Public Health Management Research Articles

Machine learning prediction of health risk and spatial dependence of geogenic contaminated groundwater from the Hetao Basin, China

Geogenic contaminated groundwater (GCG), characterized by elevated arsenic, fluoride, and iodine levels, present a significant challenge to public health and government management. Conventional survey-based approaches of collecting groundwater samples, conducting physicochemical tests, and performing spatial interpolation to obtain regional groundwater chemical component maps are inefficient and costly. More importantly, it does not take into account the actual hydrogeological conditions or the characteristics of pollutant transport and enrichment. To address this issue, we utilized Support Vector Machine (SVM), Random Forest (RF), Adaptive Boosting (AdaBoost), and Extreme Gradient Boosting (XGBoost) to analyze the likelihood of occurrence of arsenic, fluoride, and iodine as well as their spatial distribution in shallow groundwater from the Hetao Basin. Our study incorporated 20 indicators related to meteorology, soil physicochemical properties, and groundwater conditions, along with 1505 labeled samples consisting of groundwater arsenic, fluoride, and iodine concentrations and their corresponding coordinates. Subsequently, the study automatically analyzed the meteorological, soil physicochemical properties and groundwater conditions by constructing a machine learning model using the available data. In order to optimise and select the best prediction model, this paper presents a quantitative evaluation of the prediction performance of various machine learning models. The accuracy (AC), area under curve (AUC) and mean squared error (MSE) were calculated to predict the spatial distribution of CGC. Subsequently, the optimized model for predicting the spatial distribution of GCG was selected. The results showed that the XGBoost algorithm provided optimal predictions for groundwater with arsenic concentrations above 10 μg/L and fluoride concentrations exceeding 1.5 mg/L, whereas the RF model provided the best predictions for groundwater with arsenic concentrations surpassing 50 μg/L and iodine concentrations exceeding 100 μg/L. Subsequently, groundwater health risk zones were delineated based on an optimal prediction model, and demographic analysis was conducted in both the direct and potential groundwater risk zones. Model predictions indicated that hundreds of thousands of people in the Hetao Basin were facing a public health crisis caused by high concentrations of arsenic, fluoride and iodine in groundwater. These findings underscore the significant health challenge in the study area. Considering the agricultural development and increasing groundwater use in the area, our findings can guide local governments in managing the extent of groundwater development, establishing control zones, and enhancing protection measures for populations at risk from groundwater contamination.

ENVIRONMENTAL IMPACTS OF COVID-19 HOSPITALS AND ARCHITECTURAL REMEDIES

Pandemics, with their potential for widespread devastation and global impact, have historically been a critical concern for public health and society. the historical impact of pandemics on the environment underscores the interconnectedness of human lives and health, societal systems, and the environment, highlighting the need for holistic approaches to public health and environmental management. The COVID-19 pandemic has brought about significant changes in healthcare facilities worldwide, particularly in hospitals designated for COVID-19 patients to counter and serve the impact on humans which universally led to the rapid establishment of specialized hospitals to manage the surge in patients. However, such hospitals not only posed significant challenges to healthcare systems worldwide but also highlighted the need for sustainable practices in designing and operating healthcare facilities along with their significant environmental impacts. In response to these challenges, architects, designers, and healthcare professionals have explored innovative architectural and other remedies to mitigate the environmental impacts of COVID-19 hospitals. This paper explores these potential environmental impacts and proposes architectural planning strategies that include sustainable practices and green design principles through which, by implementing, COVID-19 hospitals or similar hospitals can minimize their environmental footprint and contribute not only to a more sustainable healthcare system but also create healthier and more sustainable environments for patients, healthcare workers, and the community at large. KEYWORDS: Hospital Environmental Impact, Hospital Environment Relation, COVID-19 Hospital Impact on Environment, COVID-19 Hospital Impact, Environmental Impact of Pandemics, Pandemic Hospital Impact on Environment

Dengue fever coinfection in COVID-19 era: A public health concern.

Dengue and SARS-CoV-2 coinfection is commonly encountered and constantly reported in particularly the dengue-endemic regions thus posing a co-epidemic threat. Coinfection is also significantly associated with morbidity and mortality. Comorbidity risk during a coinfection is of a greater concern. Although the pathophysiologies of the two infections vary, their identical clinical symptoms during coinfection result in diagnostic and therapeutic complexities. A literature search for the current relevant reports was carried out. The searched databases were Scopus, PubMed, Google Scholar and the Web of Science, with health agencies like the WHO. Based on the selection criteria, the most recent and pertinent reports published in English language were included for the ease of understanding, deciphering and analysing the secondary data. A delay in proper diagnosis of coinfection could result in serious complications with poor patient outcome. Whether it is a standalone dengue or COVID-19 infection or a coinfection, specific biomarkers may be utilized for its foolproof diagnosis. This article highlights the various diagnostic techniques and immune responses from the perspective of prompt and appropriate public health management for patients suffering from COVID-19 and dengue viral coinfections, both being independently or collectively capable of damaging a human body. As coinfection poses significantly large burden on an already-fragile healthcare facility, constant monitoring of a coinfected patient is needed for prompt and suitable therapeutics. Also, to maintain high vigilance and invoke appropriate preventive measures particularly in dengue endemic regions, the government, healthcare authority and the general public need to collaborate and cooperate.

Digital Transformation in Healthcare Challenges and Prospects

The following are presented, by the global community, as the main fields of Digital Transformation (DT) in Healthcare: Telemedicine Telemedicine is the remote delivery of healthcare services through Information and Communication Technologies (ICTs). It could be particularly beneficial in a range of services such as medical consultation, diagnosis remote monitoring of patients’ status and educational purposes. Patients could con- nect with healthcare providers at a distance using video calls, messaging platforms, or other communication tools. Telemedicine enhances accessibility to healthcare by overcoming geographical barriers while at the same time provides a transformative approach to healthcare services. Big Data Big data represents vast and diverse health information sets collected from several sources like Electronic Health Records (EHRs), wearable devices and social media. Big data can extract valuable insights and patterns, assisting clinical decision-making, public health management, personalised medicine and disease forecasting. Internet of Things (IoT) The Internet of Things (IoT) in healthcare refers to the interconnected network of medical devices, sensors and sys- tems that collect and exchange health data through the Inter- net. These devices offer real-time exchange of various data monitoring like patient's vital signs, and remote patient’s care, which could eventually result in the improvement of operational efficiency within healthcare systems, and patients' monitoring and care delivery. Virtual Reality (VR) in Health Virtual Reality (VR) employs immersive computer-generated environments into realistic experiences to transform medical training and education, rehabilitation, surgical planning and pain management. Employing VR tools such as headsets, users engage with three-dimensional simulation scenarios for training and skill practice in a safe environment without risking personal and patient safety. In addition, VR offers opportunities to improve outcomes, provide safer experiences to patients, while promoting the evolution of healthcare systems and care delivery. Artificial Intelligence (AI) in Health AI in healthcare is an umbrella term for the applications of Machine Learning (ML) algorithms used in medical contexts. AI algorithms analyse medical data, aiding in diagnostics, drug discovery, personalised medicine, and patient management. Virtual (personal) Assistants in Health Virtual Health Assistants (VHAs) are tools designed to engage patients, provide personalised health information and assist in various aspects of health services administration. Using Natural language Processing (NLP) and ML algorithms, VHAs offer support to remote communication between patients and healthcare providers, understand patients’ inquiries and healthcare-related issues. Also, VHAs could facil- itate appointment scheduling, symptom assessment, medication management, and health coaching, resulting at the enhancement of accessibility in healthcare and the empower- ment of the patient. Blockchain in Health Blockchain is an emerging technology, which utilises decentralised systems to record and manage healthcare information and patient data. By linking data blocks, blockchain can enhance security, interoperability and traceability, and address significant challenges such as data breaches, interoperability issues, and inefficiencies in data sharing, thus providing a stan- dardised and secure platform for data exchange across health- care systems and stakeholders. Medical Wearables Wearables emerge positive outcomes on continuing monitoring, tracking and early detecting of health issues. Wearables are devices wore on the body or putted on clothing allowing constant monitoring of health data and behaviour. They enable individuals to engage a proactive approach to their health and well-being, by empowering them to take control of their health. In addition, wearables have the potential to enhance telemedicine and population health management, while reducing healthcare costs.

Does the level of burnout differ between occupational groups in Lithuania?

The strain on workers of the healthcare system and education sector increased psychological distress and burnout. This study aimed to distinguish the occupational group that is the most affected by occupational burnout and to reveal the scope of psychosocial risk factors among each occupational group. This is a cross-sectional study that analyzed burnout syndrome among 1,046 participants of different occupational groups in association with psychosocial work environment factors in Lithuania. The anonymous questionnaire was composed of the standardized Job Content Questionnaire (JCQ), and the Copenhagen Burnout Inventory (CBI). To find out associations between psychosocial work environment factors and burnout dimensions, a multiple logistic regression model using the stepwise method was applied. The burnout levels in all three dimensions (personal, work-related, and client-related burnout) were significantly higher in physicians' and nurses' groups compared with public health professionals, teachers, and managers (p < 0.05). The job demands were associated with the personal burnout subscale for all occupations, except public health specialists - each one-unit increase of this variable significantly increased the probability of personal burnout from 10 to 16%, respectively by the occupation. Co-worker support was found to have a buffering effect for all occupational groups, except managers - and significantly reduced personal burnout for physicians (OR = 0.80), nurses (OR = 0.75), public health specialists (OR = 0.75), and teachers (OR = 0.79). The burnout levels in all three dimensions differed between occupational groups: there were significantly higher in physicians' and nurses' groups compared with public health professionals, teachers, and managers. Considering the occupational preventive measures in the healthcare sector attention should be paid to the reduction of workload and ensuring good relations between co-workers.

New records on toxic cyanobacteria from Brazil: Exploring their occurrence and geography

Cyanobacterial Harmful Algal Blooms (CyanoHABs) pose a significant threat to communities globally, impacting ecosystems and public health. This study provides an in-depth review of the current state of cyanotoxins and the distribution of CyanoHABs species in Brazil, while also detailing the methods used for their detection. Four hundred and twenty-one incidents were analyzed from 1993 to 2021, compiling cyanotoxin records and toxic CyanoHABs occurrences. The investigation begins with the first detection of microcystins in 1994 and highlights pivotal moments, like the 1996 “Caruaru Syndrome” outbreak. This event encouraged research and updated cyanotoxin-monitoring guidelines. The Brazilian drought period of 2015–2016 exacerbated cyanobacterial growth and saxitoxin levels, coinciding with Zika-related microcephaly. This study delves into methods used for cyanotoxin analysis, including ELISA, bioassays, HPLC, and LC-MS. Additionally, we investigated the toxicity of 37 cyanobacterial strains isolated from various Brazilian environments. Extracts were tested against Artemia salina and analyzed by LC-MS. Results revealed toxicity in extracts from 49 % of cyanobacterial strains. LC-MS results were analyzed using GNPS MS/MS molecular networking for comparing experimental spectra with those of cyanotoxin standards against in-house databases and the existing literature. Our research underscores the variability in cyanotoxin production among species and over time, extending beyond microcystins. LC-MS results, interpreted through the GNPS platform, revealed six cyanotoxin groups in Brazilian strains. Yet, compounds present in 75 % of the toxic extracts remained unidentified. Further research is crucial for fully comprehending the impact of potentially harmful organisms on water quality and public health management strategies. The study highlights the urgent need for continuously monitoring cyanobacteria and the cyanotoxin inclusion of management in public health policies.

Optimizing Fixation Duration for Enhanced Clarity in Pediculus humanus capitis Whole Mount Preparations Using 10% KOH at 70°C

This study evaluates the optimal fixation duration using 10% potassium hydroxide (KOH) at 70°C for whole mount preparations of Pediculus humanus capitis (head lice). Accurate head lice identification is crucial for effective public health management. Specimens were fixed for 20, 25, 30, 35, and 40 minutes at 70°C, then processed through rinsing, acetic acid treatment, dehydration, and clearing before mounting for microscopic examination. Results showed that 25 minutes of fixation provided the clearest and most detailed preparations. This duration effectively achieved tissue dehydration and clarification without significant damage. Fixation for 20 minutes was insufficient, resulting in opaque specimens due to incomplete KOH diffusion. Conversely, 40 minutes of fixation caused over-fixation, leading to tissue damage and poorer color quality. The study underscores the importance of finding the right fixation duration. While shorter times are inadequate, longer durations can degrade specimen quality. A 25-minute fixation at 70°C is optimal for balancing clarity and structural preservation, improving head lice identification. This method enhances the quality of whole mount preparations and provides practical guidance for accurate and reliable ectoparasite examination in clinical and research settings.

Brazilian Psychiatric Association Consensus on the physical structure and ideal team for psychiatric emergencies services.

An integral part of Brazil's public health system, the psychiatric emergency service (PES) has been instrumental in improving qualified support for crisis situations of mental disorders, equitable, universally accessible, and humanized. The purpose of this article is to present a systematic review and consensus about the physical area and facilities, and ideal team qualified for psychiatric emergencies services on both Brazilian settings. The authors conducted a literature search using electronic databases such as MEDLINE (PubMed), Scielo, the Cochrane Database, and documents from the WHO, the Brazilian Ministry of Health, and others deemed relevant by experts. A total of 6839 manuscripts were found, but only 46 were selected. The analysis of article content summarizes consensus statements using the Delphi method and a series of interactive versions to provide a final report. Changes to PES are evaluated considering various experiences and models. The authors highlighted that The Emergency Care Network (ECN) must be coordinated with qualified management, effective implementation of integration of all health equipment's and units. PES must have adequate infrastructure; qualified staff, including a psychiatrist; sufficient consultation and observational spaces; tools and resources for differential diagnosis; training for all staff members; and communication with the health care network to facilitate referrals following patient discharge are all necessary. These standardized models need to be available to public health managers so that they can guide the installation of new services and adjust the existing ones, always looking for improvement. The authors propose requirements for PES as a model to be passed over.

Recent Advances in Lateral Flow Assays for Viral Protein Detection with Nanomaterial-Based Optical Sensors.

Controlling the progression of contagious diseases is crucial for public health management, emphasizing the importance of early viral infection diagnosis. In response, lateral flow assays (LFAs) have been successfully utilized in point-of-care (POC) testing, emerging as a viable alternative to more traditional diagnostic methods. Recent advancements in virus detection have primarily leveraged methods such as reverse transcription-polymerase chain reaction (RT-PCR), reverse transcription-loop-mediated isothermal amplification (RT-LAMP), and the enzyme-linked immunosorbent assay (ELISA). Despite their proven effectiveness, these conventional techniques are often expensive, require specialized expertise, and consume a significant amount of time. In contrast, LFAs utilize nanomaterial-based optical sensing technologies, including colorimetric, fluorescence, and surface-enhanced Raman scattering (SERS), offering quick, straightforward analyses with minimal training and infrastructure requirements for detecting viral proteins in biological samples. This review describes the composition and mechanism of and recent advancements in LFAs for viral protein detection, categorizing them into colorimetric, fluorescent, and SERS-based techniques. Despite significant progress, developing a simple, stable, highly sensitive, and selective LFA system remains a formidable challenge. Nevertheless, an advanced LFA system promises not only to enhance clinical diagnostics but also to extend its utility to environmental monitoring and beyond, demonstrating its potential to revolutionize both healthcare and environmental safety.

A declining trend of hepatitis A and hepatitis E at tertiary care hospital in South Gujarat

Objectives: Hepatitis A virus (HAV) and Hepatitis E virus (HEV) both are spread through the fecal-oral route and cause acute viral hepatitis (AVH) and pose a major public health problem in India. This study was done to find out the proportion of positivity of HAV and HEV in patients with AVH and its seasonal trend. Materials and Methods: A retrospective study was carried out at Surat Municipal Institute of Medical Education and Research Medical College, Department of Microbiology, Surat, Gujarat. Result of 3615 blood samples of suspected AVH patients of the past 5 years (January 2018–December 2022) were taken from hospital data records. The enzyme-linked immunosorbent assay method was used to test serum samples for immunoglobulin M (IgM) HAV and IgM HEV antibodies for HAV and HEV, respectively. All samples were evaluated for liver function as well. Results: The positivity of HAV and HEV was 15.13% and 10.26%, respectively. The coinfection rate was 2.07%. HAV and HEV both affected males more than females. Among pregnant females, HEV infection had more positivity (6.77%) than HAV, which had 1.08% positivity. HAV and HEV infections had a seasonal trend, with the highest infection rate in the monsoon. Conclusion: The declining trend of cases of HAV and HEV was found in Surat city of south Gujarat which indicates increased awareness about hepatitis among people and better public health management by the civic authorities.

The hostile side of the state: Siracusa Principles, human rights and the precarity of COVID-19 policing in Nigeria

In line with global advisories, the Nigerian authorities explored what could be termed a ‘stringent’ lockdown measure to contain the transmission of the COVID-19 pandemic and prevent a public health catastrophe. In this study, I examine the appositeness of the measure and its manner of implementation within the purview of the 1984 Siracusa Principles and the International Covenant on Civil and Political Rights (ICCPR) on the derogation of human rights. The principles and ICCPR guarantee equitable access to basic healthcare for all citizens and obligate state parties to take actions to prevent potential harm to public health if such actions are necessary, lawful, evidence-based, non-discriminatory, unarbitrary, proportional, respectful of human dignity, and brief in timeframe. I argue that although the measure aligns with the principles, ICCPR and Nigeria’s COVID-19 Regulations, 2020 - its manner of implementation typified gross human rights breaches, extrajudicial practices, and repressive state behaviours. However, this study offers a novel understanding of statecraft and citizens–government relations during the pandemic – pandemic policing and public health management – while emphasising that upholding human rights and strengthening democratic ideals are central to containing future pandemics successfully.

Long-term effects of non-pharmaceutical interventions on total disease burden in parsimonious epidemiological models

The recent global COVID-19 pandemic resulted in governments enacting non-pharmaceutical interventions (NPIs) targeted at reducing transmission of SARS-CoV-2. But the NPIs also affected the transmission of viruses causing non-target seasonal respiratory diseases, including influenza and respiratory syncytial virus (RSV). In many countries, the NPIs were found to reduce cases of such seasonal respiratory diseases, but there is also evidence that subsequent relaxation of NPIs led to outbreaks of these diseases that were larger than pre-pandemic ones, due to the accumulation of susceptible individuals prior to relaxation. Therefore, the net long-term effects of NPIs on the total disease burden of non-target diseases remain unclear. Knowledge of this is important for infectious disease management and maintenance of public health. In this study, we shed light on this issue for the simplified scenario of a set of NPIs that prevent or reduce transmission of a seasonal respiratory disease for about a year and are then removed, using mathematical analyses and numerical simulations of a suite of four epidemiological models with varying complexity and generality. The model parameters were estimated using empirical data pertaining to seasonal respiratory diseases and covered a wide range. Our results showed that NPIs reduced the total disease burden of a non-target seasonal respiratory disease in the long-term. Expressed as a percentage of population size, the reduction was greater for larger values of the basic reproduction number and the immunity loss rate, reflecting larger outbreaks and hence more infections averted by imposition of NPIs. Our study provides a foundation for exploring the effects of NPIs on total disease burden in more-complex scenarios.

Recent Advances in Development of Biosensors for Monitoring of Airborne Microorganisms.

The early detection of infectious microorganisms is crucial for preventing and controlling the transmission of diseases. This article provides a comprehensive review of biosensors based on various diagnostic methods for measuring airborne pathogens. This article aims to explore recent advancements in the field of biosensors tailored for the detection and monitoring of airborne microorganisms, offering insights into emerging technologies and their potential applications in environmental surveillance and public health management. The study summarizes the research conducted on novel methods of detecting airborne microorganisms using different biological sensors, as well as the application of signal amplification technologies such as polymerase chain reaction (PCR), immunoassay reactions, molecular imprinted polymers (MIP) technique, lectin and cascade reactions, and nanomaterials. Antibody and PCR detection methods are effective for specific microbial strains, but they have limitations including limited stability, high cost, and the need for skilled operators with basic knowledge of the target structure. Biosensors based on MIP and lectin offer a low-cost, stable, sensitive, and selective alternative to antibodies and PCR. However, challenges remain, such as the detection of small gas molecules by MIP and the lower sensitivity of lectins compared to antibodies. Additionally, achieving high sensitivity in complex environments poses difficulties for both methods. The development of sensitive, reliable, accessible, portable, and inexpensive biosensors holds great potential for clinical and environmental applications, including disease diagnosis, treatment monitoring, and point-of-care testing, offering a promising future in this field. This review presents an overview of biosensor detection principles, covering component identification, energy conversion principles, and signal amplification. Additionally, it summarizes the research and applications of biosensors in the detection of airborne microorganisms. The latest advancements and future trends in biosensor detection of airborne microorganisms are also analyzed.

Human-animal entanglements in bushmeat trading in Sierra Leone: An ethnographic assessment of a potential zoonotic interface.

'Bushmeat' markets are often portrayed as chaotic spaces where exotic wild animals are sold. They are hypothesized to be important sites for zoonotic disease transmission, given the prolonged and intense nature of the cross-species encounters that occur within them. Whilst such markets have received some attention from researchers, rich qualitative descriptions of everyday practices in these markets are rare. Depictions of wild animal markets as sites for potential viral amplification often rely on exoticizing assumptions and narratives rather than actual evidence, and in some cases are based more on ideology than on science. We provide an in-depth ethnographic account of two bushmeat markets in Bo, Sierra Leone. Our analysis goes beyond common assumptions that zoonotic risk is located solely in the knowledge and behaviours of traders. Our account sheds light on the modes of touch, closeness and contact that shape this hypothesised zoonotic interface, outlining the possible risks to different people who use and spend time in the market. We found that inadequate infrastructure and sanitation facilities created risks of zoonotic disease transmission for diverse actors including traders, customers, children, and the wider public. Butchering and trading practices frequently resulted in people directly and indirectly encountering animal fluids. We also discuss how public health management of these markets focused on individual behaviours rather than on improving conditions. Urgent sanitary reform and infrastructure upgrades in these sites that support the economic needs of traders could encourage voluntary compliance with biosafety measures amongst traders seeking to balance responsibilities to family and public health. Our study reveals the value of moving beyond exoticized narratives about bushmeat markets to yield situated insights for reducing risk at this interface.

Root Cause Analysis of Gaps in Non-communicable Disease Monitoring in a Sub-district Hospital, Tamil Nadu: A Quality Improvement Initiative.

Introduction Non-communicable diseases (NCDs) present a significant public health challenge globally, and India is deeply affected. With the largest population in the world, India struggles with a high burden of NCDs, encompassing cardiovascular diseases, diabetes, cancer, and chronic respiratory conditions. These ailments contribute substantially to morbidity and mortality, placing a strain on healthcare systems. Despite efforts through public health initiatives, NCD monitoring and management remain deficient, especially at grassroots levels. Methods At a sub-district hospital in Tamil Nadu, India, a quality improvement initiative targeted diabetes and hypertension, prevalent NCDs. Utilizing Fishbone analysis and process flow diagrams, we identified gaps in NCD monitoring. Employing the Plan-Do-Study-Act model and reorienting the patient flow, we enhanced NCD monitoring by optimizing patient health record maintenance within the hospital. Results Root cause analysis identified a lack of patient record protocols and patient loss of records as key hindrances in NCD monitoring. We revamped patient flow and implemented a robust record-keeping system, boosting access to patient health records. This initiative was embraced by healthcare providers, enhancing NCD management. Leveraging these records, we assessed control rates of diabetes and hypertension patients effectively. Conclusion The research underscores the importance of maintaining comprehensive patient health records in healthcare centers for enhancing NCD monitoring. These records serve as valuable tools for healthcare providers, aiding in the monitoring and treatment of patients with diabetes and hypertension. By leveraging these records, healthcare providers can achieve better disease control outcomes, thereby improving the overall management of NCDs.

Enhancing routine immunization efforts for older adults and frail individuals: Good practices during the SARS-CoV-2 pandemic in Italy

ABSTRACT Infectious diseases pose a significant burden on the general population, particularly older adults who are more susceptible to severe complications. Immunization plays a crucial role in preventing infections and securing a healthier aging, but actual vaccination rates among older adults and frail individuals (OAFs) remains far from recommended targets. This study aims to collect and share good practices implemented in several Italian local health districts during the SARS-CoV-2 pandemic to ease routine immunization for OAFs. A 28-items questionnaire has been developed to collect information on organization aspect of immunization services and local good practices implemented before and during the SARS-CoV-2 pandemic. Twelve Public Health managers representative of 9 Italian Regions were further interviewed between January and March 2021. Despite literature suggests several effective interventions to increase vaccine demand, improve vaccine access, and enhance healthcare providers’ performance, our survey highlighted substantial heterogeneity in their implementation at local level. Seven good local practices have been identified and described: mass vaccination centers; vaccination mobile units; drive-through vaccination; co-administration; tailored pathways; cooperation among providers involved in vaccination; digitization. Our survey pointed out valuable strategies for enhancing routine immunization for OAFs. Providers should combine effective interventions adequate to their specific context and share good practices.

Probabilistic modeling of COVID-19 events: Exploring new alpha generated family for enhanced analysis capabilities

This study explores a new family of distributions to enhance the analysis capabilities of COVID-19 events, providing valuable insights for informed decision-making and effective public health management. Accurate understanding and prediction of COVID-19 transmission patterns and their impacts are crucial in reducing the mortality rate, especially in proactive control and mitigation efforts. The proposed approach focuses on a best-fit probabilistic model that incorporates a comprehensive assessment of various statistical measures. Additionally, seven well-recognized classical point estimation methods are employed to identify the most suitable approach for assisting epidemiologists in their analysis. The study analyzes COVID-19 data from multiple countries, including the Netherlands, Mexico, the United Kingdom, China, Canada, Saudi Arabia, and Italy, considering different aspects such as mortality rates and the number of deaths. By evaluating the performance of the new alpha generated family of distributions in modeling COVID-19 events. This research contributes to the advancement of our understanding of the disease's probabilistic nature. The findings have practical implications, guiding the development of public health policies, resource allocation strategies, and intervention plans, ultimately facilitating more effective control and mitigation of COVID-19 outbreaks.

Developing a Materiality Matrix for a Health Institution

The third sector plays an important role in Brazilian society and, its essential characteristics such as promoting socio-environmental responsibility, developing social causes and, reducing inequality are in line with the fundaments of ESG (Environmental, Social, and Governance). The materiality matrix is considered one of the main ESG management tools, helping organizations identify, define, and communicate actions related to the most relevant topics for the institution and its stakeholders. The objective of this study is to develop a Materiality Matrix for a third-sector health institution based on the priority topics defined by the organization and its stakeholders, alongside the guidelines of GRI and SASB. The result identified that the most relevant topics were Information Security and Privacy, Expansion/Democratization of Access to Health Services, Support for Public Health Management, Quality of Care and Patient Satisfaction, Health and Safety of Employees, and Human and Professional Development. This article contributes to enhance the health institutions in driving their efforts in a strategic way, aligning their activities with the social and environmental agendas and, at same time, raise the awareness of on critical material topics/issues for their stakeholders’ expectations.

Modeling viral evolution: A novel SIRSVIDE framework with application to SARS-CoV-2 dynamics

Understanding evolutionary trends in emerging viruses, such as severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), is crucial for effective public health management and response. Nonetheless, extensive debates have arisen concerning viral evolutionary trends, particularly the interplay between transmissibility, pathogenicity, and immune escape. In this context, we have developed a novel computational model named SIRSVIDE (Susceptible-Infected-Recovered-Susceptible-Variation-Immune Decay-Immune Escape) to simulate the transmission and evolutionary dynamics of viral populations. Our simulation results indicate that under conditions of high mutation rates, elevated transmission rates, and larger susceptible host populations, viral populations exhibit prolonged increases in transmissibility and immune escape, accompanied by reductions in pathogenicity and noticeable short-term fluctuations. However, when the total susceptible population size and mutation rate decrease, substantial uncertainty in the evolutionary trends of viral populations becomes apparent. In summary, the SIRSVIDE model establishes a comprehensive framework for generating both short- and long-term viral epidemiological and evolutionary dynamics. The simulation outcomes align with existing evidence indicating that SARS-CoV-2 is undergoing selection for heightened transmissibility, decreased pathogenicity, and enhanced immune escape. Furthermore, the model sheds light on the possible evolutionary dynamics of other viruses.

Workplace Buoyancy and Servant Leadership as Catalysts for Sustainable Disaster Management: Mitigating Emotional Exhaustion in Disaster Response Teams

Amid global crises like natural disasters and climate change, the emotional well-being of disaster response workers (DRWs) is a key factor in sustainable public health and disaster management. The study highlights the issue of emotional exhaustion among DRWs, which can impact organizational effectiveness and the health and well-being of affected communities. The study examines the roles of servant leadership (SL) and workplace buoyancy (WB) in addressing these issues. Using data from 336 DRWs involved in the 2023 Kahramanmaraş earthquake, JD-R Theory is employed to study how these factors interact in high-demand scenarios. Analysis with the Smart PLS 4 program reveals that SL and WB play key roles in reducing emotional exhaustion (EE). Notably, WB partially mediates the relationship between SL and EE. These insights are vital for creating sustainable public health and disaster management strategies in times of growing conflicts and climate crises. By extending the JD-R Theory to encompass these elements, the study provides valuable suggestions for policymakers and managers to enhance the resilience and well-being of DRWs. The study deepens our understanding of public health challenges in disaster settings and highlights the need for integrated, sustainable responses to support those on the front lines of disaster relief efforts.