Active Prevalence of Fusarium falciforme and F. acutatum Causing Basal Rot of Onion in Maharashtra, India.

Over the past decade, there have been accumulating reports from researchers, farmers, and field extension personnel on the increasing incidence and spread of onion basal rot in India. Onion basal rot disease is mainly caused by Fusarium spp. This study aimed to validate the information on the active prevalence of F. falciforme and F. acutatum causing Fusarium basal rot (FBR) in Maharashtra. A survey was conducted, and the infected plants/bulbs were collected from fields of 38 locations comprising five districts of Maharashtra, namely, Nashik, Aurangabad, Solapur, Ahmednagar, and Pune, in 2023. This disease was prevalent in high-moisture and high-oil-temperature conditions and the symptoms were observed in most of the fields, with the FBR incidence ranging from 17 to 41%. The available data of basal rot incidence from 1998 to 2022 were analyzed, based on which the prevalence of FBR was 11-50%. Tissue from the infected samples of onion bulbs was used for the isolation. The identification was performed based on colony morphology and microscopic features and confirmed through molecular markers using ITS and Tef-1α gene primers. Of the ten Fusarium isolates collected from selected locations, six species were confirmed as F. acutatum and four as F. falciforme. The pathogenicity tests performed with onion seedlings and bulbs under moist conditions proved that both F. acutatum and F. falciforme independently could cause basal rot disease symptoms but with different degrees of virulence. Koch's postulates were confirmed by reisolating the same pathogens from the infected plants. Thus, the active prevalence of FBR was confirmed in Maharashtra and also, to the best of our knowledge, this is the first report of F. falciforme and F. acutatum causing basal rot of onion independently in Maharashtra, India.

Wastewater tiling amplicon sequencing in sentinel sites reveals longitudinal dynamics of SARS-CoV-2 variants prevalence.

The ongoing evolution of SARS-CoV-2 is a significant concern, especially with the decrease in clinical sequencing efforts, which impedes the ability of public health sectors to prepare for the emergence of new variants and potential COVID-19 outbreaks. Wastewater-based epidemiology (WBE) has been proposed as a surveillance program to detect and monitor the SARS-CoV-2 variants being transmitted in communities. However, research is limited in evaluating the effectiveness of wastewater collection at sentinel sites for monitoring disease prevalence and variant dynamics, especially in terms of inferring the epidemic patterns on a broader scale, such as at the state/province level. This study utilized a multiplexed tiling amplicon-based sequencing (ATOPlex) to track the longitudinal dynamics of variant of concern (VOC) in wastewater collected from municipalities in Queensland, Australia, spanning from 2020 to 2022. We demonstrated that wastewater epidemiology measured by ATOPlex exhibited a strong and consistent correlation with the number of daily confirmed cases. The VOC dynamics observed in wastewater closely aligned with the dynamic profile reported by clinical sequencing. Wastewater sequencing has the potential to provide early warning information for emerging variants. These findings suggest that WBE at sentinel sites, coupled with sensitive sequencing methods, provides a reliable and long-term disease surveillance strategy.

Overcoming denominator problems in refugee settings with fragmented electronic records for health and immigration data: a prediction-based approach.

BACKGROUND: Epidemiological studies in refugee settings are often challenged by the denominator problem, i.e. lack of population at risk data. We develop an empirical approach to address this problem by assessing relationships between occupancy data in refugee centres, number of refugee patients in walk-in clinics, and diseases of the digestive system. METHODS: Individual-level patient data from a primary care surveillance system (PriCarenet) was matched with occupancy data retrieved from immigration authorities. The three relationships were analysed using regression models, considering age, sex, and type of centre. Then predictions for the respective data category not available in each of the relationships were made. Twenty-one German on-site health care facilities in state-level registration and reception centres participated in the study, covering the time period from November 2017 to July 2021. RESULTS: 445 observations ("centre-months") for patient data from electronic health records (EHR, 230 mean walk-in clinics visiting refugee patients per month and centre; standard deviation sd: 202) of a total of 47.617 refugee patients were available, 215 for occupancy data (OCC, mean occupancy of 348 residents, sd: 287), 147 for both (matched), leaving 270 observations without occupancy (EHR-unmatched) and 40 without patient data (OCC-unmatched). The incidence of diseases of the digestive system, using patients as denominators in the different sub-data sets were 9.2% (sd: 5.9) in EHR, 8.8% (sd: 5.1) when matched, 9.6% (sd: 6.4) in EHR- and 12% (sd 2.9) in OCC-unmatched. Using the available or predicted occupancy as denominator yielded average incidence estimates (per centre and month) of 4.7% (sd: 3.2) in matched data, 4.8% (sd: 3.3) in EHR- and 7.4% (sd: 2.7) in OCC-unmatched. CONCLUSIONS: By modelling the ratio between patient and occupancy numbers in refugee centres depending on sex and age, as well as on the total number of patients or occupancy, the denominator problem in health monitoring systems could be mitigated. The approach helped to estimate the missing component of the denominator, and to compare disease frequency across time and refugee centres more accurately using an empirically grounded prediction of disease frequency based on demographic and centre typology. This avoided over-estimation of disease frequency as opposed to the use of patients as denominators.

Trends and Disparities in Treatment and Control of Atherosclerotic Cardiovascular Disease in US Adults, 1999 to 2018.

BACKGROUND: Although cardiovascular mortality continued declining from 2000 to 2019, the rate of this decrease decelerated. We aimed to assess the trends and disparities in risk factor control and treatment among US adults with atherosclerotic cardiovascular disease to find potential causes of the deceleration. METHODS AND RESULTS: A total of 55 ,021 participants, aged ≥20 years, from the 1999 to 2018 National Health and Nutrition Examination Survey were included, of which 5717 were with atherosclerotic cardiovascular disease. Risk factor control was defined as hemoglobin A1c <7%, blood pressure <140/90 mm Hg, and non-high-density lipoprotein cholesterol <100 mg/dL. The prevalence of atherosclerotic cardiovascular disease oscillated between 7.3% and 8.9% from 1999 to 2018. A significant increasing trend was observed in the prevalence of diabetes, obesity, heavy alcohol consumption, and self-reported hypertension within the population with atherosclerotic cardiovascular disease (Ptrend≤0.001). Non-high-density lipoprotein cholesterol <100 mg/dL increased from 7.1% in 1999 to 2002 to 15.7% in 2003 to 2006, before plateauing. Blood pressure control (<140/90 mm Hg) increased until 2011 to 2014, but declined to 70.1% in 2015 to 2018 (Ptrend<0.001, Pjoinpoint=0.14). Similarly, the proportion of participants achieving hemoglobin A1c control began to decrease after 2006 (Pjoinpoint=0.05, Ptrend=0.001). The percentage of participants achieving all 3 targets increased significantly from 4.5% to 18.6% across 1999 to 2018 (Ptrend=0.02), but the increasing trend decelerated after 2005 to 2006 (Pjoinpoint<0.001). Striking disparities in risk factor control and medication use persisted between sexes, and between different racial and ethnic populations. CONCLUSIONS: Worsened control of glycemia, blood pressure, obesity, and alcohol consumption, leveled lipid control, and persistent socioeconomic disparities may be contributing factors to the observed deceleration in decreasing cardiovascular mortality trends.

Role of infrastructure and operation in disease prevalence in dairy farms: groundwork for disease prevention-based antibiotic stewardship.

Attempts at regulating misuse of antibiotics in the dairy industry have been ineffective, especially in low- and middle-income countries, who also typically have high burden of preventable infectious disease, we propose a disease prevention-based approach to minimize the need and in turn consumption of antibiotics in dairy farms. Since the immediate environment of the animals is key to disease prevalence, we targeted the infrastructure- and operation-related factors in dairy farms and their link with prevalence of most common diseases and symptoms. We conducted four focused group discussions and a cross-sectional survey in 378 dairy farms to investigate disease prevalence and associated infrastructural (housing system, and manger shape), and operational (waste management, feed management, and type of cleaning agent) parameters. The most common diseases (Mastitis and secondary infections related to Foot-and-mouth disease) and symptoms (fever and diarrhoea) in the focus area were linked with the infrastructural and operational factors on the dairy farm with higher disease prevalence reported in dairy farms, where the animals were exposed to variations in diurnal temperatures or were hard to clean. We further used ML classifiers - Neural Network (NN), k-Nearest Neighbour (kNN), Support Vector Machine (SVM), Decision Tree (DT), and Random Forest (RF) - to corroborate the relationship between infrastructure and operations of the dairy farms and disease prevalence- The DT classifier on randomly sampled data could predict the prevalence of the two most common diseases (accuracy = 92%, F1-score = 0.919) Our results open new avenues for cost-effective interventions such as use of curve-edged mangers, use of rubber mats on floors, not reusing leftover feed etc. in dairy farms to prevent the most common diseases and symptoms in dairy farms and reduce the need and consumption of antibiotics.

Wild-Type Transthyretin Cardiac Amyloidosis is Not Rare in Elderly Subjects: the CATCH Screening Study.

BACKGROUND: Wild-type transthyretin cardiac amyloidosis (ATTRwt-CA) affects older adults and is currently considered as a rare disorder. OBJECTIVE: We investigated for the first time the prevalence of ATTRwt-CA in elderly individuals from the general population. METHODS: General practitioners from Pisa, Italy, proposed a screening for ATTRwt-CA to all their patients aged 65-90 years, until 1,000 accepted. The following red flags were searched: interventricular septal thickness ≥12 mm, any echocardiographic, ECG or clinical hallmark of CA, or high sensitivity-troponin T ≥14 ng/L. Individuals with at least one red flag (n=346) were asked to undergo the search for a monoclonal protein and bone scintigraphy, and 216 accepted. RESULTS: Four patients received a non-invasive diagnosis of ATTRwt-CA. All complained of dyspnea on moderate effort. A woman and a man aged 79 and 85 years, respectively, showed an intense cardiac tracer uptake (grade 3), left ventricular (LV) wall thickening, grade 2 to 3 diastolic dysfunction, and N-terminal pro-B-type natriuretic peptide (NT-proBNP) >1,000 ng/L. Two other patients (a man aged 74 years and a woman aged 83 years) showed a grade 2 uptake, an increased LV septal thickness, but preserved diastolic function, and NT-proBNP <300 ng/L. The prevalence of ATTR-CA in subjects ≥65 years was calculated as 0.46% (i.e., 4 out of the 870 subjects completing the screening, namely 654 not meeting the criteria for Step 2 and 216 progressing to Step 2). CONCLUSIONS: ATTRwt-CA is uncommon in elderly subjects from the general population, but more frequent than expected for a rare disease.

Wild-type transthyretin cardiac amyloidosis (ATTRwt-CA) is a heart condition mostly found in older adults. ATTRwt-CA is considered a rare disease, although no systematic screening have been performed yet. The study aimed to understand how common this disease is among the general population aged 65 to 90 years in Pisa, Italy. To do this, general practitioners offered screening for ATTRwt-CA to their patients within this age group. The initial step of the screening involved checking for certain warning signs (red flags), like abnormal thickness in a part of the heart called the interventricular septum, unusual heart function observed through various tests, or elevated levels of a specific heart protein. Out of 1,000 individuals who began the screening process, 346 showed at least one of these red flags and were further examined using bone scintigraphy (a type of imaging test) and tests for a specific protein related to this condition. Of these, 216 agreed to proceed with these additional tests. The results showed that four of these patients actually had ATTRwt-CA. Their conditions varied in severity, with some showing more intense signs of the disease on the heart scans, thicker heart walls, and higher levels of heart stress proteins. All four patients experienced mild difficulty in breathing during physical activity. Based on these findings, the study concluded that about 0.46% of elderly individuals in the general population might have ATTRwt-CA, indicating that the disease is somewhat more common in this age group than previously thought.

Estimating the prevalence of dyslipidemia by measuring fenofibrate in 33 cities in China.

Dyslipidemia, recognized as a predominant risk factor for atherosclerotic cardiovascular disease (CVD), remains a pressing health concern worldwide, particularly in China with nearly 40 % of the population adversely suffering. Fenofibrate, as one of the most commonly used drugs for dyslipidemia therapy, excreted as the format of fenofibrate-acid, which showed considerable stability in sewage samples and could be detected as WBE-biomarkers to monitor the prevalence of dyslipidemia. In this work, we reported the first research on estimating the prevalence of dyslipidemia by WBE approach. 527 sewage samples from 33 cities in China were extracted by solid phase and analyzed by LC-MS/MS. The detected concentration of fenofibrate acid in sewage was on an average of 120.5 ± 59.9 ng/L, and the reverse-calculated consumption of fenofibrate based on fenofibrate acid was 77.8 ± 25.0 mg/day/1000inh. Detailed analysis unveiled an average prevalence of fenofibrate at 0.056 % ± 0.018 %, and the dyslipidemia prevalence among the population aged over 15 was ultimately estimated to be 37.9 % ± 9.3 % and was in accordance with the China Cardiovascular research result of 40.4 %, which proves that WBE is a substitutable approach of traditional epidemiological investigation methods due to its timeliness and cost-effectiveness. This study demonstrated that estimating dyslipidemia prevalence by WBE with metabolite fenofibrate acid as a biomarker is feasible in most Chinese cities.

Can polygenic risk scores help explain disease prevalence differences around the world? A worldwide investigation.

Complex disorders are caused by a combination of genetic, environmental and lifestyle factors, and their prevalence can vary greatly across different populations. The extent to which genetic risk, as identified by Genome Wide Association Study (GWAS), correlates to disease prevalence in different populations has not been investigated systematically. Here, we studied 14 different complex disorders and explored whether polygenic risk scores (PRS) based on current GWAS correlate to disease prevalence within Europe and around the world. A clear variation in GWAS-based genetic risk was observed based on ancestry and we identified populations that have a higher genetic liability for developing certain disorders. We found that for four out of the 14 studied disorders, PRS significantly correlates to disease prevalence within Europe. We also found significant correlations between worldwide disease prevalence and PRS for eight of the studied disorders with Multiple Sclerosis genetic risk having the highest correlation to disease prevalence. Based on current GWAS results, the across population differences in genetic risk for certain disorders can potentially be used to understand differences in disease prevalence and identify populations with the highest genetic liability. The study highlights both the limitations of PRS based on current GWAS but also the fact that in some cases, PRS may already have high predictive power. This could be due to the genetic architecture of specific disorders or increased GWAS power in some cases.

Gastric troubles in Iran: The role of social and economic factors in Helicobacter pylori infection.

Background: Helicobacter pylori infection is a major risk factor for gastric cancer in Iran, but the impact of socioeconomic factors on its prevalence is poorly understood. This study aimed to assess the socioeconomic inequalities and risk factors associated with H. pylori infection in Iran. Methods: This cross-sectional study was conducted based on the PERSIAN cohort study. A total of 20460 individuals aged 35 to 70 years in Ardabil, Iran were included in the study. H. pylori infection was determined based on stool tests and clinical records. Multilevel logistic regression models with random intercepts at household and community levels were used to identify risk factors associated with H. pylori prevalence. The concentration index (CIn) and concentration curve (CC) were employed to assess socioeconomic-related inequality. Results: In this study, 70.4% (CI 69.6-71.0) of the participants were infected with H. pylori, with a higher prevalence in women (71.2%) than men (69.6%). Age (OR: 1.37, CI: 1.17-1.61), sex (OR: 1.20, CI: 1.12-1.28), level of education (OR: 1.33, CI: 1.17-1.49), cardiac disease (OR: 1.32, CI:1.18-1.46), and BMI groups (OR: 2.49, CI: 1.11-5.58) were significantly associated with H. pylori infection based on the multivariable logistic regression. The results of the CIn and CC indicated that H. pylori were more prevalent among economically disadvantaged groups (CIn: -0.1065; [-0.1374 to -0.0755]). Conclusion: The prevalence of H. pylori in Iran is higher than in other developing countries, and significant socioeconomic inequality exists between the poor and the rich. To reduce the rate of gastric cancer, socio-economic and demographic factors, especially the poor and people with low levels of education, should be considered.

The urgent need for a policy on epidemiological data on cardiovascular diseases in Bangladesh.

Background: Disease prevention and healthcare policy choices cannot be made without epidemiology data. Since it is a growing country with rapidly increasing illness rates, this information is in great demand in Bangladesh. This is because there is a shortage of reliable and sufficient data, leading to inadequate preventive and treatment methods. Discussion: Poor health concerns and economic conditions mean that not all families can afford to provide the nutrition their members need, leading to an increase in the prevalence of many diseases. The outcome is an ever-increasing threat of cardiovascular disease (CVD) issues, the leading cause of death in Bangladesh, even though the underlying causes remain unknown. There is a strong demand for accurate information on CVD patients in Bangladesh, however, there is no effective framework for managing epidemiological data. This prevents an in-depth analysis of the nation's socioeconomic status, dietary practices, and way of life, as well as the implementation of sound healthcare policy. Conclusion: In this article, we present arguments on this important issue using the healthcare systems of the developed world and Bangladesh as examples.

Evaluation of Respondent-Driven Sampling Prevalence Estimators Using Real-World Reported Network Degree.

Respondent-driven sampling (RDS) is used to measure trait or disease prevalence in populations that are difficult to reach and often marginalized. The authors evaluated the performance of RDS estimators under varying conditions of trait prevalence, homophily, and relative activity. They used large simulated networks (N = 20,000) derived from real-world RDS degree reports and an empirical Facebook network (N = 22,470) to evaluate estimators of binary and categorical trait prevalence. Variability in prevalence estimates is higher when network degree is drawn from real-world samples than from the commonly assumed Poisson distribution, resulting in lower coverage rates. Newer estimators perform well when the sample is a substantive proportion of the population, but bias is present when the population size is unknown. The choice of preferred RDS estimator needs to be study specific, considering both statistical properties and knowledge of the population under study.

Human mobility and disease prevalence.

We examine the effect of human mobility on disease prevalence by studying the dependence of the total infected population at endemic equilibria with respect to population diffusion rates of a diffusive epidemic model. For small diffusion rates, our results indicate that the total infected population size is strictly decreasing with respect to the ratio of the diffusion rate of the infected population over that of the susceptible population. Moreover, when the disease local reproductive function is spatially heterogeneous, we found that: (i) for large diffusion rate of the infected population, the total infected population size is strictly maximized at large diffusion rate of the susceptible population when the recovery rate is spatially homogeneous, while it is strictly maximized at intermediate diffusion rate of the susceptible population when the difference of the transmission and recovery rates are spatially homogeneous; (ii) for large diffusion rate of the susceptible population, the total infected population size is strictly maximized at intermediate diffusion rate of the infected population when the recovery rate is spatially homogeneous, while it is strictly minimized at large diffusion rate of the infected population when the difference of the transmission and recovery rates is spatially homogeneous. Numerical simulations are provided to complement the theoretical results. Our studies may provide some insight into the impact of human mobility on disease outbreaks and the severity of epidemics.

Research data warehouse: using electronic health records to conduct population-based observational studies.

Background: Electronic health records and many legacy systems contain rich longitudinal data that can be used for research; however, they typically are not readily available. Materials and methods: At Kaiser Permanente Southern California (KPSC), a research data warehouse (RDW) has been developed and maintained since the late 1990s and widely extended in 2006, aggregating and standardizing data collected from internal and a few external sources. This article provides a high-level overview of the RDW and discusses challenges common to data warehouses or repositories for research use. To demonstrate the application of the data, we report the volume, patient characteristics, and age-adjusted prevalence of selected medical conditions and utilization rates of selected medical procedures. Results: A total of 105 million person-years of health plan enrollment was recorded in the RDW between 1981 and 2018, with most healthcare utilization data available since early or middle 1990s. Among active enrollees on December 31, 2018, 15% were ≥65 years of age, 33.9% were non-Hispanic white, 43.3% Hispanic, 11.0% Asian, and 8.4% African American, and 34.4% of children (2-17 years old) and 72.1% of adults (≥18 years old) were overweight or obese. The age-adjusted prevalence of asthma, atrial fibrillation, diabetes mellitus, hypercholesteremia, and hypertension increased between 2001 and 2018. Hospitalization and Emergency Department (ED) visit rates appeared lower, and office visit rates seemed higher at KPSC compared to the reported US averages. Discussion and conclusion: Although the RDW is unique to KPSC, its methodologies and experience may provide useful insights for researchers of other healthcare systems worldwide in the era of big data analysis.

Prevalence of Ophidiomyces ophidiicola and epizootiology of snake fungal disease in free-ranging Northern Pine Snakes (Pituophis melanoleucus melanoleucus) in New Jersey.

Snake fungal disease, caused by Ophidiomyces ophidiicola, is recognized as a potential concern for North American snakes. We tested skin swabs from Northern Pine Snakes (Pituophis melanoleucus melanoleucus) in the New Jersey pinelands for the presence of O. ophidiicola before emergence from hibernation. We used qPCR to test the collected swabs for the presence of O. ophidiicola, then determined pathogen prevalence as a function of sampling year, sampling location (skin lesion, healthy ventral skin, healthy head skin) sex, and age. There were no temporal trends in O. ophidiicola detection percentages on snakes, which varied from 58 to 83% in different years. Ophidiomyces ophidiicola detection on snakes was highest in swabs of skin lesions (71%) and lowest in head swabs (29%). Males had higher prevalence than females (82% versus 62%). The fungus was not detected in hatchling snakes (age 0) in the fall, but 75% of juveniles tested positive at the end of hibernation (age 1 year). We also screened hibernacula soil samples for the presence of O. ophidiicola. Where snakes hibernated, 69% of soil samples were positive for O. ophidiicola, and 85% of snakes lying on positive soil samples also tested positive for the pathogen. Although a high proportion of snakes (73%) tested positive for O. ophidiicola during our 4-year study, the snakes appeared healthy except for small skin lesions. We conclude that O. ophidiicola prevalence is high on hibernating Northern Pine Snakes and in the hibernacula soil, with a strong association between snakes and positive adjacent soil. This is the first demonstration that snakes likely become infected during hibernation.

Relative prevalence-based dispersal in an epidemic patch model.

In this paper, we propose a two-patch SIRS model with a nonlinear incidence rate: [Formula: see text] and nonconstant dispersal rates, where the dispersal rates of susceptible and recovered individuals depend on the relative disease prevalence in two patches. In an isolated environment, the model admits Bogdanov-Takens bifurcation of codimension 3 (cusp case) and Hopf bifurcation of codimension up to 2 as the parameters vary, and exhibits rich dynamics such as multiple coexistent steady states and periodic orbits, homoclinic orbits and multitype bistability. The long-term dynamics can be classified in terms of the infection rates [Formula: see text] (due to single contact) and [Formula: see text] (due to double exposures). In a connected environment, we establish a threshold [Formula: see text] between disease extinction and uniform persistence under certain conditions. We numerically explore the effect of population dispersal on disease spread when [Formula: see text] and patch 1 has a lower infection rate, our results indicate: (i) [Formula: see text] can be nonmonotonic in dispersal rates and [Formula: see text] ([Formula: see text] is the basic reproduction number of patch i) may fail; (ii) the constant dispersal of susceptible individuals (or infective individuals) between two patches (or from patch 2 to patch 1) will increase (or reduce) the overall disease prevalence; (iii) the relative prevalence-based dispersal may reduce the overall disease prevalence. When [Formula: see text] and the disease outbreaks periodically in each isolated patch, we find that: (a) small unidirectional and constant dispersal can lead to complex periodic patterns like relaxation oscillations or mixed-mode oscillations, whereas large ones can make the disease go extinct in one patch and persist in the form of a positive steady state or a periodic solution in the other patch; (b) relative prevalence-based and unidirectional dispersal can make periodic outbreak earlier.

Host genetic identity determines parasite community structure across time and space in oyster restoration.

Intraspecific variation in host susceptibility to individual parasite species is common, yet how these effects scale to mediate the structure of diverse parasite communities in nature is less well understood. To address this knowledge gap, we tested how host genetic identity affects parasite communities on restored reefs seeded with juvenile oysters from different sources-a regional commercial hatchery or one of two wild progenitor lines. We assessed prevalence and intensity of three micro- and two macroparasite species for 4 years following restoration. Despite the spatial proximity of restored reefs, oyster source identity strongly predicted parasite community prevalence across all years, with sources varying in their relative susceptibility to different parasites. Oyster seed source also predicted reef-level parasite intensities across space and through time. Our results highlight that host intraspecific variation can shape parasite community structure in natural systems, and reinforce the importance of considering source identity and diversity in restoration design.

Geographic accessibility to public and private health facilities in Kenya in 2021: An updated geocoded inventory and spatial analysis.

Objectives: To achieve universal health coverage, adequate geographic access to quality healthcare services is vital and should be characterized periodically to support planning. However, in Kenya, previous assessments of geographic accessibility have relied on public health facility lists only, assembled several years ago. Here, for the first time we assemble a geocoded list of public and private health facilities in 2021 and make use of this updated list to interrogate geographical accessibility to all health providers. Methods: Existing health provider lists in Kenya were accessed, merged, cleaned, harmonized, and assigned a unique geospatial location. The resultant master list was combined with road network, land use, topography, travel barriers and healthcare-seeking behavior within a geospatial framework to estimate travel time to the nearest (i) private, (ii) public, and (iii) both (public and private-PP) health facilities through a travel scenario involving walking, bicycling and motorized transport. The proportion of the population within 1 h and outside 2-h was computed at 300 × 300 spatial resolution and aggregated at subnational units used for decision-making. Areas with a high disease prevalence for common infections that were outside 1-h catchment (dual burden) were also identified to guide prioritization. Results: The combined database contained 13,579 health facilities, both in the public (55.5%) and private-for-profit sector (44.5%) in 2021. The private health facilities' distribution was skewed toward the urban counties. Nationally, average travel time to the nearest health facility was 130, 254, and 128 min while the population within 1-h was 89.4, 80.5, and 89.6% for the public, private and PP health facility, respectively. The population outside 2-h were 6% for public and PP and 11% for the private sector. Mean travel time across counties was heterogeneous, while the population within 1-h ranged between 38 and 100% in both the public sector and PP. Counties in northwest and southeast Kenya had a dual burden. Conclusion: Continuous updating and geocoding of health facilities will facilitate an improved understanding of healthcare gaps for planning. Heterogeneities in geographical access continue to persist, with some areas having a dual burden and should be prioritized toward reducing health inequities and attaining universal health coverage.

Expanding ACMG variant classification guidelines into a general framework.

BACKGROUND: The American College of Medical Genetics and Genomics (ACMG)-recommended five variant classification categories (pathogenic, likely pathogenic, uncertain significance, likely benign, and benign) have been widely used in medical genetics. However, these guidelines are fundamentally constrained in practice owing to their focus upon Mendelian disease genes and their dichotomous classification of variants as being either causal or not. Herein, we attempt to expand the ACMG guidelines into a general variant classification framework that takes into account not only the continuum of clinical phenotypes, but also the continuum of the variants' genetic effects, and the different pathological roles of the implicated genes. MAIN BODY: As a disease model, we employed chronic pancreatitis (CP), which manifests clinically as a spectrum from monogenic to multifactorial. Bearing in mind that any general conceptual proposal should be based upon sound data, we focused our analysis on the four most extensively studied CP genes, PRSS1, CFTR, SPINK1 and CTRC. Based upon several cross-gene and cross-variant comparisons, we first assigned the different genes to two distinct categories in terms of disease causation: CP-causing (PRSS1 and SPINK1) and CP-predisposing (CFTR and CTRC). We then employed two new classificatory categories, "predisposing" and "likely predisposing", to replace ACMG's "pathogenic" and "likely pathogenic" categories in the context of CP-predisposing genes, thereby classifying all pathologically relevant variants in these genes as "predisposing". In the case of CP-causing genes, the two new classificatory categories served to extend the five ACMG categories whilst two thresholds (allele frequency and functional) were introduced to discriminate "pathogenic" from "predisposing" variants. CONCLUSION: Employing CP as a disease model, we expand ACMG guidelines into a five-category classification system (predisposing, likely predisposing, uncertain significance, likely benign, and benign) and a seven-category classification system (pathogenic, likely pathogenic, predisposing, likely predisposing, uncertain significance, likely benign, and benign) in the context of disease-predisposing and disease-causing genes, respectively. Taken together, the two systems constitute a general variant classification framework that, in principle, should span the entire spectrum of variants in any disease-related gene. The maximal compliance of our five-category and seven-category classification systems with the ACMG guidelines ought to facilitate their practical application.

Comparing Survival in Patients With Lung Cancer With and Without a History of Common Autoimmune Disease.

Introduction: Autoimmune disease has both a predisposing and a protective effect toward malignancy. Though studies have investigated the risk of malignancy in patients with autoimmune disease, there is limited research on how autoimmunity affects survival. Methods: This study compared survival in patients with lung cancer with and without autoimmune disease. Patients with lung cancer were culled from the Surveillance, Epidemiology, and End Results Medicare databases (2007-2014), and autoimmune diseases were identified using diagnosis codes. Results: The overall prevalence of investigated autoimmune diseases among the 112,445 patients was 22.7%. Overall survival (OS) (p < 0.0001) was longer and cancer-specific mortality (CSM) (p < 0.0001) reduced among patients with autoimmune disease. Median OS was 5 months higher. Improved OS and CSM were also apparent in disease stages 1, 3, and 4 in the NSCLC and SCLC subgroups (p < 0.0001) and across most specific autoimmune diseases. After adjusting for the effects of age, sex, race, disease stage, and chronic kidney disease, autoimmune disease was still predictive of higher OS (hazard ratio = 1.23, 95% confidence interval: 1.21-1.25, p < 0.0001) and reduced CSM (hazard ratio = 1.16, 95% confidence interval: 1.14-1.18, p < 0.0001). Conclusions: The prevalence of rheumatoid arthritis, inflammatory bowel disease, and systemic lupus erythematous was highly enriched compared with the general population. The improvement in OS and CSM was larger in NSCLC than in SCLC, suggesting a larger role for the immune system in NSCLC. Alternate explanations for the improved survival include lead time bias, better access to health care, and a survival or autoimmunity-inducing genetic factor.

Cellular prion protein distribution in the vomeronasal organ, parotid, and scent glands of white-tailed deer and mule deer.

Chronic wasting disease (CWD) is a contagious and fatal transmissible spongiform encephalopathy affecting species of the cervidae family. CWD has an expanding geographic range and complex, poorly understood transmission mechanics. CWD is disproportionately prevalent in wild male mule deer and male white-tailed deer. Sex and species influences on CWD prevalence have been hypothesized to be related to animal behaviours that involve deer facial and body exocrine glands. Understanding CWD transmission potential requires a foundational knowledge of the cellular prion protein (PrPC) in glands associated with cervid behaviours. In this study, we characterized the presence and distribution of PrPC in six integumentary and two non-integumentary tissues of hunter-harvested mule deer (Odocoileus hemionus) and white-tailed deer (O. virginianus). We report that white-tailed deer expressed significantly more PrPC than their mule deer in the parotid, metatarsal, and interdigital glands. Females expressed more PrPC than males in the forehead and preorbital glands. The distribution of PrPC within the integumentary exocrine glands of the face and legs were localized to glandular cells, hair follicles, epidermis, and immune cell infiltrates. All tissues examined expressed sufficient quantities of PrPC to serve as possible sites of prion initial infection, propagation, and shedding.