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To explore associations between histoplasmosis and race and ethnicity, socioeconomic status, and rurality, we conducted an in-depth analysis of social determinants of health and histoplasmosis in 8 US states. Using the Minority Health Social Vulnerability Index (MH SVI), we analyzed county-level histoplasmosis incidence (cases/100,000 population) from the 8 states by applying generalized linear mixed hurdle models. We found that histoplasmosis incidence was higher in counties with limited healthcare infrastructure and access as measured by the MH SVI and in more rural counties. Other social determinants of health measured by the MH SVI tool either were not significantly or were inconsistently associated with histoplasmosis incidence. Increased awareness of histoplasmosis, more accessible diagnostic tests, and investment in rural health services could address histoplasmosis-related health disparities.

Blastomycosis is a rare, potentially fatal fungal infection caused by inhalation of Blastomyces spores, typically acquired outdoors in the midwestern and eastern United States. In 2023, the largest recorded U.S. blastomycosis outbreak occurred among workers at a paper mill in Michigan's Upper Peninsula. Few data exist on occupational risk factors or indoor exposure to Blastomyces, limiting prevention efforts. We assessed workplace environments and conditions associated with blastomycosis risk through a cross-sectional medical survey and environmental sampling. During April 22-28, 2023, we conducted a voluntary medical survey, including a work and health questionnaire and urine antigen testing, for 603 workers out of approximately 1,000 at the mill. We compared worker characteristics, work locations, and environmental exposures by blastomycosis case status and modeled disease risk using Poisson regression. We tested 533 environmental samples of outdoor soil, indoor surface dust, and raw materials for Blastomyces using polymerase chain reaction and culture-based methods. Twenty percent of workers were classified as blastomycosis cases based on positive urine antigen testing during the survey, self-reported provider diagnoses, or confirmed or probable case status reported by state or local health departments. Prevalence was highest among workers in paper machine line #1 (27%) and maintenance areas (25%). Adjusted analyses indicated a 40% [Prevalence Ratio (PR): 1.40; 95% confidence interval (CI): 1.00, 1.95] and 53% (PR: 1.53; 95% CI: 1.04, 2.25) higher risk for workers in these locations, respectively, compared to workers working elsewhere. Working in both locations doubled blastomycosis risk. Daily exposure to indoor pooling water was associated with a nearly two-fold higher prevalence of blastomycosis (PR: 1.79; 95% CI: 1.25, 2.57). All indoor and outdoor environmental samples were negative for Blastomyces. Blastomycosis was associated with specific indoor work locations and environmental conditions, suggesting the potential for occupational exposure to Blastomyces in indoor industrial settings. These findings may guide future outbreak investigations and occupational prevention strategies.

Coccidioidomycosis is an underrecognized fungal infection that can cause serious illness and constitutes a considerable public health burden. The number of cases is likely substantially higher than the nationally reported total, as surveillance does not capture patients who do not seek medical care or who are undiagnosed or misdiagnosed. Coccidioidomycosis is not reportable in all states, and cases not reported to public health entities are likewise missed. A systematic estimate of coccidioidomycosis burden is needed to raise awareness and inform public health interventions and policy. To assess the annual burden of symptomatic coccidioidomycosis in the US. This cross-sectional study developed models incorporating coccidioidomycosis cases reported to the National Notifiable Diseases Surveillance System from January 1 to December 31, 2019, as model inputs. Multipliers from US public health surveillance accounted for factors including health care-seeking behavior, underdiagnosis, underreporting, and in-hospital mortality. Multiplier values were sourced from a combination of literature review and expert opinion. Regional estimates were generated using endemicity levels categorized as high (Arizona and California), low (Nevada, New Mexico, Texas, Utah, and Washington), or unknown (all other states and Washington, DC). Data were accrued from January 1, 2022, to July 1, 2024, and analyzed from October 1, 2022, to September 1, 2024. Coccidioidomycosis reported to public health surveillance entities. Models estimated annual incident symptomatic coccidioidomycosis cases, hospitalizations, and deaths nationally and regionally in the US. A nationwide total of 273 000 (95% credible interval [CrI], 206 000-360 000) incident symptomatic coccidioidomycosis cases were estimated in 2019. High-endemic states accounted for the highest burden (125 000 [95% CrI, 94 000-165 000] cases), followed by states of unknown endemicity (103 000 [95% CrI, 66 000-155 000] cases) and low-endemic states (46 000 [95% CrI, 31 000-65 000] cases). Nationally, models estimated 23 000 annual hospitalizations (95% CrI, 18 000-28 000) and 900 annual deaths (95% CrI, 700-1100) associated with coccidioidomycosis. In this cross-sectional study, the estimated national burden of symptomatic coccidioidomycosis in 2019 was 10 to 18 times higher than the number of cases reported through national surveillance. Better awareness, diagnostic testing practices, and reporting are needed to improve patient outcomes and enhance our understanding of coccidioidomycosis epidemiology.

Coccidioidomycosis, histoplasmosis, and blastomycosis are lower respiratory tract fungal infections whose signs and symptoms can resemble those of other respiratory illnesses, including pneumonia caused by bacterial or viral etiologies; this overlap in clinical presentation might lead to missed or delayed diagnoses. The causative fungi live in the environment, often in soil or plant matter. To describe the epidemiologic characteristics of cases of coccidioidomycosis, histoplasmosis, and blastomycosis during the COVID-19 pandemic, CDC analyzed case surveillance data for 2019-2021. During this period, a total of 59,655 coccidioidomycosis cases, 3,595 histoplasmosis cases, and 719 blastomycosis cases were reported to CDC. In 2020, fewer cases of each disease occurred in spring compared with other seasons, and most cases occurred in fall; national seasonality is not typically observed, and cases were seasonally distributed more evenly in 2019 and 2021. Fewer cases coinciding with the start of the COVID-19 pandemic, along with an unusually high blastomycosis case fatality rate in 2021 (17% compared with more typical rates of 8%-10%), suggest that the pandemic might have affected patients' health care-seeking behavior, public health reporting practices, or clinical management of these diseases. Increased awareness and education are needed to encourage health care providers to consider fungal diseases and to identify pneumonia of fungal etiology. Standardized diagnostic guidance and informational resources for fungal testing could be incorporated into broader respiratory disease awareness and preparedness efforts to improve early diagnosis of coccidioidomycosis, histoplasmosis, and blastomycosis.

Objectives West Nile virus (WNV) is the most common mosquito-borne disease in the United States. Predicting the location and timing of outbreaks would allow targeting of disease prevention and mosquito control activities. Our objective was to develop software (ArboMAP) for routine WNV forecasting using public health surveillance data and meteorological observations. Materials and Methods ArboMAP was implemented using an R markdown script for data processing, modeling, and report generation. A Google Earth Engine application was developed to summarize and download weather data. Generalized additive models were used to make county-level predictions of WNV cases. Results ArboMAP minimized the number of manual steps required to make weekly forecasts, generated information that was useful for decision-makers, and has been tested and implemented in multiple public health institutions. Discussion and Conclusion Routine prediction of mosquito-borne disease risk is feasible and can be implemented by public health departments using ArboMAP. Lay Summary West Nile virus (WNV) is the most common mosquito-borne disease in the United States. To reduce the risk of WNV, public health agencies distribute information about how to avoid mosquito bites and use insecticides to reduce the abundances of disease-transmitting mosquitoes. Information about when and where the risk of getting WNV is highest would help these agencies to target their activities and use limited resources more efficiently. To support this goal, we developed the ArboMAP software system for predicting the risk of WNV disease in humans. ArboMAP uses information about recent weather combined with data obtained from trapping mosquitoes and testing them for presence of WNV to predict how many human cases will occur in future weeks. Predictions extend throughout the current WNV season (typically May-September) and are made for each county within a state. The system is implemented as a set of free software tools that can be used by epidemiologists in state and municipal departments of health. Feedback from public health agencies in South Dakota, Louisiana, Oklahoma, and Michigan has been incorporated to enhance the usability of the system and design visualizations that summarize the forecasts.

Although rabies virus is typically transmitted through mammalian animal bites or scratches, human-to-human transmission has occurred through organ and tissue transplantation. From 1978 to 2013, three transplant-transmitted rabies events in the United States affected nine tissue or organ recipients. Rabies is almost always fatal without timely receipt of postexposure prophylaxis (PEP). In January 2025, clinicians in Ohio notified the Ohio Department of Health and CDC of a suspected case of rabies in a kidney transplant recipient who died 51 days after receiving the transplant. CDC confirmed the recipient's rabies diagnosis. Investigation revealed that the deceased donor had been scratched by a skunk approximately 6 weeks before death. No other organs from that donor were transplanted; however, three persons received cornea tissue grafts. While investigation of the donor's rabies status was ongoing, the cornea recipients underwent precautionary graft removal and received PEP. None developed signs or symptoms compatible with rabies. CDC detected rabies virus RNA in an archived sample of the donor's kidney, confirming organ-derived transmission. Investigation identified 370 persons with possible exposures to the donor or kidney recipient; 357 (96%) completed risk assessments. Among those who completed risk assessments, 46 (13%) were recommended to receive PEP. Early consultation with public health officials might prevent rabies-infected organ and tissue donation or lead to prompt PEP for transplant recipients. The risk for rabies should be considered among donors who have received rabies-susceptible animal bites or scratches within the previous year, particularly those donors with acute encephalopathy.

Background Whole-genome bisulfite sequencing (WGBS) is becoming an increasingly accessible technique, used widely for both fundamental and disease-oriented research. Library preparation methods benefit from a variety of available kits, polymerases and bisulfite conversion protocols. Although some steps in the procedure, such as PCR amplification, are known to introduce biases, a systematic evaluation of biases in WGBS strategies is missing. Results We perform a comparative analysis of several commonly used pre- and post-bisulfite WGBS library preparation protocols for their performance and quality of sequencing outputs. Our results show that bisulfite conversion per se is the main trigger of pronounced sequencing biases, and PCR amplification builds on these underlying artefacts. The majority of standard library preparation methods yield a significantly biased sequence output and overestimate global methylation. Importantly, both absolute and relative methylation levels at specific genomic regions vary substantially between methods, with clear implications for DNA methylation studies. Conclusions We show that amplification-free library preparation is the least biased approach for WGBS. In protocols with amplification, the choice of bisulfite conversion protocol or polymerase can significantly minimize artefacts. To aid with the quality assessment of existing WGBS datasets, we have integrated a bias diagnostic tool in the Bismark package and offer several approaches for consideration during the preparation and analysis of WGBS datasets.

Background Hypoxia is pervasive in cancer and other diseases. Cells sense and adapt to hypoxia by activating hypoxia-inducible transcription factors (HIFs), but it is still an outstanding question why cell types differ in their transcriptional response to hypoxia. Results We report that HIFs fail to bind CpG dinucleotides that are methylated in their consensus binding sequence, both in in vitro biochemical binding assays and in vivo studies of differentially methylated isogenic cell lines. Based on in silico structural modeling, we show that 5-methylcytosine indeed causes steric hindrance in the HIF binding pocket. A model wherein cell-type-specific methylation landscapes, as laid down by the differential expression and binding of other transcription factors under normoxia, control cell-type-specific hypoxia responses is observed. We also discover ectopic HIF binding sites in repeat regions which are normally methylated. Genetic and pharmacological DNA demethylation, but also cancer-associated DNA hypomethylation, expose these binding sites, inducing HIF-dependent expression of cryptic transcripts. In line with such cryptic transcripts being more prone to cause double-stranded RNA and viral mimicry, we observe low DNA methylation and high cryptic transcript expression in tumors with high immune checkpoint expression, but not in tumors with low immune checkpoint expression, where they would compromise tumor immunotolerance. In a low-immunogenic tumor model, DNA demethylation upregulates cryptic transcript expression in a HIF-dependent manner, causing immune activation and reducing tumor growth. Conclusions Our data elucidate the mechanism underlying cell-type-specific responses to hypoxia and suggest DNA methylation and hypoxia to underlie tumor immunotolerance.