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Arthropod-borne arboviral diseases—including dengue, Zika, and chikungunya—place a substantial burden on the health of populations, globally. Dengue alone is endemic in more than 100 countries and causes more than 96 million symptomatic cases and approximately 40,000 deaths annually. The recent surge in arboviral disease outbreaks, coupled with the World Health Organization’s newly published vector control guidelines, accentuates the imperative to understand the dispersion of disease-carrying mosquitoes across diverse spatial and temporal scales. However, traditional surveillance mechanisms often fall short because of workforce limitations, logistical complexities, jurisdictional boundaries, and budgetary constraints, especially in low- and low-middle-income countries. In this article, we systematically report the design, implementation, and iterative enhancement of a groundbreaking school-based citizen science initiative for augmenting mosquito surveillance in the Solomon Islands. Key reflections encompass the initiative’s role in supporting routine government-led disease vector monitoring, sustainability through integration and fostering participant engagement, and the amalgamation of citizen-collected data with government surveillance activities. The article also discusses the impact of the citizen science initiative with regard to the Solomon Islands’ pursuit of the Sustainable Development Goals. Our findings underscore the potential of citizen science methods to support and extend public health surveillance activities and to serve as a community-engagement-for-behaviour-change tool in resource-constrained contexts.

Background: The impact of rapid urbanization taking place across the world is posing variegated challenges. Especially in terms of communicable disease, the risk is more concentrated in urban poor areas where basic amenities are inadequate. This systematic review synthesizes evidence on the effective community-based interventions (CBIs) aimed at preventing and controlling infectious diseases among the urban poor in low- and middle-income countries (LMICs). Methods: This systematic review was conducted following the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analysis) guidelines. A comprehensive search across five major databases was conducted to capture literature on CBIs published between 2011 and 2021. Scientific articles of any design that reported any type of CBIs effective in preventing and controlling infectious diseases (tuberculosis, diarrhea, typhoid, dengue, hepatitis B and C, influenza, and COVID-19) were included. Screening and selection of studies were done by two pairs of independent researchers using the predefined eligibility criteria. The risk of bias in included studies was assessed using the modified checklist outlined in the Cochrane Handbook for Systematic Reviews of Interventions and Effective Public Health Practice Project (EPHPP). Analysis of effective CBIs was guided by the conceptual framework for integrated CBIs for neglected tropical diseases (NTDs), and narrative synthesis was carried out. Geographical restrictions were limited to LMICs and papers published in English. Results: Out of 18,260 identified papers, 20 studies met the eligibility criteria and were included in this review. Community-based screening and socio-economic support, community-based vector control, behavior change communication, capacity building of the community health workers (CHWs), health education, and e- and m-health interventions were found as effective CBIs. Diversified CBIs were found to be effective for specific diseases, including tuberculosis (TB), diarrhea, dengue, influenza and ARI, and hepatitis B and C. Bundling of interventions were found to be effective against specific diseases. However, it was difficult to isolate the effectiveness of individual interventions within the bundle. The socio-cultural context was considered while designing and implementing these CBIs. Conclusion: The effectiveness of an intervention is inextricably linked to social context, stakeholder dimensions, and broader societal issues. System approach is recommended, emphasizing context-specific, multi-component interventions that address social determinants of health. Integrating these interventions with public health strategies and community involvement is crucial for sustainable outcomes. These findings can guide the design of future interventions for better prevention and control of communicable diseases in urban poor areas. Systematic review registration: PROSPERO CRD42021278689. [ABSTRACT FROM AUTHOR]

Africa's dual burden of rising incidence of infectious diseases and increasing prevalence of non-communicable diseases (NCDs), such as cardiovascular diseases and diabetes, demands innovative approaches to disease surveillance, response, and cross-border health management in response to growing economic integration and global connectivity. In this context, we propose a discursive framework for the development and implementation of a multi-disease digital health passport (MDDHP) in Africa. The MDDHP would serve as a secure platform for storing and sharing individual health data, offering a comprehensive solution to track and respond to infectious diseases, facilitate the management of NCDs, and improve healthcare access across borders. Empowering individuals to proactively manage their health and improve overall outcomes is a key aspect of the MDDHP. In the paper, we examine the key elements necessary to effectively implement MDDHP, focusing on minimizing risks, maintaining efficacy, and driving its adoption while also taking into consideration the unique contexts of the continent. The paper is intended to provide an understanding of the key principles involved and contribute to the discussion on the development and successful implementation of MDDHP in Africa. [ABSTRACT FROM AUTHOR]

This paper studies continuing optimal lockdowns (can also be interpreted as quarantines or self-isolation) in the long run if a disease (Covid-19) is endemic and immunity can fail, that is, the disease has SIRS dynamics. We model how disease related mortality affects the optimal choices in a dynamic general equilibrium neoclassical growth framework. An extended welfare function that incorporates loss from mortality is used. In a disease endemic steady state, without this welfare loss even if there is continuing mortality, it is not optimal to impose even a partial lockdown. We characterize how the optimal restriction and equilibrium outcomes vary with the effectiveness of the lockdown, the productivity of working from home, the rate of mortality from the disease, and failure of immunity. We provide the sufficiency conditions for economic models with SIRS dynamics with disease related mortality–a class of models which are non-convex and have endogenous discounting so that no existing results are applicable. [ABSTRACT FROM AUTHOR]

Laboratory automation effectively increases the throughput in sample analysis, reduces human errors in sample processing, as well as simplifies and accelerates the overall logistics. Automating diagnostic testing workflows in peripheral laboratories and also in near-patient settings -like hospitals, clinics and epidemic control checkpoints- is advantageous for the simultaneous processing of multiple samples to provide rapid results to patients, minimize the possibility of contamination or error during sample handling or transport, and increase efficiency. However, most automation platforms are expensive and are not easily adaptable to new protocols. Here, we address the need for a versatile, easy-to-use, rapid and reliable diagnostic testing workflow by combining open-source modular automation (Opentrons) and automation-compatible molecular biology protocols, easily adaptable to a workflow for infectious diseases diagnosis by detection on paper-based diagnostics. We demonstrated the feasibility of automation of the method with a low-cost Neisseria meningitidis diagnostic test that utilizes magnetic beads for pathogen DNA isolation, isothermal amplification, and detection on a paper-based microarray. In summary, we integrated open-source modular automation with adaptable molecular biology protocols, which was also faster and cheaper to perform in an automated than in a manual way. This enables a versatile diagnostic workflow for infectious diseases and we demonstrated this through a low-cost N. meningitidis test on paper-based microarrays. [ABSTRACT FROM AUTHOR]

Due to the increasingly severe challenges brought by various epidemic diseases, people urgently need intelligent outbreak trend prediction. Predicting disease onset is very important to assist decision-making. Most of the existing work fails to make full use of the temporal and spatial characteristics of epidemics, and also relies on multivariate data for prediction. In this paper, we propose a Multi-Scale Location Attention Graph Neural Networks (MSLAGNN) based on a large number of Centers for Disease Control and Prevention (CDC) patient electronic medical records research sequence source data sets. In order to understand the geography and timeliness of infectious diseases, specific neural networks are used to extract the geography and timeliness of infectious diseases. In the model framework, the features of different periods are extracted by a multi-scale convolution module. At the same time, the propagation effects between regions are simulated by graph convolution and attention mechanisms. We compare the proposed method with the most advanced statistical methods and deep learning models. Meanwhile, we conduct comparative experiments on data sets with different time lengths to observe the prediction performance of the model in the face of different degrees of data collection. We conduct extensive experiments on real-world epidemic-related data sets. The method has strong prediction performance and can be readily used for epidemic prediction. [ABSTRACT FROM AUTHOR]

Introduction: Chronic hepatitis B (CHB) is a significant public health issue worldwide, especially in the Middle East region. Around 8% to 20% of patients with CHB develop cirrhosis, which may progress to hepatocellular carcinoma. The significant morbidity and mortality associated with CHB denote the importance of high-quality treatment. Methods: We searched the PubMed, Medline, and Cochrane databases from inception to January 2024 to identify relevant studies. Search terms were generated using established treatment guidelines for CHB. We also manually searched the bibliographies of relevant literature to obtain additional papers. Results: In this narrative review, we evaluated the seven currently licensed antiviral therapies for chronic Hepatitis B treatment, including nucleos(t)ide analogs (NAs) and pegylated interferon-alpha (PEG-IFNα). NAs can be divided into two categories: high barrier to resistance and low barrier to resistance. Tenofovir disoproxil fumarate, tenofovir alafenamide, and entecavir are NAs with a high barrier to resistance. Telbivudine has shown promise in providing high efficacy with low viral resistance rates; however, it is not recommended because of insufficient evidence and lack of cost-effectiveness. Lamivudine and adefovir dipivoxil, despite being efficacious, have a low barrier to resistance, the primary reason they are no longer recommended. PEG-IFNα has high efficacy and can be completed in 48 weeks. It is not associated with resistance; however, it has been reported to have several systemic adverse effects. Conclusions: Current first-line NA treatments in the Middle East include entecavir, tenofovir disoproxil fumarate, and tenofovir alafenamide. These drugs are favored over other NAs because of their low rates of resistance. PEG-IFNα has superiority over NAs in inducing a more durable antiviral response and having a finite treatment duration. The main drawback of PEG-IFNα is an unfavorable safety profile. [ABSTRACT FROM AUTHOR]

Climate change is no longer a hypothetical problem in the Caribbean but a new reality to which regional public health systems must adapt. One of its significant impacts is the increased transmission of infectious diseases, such as dengue fever, which is endemic in the region, and the presence of the Aedes aegypti mosquito vector responsible for transmitting the disease. (1) Methods: To assess the association between climatic factors and human dengue virus infections in the Caribbean, we conducted a systematic review of published studies on MEDLINE and Web of Science databases according to Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) criteria. (2) Results: In total, 153 papers were identified, with 27 studies selected that met the inclusion criteria ranging from the northern and southern Caribbean. Rainfall/precipitation and vapor pressure had a strong positive association with dengue incidence, whereas the evidence for the impact of temperatures was mixed. (3) Conclusions: The interaction between climate and human dengue disease in the Caribbean is complex and influenced by multiple factors, including waste management, infrastructure risks, land use changes, and challenged public health systems. Thus, more detailed research is necessary to understand the complexity of dengue within the wider Caribbean and achieve better dengue disease management. [ABSTRACT FROM AUTHOR]

Background: Previously, many methods have been used to predict the incidence trends of infectious diseases. There are numerous methods for predicting the incidence trends of infectious diseases, and they have exhibited varying degrees of success. However, there are a lack of prediction benchmarks that integrate linear and nonlinear methods and effectively use internet data. The aim of this paper is to develop a prediction model of the incidence rate of infectious diseases that integrates multiple methods and multisource data, realizing ground-breaking research. Results: The infectious disease dataset is from an official release and includes four national and three regional datasets. The Baidu index platform provides internet data. We choose a single model (seasonal autoregressive integrated moving average (SARIMA), nonlinear autoregressive neural network (NAR), and long short-term memory (LSTM)) and a deep evolutionary fusion neural network (DEFNN). The DEFNN is built using the idea of neural evolution and fusion, and the DEFNN + is built using multisource data. We compare the model accuracy on reference group data and validate the model generalizability on external data. (1) The loss of SA-LSTM in the reference group dataset is 0.4919, which is significantly better than that of other single models. (2) The loss values of SA-LSTM on the national and regional external datasets are 0.9666, 1.2437, 0.2472, 0.7239, 1.4026, and 0.6868. (3) When multisource indices are added to the national dataset, the loss of the DEFNN + increases to 0.4212, 0.8218, 1.0331, and 0.8575. Conclusions: We propose an SA-LSTM optimization model with good accuracy and generalizability based on the concept of multiple methods and multiple data fusion. DEFNN enriches and supplements infectious disease prediction methodologies, can serve as a new benchmark for future infectious disease predictions and provides a reference for the prediction of the incidence rates of various infectious diseases. [ABSTRACT FROM AUTHOR]

Antimicrobial resistance poses a significant challenge to public health globally, leading to increased morbidity and mortality. AMR surveillance involves the systematic collection, analysis, and interpretation of data on the occurrence and distribution of AMR in humans, animals, and the environment for action. The West African Health Organization, part of the Economic Community of West African States (ECOWAS), is committed to addressing AMR in the region. This paper examines the status of AMR surveillance in ECOWAS countries using available WHO data from the TrACSS survey and GLASS enrollments. The analysis reveals that while progress has been made, significant challenges remain. Twelve of the fifteen ECOWAS countries are enrolled in GLASS, and ten have developed national action plans (NAPs) for AMR. However, there is a need to ensure all countries fully implement their NAPs, continue reporting to GLASS, and use the data for evidence-based actions and decision making. Surveillance systems for AMR and antimicrobial consumption/use vary across countries with some demonstrating limited capacity. All countries, except Cabo Verde, reported having a reference laboratory for AMR testing. Strengthening laboratory capabilities, data management and use, and multisectoral coordination are crucial for effective AMR surveillance and response. Based on the findings and the regional context, it is essential to prioritize capacity building, data utilization, and the adoption of standardized guidelines for AMR surveillance. Collaboration among ECOWAS countries, the WAHO, and international partners is essential to address AMR comprehensively. Ensuring a consistent supply of essential antimicrobial medications and reagents is vital. [ABSTRACT FROM AUTHOR]

Spreading quickly throughout populations, whether animal or human-borne, infectious illnesses provide serious risks and difficulties. Controlling their spread and averting disinformation requires effective risk assessment and epidemic identification. Technology-enabled data analysis on diseases allows for quick solutions to these problems. A Combinational Data Assessment Scheme intended to accelerate disease detection is presented in this paper. The suggested strategy avoids duplicate data replication by sharing data among edge devices. It uses indexed data gathering to improve early detection by using tree classifiers to discern between various kinds of information. Both data similarity and index measurements are considered throughout the data analysis stage to minimize assessment errors. Accurate risk detection and assessment based on information kind and sharing frequency are ensured by comparing non-linear accumulations with accurate shared edge data. The suggested system exhibits high accuracy, low mistakes, and decreased data repetition to improve overall effectiveness in illness detection and risk reduction. [ABSTRACT FROM AUTHOR]

Infectious diseases seriously threaten the lives of children. Timely and accurate detection of pathogenic microorganisms and targeted medication are the keys to the diagnosing and treatment of infectious diseases in children. The next-generation metagenomic sequencing technology has attracted great attention in infectious diseases because of its characteristics such as no culture, high throughput, short detection cycle, wide coverage, and a good application prospect. In this paper, we review the studies of metagenomic next-generation sequencing in pediatric infectious diseases and analyze the challenges of its application in pediatric diseases. [ABSTRACT FROM AUTHOR]

This paper study was designed to establish solutions for mixed functional fractional integral equations that involve the Riemann-Liouville fractional operator and the Erd'elyi-Kober fractional operator to describe biological population dynamics in Banach space. The results rely on the measure of non-compactness and theoretical concepts from fractional calculus. Darbo's fixed-point theorem for Banach spaces has been utilized. Moreover, the solvability of a specific non-linear integral equation that models the spread of infectious diseases with a seasonally varying periodic contraction rate has been explored by using the Banach contraction principle. Finally, two numerical examples demonstrate the practical application of these findings in the realm of fractional integral equation theory. [ABSTRACT FROM AUTHOR]

Background Myocarditis is challenging to diagnose due to its varied presentations. Endomyocardial biopsy is the gold standard for diagnosis, but its invasive nature has led to alternative non-invasive modalities, notably cardiovascular magnetic resonance (CMR). Identifying the precise aetiology of myocarditis is crucial for effective treatment, yet extra-cardiac causes are often overlooked. In this paper, we spotlight the underexplored role of CMR in diagnosing extra-cardiac aetiologies, utilizing three insightful cases for illustration. Case summary The first case is a 31-year-old patient with myocarditis secondary to a pyogenic liver abscess, identified through CMR, who improved after abscess drainage. The second case involves a 54-year-old patient with myocarditis attributed to adult T-cell leukaemia–lymphoma, with the loco-regional thickening process identified thanks to CMR. This patient had an unfavourable disease progression due to the underlying malignancy. The third case concerns a 23-year-old patient suffering from myocarditis associated with pneumonia, again illustrated effectively through CMR imaging, who recovered after antibiotic treatment. Discussion These cases underline the overlooked potential of CMR in diagnosing extra-cardiac aetiologies of myocarditis, even though such causes are rare. Despite current guidelines recognizing the importance of identifying the aetiology of myocarditis, they do not explicitly address the role of CMR in diagnosing extra-cardiac aetiologies. This article, therefore, proposes that future guidelines could emphasize the utility of CMR in exploring these causes, potentially leading to more accurate diagnoses and improved patient outcomes. It also advocates for a comprehensive, multidisciplinary approach to myocarditis diagnosis, encouraging vigilance for potential loco-regional causes, and calls for further research in this area. [ABSTRACT FROM AUTHOR]

Engagement is an important component in the advancement of gene-drive vector control research programs as developers look to transition the technology from the laboratory to the field. As research advances and engagement surrounding this novel technology is put into practice, knowledge can be gained from practical experiences and applications in the field. A relationship-based model (RBM) provides a framework for end-user development of engagement programs and strategies. The model places end users at the center of the engagement decision-making processes rather than as recipients of predetermined strategies, methods, and definitions. Successful RBM application for healthcare delivery has previously been demonstrated, and the University of California Malaria Initiative (UCMI) has applied this model to its gene-drive program in the Democratic Republic of São Tomé and Príncipe. The model emphasizes the importance of local leadership in the planning, development, and implementation of all phases of project engagement. The primary aim of this paper is to translate the model from paper to practice and provide a transparent description, using practical examples, of the UCMI program implementation of RBM at its field site. End-user development of the UCMI engagement program provides a unique approach to the development of ethical, transparent, and effective engagement strategies for malaria control programs. This paper may also serve as a reference and example for projects looking to establish an engagement program model that integrates end-user groups in the decision-making processes surrounding engagement.

The rapid development of vaccines is a crucial objective in modern biotechnology and molecular pharmacology. In this context, conducting research to expedite the selection of a potent immunogen is imperative. The candidate vaccine should induce the production of antibodies that can recognize the immunogenic epitopes of the target protein, resembling the ones found in recovered patients. One major challenge in vaccine development is the absence of straightforward and reliable techniques to determine the extent to which the spectrum of antibodies produced after vaccination corresponds to antibodies found after recovery. This paper describes a newly developed method to detect antibodies specific to immunogenic epitopes of the target protein in blood plasma and to compare them with antibody spectra generated post vaccination. Comparing the antibody pool generated in the human body after recovering from an infectious disease with the pool formed through vaccination can become a universal method for screening candidate vaccines. This method will enable the identification of candidate vaccines that can induce the production of antibodies similar to those generated in response to a natural infection. Implementing this approach will facilitate the rapid development of new vaccines, even when faced with a pandemic. [ABSTRACT FROM AUTHOR]

Health emergencies caused by epidemic-prone pathogens (EPPs) have increased exponentially in recent decades. Although vaccines have proven beneficial, they are unavailable for many pathogens. Furthermore, achieving timely and equitable access to vaccines against EPPs is not trivial. It requires decision-makers to capture numerous interrelated factors across temporal and spatial scales, with significant uncertainties, variability, delays, and feedback loops that give rise to dynamic and unexpected behavior. Therefore, despite progress in filling R&D gaps, the path to licensure and the long-term viability of vaccines against EPPs continues to be unclear. This paper presents a quantitative system dynamics modeling framework to evaluate the long-term sustainability of vaccine supply under different vaccination strategies. Data from both literature and 50 expert interviews are used to model the supply and demand of a prototypical Ebolavirus Zaire (EBOV) vaccine. Specifically, the case study evaluates dynamics associated with proactive vaccination ahead of an outbreak of similar magnitude as the 2018–2020 epidemic in North Kivu, Democratic Republic of the Congo. The scenarios presented demonstrate how uncertainties (e.g., duration of vaccine-induced protection) and design criteria (e.g., priority geographies and groups, target coverage, frequency of boosters) lead to important tradeoffs across policy aims, public health outcomes, and feasibility (e.g., technical, operational, financial). With sufficient context and data, the framework provides a foundation to apply the model to a broad range of additional geographies and priority pathogens. Furthermore, the ability to identify leverage points for long-term preparedness offers directions for further research. [ABSTRACT FROM AUTHOR]

In 2023, Katalin Karikó and Drew Weissman were awarded the Nobel Prize in Physiology or Medicine for their nucleoside base modifications research that later enabled mRNA vaccine development against COVID-19. This paper briefly reviews these achievements in the context of the development of mRNA technology and its enormous potential for medicine in the prevention of various infectious diseases and cancer treatment, including personalised therapies. It is beyond any doubt that discoveries made by Karikó and Weissman were pivotal in overcoming one of the major hurdles in the practical application of mRNA molecules, i.e., the recognition of exogenous mRNAs by endosomal Toll-like receptors and downstream innate immune response, ultimately leading to the decreased translational activity of delivered mRNA and its degradation. Although the Nobel Prize for Karikó and Weissman is fully justified, it must be stressed that mRNA technology would never unfold its potential for public health without a collective scientific effort encompassing over 40 years of research. [ABSTRACT FROM AUTHOR]

Abstract Background The impact of rapid urbanization taking place across the world is posing variegated challenges. Especially in terms of communicable disease, the risk is more concentrated in urban poor areas where basic amenities are inadequate. This systematic review synthesizes evidence on the effective community-based interventions (CBIs) aimed at preventing and controlling infectious diseases among the urban poor in low- and middle-income countries (LMICs). Methods This systematic review was conducted following the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analysis) guidelines. A comprehensive search across five major databases was conducted to capture literature on CBIs published between 2011 and 2021. Scientific articles of any design that reported any type of CBIs effective in preventing and controlling infectious diseases (tuberculosis, diarrhea, typhoid, dengue, hepatitis B and C, influenza, and COVID-19) were included. Screening and selection of studies were done by two pairs of independent researchers using the predefined eligibility criteria. The risk of bias in included studies was assessed using the modified checklist outlined in the Cochrane Handbook for Systematic Reviews of Interventions and Effective Public Health Practice Project (EPHPP). Analysis of effective CBIs was guided by the conceptual framework for integrated CBIs for neglected tropical diseases (NTDs), and narrative synthesis was carried out. Geographical restrictions were limited to LMICs and papers published in English. Results Out of 18,260 identified papers, 20 studies met the eligibility criteria and were included in this review. Community-based screening and socio-economic support, community-based vector control, behavior change communication, capacity building of the community health workers (CHWs), health education, and e- and m-health interventions were found as effective CBIs. Diversified CBIs were found to be effective for specific diseases, including tuberculosis (TB), diarrhea, dengue, influenza and ARI, and hepatitis B and C. Bundling of interventions were found to be effective against specific diseases. However, it was difficult to isolate the effectiveness of individual interventions within the bundle. The socio-cultural context was considered while designing and implementing these CBIs. Conclusion The effectiveness of an intervention is inextricably linked to social context, stakeholder dimensions, and broader societal issues. System approach is recommended, emphasizing context-specific, multi-component interventions that address social determinants of health. Integrating these interventions with public health strategies and community involvement is crucial for sustainable outcomes. These findings can guide the design of future interventions for better prevention and control of communicable diseases in urban poor areas. Systematic review registration PROSPERO CRD42021278689.

Abstract Africa’s dual burden of rising incidence of infectious diseases and increasing prevalence of non-communicable diseases (NCDs), such as cardiovascular diseases and diabetes, demands innovative approaches to disease surveillance, response, and cross-border health management in response to growing economic integration and global connectivity. In this context, we propose a discursive framework for the development and implementation of a multi-disease digital health passport (MDDHP) in Africa. The MDDHP would serve as a secure platform for storing and sharing individual health data, offering a comprehensive solution to track and respond to infectious diseases, facilitate the management of NCDs, and improve healthcare access across borders. Empowering individuals to proactively manage their health and improve overall outcomes is a key aspect of the MDDHP. In the paper, we examine the key elements necessary to effectively implement MDDHP, focusing on minimizing risks, maintaining efficacy, and driving its adoption while also taking into consideration the unique contexts of the continent. The paper is intended to provide an understanding of the key principles involved and contribute to the discussion on the development and successful implementation of MDDHP in Africa.

Climate change can affect the frequency and intensity of infectious diseases worldwide, which may further aggravate disparities in the health and disease burden. Apart from the known risk factors, the concurrent COVID-19 pandemic exposed a range of social vulnerabilities that influenced its local impacts and responses. Even though global policies consider various local vulnerabilities, the literature notes an increasing need to address their intertwined spatial implications. This paper offers a review of studies focusing on infectious diseases to understand regional variations in vulnerability and policy implications. By using the scoping review method it compares the trends of regional vulnerability in literature with the ones observed during COVID-19 along with the recent regional reports addressing issues of climate change and health for their policy implications. It finds that due to the overarching nature of global policies, various aspects of regional vulnerability remain unaddressed, and many important regional observations do not find their way to inform global policies. The paper thus argues that considering variations in regional vulnerability in global policies and developing regional guidelines could contribute to an integrated response and effective management of global hazards concerning climate change and health.

• The Orchard Sports Injury and Illness Classification System (OSIICS) is 1 of 2 sports injury classification systems recognized by the International Olympic Committee and needs regular update. • It was previously focused on injuries rather than common illness/medical condition presentations in athletes, so the most recent updates have extended medical presentation diagnoses. • Version 15 includes expansion of available diagnoses in the fields of mental health, sports concussion, sports cardiology, sports dermatology, sports ophthalmology, and infectious diseases. • The OSIICS has been previously translated into Italian, Spanish, and Catalan, and further translation into multiple other languages is planned. Sports medicine (injury and illnesses) requires distinct coding systems because the International Classification of Diseases is insufficient for sports medicine coding. The Orchard Sports Injury and Illness Classification System (OSIICS) is one of two sports medicine coding systems recommended by the International Olympic Committee. Regular updates of coding systems are required. For Version 15, updates for mental health conditions in athletes, sports cardiology, concussion sub-types, infectious diseases, and skin and eye conditions were considered particularly important. Recommended codes were added from a recent International Olympic Committee consensus statement on mental health conditions in athletes. Two landmark sports cardiology papers were used to update a more comprehensive list of sports cardiology codes. Rugby union protocols on head injury assessment were used to create additional concussion codes. It is planned that OSIICS Version 15 will be translated into multiple new languages in a timely fashion to facilitate international accessibility. The large number of recently published sport-specific and discipline-specific consensus statements on athlete surveillance warrant regular updating of OSIICS. [Display omitted] [ABSTRACT FROM AUTHOR]

Mpox is a viral disease caused by the monkey pox virus (MPXV) of the Poxviridae family. It is similar to smallpox and cowpox. Mpox is not categorized as a sexually transmitted infection, however, most transmission in the recent global outbreak has been attributed to be through men who have sex with men (MSM). Agent-based modelling (ABM) is an effective approach to simulate the spread of Mpox because it enables the detailed representation of heterogeneity among individuals or sub-populations, including variations in behaviour, susceptibility to disease, and contact patterns. This is crucial for accurately modelling diseases in populations with long tailed distributions of characteristics such as sexual activity, that has been seen in the recent Mpox outbreak. Two ABMs are presented in this paper which simulate the spread of Mpox in an artificial population. The parameters for contact formation and dissolution are drawn from the NATSAL-3 dataset (National Survey of Sexual Attitudes and Lifestyles) (Mercer et al. 2013). The presented ABMs are based on the principles of the classic compartmental Susceptible-Exposed-Infected-Recovered (SEIR) model and complexity is further added to break the assumptions of homogeneous mixing and populations. The first ABM is based on an heterogeneous population, consisting of people from two self-identified genders (male and female) and three sexual preferences: homosexual, bi-sexual and heterosexual. The second ABM is a subset of the first ABM, that focuses on the MSM population, which is considered to be at high-risk of Mpox. We report a set of experiments modelling relevant scenarios by number of imported cases, number of super-spreader events, and different vaccination strategies. Our analysis concludes that Mpox infection reaches locally stable disease-free equilibrium in the absence of concurrent partnerships. Our simulations demonstrate that prioritizing vaccines for the MSM population can significantly reduce the effective R value from 1.62 to 0.19, highlighting the potential impact of targeted vaccination strategies in mitigating Mpox transmission. [ABSTRACT FROM AUTHOR]

In this opinion paper, the author reflects on a transformative experience attending an antimicrobial stewardship workshop that shifted their perception of the looming crisis of antimicrobial resistance. The author emphasises the critical need for greater awareness and education at all levels of society, from healthcare professionals to the general population, to truly comprehend the severity of this issue. Drawing parallels between antimicrobial resistance and more recognised threats such as cancer, the author advocates for a multidisciplinary approach and heightened emphasis on education to foster responsible antimicrobial use. They propose practical strategies, including integrating stewardship principles into medical education and advocating for preventive measures such as vaccination. Ultimately, this paper urges individuals to embrace their roles as stewards of antimicrobials and to seize the opportunity to effect change for the betterment of humanity. Contribution: This opinion paper emphasises the urgent need for greater awareness and education on antimicrobial stewardship. It underscores the importance of multidisciplinary collaboration and proposes practical strategies, particularly in healthcare education. These insights align with the journal’s scope of advancing healthcare education, policy, and addressing global health challenges regarding infectious diseases.

The global population influx during the COVID-19 pandemic poses significant challenges to public health, making the prevention and control of infectious diseases a pressing concern. This paper aims to examine the impact of population influx on the spread of infectious diseases, with a specific emphasis on the mediating role of air pollution in this process. A theoretical analysis is conducted to explore the relationship between population influx, air pollution, and infectious diseases. Additionally, we establish a series of econometric models and employ various empirical tests and analytical techniques, including mediation effect test, threshold effect test, and systematic GMM test, to evaluate our hypotheses. The results indicate that: (1) Population influx directly and indirectly impacts infectious diseases. Specifically, population influx not only directly elevates the risk of infectious diseases, but also indirectly increases the incidence rate of infectious diseases by intensifying air pollution. (2) The impact of population inflow on infectious diseases exhibits regional heterogeneity. Compared to central and western China, the eastern regions exhibit a significantly higher risk of infectious diseases, exceeding the national average. (3) External factors influence the relationship between population influx and infectious diseases differently. Personal income and medical resources both help mitigate the risk of infectious diseases due to population influx, with medical resources having a more substantial effect. Contrary to expectations, abundant educational resources have not reduced the risk, instead, they have exacerbated the risk associated with population influx. This paper provides a scientific basis for formulating effective strategies for the prevention and control of infectious diseases.

Infectious diseases and armed conflicts represent two separate global security threats that endanger entire world population. The problem is that they are most often observed and analysed completely separately, without determining their interconnectedness and the way in which one threat influences the other. Hence, the subject of this paper is the analysis of their correlation, particularly one aspect of that relation that being the determination of the way in which armed conflicts influence the spread of infectious diseases. The paper is based on the assumption that the influence of armed conflicts on the spread of infectious diseases has decreased over the time. The question is whether armed conflicts used to be or still are the main catalyst for the spread of infectious diseases. Examination of literature yielded a conclusion that over the time, concurrently with ever greater interdependence of different parts of the world, the influence of armed conflicts on the spread of infectious diseases decreased. Unlike previous periods, when armed conflicts used to be major catalysts for the spread of these diseases, in 21st century, their influence has not disappeared, but it has been marginalised to a great degree. Thus the gradual process of globalisation has contributed to ever more frequent and intensive movement of people worldwide, which is favourable for fast and easy spreading of infectious diseases, drastically reducing the influence of armed conflicts on their spreading.

Laboratory automation effectively increases the throughput in sample analysis, reduces human errors in sample processing, as well as simplifies and accelerates the overall logistics. Automating diagnostic testing workflows in peripheral laboratories and also in near-patient settings -like hospitals, clinics and epidemic control checkpoints- is advantageous for the simultaneous processing of multiple samples to provide rapid results to patients, minimize the possibility of contamination or error during sample handling or transport, and increase efficiency. However, most automation platforms are expensive and are not easily adaptable to new protocols. Here, we address the need for a versatile, easy-to-use, rapid and reliable diagnostic testing workflow by combining open-source modular automation (Opentrons) and automation-compatible molecular biology protocols, easily adaptable to a workflow for infectious diseases diagnosis by detection on paper-based diagnostics. We demonstrated the feasibility of automation of the method with a low-cost Neisseria meningitidis diagnostic test that utilizes magnetic beads for pathogen DNA isolation, isothermal amplification, and detection on a paper-based microarray. In summary, we integrated open-source modular automation with adaptable molecular biology protocols, which was also faster and cheaper to perform in an automated than in a manual way. This enables a versatile diagnostic workflow for infectious diseases and we demonstrated this through a low-cost N. meningitidis test on paper-based microarrays.

BackgroundDespite the elevated risks of infection transmission, people in prisons frequently encounter significant barriers in accessing essential healthcare services in many countries. The present scoping review aimed to evaluate the state of availability and model of delivery of vaccination services within correctional facilities across the globe.MethodsFollowing the methodological framework for scoping reviews and adhering to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) extension for scoping reviews criteria, we conducted a systematic search across four peer-reviewed literature databases (Medline via PubMed, Web of Science, the Cochrane Library, Science Direct, and EBSCO), as well as 14 sources of grey literature. Two researchers meticulously examined the identified papers independently to extract pertinent data published between 2012 and 2022. The quality of the selected publications was assessed using established quality assessment tools.ResultsOf the 11,281 identified papers 52 met the inclusion criteria. With the exception of one, all the included publications presented data from high-income countries, predominantly originating from the United States. Across the world, the most prevalent vaccines available in prison settings were COVID-19 and HBV vaccines, typically distributed in response to health crises such as pandemics, epidemics, and local outbreaks. Vaccine coverage and uptake rates within correctional facilities displayed noteworthy disparities among various countries and regions. Besides, individual and organizational barriers and facilitating factors of vaccination in prison settings emerged and discussed in the text.DiscussionThe lack of vaccination services combined with low rates of vaccination coverage and uptake among people living and working in correctional facilities represents a cause for concern. Prisons are not isolated from the broader community, therefore, efforts to increase vaccine uptake among people who live and work in prisons will yield broader public health benefits.

Innate lymphoid cells (ILCs) are the main resident lymphocytes that mostly reside in tissues owing to the lack of adaptive antigen receptors. These cells are involved in early anti-infective immunity, antitumour immunity, regulation of tissue inflammation, and maintenance of homeostasis in the internal environment of tissues and have been referred to as the “first armies stationed in the human body”. ILCs are widely distributed in the lungs, colon, lymph nodes, oral mucosa and even embryonic tissues. Due to the advantage of their distribution location, they are often among the first cells to come into contact with pathogens.Relevant studies have demonstrated that ILCs play an early role in the defence against a variety of pathogenic microorganisms, including bacteria, viruses, fungi and helminths, before they intervene in the adaptive immune system. ILCs can initiate a rapid, nonspecific response against pathogens prior to the initiation of an adaptive immune response and can generate a protective immune response against specific pathogens, secreting different effectors to play a role.There is growing evidence that ILCs play an important role in host control of infectious diseases. In this paper, we summarize and discuss the current known infectious diseases in which ILCs are involved and ILC contribution to the defence against infectious diseases. Further insights into the mechanisms of ILCs action in different infectious diseases will be useful in facilitating the development of therapeutic strategies for early control of infections. [ABSTRACT FROM AUTHOR]

[Display omitted] • Developing a multi-physics computational framework for fomite disinfection. • It includes atomization, spray-air interaction, impingement, and disinfection. • Detailed validation studies against two sets of experimental data are performed. • The framework demonstrates mere 2.73% and 2.38% deviations from measured data. Disinfecting inanimate objects or materials carrying infectious agents, i.e., fomites, using spray systems reduces healthcare-associated infections in medical settings and community-acquired infections in non-medical environments. However, an accurate prediction of such systems is challenging as these systems embrace multi-physics phenomena depending on several parameters. Therefore, this paper presents a computational modeling-based multi-physics framework to evaluate the performance and effectiveness of spray systems employed in disinfecting fomites with non-porous hydrophilic surfaces. The framework includes four key phases: (i) atomizing the liquid disinfectant jet into the disinfectant droplets; (ii) interactions between disinfectant droplets and the surrounding air; (iii) impingements created by the disinfectant droplets on the fomite surface; (iv) interactions between the disinfectant depositions and pathogens causing fomite disinfection. The accuracy of the framework is evaluated using two sets of experimental data on the reduction of viable Bacillus atrophaeus spores over an 1800-second period. The results show that the framework can predict fomite disinfection via spray systems, with the deviations from the measured data being 2.73% and 2.38%. By presenting a detailed perception of the dynamics involved in fomite disinfection, this framework has the potential to improve public health practices and lead to the development of more effective and targeted disinfection strategies in diverse settings. [ABSTRACT FROM AUTHOR]

IntroductionIn 2015, the National Institute of Dental and Craniofacial Research (NIDCR) launched the Multidisciplinary Collaborative Research Consortium to Reduce Oral Health Disparities in Children, supporting four randomized trials testing strategies to improve preventive care. A Coordinating Center provides scientific expertise, data acquisition and quality assurance services, safety monitoring, and final analysis-ready datasets. This paper describes the trials' economic analysis strategies, placing these strategies within the broader context of contemporary economic analysis methods.MethodsThe Coordinating Center established a Cost Collaborative Working Group to share information from the four trials about the components of their economic analyses. Study teams indicated data sources for their economic analysis using a set of structured tables. The Group meets regularly to share progress, discuss challenges, and coordinate analytic approaches.ResultsAll four trials will calculate incremental cost-effectiveness ratios; two will also conduct cost-utility analyses using proxy diseases to estimate health state utilities. Each trial will consider at least two perspectives. Key process measures include dental services provided to child participants. The non-preference-weighted Early Childhood Oral Health Impact Scale (ECOHIS) will measure oral health-related quality of life. All trials are measuring training, implementation, personnel and supervision, service, supplies, and equipment costs.ConclusionsConsistent with best practices, all four trials have integrated economic analysis during their planning stages. This effort is critical since poor quality or absence of essential data can limit retrospective analysis. Integrating economic analysis into oral health preventive intervention research can provide guidance to clinicians and practices, payers, and policymakers.

BackgroundVaccine hesitancy, delaying or refusing to vaccinate despite the availability of vaccines, impedes the progress of achieving optimal HPV vaccine coverage. Little is known about the sources of human papillomavirus (HPV) vaccine hesitancy among racially/ethnically and geographically diverse communities. The purpose of this paper is to explore HPV vaccine hesitancy among rural, Slavic, and Latino communities that reside in counties with low HPV vaccine uptake rates.MethodsKey informant interviews and focus groups were conducted with rural, Slavic, and Latino communities that reside within counties in California that have low HPV vaccine up to date rates (16-25%). Qualitative data were transcribed verbatim and analyzed using inductive and deductive thematic analysis.ResultsA total of seven focus groups and 14 key informant interviews were conducted with 39 individuals from seven California counties. Salient themes that contributed to HPV vaccine hesitancy included the following: social media and the anti-vaccination movement; a strong belief in acquiring immunity naturally; prior vaccine experiences; and vaccine timing concerns. Participants suggested the provision of culturally appropriate, in-language, in-person easy to understand HPV vaccine education to mitigate HPV vaccine hesitancy.ConclusionsOur findings can inform future interventions to increase HPV vaccine uptake among hesitant communities.

BackgroundHIV or sexually transmitted infections remain a significant public health concern in the United States, with adolescents affected disproportionately. Adolescents engage in HIV/STI risk behaviors, including drug use and condomless sex, which increase the risk for HIV/STIs. At-risk adolescents, many of whom are racial minorities, experience HIV/STI disparities. Although at-risk adolescents are disproportionately affected by HIV/STI risk behaviors and infections and although the Centers for Disease Control and Prevention recommends routine HIV/STI testing for adolescents, relatively few adolescents report having ever been tested for HIV/STI. With expected increases in health clinic visits as a result of the Affordable Care Act combined with technological advances, health clinics and mobile health (mHealth), including apps, provide innovative contexts and tools to engage at-risk adolescents in HIV/STI prevention programs. Yet, there is a dearth of efficacious mHealth interventions in health clinics to prevent and reduce both condomless sex and drug use and increase HIV/STI testing for at-risk adolescents.ObjectiveTo address this gap in knowledge, we developed a theory-driven, culturally congruent mHealth intervention (hereon referred to as S4E [Storytelling 4 Empowerment]) that has demonstrated feasibility and acceptability in a clinical setting. The next step is to examine the preliminary efficacy of S4E on adolescent HIV/STI testing and risk behaviors. This goal will be accomplished by 2 aims: the first aim is to develop a cross-platform and universal version of S4E. The cross-platform and universal version of S4E will be compatible with both iOS and Android operating systems and multiple mobile devices, aimed at providing adolescents with ongoing access to the intervention once they leave the clinic, and the second aim is to evaluate the preliminary efficacy of S4E, relative to usual care control condition, in preventing or reducing drug use and condomless sex and increasing HIV/STI testing in a clinical sample of at-risk adolescents aged 14-21 years living in Southeast Michigan.MethodsIn this study, 100 adolescents recruited from a youth-centered community health clinic will be randomized via blocked randomization with random sequences of block sizes to one of the 2 conditions: S4E mHealth intervention or usual care. Theory-driven and culturally congruent, S4E is an mHealth adaptation of face-to-face storytelling for empowerment, which is registered with the Substance Abuse and Mental Health Services Administration's National Registry of Evidence-Based Programs and Practices.ResultsThis paper describes the protocol of our study. The recruitment began on May 1, 2018. This study was registered on December 11, 2017, in ClinicalTrials.gov. All participants have been recruited. Data analysis will be complete by the end of March 2024, with study findings available by December 2024.ConclusionsThis study has the potential to improve public health by preventing HIV/STI and substance use disorders.Trial registrationClinicalTrials.gov NCT03368456; https://clinicaltrials.gov/study/NCT03368456.International registered report identifier (irrid)DERR1-10.2196/47216.

ObjectivesSurveys can assist in screening oral diseases in populations to enhance the early detection of disease and intervention strategies for children in need. This paper aims to develop short forms of child-report and proxy-report survey screening instruments for active dental caries and urgent treatment needs in school-age children.MethodsThis cross-sectional study recruited 497 distinct dyads of children aged 8-17 and their parents between 2015 to 2019 from 14 dental clinics and private practices in Los Angeles County. We evaluated responses to 88 child-reported and 64 proxy-reported oral health questions to select and calibrate short forms using Item Response Theory. Seven classical Machine Learning algorithms were employed to predict children's active caries and urgent treatment needs using the short forms together with family demographic variables. The candidate algorithms include CatBoost, Logistic Regression, K-Nearest Neighbors (KNN), Naïve Bayes, Neural Network, Random Forest, and Support Vector Machine. Predictive performance was assessed using repeated 5-fold nested cross-validations.ResultsWe developed and calibrated four ten-item short forms. Naïve Bayes outperformed other algorithms with the highest median of cross-validated area under the ROC curve. The means of best testing sensitivities and specificities using both child-reported and proxy-reported responses were 0.84 and 0.30 for active caries, and 0.81 and 0.31 for urgent treatment needs respectively. Models incorporating both response types showed a slightly higher predictive accuracy than those relying on either child-reported or proxy-reported responses.ConclusionsThe combination of Item Response Theory and Machine Learning algorithms yielded potentially useful screening instruments for both active caries and urgent treatment needs of children. The survey screening approach is relatively cost-effective and convenient when dealing with oral health assessment in large populations. Future studies are needed to further leverage the customize and refine the instruments based on the estimated item characteristics for specific subgroups of the populations to enhance predictive accuracy.

Prisons, due to various risk factors, are environments that are conducive to infectious disease transmission, with significantly higher prevalence of infectious diseases within prisons compared to the general population. This underscores the importance of preventive measures, particularly vaccination. As part of the international project "Reaching the hard-to-reach: Increasing access and vaccine uptake among the prison population in Europe" (RISE-Vac), this study aimed to map the availability and delivery framework of vaccination services in prisons across Europe and beyond. A questionnaire designed to collect data on the availability and delivery model of vaccination services in prisons was validated and uploaded in SurveyMonkey in July 2023. Then, it was submitted to potential participants, with at least one representative from each European country. Potential participants emailed an invitation letter by the RISE-Vac partners and by the European Organization of Prison and Correctional Services (EUROPRIS). Twenty European countries responded. Vaccines are available in European countries, although their availability differs by country and type of vaccine. The first dose is offered to people living in prisons (PLP), mostly within one month, COVID-19 is the most widely offered vaccine. In all countries, vaccines are actively offered by healthcare workers; in most countries, there is no evaluation of vaccination status among people who work in prison. The survey shows variance in vaccine availability for PLP and staff across countries and vaccine types. Quality healthcare in prisons is not only a matter of the right to health but also a critical public health investment: enhancing vaccine uptake consistently among PLP and staff should be prioritized. [ABSTRACT FROM AUTHOR]

West Nile virus (WNV) is a globally widespread arthropod‐borne virus that poses a significant public health concern. Mosquitoes transmit the virus in an enzootic cycle among birds, which act as reservoirs. Climate plays a crucial role in these outbreaks as mosquitoes are highly influenced by climatic conditions, and bird migrations are also affected by weather patterns. Consequently, changes in climate can potentially impact the occurrence of WNV outbreaks. We used biogeographic modelling based on machine learning algorithms and fuzzy logic to analyse and evaluate separately the risk of WNV outbreaks in two different biogeographic regions, the Afrotropical and the Western Palaearctic region. By employing fuzzy logic tools, we constructed a comprehensive risk model that integrates the Afro‐Palaearctic system as a unified operational unit for WNV spread. This innovative approach recognizes the Afro‐Palaearctic region as a pathogeographic system, characterized by biannual connections facilitated by billions of migratory bird reservoirs carrying the disease. Subsequently, we forecasted the effects of different climate change scenarios on the spread of WNV in the Afro‐Palaearctic system for the years 2040 and 2070. Our findings revealed an increasing epidemic and epizootic risk south of the Sahara. However, the area where an upsurge in risk was forecasted the most lies within Europe, with the anticipation of risk expansion into regions presently situated beyond the virus' distribution range, including central and northern Europe. Gaining insight into the risk within the Afro‐Palaearctic system is crucial for establishing coordinated and international One Health surveillance efforts. This becomes particularly relevant in the face of ongoing climate change, which disrupts the ecological equilibrium among vectors, reservoirs, and human populations. We show that the application of biogeographical tools to assess risk of infectious disease, i.e. pathogeography, is a promising approach for understanding distribution patterns of zoonotic diseases and for anticipating their future spread. [ABSTRACT FROM AUTHOR]

Background: The COVID-19 pandemic underlined the need for pandemic planning but also brought into focus the use of mathematical modelling to support public health decisions. The types of models needed (compartment, agent-based, importation) are described. Best practices regarding biological realism (including the need for multidisciplinary expert advisors to modellers), model complexity, consideration of uncertainty and communications to decisionmakers and the public are outlined. Methods: A narrative review was developed from the experiences of COVID-19 by members of the Public Health Agency of Canada External Modelling Network for Infectious Diseases (PHAC EMN-ID), a national community of practice on mathematical modelling of infectious diseases for public health. Results: Modelling can best support pandemic preparedness in two ways: 1) by modelling to support decisions on resource needs for likely future pandemics by estimating numbers of infections, hospitalized cases and cases needing intensive care, associated with epidemics of "hypothetical-yet-plausible" pandemic pathogens in Canada; and 2) by having ready-to-go modelling methods that can be readily adapted to the features of an emerging pandemic pathogen and used for long-range forecasting of the epidemic in Canada, as well as to explore scenarios to support public health decisions on the use of interventions. Conclusion: There is a need for modelling expertise within public health organizations in Canada, linked to modellers in academia in a community of practice, within which relationships built outside of times of crisis can be applied to enhance modelling during public health emergencies. Key challenges to modelling for pandemic preparedness include the availability of linked public health, hospital and genomic data in Canada. [ABSTRACT FROM AUTHOR]

In this article, we point out that luggage disinfection is a key step in stopping the spread of infectious diseases that can be contracted at airports due to viruses and bacteria, which can spread through passenger luggage at airports. To prevent the spread of respiratory infections at airports, in this research study, we compare two types of baggage disinfection system. The first method uses UV light to disinfect luggage while selectively checking it for the presence of bacteria and viruses. The second system uses non-selective disinfection, taking into account the possibility of the spread of disease from the aircraft's home country. An analysis and simulation of a specific airport security procedure was carried out on the model under study, which is an automated system for disinfecting baggage at airports in two variants. The aim is to reduce the transmission of harmful diseases and, at the same time, to ensure the accuracy of passenger security screening by efficiently exhausting each of the proposed models. This research shows that the suggested measures to stop the spread of infectious diseases that travelers' luggage can bring in will enhance screening procedures and, in particular, boost overall security while lowering the risk of infection transmission at airports. [ABSTRACT FROM AUTHOR]

Salmonella is a significant zoonotic foodborne pathogen, and the global spread of multidrug-resistant (MDR) strains poses substantial challenges, necessitating alternatives to antibiotics. Among these alternatives, vaccines protect the community against infectious diseases effectively. This review aims to summarize the efficacy of developed Salmonella vaccines evaluated in various animal hosts and highlight key transitions for future vaccine studies. A total of 3221 studies retrieved from Web of Science, Google Scholar, and PubMed/Medline databases between 1970 and 2023 were evaluated. One hundred twenty-seven qualified studies discussed the vaccine efficacy against typhoidal and nontyphoidal serovars, including live-attenuated vaccines, killed inactivated vaccines, outer membrane vesicles, outer membrane complexes, conjugate vaccines, subunit vaccines, and the reverse vaccinology approach in different animal hosts. The most efficacious vaccine antigen candidate found was recombinant heat shock protein (rHsp60) with an incomplete Freund's adjuvant evaluated in a murine model. Overall, bacterial ghost vaccine candidates demonstrated the highest efficacy at 91.25% (95% CI = 83.69–96.67), followed by the reverse vaccinology approach at 83.46% (95% CI = 68.21–94.1) across animal hosts. More than 70% of vaccine studies showed significant production of immune responses, including humoral and cellular, against Salmonella infection. Collectively, the use of innovative methods rather than traditional approaches for the development of new effective vaccines is crucial and warrants in-depth studies. [ABSTRACT FROM AUTHOR]

Infectious diseases affecting the gastrointestinal tract often present diagnostic challenges due to the variability in clinical manifestations and overlapping symptoms. Ultrasound imaging has emerged as a valuable tool in the assessment of gastrointestinal pathologies, offering non-invasive and real-time visualization of anatomical structures. This review aims to explore the role of ultrasound in the diagnosis and management of infectious diseases involving the gastrointestinal tract. We discuss the imaging features of various infectious etiologies, such as bacterial, viral, and parasitic infections, highlighting characteristic findings on ultrasound scans. Additionally, we provide insights into the utility of ultrasound for the assessment of treatment response. Through a comprehensive analysis of existing literature and clinical case studies, this review underscores the significance of ultrasound imaging as a frontline modality in the diagnosis and management of infectious diseases affecting the gastrointestinal tract. [ABSTRACT FROM AUTHOR]

This study introduces an SIRS compartmental mathematical model encompassing vaccination and variable immunity periods for infectious diseases. I derive a basic reproduction number formula and assess the local and global stability of disease-free and the local stability of the endemic equilibria. I demonstrate that the basic reproduction number in the presence of a vaccine is highly sensitive to the rate of immunity loss, and even a slight reduction in this rate can significantly contribute to disease control. Additionally, I have derived a formula to calculate the critical efficacy period required for a vaccine to effectively manage and control the disease.The analysis conducted for the model suggests that increasing the vaccine’s immunity duration (efficacy) decelerates disease dynamics, leading to reduced rates of reinfection and less severe disease outcomes. Furthermore, this delay contributes to a decrease in the basic reproduction number ( R 0 ), thus facilitating more rapid disease control efforts. [ABSTRACT FROM AUTHOR]

Background: Assessment of artificial intelligence (AI)-based models across languages is crucial to ensure equitable access and accuracy of information in multilingual contexts. This study aimed to compare AI model efficiency in English and Arabic for infectious disease queries. Methods: The study employed the METRICS checklist for the design and reporting of AI-based studies in healthcare. The AI models tested included ChatGPT-3.5, ChatGPT-4, Bing, and Bard. The queries comprised 15 questions on HIV/AIDS, tuberculosis, malaria, COVID-19, and influenza. The AI-generated content was assessed by two bilingual experts using the validated CLEAR tool. Results: In comparing AI models' performance in English and Arabic for infectious disease queries, variability was noted. English queries showed consistently superior performance, with Bard leading, followed by Bing, ChatGPT-4, and ChatGPT-3.5 (P =.012). The same trend was observed in Arabic, albeit without statistical significance (P =.082). Stratified analysis revealed higher scores for English in most CLEAR components, notably in completeness, accuracy, appropriateness, and relevance, especially with ChatGPT-3.5 and Bard. Across the five infectious disease topics, English outperformed Arabic, except for flu queries in Bing and Bard. The four AI models' performance in English was rated as "excellent", significantly outperforming their "above-average" Arabic counterparts (P =.002). Conclusions: Disparity in AI model performance was noticed between English and Arabic in response to infectious disease queries. This language variation can negatively impact the quality of health content delivered by AI models among native speakers of Arabic. This issue is recommended to be addressed by AI developers, with the ultimate goal of enhancing health outcomes. [ABSTRACT FROM AUTHOR]

Background: Fluorine-18 fluorodeoxyglucose positron emission tomography/computed tomography ([18F]FDG PET/CT) has been suggested as a useful imaging method for diagnosing cyst infections in patients with autosomal dominant polycystic kidney disease (ADPKD). The aim of this article is to provide evidence-based data in this setting. Methods: A systematic literature review (exploring several bibliographic databases) and a bivariate meta-analysis were carried out to calculate the pooled diagnostic performance of [18F]FDG PET/CT in diagnosing probable cyst infection in ADPKD. Results: Ten studies (282 PET/CT scans and 249 patients) were included in the analysis. The pooled sensitivity and specificity of [18F]FDG PET/CT in this setting were 84.6% (95% confidence interval: 75.4–90.7) and 94.9% (95% confidence interval: 72.6–99.2), respectively, without statistical heterogeneity or significant publication bias. [18F]FDG PET/CT significantly changed patient management in more than half of ADPKD patients with suspected cyst infection. Conclusions: [18F]FDG PET/CT has high performance in diagnosing probable cyst infections in ADPKD patients with an impact on management in the majority of patients. Although more studies are warranted, the provided evidence-based data are an important step towards the integration of [18F]FDG PET/CT in clinical and diagnostic guidelines on probable cyst infection in ADPKD patients. [ABSTRACT FROM AUTHOR]

This paper introduces a promising ecological approach to classifying infectious diseases based on the reservoir of the causative organism. According to this approach, all infectious diseases are classified as anthroponoses, zoonoses, and sapronoses. Among these three, zoonoses are the most used and known category, including diseases naturally transmitted between vertebrate animals and humans. The principal reservoir of the pathogen is often populations of certain animal species. The term “anthroponoses” denotes diseases where human hosts are central to the pathogen’s life cycle and provide its survival from an evolutionary perspective. These diseases circulate only among humans, and animals are not susceptible to them. Finally, sapronoses is an emerging concept for categorizing diseases where the causative organisms grow saprophytically in the environment and parasitically in vertebrate hosts, including humans. However, the parasitic phase usually plays a secondary role. Recognizing infectious diseases as sapronoses highlights the role of the connection between diseases among humans, animals, and the environment. This ecological approach to classifying infectious diseases is worth exploring, especially in the context of One Health, which emphasizes the interdependence between these three dimensions. Theoretical exploration focusing on the complex dynamics of pathogen-host interactions is needed to develop this classification further.

Infectious diseases are a global public health problem, with emerging and re-emerging infectious diseases on the rise worldwide. Therefore, their prevention and treatment are still major challenges. Bile acids are common metabolites in both hosts and microorganisms that play a significant role in controlling the metabolism of lipids, glucose, and energy. Bile acids have historically been utilized as first-line, valuable therapeutic agents for related metabolic and hepatobiliary diseases. Notably, bile acids are the major active ingredients of cow bezoar and bear bile, which are commonly used traditional Chinese medicines (TCMs) with the therapeutic effects of clearing heat, detoxification, and relieving wind and spasm. In recent years, the promising performance of bile acids against infectious diseases has attracted attention from the scientific community. This paper reviews for the first time the biological activities, possible mechanisms, production routes, and potential applications of bile acids in the treatment and prevention of infectious diseases. Compared with previous reviews, we comprehensively summarize existing studies on the use of bile acids against infectious diseases caused by pathogenic microorganisms that are leading causes of global morbidity and mortality. In addition, to ensure a stable supply of bile acids at affordable prices, it is necessary to clarify the biosynthesis of bile acids in vivo, which will assist scientists in elucidating the accumulation of bile acids and discovering how to engineer various bile acids by means of chemosynthesis, biosynthesis, and chemoenzymatic synthesis. Finally, we explore the current challenges in the field and recommend a development strategy for bile-acid-based drugs and the sustainable production of bile acids. The presented studies suggest that bile acids are potential novel therapeutic agents for managing infectious diseases and can be artificially synthesized in a sustainable way.

The paper considers the key areas of international activities of the Federal Service for Surveillance on Consumers’ Rights Protection and Human Well-being in strengthening cooperation with specialized agencies of foreign countries in the global provision of sanitary-epidemiological welfare of the population at the current stage. Consistent work to strengthen the international network to counter emergency situations of a sanitary and epidemiological nature through effective interaction in the field of rapid response with partner countries in the near and far abroad, including through the organization of joint scientific and practical centers for the study and prevention of infectious diseases is presented. It is shown that the programs being implemented are aimed at strengthening the national healthcare structures of partner countries to achieve independence in the implementation of monitoring and anti-epidemic measures and building a single epidemiological space, independent of the influence of global and regional geopolitical fluctuations. The relevance of increasing interstate cooperation in the field of analysis and control of biological threats, primarily infectious diseases with the potential for emergencies of a sanitary and epidemiological nature of international concern, in the South American region is considered. The currently expanding strategic biosecurity collaboration with the Bolivarian Republic of Venezuela through the establishment of the first joint research center in the South American region is described. The first results of the joint work of Russian and Venezuelan specialists are presented, confirming the successful integration of Russian experience in monitoring and preventing biological threats into the system of ensuring the sanitary and epidemiological well-being of the Venezuelan population. Promising areas for further joint research are discussed.

Background: Sports medicine (injury and illnesses) requires distinct coding systems because the International Classification of Diseases is insufficient for sports medicine coding. The Orchard Sports Injury and Illness Classification System (OSIICS) is one of two sports medicine coding systems recommended by the International Olympic Committee. Regular updates of coding systems are required. Methods: For Version 15, updates for mental health conditions in athletes, sports cardiology, concussion sub-types, infectious diseases, and skin and eye conditions were considered particularly important. Results: Recommended codes were added from a recent International Olympic Committee consensus statement on mental health conditions in athletes. Two landmark sports cardiology papers were used to update a more comprehensive list of sports cardiology codes. Rugby union protocols on head injury assessment were used to create additional concussion codes. Conclusion: It is planned that OSIICS Version 15 will be translated into multiple new languages in a timely fashion to facilitate international accessibility. The large number of recently published sport-specific and discipline-specific consensus statements on athlete surveillance warrant regular updating of OSIICS.

• Largest sample size meta-analysis of mNGS in diagnosing infections was performed. • mNGS exhibits a highest diagnostic value in central system infection. • The diagnostic accuracy of mNGS varies among different infectious types. • mNGS has a great potential to exclude infection in immunocompromised patients. Early diagnosis of infectious diseases remains a challenge. This study assessed the diagnostic value of mNGS in infections and explored the effect of various factors on the accuracy of mNGS. An electronic article search of PubMed, Cochrane Library, and Embase was performed. A total of 85 papers were eligible for inclusion and analysis. Stata 12.0 was used for statistical calculation to evaluate the efficacy of mNGS for the diagnosis of infectious diseases. The AUC of 85 studies was 0.88 (95%CI, 0.85-0.90). The AUC of the clinical comprehensive diagnosis and conventional test groups was 0.92 (95%CI, 0.89-0.94) and 0.82 (95%CI, 0.78-0.85), respectively. The results of subgroup analysis indicated that the PLR and NLR were 12.67 (95%CI, 6.01-26.70) and 0.05 (95%CI, 0.03-0.10), respectively, in arthrosis infections. The PLR was 24.41 (95%CI, 5.70-104.58) in central system infections and the NLR of immunocompromised patients was 0.08 (95%CI, 0.01-0.62). mNGS demonstrated satisfactory diagnostic performance for infections, especially for bone and joint infections and central system infections. Moreover, mNGS also has a high value in the exclusion of infection in immunocompromised patients. [Display omitted] [ABSTRACT FROM AUTHOR]