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At least 127 records · Page 7

Evaluation of FluSight influenza forecasting in the 2021–22 and 2022–23 seasons with a new target laboratory-confirmed influenza hospitalizations

Accurate forecasts can enable more effective public health responses during seasonal influenza epidemics. For the 2021–22 and 2022–23 influenza seasons, 26 forecasting teams provided national and jurisdiction-specific probabilistic predictions of weekly confirmed influenza hospital admissions for one-to-four weeks ahead. Forecast skill is evaluated using the Weighted Interval Score (WIS), relative WIS, and coverage. Six out of 23 models outperform the baseline model across forecast weeks and locations in 2021–22 and 12 out of 18 models in 2022–23. Averaging across all forecast targets, the FluSight ensemble is the 2nd most accurate model measured by WIS in 2021–22 and the 5th most accurate in the 2022–23 season. Forecast skill and 95% coverage for the FluSight ensemble and most component models degrade over longer forecast horizons. In this work we demonstrate that while the FluSight ensemble was a robust predictor, even ensembles face challenges during periods of rapid change.

59 BASIC BIOLOGICAL SCIENCES↗

Crowd cluster data in the USA for analysis of human response to COVID-19 events and policies

We provide data on daily social contact intensity of clusters of people at different types of Points of Interest (POI) by zip code in Florida and California. This data is obtained by aggregating fine-scaled details of interactions of people at the spatial resolution of 10 m, which is then normalized as a social contact index. We also provide the distribution of cluster sizes and average time spent in a cluster by POI type. This data will help researchers perform fine-scaled, privacy-preserving analysis of human interaction patterns to understand the drivers of the COVID-19 epidemic spread and mitigation. Current mobility datasets either provide coarse-level metrics of social distancing, such as radius of gyration at the county or province level, or traffic at a finer scale, neither of which is a direct measure of contacts between people. We use anonymized, de-identified, and privacy-enhanced location-based services (LBS) data from opted-in cell phone apps, suitably reweighted to correct for geographic heterogeneities, and identify clusters of people at non-sensitive public areas to estimate fine-scaled contacts.

60 APPLIED LIFE SCIENCES↗

AeDES: a next-generation monitoring and forecasting system for environmental suitability of Aedes-borne disease transmission

Aedes-borne diseases, such as dengue and chikungunya, are responsible for more than 50 million infections worldwide every year, with an overall increase of 30-fold in the last 50 years, mainly due to city population growth, more frequent travels and ecological changes. In the United States of America, the vast majority of Aedes-borne infections are imported from endemic regions by travelers, who can become new sources of mosquito infection upon their return home if the exposed population is susceptible to the disease, and if suitable environmental conditions for the mosquitoes and the virus are present. Since the susceptibility of the human population can be determined via periodic monitoring campaigns, the environmental suitability for the presence of mosquitoes and viruses becomes one of the most important pieces of information for decision makers in the health sector. We present a next-generation monitoring and forecasting system for Aedes-borne diseases’ environmental suitability (AeDES) of transmission in the conterminous United States and transboundary regions, using calibrated ento-epidemiological models, climate models and temperature observations. After analyzing the seasonal predictive skill of AeDES, we briefly consider the recent Zika epidemic, and the compound effects of the current Central American dengue outbreak happening during the SARS-CoV-2 pandemic, to illustrate how a combination of tailored deterministic and probabilistic forecasts can inform key prevention and control strategies .

54 ENVIRONMENTAL SCIENCES↗

Better understanding and prediction of antiviral peptides through primary and secondary structure feature importance

The emergence of viral epidemics throughout the world is of concern due to the scarcity of available effective antiviral therapeutics. The discovery of new antiviral therapies is imperative to address this challenge, and antiviral peptides (AVPs) represent a valuable resource for the development of novel therapies to combat viral infection. We present a new machine learning model to distinguish AVPs from non-AVPs using the most informative features derived from the physicochemical and structural properties of their amino acid sequences. To focus on those features that are most likely to contribute to antiviral performance, we filter potential features based on their importance for classification. These feature selection analyses suggest that secondary structure is the most important peptide sequence feature for predicting AVPs. Our Feature-Informed Reduced Machine Learning for Antiviral Peptide Prediction (FIRM-AVP) approach achieves a higher accuracy than either the model with all features or current state-of-the-art single classifiers. Understanding the features that are associated with AVP activity is a core need to identify and design new AVPs in novel systems. The FIRM-AVP code and standalone software package are available at https://github.com/pmartR/FIRM-AVP with an accompanying web application at https://msc-viz.emsl.pnnl.gov/AVPR.

59 BASIC BIOLOGICAL SCIENCES↗

Assessing the impact of human mobility to predict regional excess death in Ecuador

Abstract COVID-19 outbreaks have had high mortality in low- and middle-income countries such as Ecuador. Human mobility is an important factor influencing the spread of diseases possibly leading to a high burden of disease at the country level. Drastic control measures, such as complete lockdown, are effective epidemic controls, yet in practice one hopes that a partial shutdown would suffice. It is an open problem to determine how much mobility can be allowed while controlling an outbreak. In this paper, we use statistical models to relate human mobility to the excess death in Ecuador while controlling for demographic factors. The mobility index provided by GRANDATA, based on mobile phone users, represents the change of number of out-of-home events with respect to a benchmark date (March 2nd, 2020). The study confirms the global trend that more men are dying than expected compared to women, and that people under 30 show less deaths than expected, particularly individuals younger than 20 with a death rate reduction between 22 and 27%. The weekly median mobility time series shows a sharp decrease in human mobility immediately after a national lockdown was declared on March 17, 2020 and a progressive increase towards the pre-lockdown level within two months. Relating median mobility to excess deaths shows a lag in its effect: first, a decrease in mobility in the previous two to three weeks decreases excess death and, more novel, we found an increase of mobility variability four weeks prior increases the number of excess deaths.

59 BASIC BIOLOGICAL SCIENCES↗

Predicting the effects of climate change on the cross-scale epidemiological dynamics of a fungal plant pathogen

The potential for climate change to exacerbate the burden of human infectious diseases is increasingly recognized, but its effects on infectious diseases of plants have received less attention. Understanding the impacts of climate on the epidemiological dynamics of plant pathogens is imperative, as these organisms play central roles in natural ecosystems and also pose a serious threat to agricultural production and food security. We use the fungal ‘flax rust’ pathogen (Melampsora lini) and its subalpine wildflower host Lewis flax (Linum lewisii) to investigate how climate change might affect the dynamics of fungal plant pathogen epidemics using a combination of empirical and modeling approaches. Our results suggest that climate change will initially slow transmission at both the within- and between-host scales. However, moderate resurgences in disease spread are predicted as warming progresses, especially if the rate of greenhouse gas emissions continues to increase at its current pace. These findings represent an important step towards building a holistic understanding of climate effects on plant infectious disease that encompasses demographic, epidemiological, and evolutionary processes. A core result is that neglecting processes at any one scale of plant pathogen transmission may bias projections of climate effects, as climate drivers have variable and cascading impacts on processes underlying transmission that occur at different scales.

59 BASIC BIOLOGICAL SCIENCES↗

Novel fold of rotavirus glycan-binding domain predicted by AlphaFold2 and determined by X-ray crystallography

The VP8* domain of spike protein VP4 in group A and C rotaviruses, which cause epidemic gastroenteritis in children, exhibits a conserved galectin-like fold for recognizing glycans during cell entry. In group B rotavirus, which causes significant diarrheal outbreaks in adults, the VP8* domain (VP8*B) surprisingly lacks sequence similarity with VP8* of group A or group C rotavirus. Here, by using the recently developed AlphaFold2 for ab initio structure prediction and validating the predicted model by determining a 1.3-Å crystal structure, we show that VP8*B exhibits a novel fold distinct from the galectin fold. This fold with a β-sheet clasping an α-helix represents a new fold for glycan recognition based on glycan array screening, which shows that VP8*B recognizes glycans containing N-acetyllactosamine moiety. Although uncommon, our study illustrates how evolution can incorporate structurally distinct folds with similar functionality in a homologous protein within the same virus genus.

59 BASIC BIOLOGICAL SCIENCES↗

Transient pattern formation in an active matter contact poisoning model

Abstract One of the most notable features in repulsive particle based active matter systems is motility-induced-phase separation (MIPS) where a dense, often crystalline phase and low density fluid coexist. Most active matter studies involve time-dependent activity; however, there are many active systems where individual particles transition from living or moving to dead or nonmotile due to lack of fuel, infection, or poisoning. Here we consider an active matter particle system at densities where MIPS does not occur. When we add a small number of infected particles that can poison other particles, rendering them nonmotile, we find a rich variety of time dependent pattern formation, including MIPS, a wetting phase, and a fragmented state formed when mobile particles plow through a nonmotile packing. We map the patterns as a function of time scaled by epidemic duration, and show that the pattern formation is robust for a wide range of poisoning rates and activity levels. We also show that pattern formation does not occur in a random death model, but requires the promotion of nucleation by contact poisoning. Our results should be relevant to biological and active matter systems where there is some form of poisoning, death, or transition to nonmotility.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Vapor detection and vapor pressure measurements of fentanyl and fentanyl hydrochloride salt at ambient temperatures

There is a need for non-contact, real-time vapor detection of drugs to combat illicit transportation and help curb the opioid epidemic. The low-volatility of drugs, like fentanyl, makes room temperature vapor detection of illicit drugs challenging, but feasible by atmospheric flow tube-mass spectrometry (AFT-MS). AFT-MS is a non-contact vapor detection approach capable of ultra-trace detection of drugs, including fentanyl and its analogs at low parts-per-quadrillion (ppqv) levels. The determination of vapor pressure values of fentanyl is necessary to understand potential vapor concentrations that may be available for detection. In this paper, vapor pressures of fentanyl free base and fentanyl hydrochloride salt (a common form of the illicit drug) were measured as a function of temperature at or near ambient conditions using the transpiration (gas saturation) method and AFT-MS. Based on our measurements, the vapor pressure of fentanyl at 25 °C is 9.0 × 10-14 atm (90 ppqv), and the vapor pressure of fentanyl hydrochloride at 25 °C is 1.8 x 10-17 atm (0.018 ppqv). We also demonstrate non-contact, real-time vapor detection of fentanyl. Preconcentration of vapors can further extend the detection capabilities. The collection, desorption, and detection of fentanyl vapors at ambient conditions was demonstrated for sampling times of seconds to an hour resulting in increased signal. AFT-MS is a viable detection method of fentanyl and other drugs for screening of packages and cargo.

atmospheric flow tube-mass spectrometry (AFT-MS), ↗

Structural basis for Zika envelope domain III recognition by a germline version of a recurrent neutralizing antibody

Recent epidemics demonstrate the global threat of Zika virus (ZIKV), a flavivirus transmitted by mosquitoes. Although infection is usually asymptomatic or mild, newborns of infected mothers can display severe symptoms, including neurodevelopmental abnormalities and microcephaly. Given the large-scale spread, symptom severity, and lack of treatment or prophylaxis, a safe and effective ZIKV vaccine is urgently needed. However, vaccine design is complicated by concern that elicited antibodies (Abs) may cross-react with other flaviviruses that share a similar envelope protein, such as dengue virus, West Nile virus, and yellow fever virus. This cross-reactivity may worsen symptoms of a subsequent infection through Ab-dependent enhancement. To better understand the neutralizing Ab response and risk of Ab-dependent enhancement, further information on germline Ab binding to ZIKV and the maturation process that gives rise to potently neutralizing Abs is needed. In this work, we use binding and structural studies to compare mature and inferred-germline Ab binding to envelope protein domain III of ZIKV and other flaviviruses. We show that affinity maturation of the light-chain variable domain is important for strong binding of the recurrent VH3-23/VK1-5 neutralizing Abs to ZIKV envelope protein domain III, and identify interacting residues that contribute to weak, cross-reactive binding to West Nile virus. These findings provide insight into the affinity maturation process and potential cross-reactivity of VH3-23/VK1-5 neutralizing Abs, informing precautions for protein-based vaccines designed to elicit germline versions of neutralizing Abs.

59 BASIC BIOLOGICAL SCIENCES↗

The impact of long-range dispersal on gene surfing

Range expansions lead to distinctive patterns of genetic variation in populations, even in the absence of selection. These patterns and their genetic consequences have been well studied for populations advancing through successive short-ranged migration events. However, most populations harbor some degree of long-range dispersal, experiencing rare yet consequential migration events over arbitrarily long distances. Although dispersal is known to strongly affect spatial genetic structure during range expansions, the resulting patterns and their impact on neutral diversity remain poorly understood. Here, we systematically study the consequences of long-range dispersal on patterns of neutral variation during range expansion in a class of dispersal models which spans the extremes of local (effectively short-ranged) and global (effectively well-mixed) migration. We find that sufficiently long-ranged dispersal leaves behind a mosaic of monoallelic patches, whose number and size are highly sensitive to the distribution of dispersal distances. We develop a coarse-grained model which connects statistical features of these spatial patterns to the evolution of neutral diversity during the range expansion. We show that growth mechanisms that appear qualitatively similar can engender vastly different outcomes for diversity: Depending on the tail of the dispersal distance distribution, diversity can be either preserved (i.e., many variants survive) or lost (i.e., one variant dominates) at long times. Our results highlight the impact of spatial and migratory structure on genetic variation during processes as varied as range expansions, species invasions, epidemics, and the spread of beneficial mutations in established populations.

59 BASIC BIOLOGICAL SCIENCES↗

Prevalence and scalable control of localized networks

The ability to control network dynamics is essential for ensuring desirable functionality of many technological, biological, and social systems. Such systems often consist of a large number of network elements, and controlling large-scale networks remains challenging because the computation and communication requirements increase prohibitively fast with network size. Here, we introduce a notion of network locality that can be exploited to make the control of networks scalable, even when the dynamics are nonlinear. We show that network locality is captured by an information metric and is almost universally observed across real and model networks. In localized networks, the optimal control actions and system responses are both shown to be necessarily concentrated in small neighborhoods induced by the information metric. This allows us to develop localized algorithms for determining network controllability and optimizing the placement of driver nodes. This also allows us to develop a localized algorithm for designing local feedback controllers that approach the performance of the corresponding best global controllers, while incurring a computational cost orders-of-magnitude lower. Here, we validate the locality, performance, and efficiency of the algorithms in Kuramoto oscillator networks, as well as three large empirical networks: synchronization dynamics in the Eastern US power grid, epidemic spreading mediated by the global air-transportation network, and Alzheimer’s disease dynamics in a human brain network. Taken together, our results establish that large networks can be controlled with computation and communication costs comparable to those for small networks.

42 ENGINEERING↗

Uncovering heterogeneous intercommunity disease transmission from neutral allele frequency time series

The COVID-19 pandemic has underscored the need for accurate epidemic forecasting to predict pathogen spread, evolution, and evaluate intervention strategies. Forecast reliability hinges on detailed knowledge of disease transmission across population segments, which may be inferred from contact surveys or mobility data. However, these indirect approaches make it difficult to estimate rare transmissions between socially or geographically distant communities. We show that the steep ramp-up of genome sequencing surveillance during the pandemic can be leveraged to directly identify transmission patterns between geographically defined communities. Our approach uses a hidden Markov model to infer the fraction of infections a community imports from others based on how rapidly allele frequencies in the focal community converge to those in the donor communities. Applying this method to SARS-CoV-2 sequencing data from England and the United States, we uncover networks of intercommunity transmission that reflect geographical relationships while exposing significant long-range interactions. The scaling of importation rate with distance is consistent across both countries, yet weaker than expected based on mobility data, highlighting limitations of indirect inference. We show that transmission patterns can change between waves of variants of concern and analyze how the inferred heterogeneity in intercommunity transmission impacts evolutionary forecasts. While applied here to geographically defined communities, our approach could be applied to those defined by other traits (e.g., age, socioeconomic status), provided time-series data can be stratified accordingly. Overall, our study highlights population genomic time series data as a crucial record of epidemiological interactions, which can be deciphered using tree-free inference methods.

Okada, Takashi [Department of Physics; University ↗

Fitness cost of vancomycin-resistant Enterococcus faecium plasmids associated with hospital infection outbreaks

Abstract Background Vancomycin resistance is mostly associated with Enterococcus faecium due to Tn1546-vanA located on narrow- and broad-host plasmids of various families. This study’s aim was to analyse the effects of acquiring Tn1546-carrying plasmids with proven epidemicity in different bacterial host backgrounds. Methods Widespread Tn1546-carrying plasmids of different families RepA_N (n = 5), Inc18 (n = 4) and/or pHTβ (n = 1), and prototype plasmids RepA_N (pRUM) and Inc18 (pRE25, pIP501) were analysed. Plasmid transferability and fitness cost were assessed using E. faecium (GE1, 64/3) and Enterococcus faecalis (JH2-2/FA202/UV202) recipient strains. Growth curves (Bioscreen C) and Relative Growth Rates were obtained in the presence/absence of vancomycin. Plasmid stability was analysed (300 generations). WGS (Illumina-MiSeq) of non-evolved and evolved strains (GE1/64/3 transconjugants, n = 49) was performed. SNP calling (Breseq software) of non-evolved strains was used for comparison. Results All plasmids were successfully transferred to different E. faecium clonal backgrounds. Most Tn1546-carrying plasmids and Inc18 and RepA_N prototypes reduced host fitness (–2% to 18%) while the cost of Tn1546 expression varied according to the Tn1546-variant and the recipient strain (9%–49%). Stability of Tn1546-carrying plasmids was documented in all cases, often with loss of phenotypic resistance and/or partial plasmid deletions. SNPs and/or indels associated with essential bacterial functions were observed on the chromosome of evolved strains, some of them linked to increased fitness. Conclusions The stability of E. faecium Tn1546-carrying plasmids in the absence of selective pressure and the high intra-species conjugation rates might explain the persistence of vancomycin resistance in E. faecium populations despite the significant burden they might impose on bacterial host strains.

Tedim, Ana P.↗

Intra- and inter-subtype HIV diversity between 1994 and 2018 in southern Uganda: a longitudinal population-based study

There is limited data on human immunodeficiency virus (HIV) evolutionary trends in African populations. We evaluated changes in HIV viral diversity and genetic divergence in southern Uganda over a 24-year period spanning the introduction and scale-up of HIV prevention and treatment programs using HIV sequence and survey data from the Rakai Community Cohort Study, an open longitudinal population-based HIV surveillance cohort. Gag (p24) and env (gp41) HIV data were generated from people living with HIV (PLHIV) in 31 inland semi-urban trading and agrarian communities (1994–2018) and four hyperendemic Lake Victoria fishing communities (2011–2018) under continuous surveillance. HIV subtype was assigned using the Recombination Identification Program with phylogenetic confirmation. Inter-subtype diversity was evaluated using the Shannon diversity index, and intra-subtype diversity with the nucleotide diversity and pairwise TN93 genetic distance. Genetic divergence was measured using root-to-tip distance and pairwise TN93 genetic distance analyses. Demographic history of HIV was inferred using a coalescent-based Bayesian Skygrid model. Evolutionary dynamics were assessed among demographic and behavioral population subgroups, including by migration status. 9931 HIV sequences were available from 4999 PLHIV, including 3060 and 1939 persons residing in inland and fishing communities, respectively. In inland communities, subtype A1 viruses proportionately increased from 14.3% in 1995 to 25.9% in 2017 (P < .001), while those of subtype D declined from 73.2% in 1995 to 28.2% in 2017 (P < .001). The proportion of viruses classified as recombinants significantly increased by nearly four-fold from 12.2% in 1995 to 44.8% in 2017. Inter-subtype HIV diversity has generally increased. While intra-subtype p24 genetic diversity and divergence leveled off after 2014, intra-subtype gp41 diversity, effective population size, and divergence increased through 2017. Intra- and inter-subtype viral diversity increased across all demographic and behavioral population subgroups, including among individuals with no recent migration history or extra-community sexual partners. This study provides insights into population-level HIV evolutionary dynamics following the scale-up of HIV prevention and treatment programs. Continued molecular surveillance may provide a better understanding of the dynamics driving population HIV evolution and yield important insights for epidemic control and vaccine development.

60 APPLIED LIFE SCIENCES↗

Divide and conquer: broadly neutralizing antibody combinations for improved HIV-1 viral coverage

Successful HIV-1 prevention and therapy will require broad and potent coverage of within-host and global viral diversity. Broadly neutralizing antibody (bNAb) combination and multispecific therapeutics provide an opportunity to meet this challenge due to the complementary activity of individual antibody components. Here, we review the principles and applications of this concept. The Antibody Mediated Prevention (AMP) trials have demonstrated the high bar for neutralization potency and breadth that bNAb-mediated prevention modalities will need to achieve to have a meaningful impact on the HIV-1 epidemic. Additional clinical studies have recently shown that an even higher bar may be required for therapeutic inhibition of the diverse within-host quasispecies present in viremic and aviremic people with HIV-1 (PWH). We discuss how the complementarity of bNAbs in terms of neutralization profiles, resistance mutations and coverage of within-host quasispecies may overcome these stringent requirements and lead to effective bNAb combination or multispecific antibody based prophylactic and therapeutic strategies. The design of next-generation bNAb-based combination or multispecific therapeutics for the prevention and/or treatment of HIV-1 infection will need to leverage the complementarity of component bNAbs to maximize the potency and breadth that will be required for clinical success.

60 APPLIED LIFE SCIENCES↗

Expanding Medicaid to Reduce Human Immunodeficiency Virus Transmission in Houston, Texas

Context: Medicaid expansion has been nationally shown to improve engagement in the human immunodeficiency virus (HIV) treatment and prevention continua, which are vital steps to stopping the HIV epidemic. New HIV infections in the United States are disproportionately concentrated among young Black men who have sex with men (YBMSM). Houston, TX, is the most populous city in the Southern United States with a racially/ethnically diverse population that is located in 1 of 11 US states that have not yet expanded Medicaid coverage as of 2021. Methods: An agent-based model that incorporated the sexual networks of YBMSM was used to simulate improved antiretroviral treatment and pre-exposure prophylaxis (PrEP) engagement through Medicaid expansion in Houston, TX. Analyses considered the HIV incidence (number of new infections and as a rate metric) among YBMSM over the next 10 years under Medicaid expansion as the primary outcome. Additional scenarios, involving viral suppression and PrEP uptake above the projected levels achieved under Medicaid expansion, were also simulated. Results: The baseline model projected an HIV incidence rate of 4.96 per 100 person years (py) and about 368 new annual HIV infections in the 10th year. Improved HIV treatment and prevention continua engagement under Medicaid expansion resulted in a 14.9% decline in the number of annual new HIV infections in the 10th year. Increasing viral suppression by an additional 15% and PrEP uptake by 30% resulted in a 44.0% decline in new HIV infections in the 10th year, and a 27.1% decline in cumulative infections across the 10 years of the simulated intervention. Findings: Simulation results indicate that Medicaid expansion has the potential to reduce HIV incidence among YBMSM in Houston. Achieving HIV elimination objectives, however, might require additional effective measures to increase antiretroviral treatment and PrEP uptake beyond the projected improvements under expanded Medicaid.

60 APPLIED LIFE SCIENCES↗

Autocrine and paracrine interferon signalling as ‘ring vaccination’ and ‘contact tracing’ strategies to suppress virus infection in a host

The innate immune response, particularly the interferon response, represents a first line of defence against viral infections. The interferon molecules produced from infected cells act through autocrine and paracrine signalling to turn host cells into an antiviral state. Although the molecular mechanisms of IFN signalling have been well characterized, how the interferon response collectively contribute to the regulation of host cells to stop or suppress viral infection during early infection remain unclear. Here, we use mathematical models to delineate the roles of the autocrine and the paracrine signalling, and show that their impacts on viral spread are dependent on how infection proceeds. In particular, we found that when infection is well-mixed, the paracrine signalling is not as effective; by contrast, when infection spreads in a spatial manner, a likely scenario during initial infection in tissue, the paracrine signalling can impede the spread of infection by decreasing the number of susceptible cells close to the site of infection. Furthermore, we argue that the interferon response can be seen as a parallel to population-level epidemic prevention strategies such as ‘contact tracing’ or ‘ring vaccination’. Thus, our results here may have implications for the outbreak control at the population scale more broadly.

59 BASIC BIOLOGICAL SCIENCES↗