BACKGROUND: The COVID-19 pandemic may have influenced partner-seeking and sexual behaviors of adults. METHODS: We examined cross-sectional survey data collected at the end of the first year (n = 1161) and second year (n = 1233) of the COVID-19 pandemic by the National Opinion Research Center's nationally representative, probability-based AmeriSpeak panel. Data were analyzed to (1) quantify behavioral changes across pandemic years, (2) examine changes of in-person dating prevalence during year 2, and (3) assess risk perception for acquiring COVID-19 or HIV/STIs through new partnerships during year 2. Weighted percentages were calculated for responses; univariate relationships between demographic characteristics and outcomes were assessed. RESULTS: Prevalence of new partners for dating remained stable across pandemic years (year 1: n = 1157 [10%]; year 2: n = 1225 [12%]). The prevalence of in-person sex with new partners was also stable (year 1: n = 1157 [7%], year 2: n = 1225 [6%]), marking a decline from a prepandemic estimate (2015-2016: 16%). Partner-seeking experiences varied by age and sexual identity in both years, and by race/ethnicity during year 2. Reports of in-person dating fluctuated throughout year 2, without clear relationship to viral variants. Respondents who met new partners in person during year 2 generally reported greater concern and preparedness for reducing risks associated with HIV/STIs than COVID-19. CONCLUSIONS: The prevalence of US adults seeking new partners for dating or sex remained stable across pandemic years. During future public health emergencies, public health officials are encouraged to offer guidance for reducing disease risks in partnerships, while emphasizing sexual health and providing tailored messaging for persons more susceptible to infection.

BACKGROUND: The use of chlorine to treat drinking water produces disinfection by-products (DBPs), which have been associated with congenital heart defects (CHDs) in some studies. METHODS: Using National Birth Defects Prevention Study data, we linked geocoded residential addresses to public water supply measurement data for DBPs. Self-reported water consumption and filtration methods were used to estimate maternal ingestion of DBPs. We estimated adjusted odds ratios and 95% confidence intervals using logistic regression controlling for maternal age, education, body mass index (BMI), race/ethnicity, and study site to examine associations between CHDs and both household DBP level and estimated ingestion of DBPs. RESULTS: Household DBP exposure was assessed for 2717 participants (1495 cases and 1222 controls). We observed a broad range of positive, null, and negative estimates across eight specific CHDs and two summary exposures (trihalomethanes and haloacetic acids) plus nine individual DBP species. Examining ingestion exposure among 2488 participants (1347 cases, 1141 controls) produced similarly inconsistent results. CONCLUSIONS: Assessing both household DBP level and estimated ingestion of DBPs, we did not find strong evidence of an association between CHDs and DBPs. Despite a large study population, DBP measurements were available for less than half of participant addresses, limiting study power.

Whole genome sequencing is replacing traditional laboratory surveillance methods as the primary tool to track and characterize clusters and outbreaks of the foodborne and zoonotic pathogen Salmonella enterica (S. enterica). In this study, 438 S. enterica isolates representing 35 serovars and 13 broad vehicle categories from one hundred epidemiologically confirmed outbreaks were evaluated for genetic variation to develop epidemiologically relevant interpretation guidelines for Salmonella disease cluster detection. The Illumina sequences were analyzed by core genome multi-locus sequence typing (cgMLST) and screened for antimicrobial resistance (AR) determinants and plasmids. Ninety-three of the one hundred outbreaks exhibited a close allele range (less than 10 allele differences with a subset closer than 5). The remaining seven outbreaks showed increased variation, of which three were considered polyclonal. A total of 16 and 28 outbreaks, respectively, showed variations in the AR and plasmid profiles. The serovars Newport and I 4,[5],12:i:-, as well as the zoonotic and poultry product vehicles, were overrepresented among the outbreaks, showing increased variation. A close allele range in cgMLST profiles can be considered a reliable proxy for epidemiological relatedness for the vast majority of S. enterica outbreak investigations. Variations associated with mobile elements happen relatively frequently during outbreaks and could be reflective of changing selective pressures.

More than 100 laboratories in the World Health Organization Global Measles and Rubella Laboratory Network (GMRLN) perform nucleic acid-based methods for case confirmation of measles or rubella infections and/or strain surveillance (genotyping). The quality of laboratory data is critical to ensure that diagnostic results and country reports to regional verification committees are based on accurate data. A molecular External Quality Assurance (mEQA) program was initiated by the US-CDC in 2014 to evaluate the performance of laboratories in the network. The inclusion of testing for measles and rubella viruses, with a focus on detection and genotyping, plus the diversity of assays and platforms employed required a flexible and comprehensive proficiency testing program. A stepwise introduction of new evaluation criteria gradually increased the stringency of the proficiency testing program, while giving laboratories time to implement the required changes. The mEQA program plays an important role in many processes in the GMRLN, including informing plans for the training of laboratory staff, access to reagents, and the submission of sequence data to global databases. The EQA program for Local Public Health Institutes in Japan is described as an example for national mEQA programs. As more laboratories initiate molecular testing, the mEQA will need to continue to expand and to adapt to the changing landscape for molecular testing.

After introducing pneumococcal conjugate vaccines (PCVs), serotype replacement occurred in Streptococcus pneumoniae. 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). Carriage data from Massachusetts (MA) and Southwest United States were used to calculate weights. Using pre-vaccine data, serotype-specific inverse-invasiveness weights were defined as the ratio of the proportion of the serotype in carriage to the proportion in invasive data. Genomic data were processed under bioinformatic pipelines to define genetically similar sequence clusters (i.e., strains), and accessory genes (COGs) present in 5-95% of isolates. Weights were applied to adjust observed strain proportions and COG frequencies. The negative frequency-dependent selection (NFDS) model predicted strain proportions by calculating the post-vaccine strain composition in the weighted invasive disease population that would best match pre-vaccine COG frequencies. Inverse-invasiveness weighting increased the correlation of COG frequencies between invasive and carriage data in linear or logit scale for pre-vaccine, post-PCV7, and post-PCV13; and between different epochs in the invasive data. Weighting the invasive data significantly improved the NFDS model's accuracy in predicting strain proportions in the carriage population in the post-PCV13 epoch, with the adjusted R(2) increasing from 0.254 before weighting to 0.545 after weighting. The weighting system adjusted invasive disease data to better represent the pneumococcal carriage population, allowing the NFDS mechanism to predict strain proportions in carriage in the post-PCV13 epoch. Our methods enrich the value of genomic sequences from invasive disease surveillance.IMPORTANCEStreptococcus pneumoniae, a common colonizer in the human nasopharynx, can cause invasive diseases including pneumonia, bacteremia, and meningitis mostly in children under 5 years or older adults. The PCV7 was introduced in 2000 in the United States within the pediatric population to prevent disease and reduce deaths, followed by PCV13 in 2010, PCV15 in 2022, and PCV20 in 2023. After the removal of vaccine serotypes, the prevalence of carriage remained stable as the vacated pediatric ecological niche was filled with certain non-vaccine serotypes. Predicting which pneumococcal clones, and which serotypes, will be most successful in colonization after vaccination can enhance vaccine design and public health interventions, while also improving our understanding of pneumococcal evolution. While carriage data, which are collected from the pneumococcal population that is competing to colonize and transmit, are most directly relevant to evolutionary studies, invasive disease data are often more plentiful. Previously, evolutionary models based on negative frequency-dependent selection (NFDS) on the accessory genome were shown to predict which non-vaccine strains and serotypes were most successful in colonization following the introduction of PCV7. Here, we show that an inverse-invasiveness weighting system applied to invasive disease surveillance data allows the NFDS model to predict strain proportions in the projected carriage population in the post-PCV13/pre-PCV15 and pre-PCV20 epoch. The significance of our research lies in using a sample of invasive disease surveillance data to extend the use of NFDS as an evolutionary mechanism to predict post-PCV13 population dynamics. This has shown that we can correct for biased sampling that arises from differences in virulence and can enrich the value of genomic data from disease surveillance and advance our understanding of how NFDS impacts carriage population dynamics after both PCV7 and PCV13 vaccination.

Multiplex-based serological surveillance is a valuable but underutilized tool to understand gaps in population-level exposure, susceptibility, and immunity to infectious diseases. Assays for which blood samples can be tested for antibodies against several pathogens simultaneously, such as multiplex bead immunoassays, can more efficiently integrate public health surveillance in low- and middle-income countries. On March 7-8, 2023 a group of experts representing research institutions, multilateral organizations, private industry, and country partners met to discuss experiences, identify challenges and solutions, and create a community of practice for integrated, multi-pathogen serosurveillance using multiplex bead assay technologies. Participants were divided into six working groups: 1) supply chain; 2) laboratory assays; 3) seroepidemiology; 4) data analytics; 5) sustainable implementation; and 6) use case scenarios. These working groups discussed experiences, challenges, solutions, and research needs to facilitate integrated, multi-pathogen serosurveillance for public health. Several solutions were proposed to address challenges that cut across working groups.

Many individually randomized group treatment (IRGT) trials randomly assign individuals to study arms but deliver treatments via shared agents, such as therapists, surgeons, or trainers. Post-randomization interactions induce correlations in outcome measures between participants sharing the same agent. Agents can be nested in or crossed with trial arm, and participants may interact with a single agent or with multiple agents. These complications have led to ambiguity in choice of models but there have been no systematic efforts to identify appropriate analytic models for these study designs. To address this gap, we undertook a simulation study to examine the performance of candidate analytic models in the presence of complex clustering arising from multiple membership, single membership, and single agent settings, in both nested and crossed designs and for a continuous outcome. With nested designs, substantial type I error rate inflation was observed when analytic models did not account for multiple membership and when analytic model weights characterizing the association with multiple agents did not match the data generating mechanism. Conversely, analytic models for crossed designs generally maintained nominal type I error rates unless there was notable imbalance in the number of participants that interact with each agent.

The Snell dwarf mouse (Pit1(dw/dw)), an animal model of congenital combined pituitary hormone deficiency, displays skeletal muscle weakness. While enhanced responsivity to repeated exposures of muscle contractions have been documented for Snell dwarf mice, the response following single exposure to distinct contraction protocols remained uncharacterized. The purpose of this study was to investigate the muscle recovery of Snell dwarf and control littermate mice following a single exposure to two separate protocols-an intermittent slow velocity (30°/s) contraction protocol or a continuous rapid velocity (500°/s) contraction protocol. Following both protocols for control mice, torque values were 30% and 80% of pre-protocol values at 5 min and 3 days, respectively. At 10 days, performance returned to baseline for the 30°/s protocol and were depressed for the 500°/s protocol. For Snell dwarf mice following both protocols, torques were depressed to 5% of pre-protocol values at 5 min and returned to baseline by 3 days. Recovery following the 30°/s protocol for control mice and both protocols for Snell dwarf mice coincided with increased transcriptional output, upregulation of cytokine-mediated signaling genes, and a distribution shift to smaller muscle fibers with reduced area per nucleus. These features represent efficacious remodeling ubiquitous across distinct contraction paradigms in the context of the Pit1 mutation.

CONTEXT: Congenital cytomegalovirus (cCMV) infection is the most common infectious cause of birth defects and the leading non-genetic cause of sensorineural hearing loss in the United States. Prior national cCMV infection prevalence estimates were based on one multi-site screening study conducted between 2007 and 2012 and were not adjusted for sociodemographic characteristics, such as maternal race and ethnicity or age. OBJECTIVE: This study sought to estimate national and state-specific prevalence of cCMV infection in the United States, adjusted for maternal race and ethnicity and maternal age group, by pooling estimates from published studies. DESIGN: We searched PubMed for U.S. cCMV newborn screening studies conducted between 2003 and 2023. From included studies, we abstracted maternal race and ethnicity- and age group-stratified cCMV prevalence to estimate strata-specific pooled prevalence. We obtained strata-specific weights from live birth data. MAIN OUTCOME MEASURE: Estimated adjusted national and state-specific prevalence estimates from 2018 to 2022. RESULTS: Four studies (conducted 2004-2005, 2008, 2007-2012, and 2016-2021) were included for data abstraction. Overall, infants born to non-Hispanic Black (9.3 [8.2-10.5] per 1000) or non-Hispanic American Indian and Alaska Native (8.5 [2.1-33.2] per 1000) mothers had the highest cCMV prevalence. The estimated race and ethnicity-adjusted prevalence was 4.6-4.7 per 1000 live births nationally and ranged from 3.9 to 6.5 per 1000 across states from 2018 to 2022. Southern states and Alaska consistently had the highest cCMV prevalence. The estimated maternal age group-adjusted prevalence was 4.3-4.4 per 1000 live births nationally and ranged from 3.8 to 5.1 per 1000 across states from 2018 to 2022. CONCLUSIONS: States with larger proportions of racial and ethnic minorities had higher estimated prevalence of cCMV infection compared to states with larger proportions of White persons. These estimates may be useful for informing cCMV surveillance at the jurisdiction level and developing tailored, culturally relevant education and prevention strategies for persons at higher risk.

Artificial intelligence (AI)-the field of computer science that designs machines to perform tasks that typically require human intelligence-has seen rapid advances in the development of foundation systems such as large language models. In the workplace, the adoption of AI technologies can result in a broad range of hazards and risks to workers, as illustrated by the recent growth in industrial robotics and algorithmic management. Sources of risk from deployment of AI technologies across society and in the workplace have led to numerous government and private sector guidelines that propose principles governing the design and use of trustworthy and ethical AI. As AI capabilities become integrated in devices, machines, and systems across industry sectors, employers, workers, and occupational safety and health practitioners will be challenged to manage AI risks to worker health, safety, and well-being. Five risk management options are presented as ways to assure that only trustworthy and ethical AI enables workplace devices, machinery, and processes. AI technologies will play a significant role in the future of work. The occupational safety and health practice and research communities need to ensure that the promise of these new AI technologies results in benefit, not harm, to workers.

Persons who work in close contact with dairy cattle and poultry that are infected with highly pathogenic avian influenza (HPAI) A(H5N1) virus are at increased risk for infection. In July 2024, the Colorado Department of Public Health & Environment responded to two poultry facilities with HPAI A(H5N1) virus detections in poultry. Across the two facilities, 663 workers assisting with poultry depopulation (i.e., euthanasia) received screening for illness; 109 (16.4%) reported symptoms and consented to testing. Among those who received testing, nine (8.3%) received a positive influenza A(H5) virus test result, and 19 (17.4%) received a positive SARS-CoV-2 test result. All nine workers who received positive influenza A(H5) test results had conjunctivitis, experienced mild illness, and received oseltamivir. This poultry exposure-associated cluster of human cases of influenza A(H5) is the first reported in the United States. The identification of these cases highlights the ongoing risk to persons who work in close contact with infected animals. Early response to each facility using multidisciplinary, multilingual teams facilitated case-finding, worker screening, and treatment. As the prevalence of HPAI A(H5N1) virus clade 2.3.4.4b genotype B3.13 increases, U.S. public health agencies should prepare to rapidly investigate and respond to illness in agricultural workers, including workers with limited access to health care.

OBJECTIVES: . The United States Centers for Disease Control and Prevention (CDC) conducts active surveillance for typhoid fever cases caused by Salmonella enterica serovar Typhi (Typhi). Here we describe the characteristics of the first two cases of mph(A)-positive azithromycin-resistant Typhi identified through US surveillance. METHODS: . Isolates were submitted to public health laboratories, sequenced, and screened for antimicrobial resistance determinants and plasmids, as part of CDC PulseNet's routine genomic surveillance. Antimicrobial susceptibility testing and long-read sequencing were also performed. Basic case information (age, sex, travel, outcome) was collected through routine questionnaires; additional epidemiological data was requested through follow-up patient interviews. RESULTS: . The patients are related and both reported travel to India (overlapping travel dates) before illness onset. Both Typhi genomes belong to the GenoTyphi lineage 4.3.1.1 and carry the azithromycin-resistance gene mph(A) on a PTU-FE (IncFIA/FIB/FII) plasmid. These strains differ genetically from mph(A)-positive Typhi genomes recently reported from Pakistan, suggesting independent emergence of azithromycin resistance in India. CONCLUSIONS: . Cases of typhoid fever caused by Typhi strains resistant to all available oral treatment options are cause for concern and support the need for vaccination of travelers to Typhi endemic regions. US genomic surveillance serves as an important global sentinel for detection of strains with known and emerging antimicrobial resistance profiles, including strains from areas where routine surveillance is not conducted.

BACKGROUND: Hepatitis C virus (HCV) disproportionately affects among people who inject drugs (PWID) globally. Despite carrying a high HCV burden, little is known about transmission dynamics in low-and-middle income countries. METHODS: We recruited PWID from Nairobi and Coastal cities of Mombasa, Kilifi and Malindi in Kenya at needle and syringe programs. Next-generation sequencing data from HCV hypervariable region 1 were analyzed using Global Hepatitis Outbreak and Surveillance Technology (GHOST) to identify transmission clusters. RESULTS: HCV strains belonged to genotype 1a (n=64, 46.0%), 4a (n=72, 51.8%), and were mixed HCV/1a/4a (n=3, 2.2%). HCV/1a was dominant (61.2%) in Nairobi while HCV/4a was dominant in Malindi (85.7%) and Kilifi (60.9%); whereas both genotypes were evenly identified in Mombasa (45.3%, for HCV/1a and 50.9% for HCV/4a). GHOST identified 11 transmission clusters involving 90 cases. Strains in the two largest clusters (n=38 predominantly HCV/4a, and n=32 HCV/1a) were sampled from all four cities. CONCLUSION: Transmission clusters involving 64.7% of cases indicate an effective sampling of major HCV strains circulating among PWID. Large clusters involving 77.8% of strains from Nairobi and Coast suggest successful introduction of two ancestral HCV/1a and HCV/4a strains to PWID, with widely spread progeny. Disruption of the country-wide transmission network is essential for HCV elimination.

The taxonomy of the Cryptococcus gattii species complex continues to evolve, and has been divided into five pathogenic species. The objective of this systematic review was to summarise the geographical distribution of the C gattii species complex and the species within the C gattii species complex. We searched PubMed for articles related to human, animal, ecological, or laboratory-based studies of C gattii species complex isolates with traceable geographical origin published from January, 1970, until September, 2021. Having extracted their geographical origin, we used ArcMap to construct maps according to the highest degree of resolution allowed by their reported taxonomy, to reflect the most likely area of transmission on the basis of published reports of human isolates. 604 such articles were included in the study. This review indicated that although C gattii species complex isolates have been reported globally, understanding their heterogeneous geographical distribution by species can have implications for researchers and clinicians in formulating research questions and considering diagnostic quandaries.

OBJECTIVES: The Laboratory Response Network (LRN) consists of US and international laboratories that respond to public health emergencies, such as biothreats. We used a qualitative approach to assess the successes and challenges of the LRN during the initial 10 weeks of the 2022 mpox outbreak (May 17-July 31, 2022). METHODS: We conducted 9 unstructured interviews, which included 3 interviews with subject matter experts from the Centers for Disease Control and Prevention (CDC) and 6 interviews with state and local public health laboratories and epidemiologists and Association of Public Health Laboratories (APHL) staff. We asked guiding questions on investments in preparedness, successes, and challenges during the initial mpox response and asked for suggestions to improve future LRN responses to infectious disease outbreaks. We also reviewed data from 2 contemporaneous APHL surveys conducted in June and July 2022 in 84 LRN public health laboratories. RESULTS: Notable successes included availability of an assay that had received clearance from the US Food and Drug Administration (FDA) for testing orthopoxviruses (non-variola Orthopoxvirus [NVO] assay) and a trained workforce; strong relationships among FDA, CDC, and the LRN; and strong communications between LRN laboratories and CDC. Challenges included variability among LRN laboratories in self-reported testing capacity, barriers to accessing the NVO assay for health care providers, and gaps in LRN function during surges of testing needs. CONCLUSIONS: The LRN system plays an essential role in the response to emerging infectious disease outbreaks in the United States. Lessons learned from the LRN's initial response to the mpox outbreak can help guide improvements to better position the LRN for future responses, including continued engagement with health care providers, commercial laboratories, and laboratories in health care settings.

Radon is a known cause of lung cancer. Protective standards for radon exposure are derived largely from studies of working populations that are prone to healthy worker survivor bias. This bias can lead to under-protection of workers and is a key barrier to understanding health effects of many exposures. We apply inverse probability weighting to study a set of hypothetical exposure limits among 4,137 male, White and American Indian radon-exposed uranium miners in the Colorado Plateau followed from 1950 to 2005. We estimate cumulative risk of lung cancer through age 90 under hypothetical occupational limits. We estimate that earlier implementation of the current US Mining Safety and Health Administration annual standard of 4 working level months (implemented here as a monthly exposure limit) could have reduced lung cancer mortality from 16/100 workers to 6/100 workers (95% confidence intervals: 3/100, 8/100), in contrast with previous estimates of 10/100 workers. Our estimate is similar to that among contemporaneous occupational cohorts. Inverse probability weighting is a simple and computationally efficient way address healthy worker survivor bias in order to contrast health effects of exposure limits and estimate the number of excess health outcomes under exposure limits at work.

Information on microorganisms in indoor air of various institutional and commercial buildings has significant value in a public health management perspective. However, there is a lack of prior research comparing indoor airborne microbiota across different categories of those buildings. We characterized indoor airborne bacteria in 10 buildings (two for each of five categories: train station, parking garage, mart, public library, and daycare center) during summer and winter. The 16S rRNA gene in the bacterial gDNA extracted from samples was quantified using quantitative real-time polymerase chain reaction and sequenced with the Illumina MiSeq™ platform for characterizing community composition. We collected information on temperature, relative humidity, CO2 concentration, and particulate matter (PM) concentrations by particle size (<1 µm, 1–2.5 µm, 2.5–10 µm) indoors. We performed a multivariate regression analysis to identify factors influencing bacterial quantity and Permutational Multivariate Analysis of Variance (PERMANOVA) to determine factors affecting cluster dissimilarity. We found that bacterial concentration was significantly (p-values < 0.05) associated with season and CO2 concentration. The PERMANOVA analyses showed the significant (p-values < 0.05) associations of bacterial cluster dissimilarity with season, building category, and CO2. Our study indicated that the season, and CO2 concentrations may be important factors associated with the indoor airborne bacterial concentration and composition. Building category and usage appeared to significantly influence the bacterial community composition but not the concentration. Our study may provide basic data on bacterial community composition and their concentration that are needed for properly managing microbial exposures in occupants or customers of the studied institutional and commercial buildings. Copyright © 2024 American Association for Aerosol Research. © 2024 American Association for Aerosol Research.

We examined whether mixtures of urinary concentrations of bisphenol A (BPA), parabens and phthalate metabolites were associated with serum lipid levels among 175 pregnant women who enrolled in the Environment and Reproductive Health (EARTH) Study (2005-2017), including triglycerides, total cholesterol, high-density lipoprotein (HDL), non-HDL, and low-density lipoprotein (LDL). We applied Bayesian Kernel Machine Regression (BKMR) and quantile g-computation while adjusting for confounders. In the BKMR models, we found no associations between chemical mixture and lipid levels, e.g., total cholesterol [mean difference (95% CRI, credible interval) = 0.02 (-0.31, 0.34)] and LDL [mean difference (95% CRI) = 0.10 (-0.22, 0.43)], when comparing concentrations at the 75th to the 25th percentile. When stratified by BMI, we found suggestive positive relationships between urinary propylparaben and total cholesterol and LDL among women with high BMI [mean difference (95% CRI) = 0.25 (-0.26, 0.75) and 0.35 (-0.25, 0.95)], but not with low BMI [mean difference (95% CRI) = 0.00 (-0.06, 0.07) and 0.00 (-0.07, 0.07)]. No association was found by quantile g-computation. This exploratory study suggests mixtures of phenol and phthalate metabolites were not associated with serum lipid levels during pregnancy, while there were some suggestive associations for certain BMI subgroups. Larger longitudinal studies with multiple assessments of both exposure and outcome are needed to corroborate these novel findings.

BACKGROUND& AIMS: The protection provided by rotavirus (RV) vaccines is highly heterogeneous amongst individuals. We hypothesized that microbiota composition might influence RV vaccine efficacy. METHODS: First, we examined the potential of segmented filamentous bacteria (SFB) colonization to influence RV vaccine efficacy in mice. Next, we probed the Influence of human microbiomes on RV vaccination via administering mice fecal microbial transplants (FMT) from children with robust or minimal RV vaccine responsiveness. Post-FMT, mice were subjected to RV vaccination followed by RV challenge. RESULTS: SFB colonization induced a phenotype that was reminiscent of RV vaccine failure, i.e. failure to generate RV antigens and, consequently, anti-RV antibodies following RV vaccination resulting in proneness to RV challenge after SFB levels diminished. FMT from children to mice recapitulated donor vaccination phenotype. Specifically, mice receiving FMT from high-responsive vaccinees copiously shed RV antigens and robustly generated anti-RV antibodies following RV vaccination. Concomitantly, such mice were impervious to RV challenge. In contrast, mice receiving FMT from children who had not responded to RV vaccination exhibited only modest responses to RV vaccination and, concomitantly, remained prone to RV challenge. Microbiome analysis ruled out a role for SFB but suggested involvement of Clostridium perfringens. Oral administration of cultured C. perfringens to gnotobiotic mice partially recapitulated the RV vaccine non-responder phenotype. Analysis of published microbiome data found C. perfringens abundance in children modestly associated with RV vaccine failure. CONCLUSION: Microbiota composition influences RV vaccine efficacy with C. perfringens being one, perhaps of many, potential contributing taxa.

Hybrid immunity, as a result of infection and vaccination to SARS-CoV-2, has been well studied in adults but limited evidence is available in children. We evaluated the antibody responses to primary SARS-CoV-2 infection among vaccinated and unvaccinated children aged ≥ 5 years. METHODS: A longitudinal cohort study of children aged ≥ 5 was conducted during August 2021-August 2022, at sites in Arizona, Texas, Utah, and Florida. Children submitted weekly nasal swabs for PCR testing and provided sera 14-59 days after PCR-confirmed SARS-CoV-2 infection. Antibodies were measured by ELISA against the receptor-binding domain (RBD) and S2 domain of ancestral Spike (WA1), in addition to Omicron (BA.2) RBD, following infection in children, with and without prior monovalent ancestral mRNA COVID-19 vaccination. RESULTS: Among the 257 participants aged 5 to 18 years, 166 (65%) had received at least two mRNA COVID-19 vaccine doses ≥ 14 days prior to infection. Of these, 53 occurred during Delta predominance, with 37 (70%) unvaccinated at the time of infection. The remaining 204 infections occurred during Omicron predominance, with 53 (26%) participants unvaccinated. After adjusting for weight, age, symptomatic infection, and gender, significantly higher mean RBD AUC values were observed among the vaccinated group compared to the unvaccinated group for both WA1 and Omicron (p < 0.0001). A smaller percentage of vaccinated children reported fever during illness, with 55 (33%) reporting fever compared to 44 (48%) unvaccinated children reporting fever (p = 0.021). CONCLUSIONS: Children with vaccine-induced immunity at the time of SARS-CoV-2 infection had higher antibody levels during convalescence and experienced less fever compared to unvaccinated children during infection.

BACKGROUND: Artemether-lumefantrine (AL) is the first line anti-malarial drug for the treatment of uncomplicated malaria in Tanzania. The World Health Organization (WHO) recommends regular efficacy monitoring of anti-malarial drugs to inform case management policy decisions. This study assessed the safety and efficacy of AL for treating uncomplicated P. falciparum malaria in Tanzania in 2022. METHODS: Children 6 months to 10 years with uncomplicated P. falciparum malaria were recruited from four sentinel sites and treated with the standard 6 dose, 3-day regimen for AL. Clinical and parasitological responses were monitored for 28 days using the WHO standard protocol. Genotyping based on msp1, msp2 and glurp was used to distinguish recrudescence from reinfection. SANGER sequencing was used to detect K13 mutations. RESULTS: 352 participants, 88 per site, were enrolled. Four withdrew and 55 experienced parasite recurrence. The PCR corrected Kaplan-Meier efficacies were, 89.9% in Pwani, 95.0% in Kigoma, 94.4% in Tanga, and 98.9% in Morogoro. No K13 mutations were found. CONCLUSIONS: Artemether-lumefantrine remains highly efficacious in three regions of Tanzania but the PCR-corrected efficacy in Pwani fell below the WHO-defined 90% threshold at which policy change is recommended. Implementing strategies to diversify ACTs to ensure effective case management in Tanzania is critical.

Hard ticks (Acari: Ixodidae) have been historically identified by morphological methods which require highly specialized expertise and more recently by DNA-based molecular assays that involve high costs. Although both approaches provide complementary data for tick identification, each method has limitations which restrict their use on large-scale settings such as regional or national tick surveillance programs. To overcome those obstacles, the matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) has been introduced as a cost-efficient method for the identification of various organisms, as it balances performance, speed, and high data output. Here we describe the use of this technology to validate the distinction of two closely related Dermacentor tick species based on the development of the first nationwide MALDI-TOF MS reference database described to date. The dataset obtained from this protein-based approach confirms that tick specimens collected from United States regions west of the Rocky Mountains and identified previously as Dermacentor variabilis are the recently described species, Dermacentor similis. Therefore, we propose that this integrative taxonomic tool can facilitate vector and vector-borne pathogen surveillance programs in the United States and elsewhere.

PURPOSE: To investigate the prevalence, patterns, and predictors of SARS-CoV-2 RNA and culturable virus in tears of a case-ascertained household cohort. DESIGN: Prospective, longitudinal case-ascertained household cohort identified through convenience sampling. METHODS: This analysis was restricted to individuals who were non-hospitalized, symptomatic, and tested positive for SARS-CoV-2 by nasal RT-PCR. Tears and anterior nasal biospecimens were serially collected throughout the acute period. Tears specimens were collected by the study staff using Schirmer test strips, and nasal specimens were self-collected. For both, SARS-CoV-2 RNA was quantified using qRT-PCR, and culturable virus was detected using presence of cytopathic effect (CPE) in tissue culture; positive CPE was confirmed by a qRT-PCR step. A series of cross-sectional unadjusted analyses were performed investigating the relationship between different sociodemographic determinants and biological factors associated with tears RNA positivity. RESULTS: Among the 83 SARS-CoV-2 infected participants, 10 (12%) had at least one RNA-positive tears specimen. Amongst these 10, 5 (50%) had concurrent presence of culturable virus, at a median of 7 days postsymptom onset (IQR: 4-7 days) (absolute range: 4-8 days). CONCLUSIONS: In this longitudinal cohort, we found evidence of culturable virus in the tears of a small proportion of nonhospitalized SARS-CoV-2 infected individuals. Current public health infection precautions do not account for transmission via tears, so these findings may improve our understanding of potential sources of SARS-CoV-2 transmission and contribute to developing future guidelines.

We report a single case of invasive pneumococcal disease (IPD) by serotype 4, multilocus sequence type 10172 (serotype 4/ST10172) isolate with vanG-type resistance genes and reduced vancomycin susceptibility. The isolate was recovered during 2022 from a 66-year-old resident with bacteremic pneumococcal pneumonia within a CDC Active Bacterial Core surveillance (ABCs) site hospital. The patient had received 23-valent pneumococcal polysaccharide vaccine and there was no evidence of concurrent or prior receipt of vancomycin in the previous year. Serotype 4/ST10172 IPD has shown increases within western ABCs sites and the recent acquisition of a vanG element warrants close monitoring of this lineage.

Neisseria gonorrhoeae is a global threat to public health due to the accumulation of antimicrobial resistance mechanisms. ST-1901 is an internationally important sequence type (ST) because of its high incidence and the usual occurrence of chromosomally determined resistance. In this study, we describe the evolution of the ST-1901 and its single locus variants in Rio de Janeiro from 2006 to 2022. We analyzed 82 N. gonorrhoeae isolates according to antimicrobial susceptibility profile, resistance mechanisms, molecular typing, and phylogenetics. Six different single locus variants were detected. Phylogenetic analysis identified five clades, which share similar characteristics. Resistance rates for penicillin and tetracycline decreased due to the lower occurrence of resistance plasmids, but intermediary resistance to penicillin rose. Resistance to ciprofloxacin remained high throughout all clades and the years of the study. Regarding resistance to azithromycin, alterations in mtrR promoter and gene, and 23S rRNA encoding gene rrl were detected, with a notable rise in the incidence of C2611T mutations in more recent years occurring in 4 out of 5 clades. In contrast, beta-lactam resistance associated penA 34 mosaic was found only in one persisting clade (Clade D), as well as unique G45D and A39T mutations in mtrR gene and its promoter (Nm-Like) were found in only Clade B. Taken together, these data suggest that ST-1901, a persistently circulating lineage of N. gonorrhoeae in Rio de Janeiro, has undergone changes over the years and may evolve to develop resistance to the current recommended dual therapy adopted in Brazil, ceftriaxone and azithromycin.

Despite the emergence of antimicrobial-resistant (AMR) strains of Neisseria gonorrhoeae, the treatment of gonorrhea remains empiric and according to standardized guidelines, which are informed by the national prevalence of resistant strains. Yet, the prevalence of AMR varies substantially across geographic and demographic groups. We investigated whether data from the national surveillance system of AMR gonorrhea in the US could be used to personalize the empiric treatment of gonorrhea. We used data from the Gonococcal Isolate Surveillance Project collected between 2000-2010 to train and validate machine learning models to identify resistance to ciprofloxacin (CIP), one of the recommended first-line antibiotics until 2007. We used these models to personalize empiric treatments based on sexual behavior and geographic location and compared their performance with standardized guidelines, which recommended treatment with CIP, ceftriaxone (CRO), or cefixime (CFX) between 2005-2006, and either CRO or CFX between 2007-2010. Compared with standardized guidelines, the personalized treatments could have replaced 33% of CRO and CFX use with CIP while ensuring that 98% of patients were prescribed effective treatment during 2005-2010. The models maintained their performance over time and across geographic regions. Predictive models trained on data from national surveillance systems of AMR gonorrhea could be used to personalize the empiric treatment of gonorrhea based on patients' basic characteristics at the point of care. This approach could reduce the unnecessary use of newer antibiotics while maintaining the effectiveness of first-line therapy.

The detection of evolutionary transitions in influenza A (H3N2) viruses' antigenicity is a major obstacle to effective vaccine design and development. In this study, we describe Novel Influenza Virus A Detector (NIAViD), an unsupervised machine learning tool, adept at identifying these transitions, using the HA1 sequence and associated physico-chemical properties. NIAViD performed with 88.9% (95% CI, 56.5-98.0%) and 72.7% (95% CI, 43.4-90.3%) sensitivity in training and validation, respectively, outperforming the uncalibrated null model-33.3% (95% CI, 12.1-64.6%) and does not require potentially biased, time-consuming and costly laboratory assays. The pivotal role of the Boman's index, indicative of the virus's cell surface binding potential, is underscored, enhancing the precision of detecting antigenic transitions. NIAViD's efficacy is not only in identifying influenza isolates that belong to novel antigenic clusters, but also in pinpointing potential sites driving significant antigenic changes, without the reliance on explicit modelling of haemagglutinin inhibition titres. We believe this approach holds promise to augment existing surveillance networks, offering timely insights for the development of updated, effective influenza vaccines. Consequently, NIAViD, in conjunction with other resources, could be used to support surveillance efforts and inform the development of updated influenza vaccines.

BACKGROUND: Tanzania has made significant progress in improving access to HIV care and treatment. However, virologic suppression among people living with HIV (PLHIV) has not been fully realized. In March 2019, Tanzania introduced a World Health Organization (WHO)-recommended dolutegravir-based regimen as the default first-line regimen. Eighteen months later we investigated the HIV viral suppression rates and the factors associated with lack of viral suppression among PLHIV (children and adults) in Tanzania. METHODOLOGY: A cross-sectional survey was conducted from September to December 2020 among PLHIV on antiretroviral therapy (ART) in Tanzania. Whole blood samples, demographic data and clinical information were obtained from eligible adults (≥15 years) and children (< 15 years) attending thirty-six HIV care and treatment centres located in 22 regions of Tanzania mainland. A whole blood sample from each participant was processed into plasma and HIV viral load was estimated using real-time PCR. HIV viral suppression was defined at a cut-off of < 50 copies/mL as recommended by WHO. Analyses were conducted using descriptive statistics to establish the national representative prevalence of viral suppression, and logistic regression analyses to determine independent factors associated with non-suppression. RESULTS: A total of 2,039 PLHIV on ART were recruited; of these, adults and children were 57.5% (n = 1173) and 42.5% (n = 866), respectively. Among the adult population, the mean age and standard deviation (SD) was 42.1 ± 12.4 years, with 64.7% being female. Among children, the mean age and SD were 9.6 ± 3 years, and 53.2% were female. Overall viral suppression at < 50 copies/mL (undetectable) was achieved in 87.8% of adults and 74.4% of children. Adults and children on dolutegravir-based regimen recorded viral suppression rates of 89.7% and 85.1% respectively. Factors independently associated with lack of viral suppression status in the adult population were age and ART adherence while in the children population, the factors were sex, ART adherence, and current ART regimen (p<0.05). CONCLUSION: Dolutegravir-based regimens are promising to help attain epidemic control in Tanzania. More efforts especially on ART adherence are needed to attain optimal treatment outcomes for children and adults PLHIV in Tanzania.

During routine clinical practice, infectious disease physicians encounter patients with difficult-to-diagnose clinical syndromes and may order advanced molecular testing to detect pathogens. These tests may identify potential infectious causes for illness and allow clinicians to adapt treatments or stop unnecessary antimicrobials. Cases of pathogen-agnostic disease testing also provide an important window into known, emerging, and reemerging pathogens and may be leveraged as part of national sentinel surveillance. A survey of Emerging Infections Network members, a group of infectious disease providers in North America, was conducted in May 2023. The objective of the survey was to gain insight into how and when infectious disease physicians use advanced molecular testing for patients with difficult-to-diagnose infectious diseases, as well as to explore the usefulness of advanced molecular testing and barriers to use. Overall, 643 providers answered at least some of the survey questions; 478 (74%) of those who completed the survey had ordered advanced molecular testing in the last two years, and formed the basis for this study. Respondents indicated that they most often ordered broad-range 16S rRNA gene sequencing, followed by metagenomic next-generation sequencing and whole genome sequencing; and commented that in clinical practice, some, but not all tests were useful. Many physicians also noted several barriers to use, including a lack of national guidelines and cost, while others commented that whole genome sequencing had potential for use in outbreak surveillance. Improving frontline physician access, availability, affordability, and developing clear national guidelines for interpretation and use of advanced molecular testing could potentially support clinical practice and public health surveillance.