Search

Infectious risks escalate with complex donning and doffing personal protective equipment (PPE) protocols. Recent studies suggest that PPE donning and doffing behaviors that deviate from protocol during PPE reuse compounded the risks of health care worker (HCW) self-contamination. This study quantified the occurrence of behaviors associated with known risks in PPE use and reuse. We conducted a prospective study of emergency department HCWs and video-recorded PPE donning and doffing 5 times in simulated patient encounters. Trained coders recorded HCW behaviors according to an evidence-based guide. All 28 participants deviated from the Centers for Disease Control and Prevention (CDC) sanctioned donning and doffing protocol order, and most were documented to have (92.85%) self-contaminated at least once during each simulated clinical encounter. Behaviors that compounded self-contamination due to PPE reuse were also observed. Wide variation in PPE donning and doffing behaviors was found among front-line, experienced HCWs. Future work is needed to determine which deviations put HCWs at increased risk for accidental self-contamination and what changes are needed to the CDC protocol for protecting HCW from infections. [ABSTRACT FROM AUTHOR]

Addressing environmental and public health problems requires concerted efforts from both the government and its citizens. The government typically has more information than the citizens do about the severity of a problem, and spillovers of citizens' adaptation efforts complicate that asymmetric information problem. This paper presents a model in which an informed government chooses a mitigation policy and uninformed citizens choose adaptation efforts sequentially and non-cooperatively. We find that mitigation and adaptation either strategically complement each other or are substitutes for each other in equilibrium, depending upon whether the government uses an overly stringent or an overly lax mitigation policy to signal the severe state. We then extend our analysis to a two-nation model in which the pollution or public health problem is transboundary. National governments (in this case, two) then have incentives to free-ride in both their mitigation and their information transmission. We find that information asymmetry may not distort mitigation in this case. Meanwhile, there also exists another refined equilibrium in which one national government pools and relies on the other's stringent policy to signal the severe state. [ABSTRACT FROM AUTHOR]

Background: Antimicrobials are frequently administered at end-of-life (EOL) and their non-beneficial use may subject patients to unnecessary harms. Studies analyzing factors for antimicrobial prescribing in solid tumor cancer patients at the EOL are lacking. Thus, we aimed to identify factors and patterns associated with antimicrobial use in hospitalized adults with cancer at EOL. Methods: We used a retrospective cohort design to review electronic medical records of terminal hospitalized patients ≥18 years with solid tumors admitted to non-intensive care units in a metropolitan comprehensive cancer center during 2019 and assessed antimicrobial use in the last 7 days of life. Results: Among 633 cancer patients, 59% (n = 376) received antimicrobials (AM+) within the last 7 days of life. AM + patients were older (P =.012), mostly of male gender (55%), and non-Hispanic ethnicity (87%). AM + patients were significantly more likely to have a foreign device, suspected signs of infection, neutropenia, positive blood culture result, documented advance directive; receive laboratory or radiologic testing, and a palliative care or infectious disease consultation (all P <.05). No statistically significant differences were observed in the presence of documented goals of care discussions, or EOL discussions/EOL care orders. Conclusion: Antimicrobial use at the EOL is common in solid tumor cancer patients at the EOL and is associated with increased utilization of invasive interventions. There is an opportunity for infectious disease specialists to build primary palliative care skills and partner with antimicrobial stewardship programs to better advise patients, decision makers, and primary teams on the use of antimicrobials at the EOL. [ABSTRACT FROM AUTHOR]

Pathogen agnostic sequencing, also known as metagenomic sequencing, is a useful tool for biodefense and public health surveillance. It involves sequencing genetic material in a sample to detect and monitor infectious diseases. Next-generation sequencing technologies have made this method more affordable and accessible. The US Department of Defense's Global Emerging Infections Surveillance program has successfully integrated pathogen agnostic sequencing into its infectious disease surveillance network. The program has established a consortium to promote collaboration and standardization, conducted proficiency testing exercises, and funded surveillance activities using this method. The text discusses the challenges and opportunities associated with pathogen agnostic sequencing, highlighting the need for standardized protocols and methods, as well as collaboration between the biodefense and public health communities. The conclusion emphasizes the value of past investments in this technology and the need for continued investment to prepare for future threats. [Extracted from the article]

Frequent foodborne illnesses with unknown causative agents highlight the need to explore zoonotic potential foodborne pathogens (PFPs). An effective PFP prioritization tool is indispensable, especially after experiencing the recent pandemic caused by zoonotic SARS-CoV-2. Risk information on pathogens (excluding 30 known foodborne pathogens) provided by governmental and international organizations was reviewed to generate a list of PFPs. Risk-ranking of PFPs was conducted based on a literature review of food poisoning or detection cases, and the ranks were determined with a decision tree. PFPs were prioritized by infectious disease (ID), veterinary medicine (VET), and food safety (FS) experts through a pre- and postpandemic Delphi survey, and key criteria in their decisions were illuminated. Among 339 PFPs, 32 rank-1 PFPs were involved in the foodborne outbreak(s). Discrepancies in opinions on prioritization between experts in different fields deepened after the pandemic. Only VET and FS experts valued the plausibility of foodborne transmission in evaluating bacteria and viruses, and a significant correlation between their selection of PFPs was found (p < .05). The impact of the pandemic induced all fields to focus more on human transmission and severity/fatality in prioritizing viruses, and only FS experts emphasized the plausibility of foodborne transmission after the pandemic. In contrast to prioritizing bacteria or viruses, ID and VET experts are unusually focused on foodborne transmission when prioritizing parasites. Criteria of consensus deduced by interdisciplinary experts with different interests and the criteria directly related to foodborne transmission should be acknowledged for adequate PFP prioritization. [ABSTRACT FROM AUTHOR]

Neglected tropical diseases (NTDs) introduce considerable morbidity and mortality on a global scale, directly impacting over 1 billion individuals as well as their families and communities. Afflicted individuals may have limited access to resources and care in these regions, contributing to a high proportion of chronic, progressive, and systemic disease. The cardiovascular system is at particular risk of demise for several NTDs, yet remains largely unstudied due in part to the lack of robust data collection mechanisms in the most impacted regions. The present review is a part of the Neglected Tropical Diseases and other Infectious Diseases affecting the Heart (NET-Heart) Project, aiming at summarizing the current knowledge on cardiovascular implications of NTDs and providing diagnostic as well as management recommendations which can be tailored to low-resource settings. The diagnostic and management algorithms of 13 unique NTDs are presented and summarized. Recognizing cardiac manifestations of NTDs can significantly alter disease trajectory and all physicians benefit from improved knowledge about NTDs. Great potential exists to advance patient care by improving data collection, communication, and international collaboration. [ABSTRACT FROM AUTHOR]

Background: Severe respiratory infections, including pneumonia or bronchiolitis, caused by RSV can range from mild upper respiratory tract infections to those leading to hospitalization and serious complications such as respiratory failure in children. High-risk groups, such as premature infants and infants with underlying medical conditions, have a higher susceptibility to severe RSV disease. We conducted a retrospective study from years 2015 to 2022 in the Local Health Authority (LHA) of Pescara that counts about 320,000 inhabitants, with the aim to evaluate the burden of RSV infection, focusing on the incidence, hospitalization, and characteristics that may prolong hospital stays. Methods: All hospitalizations from 2015 to 2022 were extracted from the hospital discharge record. The monthly hospitalization rates were calculated and standardized by gender and age for the population resident in the Province of Pescara on 1 January 2015. Results: During the study period, 31,837 admissions were reported among patients aged less than 6 years. Of those, 520 hospitalizations were referred for bronchiolitis. Monthly admission rates highlighted the seasonality of bronchiolitis admissions, with higher rates in the months from December to March in all study years included. The winter seasons of years 2021 and 2022 reported a surge in bronchiolitis incidence, with a rate of 4.0/1000 (95% CI 2.964–5.146) in December 2021 and 4.0 (95% CI 2.891–5.020) in December 2022. Conclusions: Bronchiolitis represents an important cause of hospitalization among patients aged less than 6 years. The incidence was particularly increased during the winter seasons in years 2021 and 2022. [ABSTRACT FROM AUTHOR]

A patient with acquired immunodeficiency syndrome presented with findings concerning for acute invasive fungal sinusitis, which is typically associated with Mucorales. However, debridement and pathological analysis revealed Cytomegalovirus, a pathology rarely encountered. Laryngoscope, 134:92–96, 2024 [ABSTRACT FROM AUTHOR]

Dengue fever (DF) is an infectious disease that is still a problem in Indonesia. The total death rate due to DF was 705 people in 2021; in 2022, this increased to 1183 (Indonesian Ministry of Health, 2023). Seeing this fact, prevention efforts are still needed when handling DF cases in all of the regions of Indonesia. This research was conducted in the Kendari area of Southeast Sulawesi, where there are still cases of DF. The purpose of this study was to create a spatial model of dengue susceptibility using a support vector machine. Landsat 8 imagery was used to intercept data on building density, vegetation density, land use, and land surface temperatures. Rainfall and humidity variables were obtained from the Meteorological, Climatological, and Geophysical Agency (BMKG). Based on the modeling results, the districts of Wua-wua, Kadia, Barunga, Poasi, and Puuwatu are areas with high susceptibility. The results of testing the susceptibility model to dengue hemorrhagic fever (DHF) in Kendari obtained an area under the curve (AUC) of 0.75, meaning that this model was well-accepted. [ABSTRACT FROM AUTHOR]

Macrophage migration inhibitory factor (MIF) and its homolog, D-dopachrome tautomerase (D-DT), are cytokines that play critical roles in the immune response to various infectious diseases. This review provides an overview of the complex involvement of MIF and D-DT in bacterial, viral, fungal, and parasitic infections. The role of MIF in different types of infections is controversial, as it has either a protective function or a host damage-enhancing function depending on the pathogen. Depending on the specific role of MIF, different therapeutic options for MIF-targeting drugs arise. Human MIF-neutralizing antibodies, anti-parasite MIF antibodies, small molecule MIF inhibitors or MIF-blocking peptides, as well as the administration of exogenous MIF or MIF activity-augmenting small molecules have potential therapeutic applications and need to be further explored in the future. In addition, MIF has been shown to be a potential biomarker and therapeutic target in sepsis. Further research is needed to unravel the complexity of MIF and D-DT in infectious diseases and to develop personalized therapeutic approaches targeting these cytokines. Overall, a comprehensive understanding of the role of MIF and D-DT in infections could lead to new strategies for the diagnosis, treatment, and management of infectious diseases. [ABSTRACT FROM AUTHOR]

Pathogen discovery plays a crucial role in the fields of infectious diseases, clinical microbiology, and public health. During the past four years, the global response to the COVID-19 pandemic highlighted the importance of early and accurate identification of novel pathogens for effective management and prevention of outbreaks. The post-COVID era has ushered in a new phase of infectious disease research, marked by accelerated advancements in pathogen discovery. This review encapsulates the recent innovations and paradigm shifts that have reshaped the landscape of pathogen discovery in response to the COVID-19 pandemic. Primarily, we summarize the latest technology innovations, applications, and causation proving strategies that enable rapid and accurate pathogen discovery for both acute and historical infections. We also explored the significance and the latest trends and approaches being employed for effective implementation of pathogen discovery from various clinical and environmental samples. Furthermore, we emphasize the collaborative nature of the pandemic response, which has led to the establishment of global networks for pathogen discovery. [ABSTRACT FROM AUTHOR]

Understanding infectious disease pathogenesis and evaluating novel candidate treatment interventions for human use frequently requires prior or parallel analysis in animal model systems. While rodent species are frequently applied in such studies, there are situations where non-human primate (NHP) species are advantageous or required. These include studies of animals that are anatomically more akin to humans, where there is a need to interrogate the complexity of more advanced biological systems or simply reflect susceptibility to a specific infectious agent. The contribution of different arms of the immune response may be addressed in a variety of NHP species or subspecies in specific physiological compartments. Such studies provide insights into immune repertoires not always possible from human studies. However, genetic variation in outbred NHP models may confound, or significantly impact the outcome of a particular study. Thus, host factors need to be considered when undertaking such studies. Considerable knowledge of the impact of host immunogenetics on infection dynamics was elucidated from HIV/SIV research. NHP models are now important for studies of emerging infections. They have contributed to delineating the pathogenesis of SARS-CoV-2/COVID-19, which identified differences in outcomes attributable to the selected NHP host. Moreover, their use was crucial in evaluating the immunogenicity and efficacy of vaccines against COVID-19 and establishing putative correlates of vaccine protection. More broadly, neglected or highly pathogenic emerging or re-emergent viruses may be studied in selected NHPs. These studies characterise protective immune responses following infection or the administration of candidate immunogens which may be central to the accelerated licensing of new vaccines. Here, we review selected aspects of host immunogenetics, specifically MHC background and TRIM5 polymorphism as exemplars of adaptive and innate immunity, in commonly used Old and New World host species. Understanding this variation within and between NHP species will ensure that this valuable laboratory source is used most effectively to combat established and emerging virus infections and improve human health worldwide. [ABSTRACT FROM AUTHOR]

Copyright of Bundesgesundheitsblatt - Gesundheitsforschung - Gesundheitsschutz is the property of Springer Nature and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

This research combines the COVID-19 and BCG vaccination subpopulations to examine the spread of COVID-19 coinfection and tuberculosis (TB) using a compartmental mathematical model. The model analysis yields the non-endemic and endemic equilibrium points in addition to the basic reproduction number. The vaccination variable in the model can reduce the incidence of COVID-19, TB, and coinfection. A sensitivity analysis using elasticity index is conducted and the result is that the natural death rate parameter is the most influential in relation to the accelerated spread of COVID-19 co-infection with tuberculosis. Additionally, we conduct a timedependent sensitivity analysis to determine how varying parameter values influence each subpopulation. By using this technique, we calculate the sensitivity index after reaching equilibrium of several groups of parameters, and the result is that resusceptible, immunity rate, symptomatic transition rate of TB, COVID-19 recovery rate, and natural death rate are the most influential for each group of parameters on the dynamics of each subpopulation. [ABSTRACT FROM AUTHOR]

Morning Report is a time-honored tradition where physicians-in-training present cases to their colleagues and clinical experts to collaboratively examine an interesting patient presentation. The Morning Report section seeks to carry on this tradition by presenting a patient's chief concern and story, inviting the reader to develop a differential diagnosis and discover the diagnosis alongside the authors of the case. This report examines the case of a 14-year-old girl who presented with 1 week of dyspnea, nonproductive cough, and pleuritic chest pain after traveling to the Caribbean. Using questions, physical examination, and testing, an illness script for the presentation emerges. As the clinical course progresses, the differential is refined until a diagnosis is made. [ABSTRACT FROM AUTHOR]

Randomized encouragement trial designs, where participants are randomly assigned to an opportunity or encouragement to receive treatment instead of to the treatment itself, can be useful for interventions where randomization to the intervention itself is deemed impossible or unethical. The nature of encouragement may itself influence the success of the trial. "Nudges" are interventions designed to influence decisions without restricting choice and may be utilized to improve randomized encouragement trials as well as in efforts to optimize real-world implementation of guideline-recommended interventions. Nudges are hypothesized to steer citizens toward appropriate health-related behavior and influence health care delivery through optimization of prescribing patterns, diagnostic testing, and compliance and adherence. Several prior randomized implementation trials have investigated the implementation of nudging into health care delivery; however, these have often been limited in geographical and demographic reach and results are mixed. To address evidence gaps, we are now introducing the Danish Nationwide Utilization of Danish Government Electronic Letter System (NUDGE) trial concept. Combining randomized encouragement trial designs with several advantages inherent in the Danish health care system, including universal free-of-charge health care, population-based health care registries, and comprehensive electronic communication systems, our trial concept enables testing of low-touch, potentially scalable nudges in a public health messaging context on a nationwide level. The concept may be applied across numerous populations and study aims. Future findings may inform health care policy decisions on a global level. [ABSTRACT FROM AUTHOR]

Objective: The objective of this study was to compare postoperative 90-day mortality between (1) fully vaccinated patients with COVID- 19-positive and negative diagnosis, and (2) vaccinated and unvaccinated patients with COVID-19 positive diagnosis. Background: Societal guidelines recommend postponing elective operations for at least 7 weeks in unvaccinated patients with preoperative coronavirus disease 2019 (COVID-19) infection. The role of vaccination in this infection-operation time risk is unclear. Methods: We conducted a national US multicenter retrospective, matched cohort study spanning July 2021 to October 2022. Participants were included if they underwent a high-risk general, vascular, orthopedic, neurosurgery, or genitourinary surgery. All-cause mortality occurring within 90 days of the index operation was the primary outcome. Inverse probability treatment weighted propensity scores were used to adjust logistic regression models examining the independent and interactive associations between mortality, exposure status, and infection proximity. Results: Of 3401 fully vaccinated patients in the 8-week preoperative period, 437 (12.9%) were COVID-19--positive. Unadjusted mortality rates were not significantly different between vaccinated patients with COVID-19 (22, 5.0%) and vaccinated patients without COVID-19 (99, 3.3%; P = 0.07). After inverse probability treatment weighted adjustment, mortality risk was not significantly different between vaccinated COVID-19--positive patients compared to vaccinated patients without COVID-19 (adjusted odds ratio = 1.38, 95% CI: 0.70, 2.72). The proximity of COVID-19 diagnosis to the index operation did not confer added mortality risk in either comparison cohort. Conclusions: Contrary to risks observed among unvaccinated patients, postoperative mortality does not differ between patients with and without COVID-19 when vaccinated against the severe acute respiratory syndrome coronavirus 2 virus and receiving a high-risk operation within 8 weeks of the diagnosis, regardless of operation timing relative to diagnosis. [ABSTRACT FROM AUTHOR]

A small percentage of bladder cancers in the general population have been found to harbor DNA viruses. In contrast, up to 25% of tumors of solid organ transplant recipients, who are at an increased risk of developing bladder cancer and have an overall poorer outcomes, harbor BK polyomavirus (BKPyV). To better understand the biology of the tumors and the mechanisms of carcinogenesis from potential oncoviruses, we performed whole genome and transcriptome sequencing on bladder cancer specimens from 43 transplant patients. Nearly half of the tumors from this patient population contained viral sequences. The most common were from BKPyV (N=9, 21%), JC polyomavirus (N=7, 16%), carcinogenic human papillomaviruses (N=3, 7%), and torque teno viruses (N=5, 12%). Immunohistochemistry revealed variable Large T antigen expression in BKPyV-positive tumors ranging from 100% positive staining of tumor tissue to less than 1%. In most cases of BKPyV-positive tumors, the viral genome appeared to be clonally integrated into the host chromosome consistent with microhomology-mediated end joining and coincided with focal amplifications of the tumor genome similar to other virus-mediated cancers. Significant changes in host gene expression consistent with the functions of BKPyV Large T antigen were also observed in these tumors. Lastly, we identified four mutation signatures in our cases, with those attributable to APOBEC3 and SBS5 being the most abundant. Mutation signatures associated with an antiviral drug, ganciclovir, and aristolochic acid, a nephrotoxic compound found in some herbal medicines, were also observed. The results suggest multiple pathways to carcinogenesis in solid organ transplant recipients with a large fraction being virus-associated.

Human Immunodeficiency Virus (HIV) continues to be a significant public health problem, with ~1.2 million Americans living with HIV and ~14% unaware of their infection. The Centers for Disease Control and Prevention recommends that patients 13 to 64 years of age get screened for HIV at least once, and those with higher risk profiles screen at least annually. Unfortunately, screening rates are below recommendations for high-risk populations, leading to problems of delayed diagnosis. Novel technologies have been applied in HIV research to increase prevention, testing and treatment. Conversational agents, with potential for integrating artificial intelligence and natural language processing, may offer an opportunity to improve outreach to these high-risk populations. The feasibility, accessibility and acceptance of using conversational agents for HIV testing outreach is important to evaluate, especially amidst a global coronavirus disease 2019 pandemic when clinical services have been drastically affected. This viewpoint explores the application of a conversational agent in increasing HIV testing among high-risk populations.

Circular DNA offers benefits over linear DNA in diagnostic and field assays, but currently, circular DNA generation is lengthy, inefficient, highly dependent on the length and sequence of DNA, and can result in unwanted chimeras. We present streamlined methods for generating PCR-targeted circular DNA from a 700 bp amplicon of rv0678, the high GC content (65%) gene implicated in Mycobacterium tuberculosis bedaquiline resistance, and demonstrate that these methods work as desired. We employ self-circularization with and without splints, a Gibson cloning-based approach, and novel 2 novel methods for generating pseudocircular DNA. The circular DNA can be used as a template for rolling circle PCR followed by long-read sequencing, allowing for the error correction of sequence data, and improving the confidence in the drug resistance determination and strain identification; and, ultimately, improving patient treatment. IMPORTANCE Antimicrobial resistance is a global health threat, and drug resistant tuberculosis is a principal cause of antimicrobial resistance-related fatality. The long turnaround time and the need for high containment biological laboratories of phenotypic growth-based Mycobacterium tuberculosis drug susceptibility testing often commit patients to months of ineffective treatment, and there is a groundswell of effort in shifting from phenotypic to sequencing-based genotypic assays. Bedaquiline is a key component to newer, all oral, drug resistant, tuberculosis regimens. Thus, we focus our study on demonstrating the circularization of rv0678, the gene that underlies most M. tuberculosis bedaquiline resistance. We present 2 novel methods for generating pseudocircular DNA. These methods greatly reduce the complexity and time needed to generate circular DNA templates for rolling circle amplification and long-read sequencing, allowing for error correction of sequence data, and improving confidence in the drug resistance determination and strain identification.

Climate change is a complex problem involving nonlinearities and feedback that operate across scales. No single discipline or way of thinking can effectively address the climate crisis. Teams of natural scientists, social scientists, engineers, economists, and policymakers must work together to understand, predict, and mitigate the rapidly accelerating impacts of climate change. Transdisciplinary approaches are urgently needed to address the role that microorganisms play in climate change. Here, we demonstrate with case studies how diverse teams and perspectives provide climate-change insight related to the range expansion of emerging fungal pathogens, technological solutions for harmful cyanobacterial blooms, and the prediction of disease-causing microorganisms and their vector populations using massive networks of monitoring stations. To serve as valuable members of a transdisciplinary climate research team, microbiologists must reach beyond the boundaries of their immediate areas of scientific expertise and engage in efforts to build open-minded teams aimed at scalable technologies and adoptable policies.

Protection against Plasmodium falciparum, which is primarily antibody-mediated, requires recurrent exposure to develop. The study of both naturally acquired limited immunity and vaccine induced protection against malaria remains critical for ongoing eradication efforts. Towards this goal, we deployed a customized P. falciparum PhIP-seq T7 phage display library containing 238,068 tiled 62-amino acid peptides, covering all known coding regions, including antigenic variants, to systematically profile antibody targets in 198 Ugandan children and adults from high and moderate transmission settings. Repeat elements - short amino acid sequences repeated within a protein - were significantly enriched in antibody targets. While breadth of responses to repeat-containing peptides was twofold higher in children living in the high versus moderate exposure setting, no such differences were observed for peptides without repeats, suggesting that antibody responses to repeat-containing regions may be more exposure dependent and/or less durable in children than responses to regions without repeats. Additionally, short motifs associated with seroreactivity were extensively shared among hundreds of antigens, potentially representing cross-reactive epitopes. PfEMP1 shared motifs with the greatest number of other antigens, partly driven by the diversity of PfEMP1 sequences. These data suggest that the large number of repeat elements and potential cross-reactive epitopes found within antigenic regions of P. falciparum could contribute to the inefficient nature of malaria immunity.

A case-control study was conducted between 1 December 2021 and 31 January 2022 to identify factors, which increase risk for coronavirus disease 2019 (COVID-19) among athletes in the National Basketball Association (NBA). Behavioral factors and stadium attendance significantly decreased time to COVID-19 infection, but local COVID-19 rates were not associated in a multivariable model.

Proteolysis is a central regulator of many biological pathways and the study of proteases has had a significant impact on our understanding of both native biology and disease. Proteases are key regulators of infectious disease and misregulated proteolysis in humans contributes to a variety of maladies, including cardiovascular disease, neurodegeneration, inflammatory diseases, and cancer. Central to understanding a protease's biological role, is characterizing its substrate specificity. This chapter will facilitate the characterization of individual proteases and complex, heterogeneous proteolytic mixtures and provide examples of the breadth of applications that leverage the characterization of misregulated proteolysis. Here we present the protocol of Multiplex Substrate Profiling by Mass Spectrometry (MSP-MS), a functional assay that quantitatively characterizes proteolysis using a synthetic library of physiochemically diverse, model peptide substrates, and mass spectrometry. We present a detailed protocol as well as examples of the use of MSP-MS for the study of disease states, for the development of diagnostic and prognostic tests, for the generation of tool compounds, and for the development of protease-targeted drugs.

There is an increased interest in utilizing real-world data (RWD) for pharmaceutical research and regulatory decision-making. The development and use of pediatric medicines could benefit greatly from real-world data studies given nearly half of drugs prescribed to children are "off-label", meaning there is a lack of pediatric-specific evidence from controlled trials, while there is an abundance of data from routine clinical practice. Currently, the use of real-world data, such as data from electronic health records, is lacking in pediatric research, especially within infectious diseases. Here, we discuss opportunities and challenges for real-world data to generate evidence on the optimal treatment and management of infectious diseases in children.

Histoplasma capsulatum is a geographically specific dimorphic fungus that can cause a spectrum of diseases. While most cases are asymptomatic pulmonary infections, in severe cases, particularly in immunocompromised patients, disseminated disease can occur. Histoplasmosis in California is limited to only a few case reports. In this article, we describe a rare case of disseminated histoplasmosis in a non-endemic region presenting with diagnostically challenging symptomatology, including altered mental status, status epilepticus, septic shock, and bilateral adrenal masses.

China has been continuously improving its monitoring methods and strategies to address key infectious diseases (KIDs). After the severe acute respiratory syndrome epidemic in 2003, China established a comprehensive reporting system for infectious diseases (IDs) and public health emergencies. The relatively lagging warning thresholds, limited warning information, and outdated warning technology are insufficient to meet the needs of comprehensive monitoring for modern KIDs. Strengthening early monitoring and warning capabilities to enhance the public health system has become a top priority, with increasing demand for early warning thresholds, information, and techniques, thanks to constant innovation and development in molecular biology, bioinformatics, artificial intelligence, and other identification and analysis technologies. A panel of 31 experts has recommended a fourth-generation comprehensive surveillance system targeting KIDs (41 notifiable diseases and emerging IDs). The aim of this surveillance system is to systematically monitor the epidemiology and causal pathogens of KIDs in hosts such as humans, animals, and vectors, along with associated environmental pathogens. By integrating factors influencing epidemic spread and risk assessment, the surveillance system can serve to detect, predict, and provide early warnings for the occurrence, development, variation, and spread of known or novel KIDs. Moreover, we recommend comprehensive ID monitoring based on the fourth-generation surveillance system, along with a data-integrated monitoring and early warning platform and a consortium pathogen detection technology system. This series of considerations is based on systematic and comprehensive monitoring across multiple sectors, dimensions, factors, and pathogens that is supported by data integration and connectivity. This expert consensus will provides an opportunity for collaboration in various fields and relies on interdisciplinary application to enhance comprehensive monitoring, prediction, and early warning capabilities for the next generation of ID surveillance. This expert consensus will serve as a reference for ID prevention and control as well as other related activities.

Background: During the COVID-19 pandemic there was a plethora of dynamical forecasting models created, but their ability to effectively describe future trajectories of disease was mixed. A major challenge in evaluating future case trends was forecasting the behavior of individuals. When behavior was incorporated into models, it was primarily incorporated exogenously (e.g., fitting to cellphone mobility data). Fewer models incorporated behavior endogenously (e.g., dynamically changing a model parameter throughout the simulation). Methods: This review aimed to qualitatively characterize models that included an adaptive (endogenous) behavioral element in the context of COVID-19 transmission. We categorized studies into three approaches: 1) feedback loops, 2) game theory/utility theory, and 3) information/opinion spread. Findings: Of the 92 included studies, 72% employed a feedback loop, 27% used game/utility theory, and 9% used a model if information/opinion spread. Among all studies, 89% used a compartmental model alone or in combination with other model types. Similarly, 15% used a network model, 11% used an agent-based model, 7% used a system dynamics model, and 1% used a Markov chain model. Descriptors of behavior change included mask-wearing, social distancing, vaccination, and others. Sixty-eight percent of studies calibrated their model to observed data and 25% compared simulated forecasts to observed data. Forty-one percent of studies compared versions of their model with and without endogenous behavior. Models with endogenous behavior tended to show a smaller and delayed initial peak with subsequent periodic waves. Interpretation: While many COVID-19 models incorporated behavior exogenously, these approaches may fail to capture future adaptations in human behavior, resulting in under- or overestimates of disease burden. By incorporating behavior endogenously, the next generation of infectious disease models could more effectively predict outcomes so that decision makers can better prepare for and respond to epidemics. Funding: This study was funded in-part by Centers for Disease Control and Prevention (CDC) MInD-Healthcare Program (1U01CK000536), the National Science Foundation (NSF) Modeling Dynamic Disease-Behavior Feedbacks for Improved Epidemic Prediction and Response grant (2229996), and the NSF PIPP Phase I: Evaluating the Effectiveness of Messaging and Modeling during Pandemics grant (2200256).

Tropical infectious diseases inflict an unacceptable burden of disease on humans living in developing countries. Although anti-pathogenic drugs have been widely used, they carry a constant threat of selecting for resistance. Vaccines offer a promising means by which to enhance the global control of tropical infectious diseases; however, these have been difficult to develop, mostly because of the complex nature of the pathogen lifecycles. Here, we present recently developed vaccine candidates for five tropical infectious diseases in the form of a catalog that have either entered clinical trials or have been licensed for use. We deliberate on recently licensed dengue vaccines, provide evidence why combination vaccination could have a synergistic impact on schistosomiasis, critically appraise the value of typhoid conjugate vaccines, and discuss the potential of vaccines in the efforts to eliminate vivax malaria and hookworms.

The commonly heard aphorism about history repeating itself suggests an endless cycle of recurring events. However, George Santayana offered a similar sentiment when he said, ''Those who do not learn from history are doomed to repeat it''. This emphasises that the responsibility for the recurrence of events lies not with history itself, but with humanity. It underscores that if we desire change, it is our responsibility to initiate it, rather than attributing it to external forces such as fate, luck, or time. With this thought in mind, here we offer a narrative view from sub-Saharan Africa, focusing primarily on our own experiences in Nigeria and Uganda, on what harsh lessons can be learnt from the COVID-19 pandemic regarding emergency preparedness to respond effectively to the next major infectious disease outbreak. Four strategies are suggested, the implementation of which may contribute substantially to safeguarding against an experience similar to the catastrophic public health, social and economic costs borne by African nations during COVID-19 and in its immediate aftermath.

Marburg virus (MARV), a member of Filoviridae family, is notorious for causing Marburg virus disease (MVD), one of the deadliest known infectious diseases. Over the past five decades, more than 15 MVD outbreaks have been reported in the African countries, and this has been reported from Equatorial Guinea on February 2023. Few bat species like Rousettus aegyptiacus and Hipposideros caffer, among other members of the Chiroptera order, may serve as a natural reservoir for the virus, which can transmit the disease to humans and other mammals. In humans, severe infections have been reported due to MVD and are characterized by clinical symptoms such as abdominal pain, nausea, vomiting, pharyngitis, and diarrhea, eventually progressing to hemorrhagic manifestations. The disease carries an extremely high mortality and morbidity rate. Developing and implementing rapid, accurate, affordable, and efficient diagnostic and therapeutic measures is essential to address the substantial threat MARV poses. Increased focus on health education, enhancement of laboratory services and facilities, adherence to patient safety protocols, and robust surveillance systems are urgently needed to combat this fatal disease. This review aims to present a comprehensive summary of the various attributes and characteristics of MARV/MVD, along with strategies for its prevention and control. Further, this review article also discusses the potential role of medicinal plants in addressing health challenge.

During large scale outbreaks of infectious diseases, it is imperative that media report about the potential risks. Because media reporting plays a vital role in disseminating crucial information about diseases and its associated risk, understanding how media reports could influence individuals’ behavior and its potential impact on disease transmission dynamics is important. A mathematical model within an optimal control framework of a generic disease, accounting for treatment and media reporting of disease-induced deaths is formulated. Due to the complexity of choosing the best media function, our goal is to attempt to address the following research question: what is the effect of the media-induced functional response on mitigating the spread of the disease? Connecting the functional forms to the control problem is an approach that is not very developed in the literature. Thus, this study analyses the effect of different incidence functions on disease transmission, and the qualitative nature of epidemic dynamics by carrying out optimal control analysis using three different contact rates and a media function that is dependent on the number of deaths. Theoretical analyses show that the functional forms of the effective contact rate have no effect on initial disease transmission. Time-dependent controls for treatment and vaccination with a constant effective contact rate are incorporated to determine optimal control strategies. Numerical simulations show the short-term impact of media coverage on mitigating the spread of the disease, and it is observed that with three incidence functions used, the qualitative nature of the controls remains the same. The effective contact rates are graphically shown to have a population-level effect on the disease dynamics as the number of treated and recovered individuals could be significantly different. Finally, it is shown that treatment of infectives should be at its maximum rate for a longer period compared to vaccination, while concurrent implementation of vaccination and treatment is more impactful in mitigating the spread of the disease. Thus, it is imperative that media reports and health policy decision making on infectious diseases are contextualized.

Background The Coronavirus disease-19 (COVID-19) infection of severe acute respiratory syndrome coronavirus-2 (SARS-Cov-2) has emerged as a recent pandemic, increasing the need for epidemiological studies and studies on public health. Only some studies have evaluated the awareness of medical undergraduates in India and other countries, leading to a lack of literature. Methods This study is a descriptive cross-sectional questionnaire-based study conducted in Kasturba Medical College, Mangalore, India, between June to August 2020. An online survey using Google Forms was circulated among undergraduate medical students in India by a convenient sampling method for data collection. Descriptive analysis was derived based on frequencies and percentages, and the association with age, gender, and year of undergraduate training medical course was derived using the chi-square test. Results Altogether, 630 students from India responded to the survey, with a maximum response from students studying in the second year (38.7%). Nearly 63.85% of responders identified themselves as females. Knowledge regarding the human-to-human transmission of the virus, symptoms, complications, definition of “close contact, quarantine, and its indications was adequate among the students, with more than 70% correct responses. However, one-fourth of the students needed to gain more knowledge about masks. Respiratory hygiene was poor among 24.8%. Nearly 40% of students were unaware of the management of patients with COVID-19. Conclusion There is a need for regular quality training and institutional programs on infection control of COVID-19 and other infectious diseases across all Indian medical colleges to educate undergraduate medical students, who are future healthcare professionals, thus minimizing the risk of transmission and providing standardized care for patients.

Host-microbe interactions are complex and ever-changing, especially during infections, which can significantly impact human physiology in both health and disease by influencing metabolic and immune functions. Infections caused by pathogens such as bacteria, viruses, fungi, and parasites are the leading cause of global mortality. Microbes have evolved various immune evasion strategies to survive within their hosts, which presents a multifaceted challenge for detection. Intracellular microbes, in particular, target specific cell types for survival and replication and are influenced by factors such as functional roles, nutrient availability, immune evasion, and replication opportunities. Identifying intracellular microbes can be difficult because of the limitations of traditional culture-based methods. However, advancements in integrated host microbiome single-cell genomics and transcriptomics provide a promising basis for personalized treatment strategies. Understanding host-microbiota interactions at the cellular level may elucidate disease mechanisms and microbial pathogenesis, leading to targeted therapies. This article focuses on how intracellular microbes reside in specific cell types, modulating functions through persistence strategies to evade host immunity and prolong colonization. An improved understanding of the persistent intracellular microbe-induced differential disease outcomes can enhance diagnostics, therapeutics, and preventive measures.

ObjectiveThis study focuses on enhancing the precision of epidemic time series data prediction by integrating Gated Recurrent Unit (GRU) into a Graph Neural Network (GNN), forming the GRGNN. The accuracy of the GNN (Graph Neural Network) network with introduced GRU (Gated Recurrent Units) is validated by comparing it with seven commonly used prediction methods.MethodThe GRGNN methodology involves multivariate time series prediction using a GNN (Graph Neural Network) network improved by the integration of GRU (Gated Recurrent Units). Additionally, Graphical Fourier Transform (GFT) and Discrete Fourier Transform (DFT) are introduced. GFT captures inter-sequence correlations in the spectral domain, while DFT transforms data from the time domain to the frequency domain, revealing temporal node correlations. Following GFT and DFT, outbreak data are predicted through one-dimensional convolution and gated linear regression in the frequency domain, graph convolution in the spectral domain, and GRU (Gated Recurrent Units) in the time domain. The inverse transformation of GFT and DFT is employed, and final predictions are obtained after passing through a fully connected layer. Evaluation is conducted on three datasets: the COVID-19 datasets of 38 African countries and 42 European countries from worldometers, and the chickenpox dataset of 20 Hungarian regions from Kaggle. Metrics include Average Root Mean Square Error (ARMSE) and Average Mean Absolute Error (AMAE).ResultFor African COVID-19 dataset and Hungarian Chickenpox dataset, GRGNN consistently outperforms other methods in ARMSE and AMAE across various prediction step lengths. Optimal results are achieved even at extended prediction steps, highlighting the model’s robustness.ConclusionGRGNN proves effective in predicting epidemic time series data with high accuracy, demonstrating its potential in epidemic surveillance and early warning applications. However, further discussions and studies are warranted to refine its application and judgment methods, emphasizing the ongoing need for exploration and research in this domain.

Introduction: Climate and land use change may cause the geographical range of mosquitoes to expand, shift, or contract, ultimately changing what communities are at risk for contracting mosquito-borne diseases. Across North and South America, mosquitoes from the Aedes and Culex genera are vectors for numerous diseases, including chikungunya, dengue, various equine encephalitis viruses, Saint Louis encephalitis virus, West Nile virus, yellow fever virus, and Zika virus. The goal of our study was to project the geographical distributions of important mosquito vectors across North and South America in response to climate change, which is important to inform public health planning. Methods: We used an ecological niche model and future projections of climate and land use to project the geographical ranges of two Aedes species (Ae. aegypti, Ae. albopictus) and seven Culex species (Cx. erraticus, Cx. nigripalpus, Cx. pipiens, Cx. quinquefasciatus, Cx. restuans, Cx. salinarius, Cx. tarsalis) over North and South America in response to both a high (Shared Socioeconomic Pathway [SSP] 5, Representative Concentration Pathway [RCP] 8.5) and moderate (SSP2 RCP4.5) climate warming scenario through years 2050 and 2090. Results: For SSP5 RCP8.5, six species (Ae. aegypti, Ae. albopictus, Cx. erraticus, Cx. nigripalpus, Cx. quinquefasciatus, Cx. restuans) are projected to expand in geographical range, two species (Cx. pipiens, Cx. tarsalis) are projected to shift in geographical range, and one species (Cx. salinarius) is projected to nearly remain the same. Five species (Ae. aegypti, Ae. albopictus, Cx. erraticus, Cx. nigripalpus, Cx. quinquefasciatus) show the largest increase in high habitat suitability (>0.5 on a 0–1 scale) for SSP5 RCP8.5, three species (Cx. pipiens, Cx. restuans, Cx. tarsalis) show the largest increase for SSP2 RCP4.5, and one species (Cx. salinarius) shows a relatively small decrease in response to both scenarios. Conclusions: We found that all nine species responded resiliently to climate change under both the high and moderate climate warming scenario, suggesting mosquito-borne disease is likely to be a continued threat in response to climate change. The projected geographical ranges can be used to inform disease risk analyses and mitigation strategies in response to climate change.

The world has seen unprecedented gains in the global genomic surveillance capacities for pathogens with pandemic and epidemic potential within the last 4 years. To strengthen and sustain the gains made, WHO is working with countries and partners to implement the Global Genomic Surveillance Strategy for Pathogens with Pandemic and Epidemic Potential 2022–2032. A key technical product developed through these multi-agency collaborative efforts is a genomics costing tool (GCT), as sought by many countries. This tool was developed by five institutions – Association of Public Health Laboratories, FIND, The Global Fund to Fight AIDS, Tuberculosis and Malaria, UK Health Security Agency, and the World Health Organization. These institutions developed the GCT to support financial planning and budgeting for SARS-CoV-2 next-generation sequencing activities, including bioinformatic analysis. The tool costs infrastructure, consumables and reagents, human resources, facility and quality management. It is being used by countries to (1) obtain costs of routine sequencing and bioinformatics activities, (2) optimize available resources, and (3) build an investment case for the scale-up or establishment of sequencing and bioinformatics activities. The tool has been validated and is available in English and Russian at https://www.who.int/publications/i/item/9789240090866. This paper aims to highlight the rationale for developing the tool, describe the process of the collaborative effort in developing the tool, and describe the utility of the tool to countries.

Coxiella burnetii is a bacterial pathogen capable of causing serious disease in humans and abortions in goats. Infected goats can shed C. burnetii through urine, feces, and parturient byproducts, which can lead to infections in humans when the bacteria are inhaled. Goats are important C. burnetii reservoirs as evidenced by goat-related outbreaks across the world. To better understand the current landscape of C. burnetii infection in the domestic goat population, 4,121 vaginal swabs from 388 operations across the United States were analyzed for the presence of C. burnetii by IS1111 PCR as part of the United States Department of Agriculture, Animal Plant Health Inspection Service, Veterinary Services’ National Animal Health Monitoring System Goats 2019 Study. In total, 1.5% (61/4121) of swabs representing 10.3% (40/388) (weighted estimate of 7.8, 95% CI 4.4–13.5) of operations were positive for C. burnetii DNA. The quantity of C. burnetii on positive swabs was low with an average Ct of 37.9. Factors associated with greater odds of testing positive included suspected Q fever in the herd in the previous 3 years, the presence of wild deer or elk on the operation, and the utilization of hormones for estrus synchronization. Factors associated with reduced odds of testing positive include the presence of kittens and treatment of herds with high tannin concentrate plants, diatomaceous earth, and tetrahydropyrimidines. In vitro analysis demonstrated an inhibitory effect of the tetrahydropyrimidine, pyrantel pamoate, on the growth of C. burnetii in axenic media as low as 1 μg per mL. The final multivariable logistic regression modeling identified the presence of wild predators on the operation or adjacent property (OR = 9.0, 95% CI 1.3–61.6, p value = 0.0248) as a risk factor for C. burnetii infection.

The COVID-19 pandemic has necessitated the development of robust tools for tracking and modeling the spread of the virus. We present ‘K-Track-Covid,’ an interactive web-based dashboard developed using the R Shiny framework, to offer users an intuitive dashboard for analyzing the geographical and temporal spread of COVID-19 in South Korea. Our dashboard employs dynamic user interface elements, employs validated epidemiological models, and integrates regional data to offer tailored visual displays. The dashboard allows users to customize their data views by selecting specific time frames, geographic regions, and demographic groups. This customization enables the generation of charts and statistical summaries pertinent to both daily fluctuations and cumulative counts of COVID-19 cases, as well as mortality statistics. Additionally, the dashboard offers a simulation model based on mathematical models, enabling users to make predictions under various parameter settings. The dashboard is designed to assist researchers, policymakers, and the public in understanding the spread and impact of COVID-19, thereby facilitating informed decision-making. All data and resources related to this study are publicly available to ensure transparency and facilitate further research.

Abstract Objectives Hyperpyrexia has been associated with a greater prevalence of bacterial infections in the pediatric population, which prior to routine childhood vaccinations, has led to invasive testing and empiric antibiotic use for urinary tract infections, bacterial pneumonia, bacteremia, and bacterial meningitis. Since the implementation of routine childhood vaccinations, the prevalence of serious bacterial infections (SBIs) has declined. This study aims to determine if there is an association between hyperpyrexia and serious bacterial infections in well‐appearing febrile pediatric patients presenting to the emergency department (ED). Methods This is a cross‐sectional study conducted between January 1, 2019, and December 31, 2019, at a single urban tertiary care pediatric ED. Patients were included if they were between 61 days and ≤18 years old presenting with a chief complaint of fever. Patients were excluded if they received antibiotics within 3 days of presentation, underwent surgical procedures within 2 weeks of presentation, had an ED visit for febrile illness within 2 weeks of study visit, were transferred from another institution, or were ill appearing. Prevalence of SBI was described and compared by presence of hyperpyrexia, age group, chronic medical condition, gender, and vaccination status. Logistic regression was used to analyze the association between SBIs and hyperpyrexia. Results Of the 3862 charts reviewed, 2565 patients were included. The prevalence of SBI was 5.6%. A total of 413 patients presented with hyperpyrexia. Of the patients with hyperpyrexia, 31 (7.5%) had a serious bacterial infection. Hyperpyrexia was not significantly associated with SBIs in our logistic regression models (adjusted Odds Ratio 1.40, 95% confidence interval 0.92–2.12). Conclusions Serious bacterial infections were uncommon in our population. There is no statistically significant association between hyperpyrexia and SBIs in well‐appearing pediatric patients presenting to the ED with fever. The lack of a statistically significant association between hyperpyrexia and SBIs argues that clinicians should be cautious using hyperpyrexia as an independent risk factor for SBIs. More research is needed to identify independent and grouped SBI risk factors in well‐appearing pediatric patients presenting to the ED.

BackgroundTuberculosis (TB) is a major public health emergency in many countries, including Kazakhstan. Despite the decline in the incidence rate and having one of the highest treatment effectiveness in the world, the incidence rate of TB remains high in Kazakhstan. Social and environmental factors along with host genetics contribute to pulmonary tuberculosis (PTB) incidence. Due to the high incidence rate of TB in Kazakhstan, our research aimed to study the epidemiology and genetics of PTB in Kazakhstan.Materials and methods1,555 participants were recruited to the case–control study. The epidemiology data was taken during an interview. Polymorphisms of selected genes were determined by real-time PCR using pre-designed TaqMan probes.ResultsEpidemiological risk factors like diabetes (χ2 = 57.71, p

BackgroundAt the beginning of the year 2023, the Chatbot Generative Pre-Trained Transformer (ChatGPT) gained remarkable attention from the public. There is a great discussion about ChatGPT and its knowledge in medical sciences, however, literature is lacking to evaluate the ChatGPT knowledge level in public health. Therefore, this study investigates the knowledge of ChatGPT in public health, infectious diseases, the COVID-19 pandemic, and its vaccines.MethodsMultiple Choice Questions (MCQs) bank was established. The question’s contents were reviewed and confirmed that the questions were appropriate to the contents. The MCQs were based on the case scenario, with four sub-stems, with a single correct answer. From the MCQs bank, 60 MCQs we selected, 30 MCQs were from public health, and infectious diseases topics, 17 MCQs were from the COVID-19 pandemic, and 13 MCQs were on COVID-19 vaccines. Each MCQ was manually entered, and tasks were given to determine the knowledge level of ChatGPT on MCQs.ResultsOut of a total of 60 MCQs in public health, infectious diseases, the COVID-19 pandemic, and vaccines, ChatGPT attempted all the MCQs and obtained 17/30 (56.66%) marks in public health, infectious diseases, 15/17 (88.23%) in COVID-19, and 12/13 (92.30%) marks in COVID-19 vaccines MCQs, with an overall score of 44/60 (73.33%). The observed results of the correct answers in each section were significantly higher (p = 0.001). The ChatGPT obtained satisfactory grades in all three domains of public health, infectious diseases, and COVID-19 pandemic-allied examination.ConclusionChatGPT has satisfactory knowledge of public health, infectious diseases, the COVID-19 pandemic, and its vaccines. In future, ChatGPT may assist medical educators, academicians, and healthcare professionals in providing a better understanding of public health, infectious diseases, the COVID-19 pandemic, and vaccines.

BackgroundIn an era wherein, persuasive evidence continues to witness the association between systemic and periodontal diseases, the absence of scientific data on dental professionals’ comprehension concerning the HIV infection and periodontal link is lamentably backward. Thus, the key objective of this research is to ascertain the extent of comprehension possessed by dentists and dental hygienists concerning periodontal implications and their management in HIV patients.MethodsIt is a quantitative cross-sectional survey employing a descriptive approach focusing on a specific cohort of dental professionals. The study setting featured an online platform for the distribution of concealed, closed-ended, structured questionnaire. The data was gathered for four sections: six comprehension statements about periodontal manifestations in HIV patients; fifteen comprehension statements about HIV patients’ periodontal management; eight familiarity statements about HIV management; and two educational statements about HIV. The comparisons of comprehension scores were drawn between variables such as specialties, age groups, and genders.ResultsThe survey represented 468 dental professionals representing distinct dental specialties, with a mean age of 24.26 ± 7.53 years. The mean comprehension score for all groups of participants is 10.31 ± 9.34 (33.25%). The highest scores were recorded among those aged 31–40 (20.67 ± 8.31), followed by those aged 40+ (19.38 ± 9.39), 20–30 (9.53 ± 8.96), and under 20 (8.92 ± 8.57), at p

Pesantren is an Islamic educational institution that provides religious education services. Pesantren usually provides dormitories for students, where many people live in one location, resulting in crowded living conditions for an extended period. If anyone who infected an infectous disease which can easily transmit to other, and moreover this can lead to an outbreak which can lead enormous losses. Therefore, we want to do an analysis situation of infectious disease that happened in Pondok Pesantren X. We managed to interview 102 santri and observed some dormitory room. Based on our analysis on the infectious disease situation, we can conclude that the diseases recorded in the clinic do not encompass all illnesses experienced by the students. Common infectious diseases among students in the Pondok Pesantren not only scabies as many people says so, there are also acute respiratory infections, gastroenteritis, typhoid, COVID-19, tuberculosis (TBC), and dengue fever (DBD). We suggest the Caregiver and administrators of the Pondok Pesantren can encourage students to avoid risky behaviors leading to infectious diseases.

Randomized trials are widely regarded as providing the most robust evidence for guiding patient management and informing public health policy. A typical individual-randomized trial (IRT) randomly assigns individual participants into treatment and control groups and then compares their outcomes to estimate the intervention effect. However, sometimes individual randomization may not be feasible or optimal, prompting the consideration of a cluster-randomized trial (CRT), where groups of individuals are randomly assigned to different treatment conditions. When aiming to assess the broad population effects of an intervention, a cluster-randomized design is often used. In certain scenarios, the intervention is designed to be delivered to groups of individuals. [ABSTRACT FROM AUTHOR]