The NIAID Data Ecosystem Discovery Portal (https://data.niaid.nih.gov) provides a unified search interface for over 4 million datasets relevant to infectious and immune-mediated disease (IID) research. Integrating metadata from domain-specific and generalist repositories, the Portal enables researchers to identify and access datasets using user-friendly filters or advanced queries, without requiring technical expertise. The Portal supports discovery of a wide range of resources, including epidemiological, clinical, and multi-omic datasets, and is designed to accommodate exploratory browsing and precise searches. The Portal provides filters, prebuilt queries, and dataset collections to simplify the discovery process for users. The Portal additionally provides documentation and an API for programmatic access to harmonized metadata. By easing access barriers to important biomedical datasets, the NIAID Data Ecosystem Discovery Portal serves as an entry point for researchers working to understand, diagnose, or treat IID. Valuable datasets are often overlooked because they are difficult to locate. The NIAID Data Ecosystem Discovery Portal fills this gap by providing a centralized, searchable interface that empowers users with varying levels of technical expertise to find and reuse data. By standardizing key metadata fields and harmonizing heterogeneous formats, the Portal improves data findability, accessibility, and reusability. This resource supports hypothesis generation, comparative analysis, and secondary use of public data by the IID research community, including those funded by NIAID. The Portal supports data sharing by standardizing metadata and linking to source repositories, and maximizes the impact of public investment in research data by supporting scientific advancement via secondary use.
Nitish Vikas Deshpande, Miguel Rodrigo Castellanos, Saeed R. Khosravirad
et al.
A parasitic reconfigurable antenna array is a low-power approach for beamforming using passive tunable elements. Prior work on reconfigurable antennas in communication theory is based on ideal radiation pattern abstractions. It does not address the problem of physical realizability. Beamforming with parasitic elements is inherently difficult because mutual coupling creates non-linearity in the beamforming gain objective. We develop a multi-port circuit-theoretic model of the hybrid array with parasitic elements and antennas with active RF chain validated through electromagnetic simulations with a dipole array. We then derive the beamforming weight of the parasitic element using the theoretical beam pattern expression for the case of a single active antenna and multiple parasitic elements. We show that the parasitic beamforming is challenging because the weights are subject to coupled magnitude and phase constraints. We simplify the beamforming optimization problem using a shift-of-origin transformation to the typical unit-modulus beamforming weight. With this transformation, we derive a closed-form solution for the reconfigurable parasitic reactance. We generalize this solution to the multi-active multi-parasitic hybrid array operating in a multi-path channel. Our proposed hybrid architecture with parasitic elements outperforms conventional architectures in terms of energy efficiency.
Francisca Ogochukwu Onukansi, Collins Chibueze Anokwuru, Stanley Chinedu Eneh
et al.
Abstract Traditional medicine (TM) has been a cornerstone of healthcare across various cultures, especially in Africa, where it has played an integral role in the management of diseases such as malaria. Despite the popularity and historical significance of TM, scientific validation remains a key challenge, hindering its widespread acceptance in modern healthcare systems. This study explores the potential of traditional African medicine, particularly in the context of Nigeria, as a vital resource in the fight against malaria. Drawing on the success of plants like Artemisia annua in the development of modern anti-malarial drugs, the research emphasizes the need for comprehensive investment in TM research. With Nigeria facing the highest malaria burden globally, the research advocates for increased funding, scientific investigations into the efficacy of traditional remedies, and enhanced regulation of herbal medicine. The paper also highlights the growing trust and reliance on herbal remedies in rural areas of Nigeria and the importance of ensuring their safety through pharmacological testing. This study examines these issues through an analysis of existing literature, historical applications, and documented successes of herbal treatments. By integrating traditional medicine into national health systems, Nigeria could unlock new strategies for combating malaria and other infectious diseases, advancing toward sustainable health outcomes.
Arctic medicine. Tropical medicine, Infectious and parasitic diseases
Aubrey Sawyer, Cara Ray, James Stacey Klutts
et al.
Background: Carbapenem-resistant Acinetobacter baumannii (CRAB) and Pseudomonas aeruginosa (CRPA) are drug-resistant pathogens causing high mortality rates with limited treatment options. Understanding the incidence of these organisms and laboratory knowledge of testing protocols is important for controlling their spread in healthcare settings. This project assessed how often Veterans Affairs (VA) healthcare facilities identify CRAB and CRPA and testing practices used. Method: An electronic survey was distributed to 126 VA acute care facilities September-October 2023. The survey focused on CRAB and CRPA incidence, testing and identification, and availability of testing resources. Responses were analyzed by complexity of patients treated at VA facilities (High, Medium, Low) using Fisher’s exact tests. Result: 77 (61.1%) facilities responded, most in urban settings (85.4%). Most respondents were lead or supervisory laboratory technologists (84.2%) from high complexity facilities (69.0%). Few facilities detected CRAB ≥ once/month (4.4%), with most reporting that they have not seen CRAB at their facility (55.0%). CRPA was detected more frequently: 19% of facilities with isolates ≥ once/month, 29.2% a few times per year, and 26.9% reporting had not seen the organism. No differences in CRAB or CRPA incidence was found by facility complexity. Nearly all facilities, regardless of complexity, utilize the recommended methods of MIC or disk diffusion to identify CRAB or CRPA (91.9%) with remaining facilities reporting that testing is done off-site (7.8%). More high complexity facilities perform on-site testing compared to low complexity facilities (32.0% vs 2.7%, p=0.04). 83% of laboratories test for Carbapenemase production, with one-fourth using off-site reference labs. One-fourth of facilities perform additional antibiotic susceptibility testing for CRAB and CRPA isolates, most of which test for susceptibility to combination antibiotics; no differences between complexities were found. Agreement that sufficient laboratory and equipment resources were available was higher in high complexity than in medium complexity facilities (70.7% vs 33.3%, p=0.01), but not low complexity facilities (43.8%). Conclusion: Having timely and accurate testing protocols for CRAB and CRPA are important to quickly control spread and reduce associated mortality. This study shows that most VA protocols follow recommended testing and identification guidelines. Interestingly, there was no difference in CRAB or CRPA incidence for facilities providing higher vs lower complexity of care. While high and low complexity facilities generally reported sufficient resources for CRAB and CRPA evaluation, some medium-complexity labs, who may feel more compelled than low-complexity labs to bring testing in house, reported that additional resources would be required.
Infectious and parasitic diseases, Public aspects of medicine
Andrea Radici, Daniele Bevacqua, Leonardo Miele
et al.
Increasing cultivated lands, crop homogenization and global food trade have fostered the spread of crop pests and diseases. Optimizing crop protection is urgently needed to ensure food safety. One aspect of crop protection is surveillance, which focuses on the early detection of a parasite, and control, aiming to fight and possibly eradicate it. Network theory has been widely used to model the spread of human and animal infectious diseases in systems described through nodes and edges. It has been successfully used to optimize monitoring and immunization campaigns. In crop protection, there is a growing literature using this theory to describe parasites spread and to conceive protection strategies. Here we review the use of network theory in crop protection, from the more descriptive to the more applied approaches aimed to optimize crop protection. We retrace the logical process that has led epidemiological models to rely on network theory, and we provide examples of how the spread of crop parasites has been represented via a network description. We define the objectives of surveillance and control, and we show how these have been declined in the network-based epidemiological sphere and then adapted in the agricultural context. We eventually discuss the discrepancy between the application of network theory in surveillance and control to identify culprits and solutions. We find that: i) scientists have successfully interpreted very different modes of parasitic transmission under the lens of network theory; ii) while network-based surveillance has progressively clarified its objectives and sound tools have been proposed, network-based control has been less studied and applied; iii) network-thinking must address how to properly define edges and nodes at different geographic scale to broad its application in crop protection.
Mahdi Salehi, Samuel Manda, Mohammad Arashi
et al.
The COVID-19 pandemic caused major disruptions and contributed to the loss of livelihoods and income. The pandemic also provided public health and health systems policy shifts towards better promotion and protection in responding to such disasters and emergencies. Due to differing effects of socio-economic infectious disease vulnerabilities and pre-pandemic levels of preparedness for health emergencies, health system strengthening requires targeted and ununiform implementation. We employ spatial statistical methods on the COVID-19 confirmed cases in identifying wards that could be targeted for strengthening health security in the Gauteng Province, South Africa. In this way, the identified high-risk wards would be more effective and prepared to respond to future pandemics and emergencies.
Sebastian Contreras, Karen Y. Oróstica, Anamaria Daza-Sanchez
et al.
Genomic surveillance of infectious diseases allows monitoring circulating and emerging variants and quantifying their epidemic potential. However, due to the high costs associated with genomic sequencing, only a limited number of samples can be analysed. Thus, it is critical to understand how sampling impacts the information generated. Here, we combine a compartmental model for the spread of COVID-19 (distinguishing several SARS-CoV-2 variants) with different sampling strategies to assess their impact on genomic surveillance. In particular, we compare adaptive sampling, i.e., dynamically reallocating resources between screening at points of entry and inside communities, and constant sampling, i.e., assigning fixed resources to the two locations. We show that adaptive sampling uncovers new variants up to five weeks earlier than constant sampling, significantly reducing detection delays and estimation errors. This advantage is most prominent at low sequencing rates. Although increasing the sequencing rate has a similar effect, the marginal benefits of doing so may not always justify the associated costs. Consequently, it is convenient for countries with comparatively few resources to operate at lower sequencing rates, thereby profiting the most from adaptive sampling. Finally, our methodology can be readily adapted to study undersampling in other dynamical systems.
Mathematical models of infectious disease transmission typically neglect within-host dynamics. Yet within-host dynamics - including pathogen replication, host immune responses, and interactions with microbiota - are crucial not only for determining the progression of disease at the individual level, but also for driving within-host evolution and onwards transmission, and therefore shape dynamics at the population level. Various approaches have been proposed to model both within- and between-host dynamics, but these typically require considerable simplifying assumptions to couple processes at contrasting scales (e.g., the within-host dynamics quickly reach a steady state) or are computationally intensive. Here we propose a novel, readily adaptable and broadly applicable method for modelling both within- and between-host processes which can fully couple dynamics across scales and is both realistic and computationally efficient. By individually tracking the deterministic within-host dynamics of infected individuals, and stochastically coupling these to continuous host state variables at the population-level, we take advantage of fast numerical methods at both scales while still capturing individual transient within-host dynamics and stochasticity in transmission between hosts. Our approach closely agrees with full stochastic individual-based simulations and is especially useful when the within-host dynamics do not rapidly reach a steady state or over longer timescales to track pathogen evolution. By applying our method to different pathogen growth scenarios we show how common simplifying assumptions fundamentally change epidemiological and evolutionary dynamics.
Arindam Saha, Maziar Ghorbani, Diana Suleimenova
et al.
Agent-based models are widely used to predict infectious disease spread. For these predictions, one needs to understand how each input parameter affects the result. Here, some parameters may affect the sensitivities of others, requiring the analysis of higher order coefficients through e.g. Sobol sensitivity analysis. The geographical structures of real-world regions are distinct in that they are difficult to reduce to single parameter values, making a unified sensitivity analysis intractable. Yet analyzing the importance of geographical structure on the sensitivity of other input parameters is important because a strong effect would justify the use of models with real-world geographical representations, as opposed to stylized ones. Here we perform a grouped Sobol's sensitivity analysis on COVID-19 spread simulations across a set of three diverse real-world geographical representations. We study the differences in both results and the sensitivity of non-geographical parameters across these geographies. By comparing Sobol indices of parameters across geographies, we find evidence that infection rate could have more sensitivity in regions where the population is segregated, while parameters like recovery period of mild cases are more sensitive in regions with mixed populations. We also show how geographical structure affects parameter sensitivity changes over time.
In this paper we study a nonlinear reaction-diffusion system which models an infectious disease caused by bacteria such as those for cholera. One of the significant features in this model is that a certain portion of the recovered human hosts may lose a lifetime immunity and could be infected again. Another important feature in the model is that the mobility for each species is allowed to be dependent upon both the location and time. With the whole population assumed to be susceptible with the bacteria, the model is a strongly coupled nonlinear reaction-diffusion system. We prove that the nonlinear system has a unique solution globally in any space dimension under some natural conditions on the model parameters and the given data. Moreover, the long-time behavior and stability analysis for the solutions are carried out rigorously. In particular, we characterize the precise conditions on variable parameters about the stability or instability of all steady-state solutions. These new results provide the answers to several open questions raised in the literature.
Sanmitra Ghosh, Paul J. Birrell, Daniela De Angelis
Modelling the transmission dynamics of an infectious disease is a complex task. Not only it is difficult to accurately model the inherent non-stationarity and heterogeneity of transmission, but it is nearly impossible to describe, mechanistically, changes in extrinsic environmental factors including public behaviour and seasonal fluctuations. An elegant approach to capturing environmental stochasticity is to model the force of infection as a stochastic process. However, inference in this context requires solving a computationally expensive ``missing data" problem, using data-augmentation techniques. We propose to model the time-varying transmission-potential as an approximate diffusion process using a path-wise series expansion of Brownian motion. This approximation replaces the ``missing data" imputation step with the inference of the expansion coefficients: a simpler and computationally cheaper task. We illustrate the merit of this approach through two examples: modelling influenza using a canonical SIR model, and the modelling of COVID-19 pandemic using a multi-type SEIR model.
Bardia Hejazi, Oliver Schlenczek, Birte Thiede
et al.
Airborne diseases can be transmitted by infectious aerosols in the near field, i.e., in close proximity, or in the far field, i.e., by infectious aerosols that are well mixed within the indoor air. Is it possible to say which mode of disease transmission is predominant in large indoor spaces? We addressed this question by measuring the transport of aerosols equivalent to the size of human respiratory particles in two large hardware stores (V>10000 m$^3$). We found that aerosol concentrations in both stores decreased rapidly and almost independently of aerosol size, despite the different ventilation systems. A persistent and directional airflow on the order of a few cm/s was observed in both stores. Consequently, aerosol dynamics in such open settings can be expected to be dominated by turbulent dispersion and sweeping, and the accumulation of infectious aerosols in the indoor air is unlikely to contribute significantly to the risk of infection as long as the occupancy of the store is not too high. Under these conditions, well-fitting face masks are an excellent means of preventing disease transmission by human aerosols.
Aref Shariati, Shabnam Razavi, Ehsanollah Ghaznavi-Rad
et al.
Abstract Background and aim Recent studies have proposed that commensal bacteria might be involved in the development and progression of gastrointestinal disorders such as colorectal cancer (CRC). Therefore, in this study, the relative abundance of Fusobacterium nucleatum, Bacteroides fragilis, Streptococcus bovis/gallolyticus, and Enteropathogenic Escherichia coli (EPEC) in CRC tissues, and their association with clinicopathologic characteristics of CRC was investigated in Iranian patients. Moreover, the role of these bacteria in the CRC-associated mutations including PIK3CA, KRAS, and BRAF was studied. Method To these ends, the noted bacteria were quantified in paired tumors and normal tissue specimens of 30 CRC patients, by TaqMan quantitative Real-Time Polymerase Chain Reaction (qPCR). Next, possible correlations between clinicopathologic factors and mutations in PIK3CA, KRAS, and BRAF genes were analyzed. Results In studied samples, B. fragilis was the most abundant bacteria that was detected in 66 and 60% of paired tumor and normal samples, respectively. Furthermore, 15% of the B. fragilis-positive patients were infected with Enterotoxigenic B. fragilis (ETBF) in both adenocarcinoma and matched adjacent normal samples. F. nucleatum was also identified in 23% of tumors and 13% of adjacent normal tissue samples. Moreover, the relative abundance of these bacteria determined by 2-ΔCT was significantly higher in CRC samples than in adjacent normal mucosa (p < 0.05). On the other hand, our findings indicated that S. gallolyticus and EPEC, compared to adjacent normal mucosa, were not prevalent in CRC tissues. Finally, our results revealed a correlation between F. nucleatum-positive patients and the KRAS mutation (p = 0.02), while analyses did not show any association between bacteria and mutation in PIK3CA and BRAF genes. Conclusion The present study is the first report on the analysis of different bacteria in CRC tissue samples of Iranian patients. Our findings revealed that F. nucleatum and B. fragilis might be linked to CRC. However, any link between gut microbiome dysbiosis and CRC remains unknown.
Neoplasms. Tumors. Oncology. Including cancer and carcinogens, Infectious and parasitic diseases
The aim of this study is to analyze data on the structure and dynamics of imported parasitic diseases and the potential risk of local spread of already eradicated diseases, and of those that do not have local spread so far, but there are environmental conditions for their occurrence. Material and Methods. This is a retrospective cross-sectional analysis of imported parasitic diseases in the country for a seven-year period. We used data from the annual analyzes of parasitic morbidity developed by the NCIPD, data from the diagnostic and reference activity of the National Reference Laboratory for Diagnosis of Parasitic Diseases, and data from the annual reports of the Regional Health Inspectorates. Results. During the period 2014-2020, 22 862 persons were studied, of whom 896 (3.9%) were Bulgarian citizens and 21 966 (96.1%) were foreigners. Imported parasite diseases were found in 794 people (prevalence 3.47%). Different types of parasites causing pathology of the gastrointestinal tract accounted for 87.53% (n = 695) of the identified pathogens, while the relative share of vector-borne parasitic diseases was 12.47% (malaria 11.09%, visceral and cutaneous leishmaniasis 1.38%). Conclusion. There are favorable climate and fauna conditions in the country for the local spread of a number of parasitic diseases. Control measures with respect to this pathology are associated with timely detection and remediation of the source of infection. In the country, there is an algorithm for diagnosis, hospitalization, treatment, prevention and control of imported parasitic diseases, but it is difficult to be applied to migrants entering in the country illegally. The deficiencies in the surveillance and control of imported parasitic diseases pose a real danger for a local spread of already eradicated parasitic diseases, such as malaria, and from outbreaks of diseases that do not have local spread till the present moment.