healthcare infrastructure. However, challenges such as navigating regulatory landscapes, managing a layered cost structure, and training local human capital must be addressed. Theoretical Contribution/Originality: Preliminary assessment for the joint venture’s establishment helps the partners to comprehensively assess their internal situation both as individual business and as future partners, prior to capitalizing the opportunity that comes with Indonesia’s vision towards healthcare self-sufficiency. As a result, partners’ synergistic strengths and aligned individual business needs positions the venture for competitive pricing and expansion in Southeast Asia and beyond. Keywords: Medical Devices; Joint Venture; Local Manufacturing; Market Dynamics; Strategic Fit

Increasing public awareness through education and the implementation of routine blood donations

This community service program aims to increase public awareness and participation in blood donation activities through education and the regular implementation of blood donation. Adequate blood availability in blood transfusion units is critical to saving lives, but community participation in blood donation is still low in some areas. Through this activity, counselling was carried out to the community about the benefits of blood donation, health requirements, and the importance of blood donation continuity for medical emergency needs. This program collaborates with the Indonesia Red Cross (PMI) and local health facilities to organize routine blood donation activities every three months. It is hoped that with this program, community participation in blood donation will increase significantly, and sustainable awareness about the importance of sharing and helping others through blood donation will be created. The results of this activity were measured through an increase in the number of blood donation participants and an evaluation of community knowledge after counselling was carried out

The locality challenges facing the ‘levelling up’ of sport participation and health inequality in England

ABSTRACT In the context of the UK Government’s levelling up agenda, current sport policy seeks to reduce inequalities in sport participation, supported by investment in facilities. Drawing on a socio-ecological theoretical framework, this paper analyses a large-scale dataset measuring individual sport and fitness participation, local authority facility availability and level of multiple deprivation to examine the individual/compositional and locality/contextual influences on participation in sport and fitness activities for men and women in England. Multi-level regressions highlight the challenges faced for policy, arguing that scaled-up local action is needed to account for the interaction between individual factors, facility availability and area deprivation.

Study on the Natural Ventilation Model of a Single-Span Plastic Greenhouse in a High-Altitude Area

The natural ventilation model plays a crucial role in greenhouse environmental control. It has been extensively studied by previous researchers, but it is limited to low-altitude areas. This study established a numerical model of single-span plastic greenhouses in high-altitude areas. The model was validated using measured data, showing a good agreement between the measured and simulated values. By setting boundary conditions based on on-site monitoring data, ventilation rates were extracted under different conditions for numerical simulations. Through nonlinear fitting, an empirical formula for natural ventilation rates, with a determination coefficient (R2) of 0.9724, was derived. The formula was validated through an energy balance analysis of indoor air. Different ventilation opening sizes were simulated to derive an empirical formula for natural ventilation rates based on opening size. Building on this, the relationship between plant height and ventilation rate was analyzed. As the dominant factors of natural ventilation change with environmental fluctuations, this study also proposed the threshold wind speed for wind pressure ventilation, thermal pressure ventilation, and coupled ventilation, filling the knowledge gap in relevant ventilation rate calculations. This is the first time that a natural ventilation model of single-span plastic greenhouses in high-altitude areas has been proposed, providing the basis in terms of modeling for the further development of local facility agriculture.

Measuring and optimizing the spatial accessibility of primary health care in remote and rural areas: a case study of Liannan Yao Autonomous County in China

The need for equitable access to primary healthcare services in the current global context has attracted widespread attention, prompting nations to continuously enhance their grassroots medical service levels. In response, China launched the "Healthy China" initiative, which prioritizes the enhancement of national health as a core goal of the healthcare system and uses this opportunity to deepen reforms aimed at strengthening primary care. However, in remote and rural areas, the optimization of medical resource allocation and the achievement of balanced service development remain critical challenges owing to limited resources. This study selected Liannan Yao Autonomous County, which is situated in the northwestern corner of Guangdong Province, as a case study due to its remote mountainous location, underdeveloped economy, and minority region characteristics. Through field research and interviews, this study thoroughly explored the needs of both supply and demand, factoring in elements such as the service capability of healthcare facilities and residents' travel thresholds to enhance the two-step floating catchment area model, thus making it more applicable to remote villages. By integrating electric bikes and cars, which are the primary means of transportation in rural areas, this study conducted a thorough analysis and comparison of the accessibility of medical services in Liannan Yao Autonomous County (Liannan County) . The results reveal significant disparities in healthcare accessibility, an uneven distribution of medical resources, and varying impacts of transportation conditions and facility service capabilities on accessibility. Notably, the study revealed that improving transportation conditions alone has limited effects in rural areas; the key lies in balancing medical service capabilities and the rationality of overall layouts. From the perspectives of equity and efficiency, this study employs the equitable coverage model and the efficiency-driven model to construct two scenarios, comparing accessibility changes in Liannan County under both conditions and proposing strategies to improve the spatial layout of local healthcare facilities. This research not only deepens the understanding of healthcare service accessibility in rural areas but also provides a scientific basis for optimizing resource allocation and enhancing primary medical services, offering valuable guidance and reference for Liannan County and other similar rural regions.

Expanding the roles of malaria post workers in Thailand: A qualitative study of stakeholder perspectives.

In Thailand, since the 2000s, malaria post (MP) workers have been tasked with promptly detecting and treating all malaria cases to prevent onward transmission in the communities. Expanding their roles to provide health services beyond malaria has been proposed as a strategy to sustain their activities until elimination is reached. This article examines the perspectives of stakeholders on community-based malaria care to assess prospects for expanding the role of MPs. The study incorporated in-depth interviews (IDIs) and focus group discussions (FGDs). In forested communities and local health facilities in northeast Thailand bordering Lao PDR and Cambodia, where malaria transmission is low, IDIs were conducted with 13 MPs and 23 community members. An additional 14 policymakers and implementers across the health sector in Thailand were interviewed. The respondents highlighted how in these border areas population groups most at risk of malaria, namely forest goers and migrants, are reluctant to visit public health facilities. In these areas, MP workers are well integrated in their communities and remain relevant although the communities no longer see malaria as spriority. Common conditions such as dengue, diabetes, insect bites, diarrhea, mental illness and substance abuse, were identified as local health concerns needing potential add-on services from MP workers. Although challenges in terms of training, supervision, and financing were raised, opportunities included additional funds from local administrative offices to maintain and integrate malaria activities with other health programmes. Changes to the roles of MPs should be adapted to changing local needs, some of which were identified in this study, should avoid duplication and potential tensions with other local health programmes, and need to build on the capacity of the community and primary care system. These enabling factors are worthy of consideration by any malaria programmes looking into maintaining their village malaria workers in the Greater Mekong Subregion.

AI learning-driven optimization of microgrid systems for rural electrification and economic empowerment

Artificial Intelligence (AI) and machine learning (ML) are transforming the landscape of rural electrification through their application in microgrid systems. Microgrids, localized networks that can operate independently or in conjunction with the main grid, offer a viable solution for delivering reliable electricity to rural areas. AI-driven optimization enhances the performance and efficiency of these microgrids, addressing the unique challenges faced in remote regions and contributing to economic empowerment. AI technologies, including machine learning algorithms and data analytics, play a critical role in optimizing microgrid systems. By employing predictive maintenance, AI can forecast equipment failures and schedule timely repairs, thereby minimizing downtime and reducing maintenance costs. Additionally, AI enhances energy management through precise load forecasting, optimizing energy distribution, and integrating renewable energy sources like solar and wind. This not only balances energy supply and demand but also mitigates the variability associated with renewable sources. The impact of AI-driven microgrid optimization on rural electrification is profound. Improved system reliability and efficiency result in more stable energy supplies, which is crucial for supporting local businesses, educational facilities, and healthcare services in remote areas. Economically, the reduction in energy costs and the creation of new job opportunities further empower rural communities. Socially, reliable electricity enhances the quality of life, enabling better educational outcomes and promoting economic development. Successful implementations of AI in microgrid systems have demonstrated significant benefits. For instance, AI-optimized microgrids in rural communities have shown improved performance and stability, leading to greater energy access and economic benefits. However, challenges remain, including technical complexities, financial constraints, and regulatory hurdles. Addressing these challenges through continued research, investment, and policy support is essential for scaling AI-driven solutions and achieving broader impacts. AI-driven optimization of microgrid systems offers a powerful tool for advancing rural electrification and economic empowerment. By leveraging AI technologies, we can enhance energy reliability, reduce costs, and foster economic growth in underserved regions, paving the way for a more equitable and sustainable future. Keywords: AI Learning-Driven, Microgrid Systems, Rural Electrification, Economic Empowerment.

Optimizing the health of the elderly through screening and health education

The increasing number of older adults in Indonesia demands more attention to efforts to optimize their health. The elderly are susceptible to various chronic and degenerative diseases that can reduce the quality of life. Therefore, a comprehensive approach through screening and health education is urgently needed to improve the health status of older adults. This community service aims to conduct health screenings and provide health education to older adults in certain areas. The methods used include basic health checks such as blood pressure, blood sugar, and body mass index (BMI), as well as counseling on healthy lifestyles, nutrition, and the importance of physical activity. The results of this activity show that many older adults are not aware of their actual health conditions. Through screening, several cases of hypertension, diabetes, and obesity were found that required further treatment. In addition, the health education provided is able to increase the knowledge and awareness of older adults regarding the importance of maintaining a healthy lifestyle. This community service concludes that the combination of screening and health education is effective in detecting health problems and increasing the awareness of the elderly about the importance of prevention and early treatment. Recommendations for similar programs in the future are to expand the reach of activities, strengthen collaboration with local health facilities, and develop more comprehensive educational materials