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At least 109 records · Page 6
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

The Novel Carbapenem, JDB/PQ-1-219, Has Potent Broad Spectrum Activity against Multi-Drug Resistant Acinetobacter baumannii

Carbapenem resistance in Acinetobacter baumannii, driven largely by class D, along with class A and class B β- lactamases, has severely compromised the utility of these last resort antibiotics. As a result, infections caused by such pathogens are characterized by extremely high mortality rates. Here we describe the antimicrobial activity of the novel C5 methyl-substituted carbapenem JDB/PQ-1−219 against multidrug resistant A. baumannii and the mechanism of its interaction with its major carbapenemase, OXA-23. JDB/PQ-1-219 exhibits potent antimicrobial activity against A. baumannii producing various carbapenemases, with MICs that are all in the clinically susceptible range. The compound has unrestricted ingress through porins and avoids egress by efflux pumps, a unique property when compared to all commercial carbapenems. Kinetic experiments demonstrated that unlike for other carbapenems, acylation of OXA-23 by JDB/ PQ-1-219 is monophasic, and mass spectrometry studies showed that this results from the conversion of all enzyme into a reversible tetrahedral intermediate which gradually transitions into the stable acyl-enzyme complex. No deacylation of this complex is observed over a physiologically relevant time period, making JDB/PQ-1−219 an extremely potent inhibitor of OXA-23. Time-resolved crystallography revealed fine details of active site dynamics, leading to complete inhibition of the enzyme. Together, these studies identify JDB/PQ-1-219 as a uniquely effective novel carbapenem with clinically significant levels of activity against multidrug resistant A. baumannii.

Acinetobacter baumannii↗
DOE OSTI2021

Validating deep learning inference during chest X-ray classification for COVID-19 screening

Abstract The new coronavirus unleashed a worldwide pandemic in early 2020, and a fatality rate several times that of the flu. As the number of infections soared, and capabilities for testing lagged behind, chest X-ray (CXR) imaging became more relevant in the early diagnosis and treatment planning for patients with suspected or confirmed COVID-19 infection. In a few weeks, proposed new methods for lung screening using deep learning rapidly appeared, while quality assurance discussions lagged behind. This paper proposes a set of protocols to validate deep learning algorithms, including our ROI Hide-and-Seek protocol, which emphasizes or hides key regions of interest from CXR data. Our protocol allows assessing the classification performance for anomaly detection and its correlation to radiological signatures, an important issue overlooked in several deep learning approaches proposed so far. By running a set of systematic tests over CXR representations using public image datasets, we demonstrate the weaknesses of current techniques and offer perspectives on the advantages and limitations of automated radiography analysis when using heterogeneous data sources.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Modeling the emergence of viral resistance for SARS-CoV-2 during treatment with an anti-spike monoclonal antibody

To mitigate the loss of lives during the COVID-19 pandemic, emergency use authorization was given to several anti-SARS-CoV-2 monoclonal antibody (mAb) therapies for the treatment of mild-to-moderate COVID-19 in patients with a high risk of progressing to severe disease. Monoclonal antibodies used to treat SARS-CoV-2 target the spike protein of the virus and block its ability to enter and infect target cells. Monoclonal antibody therapy can thus accelerate the decline in viral load and lower hospitalization rates among high-risk patients with variants susceptible to mAb therapy. However, viral resistance has been observed, in some cases leading to a transient viral rebound that can be as large as 3–4 orders of magnitude. As mAbs represent a proven treatment choice for SARS-CoV-2 and other viral infections, evaluation of treatment-emergent mAb resistance can help uncover underlying pathobiology of SARS-CoV-2 infection and may also help in the development of the next generation of mAb therapies. Although resistance can be expected, the large rebounds observed are much more difficult to explain. We hypothesize replenishment of target cells is necessary to generate the high transient viral rebound. Thus, we formulated two models with different mechanisms for target cell replenishment (homeostatic proliferation and return from an innate immune response antiviral state) and fit them to data from persons with SARS-CoV-2 treated with a mAb. We showed that both models can explain the emergence of resistant virus associated with high transient viral rebounds. We found that variations in the target cell supply rate and adaptive immunity parameters have a strong impact on the magnitude or observability of the viral rebound associated with the emergence of resistant virus. Both variations in target cell supply rate and adaptive immunity parameters may explain why only some individuals develop observable transient resistant viral rebound. Our study highlights the conditions that can lead to resistance and subsequent viral rebound in mAb treatments during acute infection.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2021

The SARS-CoV-2 Spike Variant D614G Favors an Open Conformational State

The COVID-19 pandemic underwent a rapid transition with the emergence of a dominant viral variant (from the “D-form” to the “G-form”) that carried an amino acid substitution D614G in its “Spike” protein. The G-form is more infectious in vitro and associated with increased viral loads. To gain insight into the molecular-level underpinnings of these characteristics, we employed microsecond all-atom simulations. Here we show that changes in the protein energetics favor a higher population of infection-capable (open) states through release of hydrogen bonds of an asymmetry present in the D-form but not the G-form. Thus, the increased infectivity of the G-form is likely due to a higher rate of profitable binding encounters with the host receptor. It is also predicted to be more neutralization sensitive due to enhanced exposure of the receptor binding domain, a key target region for neutralizing antibodies. These results are significant for vaccine design. The Molecular Dynamics Simulations datasets generated in this study, namely that of the soluble form SARS-CoV-2 Spike protein are made available here. Details of the trajectory and supporting files are given in the README.txt file.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

GenAI-Based Digital Twins Aided Data Augmentation Increases Accuracy in Real-Time Cokurtosis-Based Anomaly Detection of Wearable Data

Early detection of potential infectious disease outbreaks is crucial for developing effective interventions. In this study, we introduce advanced anomaly detection methods tailored for health datasets collected from wearables, offering insights at both individual and population levels. Leveraging real-world physiological data from wearables, including heart rate and activity, we developed a framework for the early detection of infection in individuals. Despite the availability of data from recent pandemics, substantial gaps remain in data collection, hindering method development. To bridge this gap, we utilized Wasserstein Generative Adversarial Networks (WGANs) to generate realistic synthetic wearable data, augmenting our dataset for training. Subsequently, we use these augmented datasets to implement a cokurtosis-based technique for anomaly detection in multivariate time-series data. Our approach includes a comprehensive assessment of uncertainties in synthetic data compared to the actual data upon which it was modeled, as well as the uncertainty associated with fine-tuning anomaly detection thresholds in physiological measurements. Through our work, we present an enhanced method for early anomaly detection in multivariate datasets, with promising applications in healthcare and beyond. This framework could revolutionize early detection strategies and significantly impact public health response efforts in future pandemics.

Data-Driven Digital Twins↗
DOE OSTI2023

PANDEMIC: Occupancy driven predictive ventilation control to minimize energy consumption and infection risk

During the SARS-CoV-2 (COVID-19) pandemic, governments around the world have formulated policies requiring ventilation systems to operate at a higher outdoor fresh air flow rate for a sufficient time, which has led to a sharp increase in building energy consumption. Therefore, it is necessary to identify an energy-efficient ventilation strategy to reduce the risk of infection. In this study, we developed an occupant-number-based model predictive control (OBMPC) algorithm for building ventilation systems. First, we collected the occupancy and Heating, ventilation, and air conditioning system (HVAC) data from March to July 2021. Then, four different models (Auto regression moving average-based multilayer perceptron (ARMA_MLP), Recurrent neural networks (RNN), Long short-term memory networks (LSTM), and Nonhomogeneous Markov with change points detection (NH_Markov)) were used to predict the number of room occupants from 15 min to 24 h ahead with an interval output. We found that each model could predict the number of occupants with 85% accuracy using a one-person offset. Furthermore, the accuracy of 15 min of the ahead prediction could reach 95% with a one-person offset, but none of them could track abrupt changes. The occupancy prediction results were used to calculate the ventilation demand using the Wells-Riley equation, and the upper bound can maintain an infection risk lower than 2% for 93% of the day. This OBMPC model could reduce the coil load by 52.44% and shift the peak load by 3 h up to 5 kW compared with 24 × 7 h full outdoor air (OA) system when people wear masks in the space. The occupancy prediction uncertainty could cause a 9% to 26% difference in demand ventilation, a 0.3°C to 2.4°C difference in zone temperature, a 28.5% to 44.5% difference in outdoor airflow rate, and a 10.7% to 28.2% difference in coil load.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2021

Integrin alpha 6 as a stemness driver is a novel promising target for HPV (+) head and neck squamous cell carcinoma

Although the incidence rates of head and neck squamous cell carcinoma (HNSCC) associated with human papilloma virus (HPV) infection have recently been on the rise, the underlying mechanism of its tumorigenesis remains largely unknown. Here, we investigated whether HNSCC cells with high expression of integrin alpha 6 (ITGα6), one of the HPV receptors, have a preference during HPV infection. In addition, we examined the gain or loss of function of the ITGα6 gene in HPV + ve HNSCC cells, as well as its prognostic value in patients with HNSCC. HPV pseudovirus was found to be more infective, with HNSCC cells featuring an overexpressed ITGα6 gene compared to the control cells. Overexpression and suppression of ITGα6 respectively increases and decreases stemness phenotypes of HPV + ve HNSCC cells. Furthermore, ITGα6 can regulate stemness by partially mediating AKT pathway in HPV + ve HNSCC cells. Finally, patients with HPV + ve HNSCC had a poor prognosis in cases of elevated ITGα6 expression; however, the expression levels of ITGα6 did not influence the survival rates of HPV-negative HNSCC patients. In conclusion, ITGα6 can serve as a potential therapeutic target for HPV + ve HNSCC cancer-like stem cells (CSCs).

60 APPLIED LIFE SCIENCES↗
DOE OSTI2020

Epidemiological surveillance of common respiratory viruses in patients with suspected COVID-19 in Southwest China

Abstract Background The outbreak of coronavirus disease 2019 (COVID-19) caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is currently the peak season of common respiratory viral infections. However, the clinical symptoms of most SARS-CoV-2 infected patients are not significantly different from those of common respiratory viral infections. Therefore, knowing the epidemiological patterns of common respiratory viruses may be valuable to improve the diagnostic and therapeutic efficacy of patients with suspected COVID-19, especially in Southwest China (a mild epidemic area). Methods A total of 2188 patients with clinically suspected of COVID-19 in Southwest China were recruited from January 21 to February 29, 2020. Nasopharyngeal swabs, throat swabs and sputum specimens were collected to detect SARS-CoV-2 by using real-time reverse transcription-polymerase chain reaction (RT-PCR) and other 12 viruses via PCR fragment analysis combined with capillary electrophoresis. Clinical characteristics and laboratory test findings were acquired from electronic medical records. All data were analyzed to unravel the epidemiological patterns. Results Only 1.1% (24/2188) patients with suspected COVID-19 were eventually confirmed to have SARS-CoV-2 infection, and the most frequently observed symptoms were fever (75.0%, 18/24) and cough (20.8%, 5/24). The overall detection rate of other respiratory pathogens was 10.3% (226/2188). Among them, human rhinovirus (3.2%, 71/2188), human parainfluenza viruses (1.6%, 35/2188), influenza B virus (1.2%, 26/2188) and mycoplasma pneumonia (1.2%, 26/2188) were the predominantly detected pathogens in this study. Moreover, the co-infection was observed in 22 specimens. Notably, one COVID-19 case had a coexisting infection with human parainfluenza virus (4.2%, 1/24) and bocavirus was the most common virus tending to occur in co-infection with other respiratory pathogens. Conclusions This study reveals the epidemiological features of common respiratory viruses and their clinical impact during the ongoing outbreak of COVID-19 in a mild epidemic area. The findings highlight the importance of understanding the transmission patterns of the common respiratory virus in COVID-19 regions, which can provide information support for the development of appropriate treatment plans and health policies, while eliminating unnecessary fear and tension.

Si, Yanjun↗
DOE OSTI2026

Vicennial metagenomic time series unveils evolutionary dynamics of giant viruses in a freshwater ecosystem

Giant viruses play crucial ecological roles in aquatic ecosystems, yet their evolutionary dynamics in response to environmental changes, particularly in freshwater environments, are not well understood. We analyzed a 20-year time series (2000-2019) of 471 co-assembled metagenomes from Lake Mendota (USA) to reconstruct 1512 giant virus metagenome-assembled genomes, providing insights into viral genome evolution. Viruses in the order Imitervirales dominate the virome, remaining consistent across seasons and years. Our findings reveal gene duplication (23% of genes) and horizontal gene transfer (29% of genes) as key drivers of genomic innovation. A co-occurrence network analysis indicates increased virus-host interactions following the introduction of an invasive predatory zooplankton in 2009, highlighting potential hosts in Bigyra, Perkinsea, and Euglenozoa. While single nucleotide polymorphism analysis shows predominantly purifying selection in viral genes, there is a significant increase in positively selected genes post-invasion, particularly those related to infection. Comparative evolutionary analyses reveal that giant viruses exhibit genome-wide substitution rates similar to co-occurring bacteria but significantly slower than smaller dsDNA phages, suggesting both stability and adaptability. Our study demonstrates that freshwater giant viruses employ various evolutionary strategies to respond to environmental change. These results underscore their significant yet often underappreciated role in freshwater ecosystem dynamics.

Vasquez, Yumary M↗
DOE OSTI2020

Small Particle Aerosol Exposure of African Green Monkeys to MERS-CoV as a Model for Highly Pathogenic Coronavirus Infection

Emerging coronaviruses are a global public health threat because of the potential for person-to-person transmission and high mortality rates. Middle East respiratory syndrome coronavirus (MERS-CoV) emerged in 2012, causing lethal respiratory disease in $\gg$35% of cases. Primate models of coronavirus disease are needed to support development of therapeutics, but few models exist that recapitulate severe disease. For initial development of a MERS-CoV primate model, 12 African green monkeys were exposed to 10 3 , 10 4 , or 10 5 PFU target doses of aerosolized MERS-CoV. We observed a dose-dependent increase of respiratory disease signs, although all 12 monkeys survived for the 28-day duration of the study. This study describes dosedependent effects of MERS-CoV infection of primates and uses a route of infection with potential relevance to MERSCoV transmission. Aerosol exposure of African green monkeys might provide a platform approach for the development of primate models of novel coronavirus diseases.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Deletion of E184L, a Putative DIVA Target from the Pandemic Strain of African Swine Fever Virus, Produces a Reduction in Virulence and Protection against Virulent Challenge

African swine fever (ASF) is currently causing a major pandemic affecting the swine industry and protein availability from Central Europe to East and South Asia. No commercial vaccines are available, making disease control dependent on the elimination of affected animals. Here, we show that the deletion of the African swine fever virus (ASFV) E184L gene from the highly virulent ASFV Georgia 2010 (ASFV-G) isolate produces a reduction in virus virulence during the infection in swine. Of domestic pigs intramuscularly inoculated with a recombinant virus lacking the E184L gene (ASFV-GDE184L), 40% experienced a significantly (5 days) delayed presentation of clinical disease and, overall, had a 60% rate of survival compared to animals inoculated with the virulent parental ASFV-G. Importantly, all animals surviving ASFV-G-DE184L infection developed a strong antibody response and were protected when challenged with ASFV-G. As expected, a pool of sera from ASFV-G-DE184L-inoculated animals lacked any detectable antibody response to peptides partially representing the E184L protein, while sera from animals inoculated with an efficacious vaccine candidate, ASFV-GDMGF, strongly recognize the same set of peptides. These results support the potential use of the E184L deletion for the development of vaccines able to differentiate infected from vaccinated animals (DIVA). Therefore, it is shown here that the E184L gene is a novel ASFV determinant of virulence that can potentially be used to increase safety in preexisting vaccine candidates, as well as to provide them with DIVA capabilities. To our knowledge, E184L is the first ASFV gene product experimentally shown to be a functional DIVA antigenic marker.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

An Overview of Biofilm Formation–Combating Strategies and Mechanisms of Action of Antibiofilm Agents

Biofilm formation on surfaces via microbial colonization causes infections and has become a major health issue globally. The biofilm lifestyle provides resistance to environmental stresses and antimicrobial therapies. Biofilms can cause several chronic conditions, and effective treatment has become a challenge due to increased antimicrobial resistance. Antibiotics available for treating biofilm-associated infections are generally not very effective and require high doses that may cause toxicity in the host. Therefore, it is essential to study and develop efficient anti-biofilm strategies that can significantly reduce the rate of biofilm-associated healthcare problems. In this context, some effective combating strategies with potential anti-biofilm agents, including plant extracts, peptides, enzymes, lantibiotics, chelating agents, biosurfactants, polysaccharides, organic, inorganic, and metal nanoparticles, etc., have been reviewed to overcome biofilm-associated healthcare problems. From their extensive literature survey, it can be concluded that these molecules with considerable structural alterations might be applied to the treatment of biofilm-associated infections, by evaluating their significant delivery to the target site of the host. To design effective anti-biofilm molecules, it must be assured that the minimum inhibitory concentrations of these anti-biofilm compounds can eradicate biofilm-associated infections without causing toxic effects at a significant rate.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

A Stochastic Intracellular Model of Anthrax Infection With Spore Germination Heterogeneity

We present a stochastic mathematical model of the intracellular infection dynamics of Bacillus anthracis in macrophages. Following inhalation of B. anthracis spores, these are ingested by alveolar phagocytes. Ingested spores then begin to germinate and divide intracellularly. This can lead to the eventual death of the host cell and the extracellular release of bacterial progeny. Some macrophages successfully eliminate the intracellular bacteria and will recover. Here, a stochastic birth-and-death process with catastrophe is proposed, which includes the mechanism of spore germination and maturation of B. anthracis . The resulting model is used to explore the potential for heterogeneity in the spore germination rate, with the consideration of two extreme cases for the rate distribution: continuous Gaussian and discrete Bernoulli. We make use of approximate Bayesian computation to calibrate our model using experimental measurements from in vitro infection of murine peritoneal macrophages with spores of the Sterne 34F2 strain of B. anthracis . The calibrated stochastic model allows us to compute the probability of rupture, mean time to rupture, and rupture size distribution, of a macrophage that has been infected with one spore. We also obtain the mean spore and bacterial loads over time for a population of cells, each assumed to be initially infected with a single spore. Our results support the existence of significant heterogeneity in the germination rate, with a subset of spores expected to germinate much later than the majority. Furthermore, in agreement with experimental evidence, our results suggest that most of the spores taken up by macrophages are likely to be eliminated by the host cell, but a few germinated spores may survive phagocytosis and lead to the death of the infected cell. Finally, we discuss how this stochastic modelling approach, together with dose-response data, allows us to quantify and predict individual infection risk following exposure.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Evidence of Asexual Overwintering of Melampsora paradoxa and Mapping of Stem Rust Host Resistance in Salix

Melampsora rust is a devastating disease of shrub willow in North America. Previous work has identified Melampsora paradoxa as one of two identified rust species in New York State that infect Salix purpurea and other important Salix host species, however little is known about the population of this rust species in this region. Genotyping-by-sequencing was used to identify single nucleotide polymorphisms (SNPs) and assess population diversity of M. paradoxa isolates collected from three Salix breeding populations in Geneva, NY between 2015 and 2020. Statistical analyses of SNP revealed that all isolates collected were clonally derived even though they were collected across years. In 2020, isolates were collected from stem infections where uredospore pustules were observed, and these isolates were also identical to M. paradoxa collected in previous seasons. These data suggest that M. paradoxa sampled across multiple years overwintered and reproduced asexually and that stem infection is a possible mechanism for overwintering, both of which are novel findings for this rust species. Additionally, field disease ratings were conducted on a S. purpurea × S. suchowensis F 1 breeding population with high disease severity, enabling the discovery of QTL for resistance on chromosomes 1 and 19. Lastly, Colletotrichum salicis was frequently associated with stem rust and may play a role in M. paradoxa stem infection. Together, this work is the first substantial exploration into M. paradoxa population biology, stem infection, and host resistance in Salix.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Structure-based design of SARS-CoV-2 papain-like protease inhibitors

The COVID-19 pandemic is caused by SARS-CoV-2, an RNA virus with high transmissibility and mutation rate. Given the paucity of orally bioavailable antiviral drugs to combat SARS-CoV-2 infection, there is a critical need for additional antivirals with alternative mechanisms of action. Papain-like protease (PL pro ) is one of the two SARS-CoV-2 encoded viral cysteine proteases essential for viral replication. PL pro cleaves at three sites of the viral polyproteins. In addition, PLpro antagonizes the host immune response upon viral infection by cleaving ISG15 and ubiquitin from host proteins. Therefore, PL pro is a validated antiviral drug target. In this study, we report the X-ray crystal structures of papain-like protease (PL pro ) with two potent inhibitors, Jun9722 and Jun9843 . Subsequently, we designed and synthesized several series of analogs to explore the structure-activity relationship, which led to the discovery of PL pro inhibitors with potent enzymatic inhibitory activity and antiviral activity against SARS-CoV-2. Together, the lead compounds are promising drug candidates for further development.

60 APPLIED LIFE SCIENCES↗
NASA NTRS2023

Broader Impacts and Outreach Videos on Ocean Physics and Biogeochemistry

This is just a preliminary NF1676 in advance of filming for a project....A convergent team of experts in biology, chemistry, physics, engineering, mathematics, and computational modeling examine how dynamic and coupled phytoplankton-pathogen-particle-predator linkages coalesce to explain the observed high spatial variability in the efficiency of the export of particulate organic carbon (POC) to the deep ocean. They elucidate and quantify the linkages between viruses and ballast minerals to increase understanding of carbon cycling in the oceanic biological carbon pump and the impact of viruses within it. By providing knowledge than can be used to improve the parameterization of carbon export in Earth system models, the project will help reduce uncertainty in regional marine biogeochemical projections, potentially improving marine ecosystem and fisheries management on timescales from seasons to decades. The project includes activities that provide teaching resources and hands-on training to educators within a ‘Tools of Science’ program that provides a simple and succinct way to communicate the process of scientific research to students in a way that is useful to teachers. The project couples laboratory-based experiments on model host-virus-grazer systems with extensive field based observational and manipulative studies on natural populations of diatoms and coccolithophores, the two phytoplankton groups that account for most of the estimated particulate organic matter flux to the deep ocean. Experiments and measurements integrate diagnostic biological and chemical controls on infection and particle coagulation theory with microscale physics and grazing to quantify links to each hypothesized export mechanism under field-relevant turbulent conditions. Cutting-edge engineering and analytical tools are used to diagnose and track infection dynamics while characterizing and quantifying particle aggregation and disaggregation, mineral dissolution, sinking dynamics, grazing rates, and fecal pellet production at unprecedented resolution and under well-defined, microscale physical regimes. Field campaigns elucidate the relative efficiency of hypothesized mechanisms in stimulating POC export in natural blooms, while providing bulk and size-resolved estimates of POC flux.

Daniel B Whitt↗
DOE OSTI2023

Changes in trachoma indicators in Kiribati with two rounds of azithromycin mass drug administration, measured in serial population-based surveys

Baseline mapping in the two major population centers of Kiribati showed that trachoma was a public health problem in need of programmatic interventions. After conducting two annual rounds of antibiotic mass drug administration (MDA), Kiribati undertook trachoma impact surveys in 2019, using standardized two-stage cluster surveys in the evaluation units of Kiritimati Island and Tarawa. In Kiritimati, 516 households were visited and in Tarawa, 772 households were visited. Nearly all households had a drinking water source and access to an improved latrine. The prevalence of trachomatous trichiasis remained above the elimination threshold (0.2% in ≥15-year-olds) and was virtually unchanged from baseline. The prevalence of trachomatous inflammation—follicular (TF) in 1–9-year-olds decreased by approximately 40% from baseline in both evaluation units but remained above the 5% TF prevalence threshold for stopping MDA. TF prevalence at impact survey was 11.5% in Kiritimati and 17.9% in Tarawa. Infection prevalence in 1–9-year-olds by PCR was 0.96% in Kiritimati and 3.3% in Tarawa. Using a multiplex bead assay to measure antibodies to the C. trachomatis antigen Pgp3, seroprevalence in 1–9-year-olds was 30.2% in Kiritimati and 31.4% in Tarawa. The seroconversion rate, in seroconversion events/100 children/year, was 9.0 in Kiritimati and 9.2 in Tarawa. Seroprevalence and seroconversion rates were both assessed by four different assays, with strong agreement between tests. These results show that, despite decreases in indicators associated with infection at impact survey, trachoma remains a public health problem in Kiribati, and provide additional information about changes in serological indicators after MDA.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2022

Modeling hepatitis C micro-elimination among people who inject drugs with direct-acting antivirals in metropolitan Chicago

Hepatitis C virus (HCV) infection is a leading cause of chronic liver disease and mortality worldwide. Direct-acting antiviral (DAA) therapy leads to high cure rates. However, persons who inject drugs (PWID) are at risk for reinfection after cure and may require multiple DAA treatments to reach the World Health Organization’s (WHO) goal of HCV elimination by 2030. Using an agent-based model (ABM) that accounts for the complex interplay of demographic factors, risk behaviors, social networks, and geographic location for HCV transmission among PWID, we examined the combination(s) of DAA enrollment (2.5%, 5%, 7.5%, 10%), adherence (60%, 70%, 80%, 90%) and frequency of DAA treatment courses needed to achieve the WHO’s goal of reducing incident chronic infections by 90% by 2030 among a large population of PWID from Chicago, IL and surrounding suburbs. We also estimated the economic DAA costs associated with each scenario. Our results indicate that a DAA treatment rate of >7.5% per year with 90% adherence results in 75% of enrolled PWID requiring only a single DAA course; however 19% would require 2 courses, 5%, 3 courses and <2%, 4 courses, with an overall DAA cost of $325 million to achieve the WHO goal in metropolitan Chicago. We estimate a 28% increase in the overall DAA cost under low adherence (70%) compared to high adherence (90%). Our modeling results have important public health implications for HCV elimination among U.S. PWID. Using a range of feasible treatment enrollment and adherence rates, we report robust findings supporting the need to address re-exposure and reinfection among PWID to reduce HCV incidence.

60 APPLIED LIFE SCIENCES↗