Linkage-based ortholog refinement in bacterial pangenomes with CLARC.

Bacterial genomes exhibit significant variation in gene content and sequence identity. Pangenome analyses explore this diversity by classifying genes into core and accessory clusters of orthologous groups (COGs). However, strict sequence identity cutoffs can misclassify divergent alleles as different genes, inflating accessory gene counts.

Burden of Acute Respiratory Infections Caused by Influenza Virus, Respiratory Syncytial Virus, and SARS-CoV-2 with Consideration of Older Adults: A Narrative Review.

Influenza virus, respiratory syncytial virus (RSV), and severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) are acute respiratory infections (ARIs) that can cause substantial morbidity and mortality among at-risk individuals, including older adults. In this narrative review, we summarize themes identified in the literature regarding the epidemiology, seasonality, immunity after infection, clinical presentation, and transmission for these ARIs, along with the impact of the COVID-19 pandemic on seasonal patterns of influenza and RSV infections, with consideration of data specific to older adults when available. As the older adult population increases globally, it is of paramount importance to fully characterize the true disease burden of ARIs in order to develop appropriate mitigation strategies to minimize their impact in vulnerable populations.

Politicians, power, and the people's health: US elections and state health outcomes, 2012-2024.

Our descriptive study examined current associations (2022-2024) between US state-level health outcomes and 4 US state-level political metrics: 2 rarely used in public health research (political ideology of elected representatives based on voting records; trifectas, where 1 party controls the executive and legislative branches) and 2 more commonly used (state policies enacted; voter political lean). The 8 health outcomes spanned the life course: infant mortality, premature mortality (death at age <65), health insurance (adults aged 35-64), vaccination for children and persons aged ≥65 (flu; COVID-19 booster), maternity care deserts, and food insecurity. For the first 3 outcomes, we also examined trends in associations (2012-2024).

Rapid inference of antibiotic susceptibility phenotype of uropathogens using metagenomic sequencing with neighbor typing.

Unlabelled: Timely diagnostic tools are needed to improve antibiotic treatment. Pairing metagenomic sequencing with genomic neighbor typing algorithms may support rapid clinically actionable results. We created resistance-associated sequence elements (RASE) databases for and .

Visualizing Neighborhood COVID-19 Levels, Trends, and Inequities in Wastewater: An Equity-Centered Approach and Comparison to CDC Methods.

Context: Monitoring neighborhood-level SARS-CoV-2 wastewater concentrations can help guide public health interventions and provide early warning ahead of lagging COVID-19 clinical indicators. To date, however, U.S.

Prediction of post-PCV13 pneumococcal evolution using invasive disease data enhanced by inverse-invasiveness weighting.

After introducing pneumococcal conjugate vaccines (PCVs), serotype replacement occurred in . Predicting which pneumococcal strains will become common in carriage after vaccination can enhance vaccine design, public health interventions, and understanding of pneumococcal evolution. Invasive pneumococcal isolates were collected during 1998-2018 by the Active Bacterial Core surveillance (ABCs).

Successful treatment of SARS-CoV-2 in an immunocompromised patient with persistent infection for 245 days: A case report.

Background: Immunocompromised patients receiving B-cell-depleting therapies are at increased risk of persistent SARS-CoV-2 infection, with many experiencing fatal outcomes. We report a successful outcome in a patient with rheumatoid arthritis (RA) on rituximab diagnosed with COVID-19 in July 2020 with persistent infection for over 245 days.

Results: The patient received numerous treatment courses for persistent COVID-19 infection, including remdesivir, baricitinib, immunoglobulin and high doses of corticosteroids followed by a prolonged taper due to persistent respiratory symptoms and cryptogenic organizing pneumonia.

Prediction of post-PCV13 pneumococcal evolution using invasive disease data enhanced by inverse-invasiveness weighting.

Background: After introduction of pneumococcal conjugate vaccines (PCVs), serotype replacement occurred in the population of Predicting which pneumococcal clones and serotypes will become more common in carriage after vaccination can enhance vaccine design and public health interventions, while also improving our understanding of pneumococcal evolution. We sought to use invasive disease data to assess how well negative frequency-dependent selection (NFDS) models could explain pneumococcal carriage population evolution in the post-PCV13 epoch by weighting invasive data to approximate strain proportions in the carriage population.

Methods: Invasive pneumococcal isolates were collected and sequenced during 1998-2018 by the Active Bacterial Core surveillance (ABCs) from the Centers for Disease Control and Prevention (CDC).

Sink-traps are a major source for carbapenemase-producing transmission.

Objective: We studied the extent of carbapenemase-producing Enterobacteriaceae (CPE) sink contamination and transmission to patients in a nonoutbreak setting.

Methods: During 2017-2019, 592 patient-room sinks were sampled in 34 departments. Patient weekly rectal swab CPE surveillance was universally performed.

Quantitatively assessing early detection strategies for mitigating COVID-19 and future pandemics.

Researchers and policymakers have proposed systems to detect novel pathogens earlier than existing surveillance systems by monitoring samples from hospital patients, wastewater, and air travel, in order to mitigate future pandemics. How much benefit would such systems offer? We developed, empirically validated, and mathematically characterized a quantitative model that simulates disease spread and detection time for any given disease and detection system. We find that hospital monitoring could have detected COVID-19 in Wuhan 0.

Inferring bacterial transmission dynamics using deep sequencing genomic surveillance data.

Identifying and interrupting transmission chains is important for controlling infectious diseases. One way to identify transmission pairs - two hosts in which infection was transmitted from one to the other - is using the variation of the pathogen within each single host (within-host variation). However, the role of such variation in transmission is understudied due to a lack of experimental and clinical datasets that capture pathogen diversity in both donor and recipient hosts.

Quantitatively assessing early detection strategies for mitigating COVID-19 and future pandemics.

Researchers and policymakers have proposed systems to detect novel pathogens earlier than existing surveillance systems by monitoring samples from hospital patients, wastewater, and air travel, in order to mitigate future pandemics. How much benefit would such systems offer? We developed, empirically validated, and mathematically characterized a quantitative model that simulates disease spread and detection time for any given disease and detection system. We find that hospital monitoring could have detected COVID-19 in Wuhan 0.

Estimated preventable COVID-19-associated deaths due to non-vaccination in the United States.

While some studies have previously estimated lives saved by COVID-19 vaccination, we estimate how many deaths could have been averted by vaccination in the US but were not because of a failure to vaccinate. We used a simple method based on a nationally representative dataset to estimate the preventable deaths among unvaccinated individuals in the US from May 30, 2021 to September 3, 2022 adjusted for the effects of age and time. We estimated that at least 232,000 deaths could have been prevented among unvaccinated adults during the 15 months had they been vaccinated with at least a primary series.

The evolving roles of US political partisanship and social vulnerability in the COVID-19 pandemic from February 2020-February 2021.

The COVID-19 pandemic has had intense, heterogeneous impacts on different communities and geographies in the United States. We explore county-level associations between COVID-19 attributed deaths and social, demographic, vulnerability, and political variables to develop a better understanding of the evolving roles these variables have played in relation to mortality. We focus on the role of political variables, as captured by support for either the Republican or Democratic presidential candidates in the 2020 elections and the stringency of state-wide governor mandates, during three non-overlapping time periods between February 2020 and February 2021.

Addressing spatial misalignment in population health research: a case study of US congressional district political metrics and county health data.

Areal spatial misalignment, which occurs when data on multiple variables are collected using mismatched boundary definitions, is a ubiquitous obstacle to data analysis in public health and social science research. As one example, the emerging sub-field studying the links between political context and health in the United States faces significant spatial misalignment-related challenges, as the congressional districts (CDs) over which political metrics are measured and administrative units, e.g.

Association of body mass index with COVID-19-related neurologic sequelae: a retrospective cohort study.

We sought to explore the relationship between body mass index (BMI) and neurologic outcomes following acute COVID-19 infection. We conducted a retrospective electronic medical record-based cohort study enrolling adults with laboratory-confirmed acute COVID-19 infection who presented to 1 of 12 academic and community hospitals in Southwestern Ontario, Canada between April 1, 2020 and July 31, 2021. Primary subjective (anosmia, dysgeusia, and/or headache) and objective (aseptic meningitis, ataxia, delirium, encephalopathy, encephalitis, intracranial hemorrhage, ischemic stroke, and/or seizure) composite neurologic outcomes were assessed, comparing obese and overweight individuals to those with underweight/normal BMI indices, adjusting for baseline characteristics.

Monkeypox Virus Infections in Humans.

Human monkeypox is a viral zoonosis endemic to West and Central Africa that has recently generated increased interest and concern on a global scale as an emerging infectious disease threat in the midst of the slowly relenting COVID-2019 disease pandemic. The hallmark of infection is the development of a flu-like prodrome followed by the appearance of a smallpox-like exanthem. Precipitous person-to-person transmission of the virus among residents of 100 countries where it is nonendemic has motivated the immediate and widespread implementation of public health countermeasures.

Relationship of political ideology of US federal and state elected officials and key COVID pandemic outcomes following vaccine rollout to adults: April 2021-March 2022.

Background: Scant research, including in the United States, has quantified relationships between the political ideologies of elected representatives and COVID-19 outcomes among their constituents.

Methods: We analyzed observational cross-sectional data on COVID-19 mortality rates (age-standardized) and stress on hospital intensive care unit (ICU) capacity for all 435 US Congressional Districts (CDs) in a period of adult vaccine availability (April 2021-March 2022). Political metrics comprised: (1) ideological scores based on each US Representative's and Senator's concurrent overall voting record and their specific COVID-19 votes, and (2) state trifectas (Governor, State House, and State Senate under the same political party control).

Linking contact tracing with genomic surveillance to deconvolute SARS-CoV-2 transmission on a university campus.

Contact tracing and genomic data, approaches often used separately, have both been important tools in understanding the nature of SARS-CoV-2 transmission. Linked analysis of contact tracing and sequence relatedness of SARS-CoV-2 genomes from a regularly sampled university environment were used to build a multilevel transmission tracing and confirmation system to monitor and understand transmission on campus. Our investigation of an 18-person cluster stemming from an athletic team highlighted the importance of linking contact tracing and genomic analysis.

Causal discovery for the microbiome.

Measurement and manipulation of the microbiome is generally considered to have great potential for understanding the causes of complex diseases in humans, developing new therapies, and finding preventive measures. Many studies have found significant associations between the microbiome and various diseases; however, Koch's classical postulates remind us about the importance of causative reasoning when considering the relationship between microbes and a disease manifestation. Although causal discovery in observational microbiome data faces many challenges, methodological advances in causal structure learning have improved the potential of data-driven prediction of causal effects in large-scale biological systems.

Methods for early characterisation of the severity and dynamics of SARS-CoV-2 variants: a population-based time series analysis in South Africa.

Background: Assessment of disease severity associated with a novel pathogen or variant provides crucial information needed by public health agencies and governments to develop appropriate responses. The SARS-CoV-2 omicron variant of concern (VOC) spread rapidly through populations worldwide before robust epidemiological and laboratory data were available to investigate its relative severity. Here we develop a set of methods that make use of non-linked, aggregate data to promptly estimate the severity of a novel variant, compare its characteristics with those of previous VOCs, and inform data-driven public health responses.