Prevalence Estimates Research Articles

Antimicrobial resistance among common bacterial pathogens in Indonesia: a systematic review

The WHO Global Antimicrobial Resistance Surveillance System (GLASS) aims to describe antimicrobial resistance (AMR) patterns and trends in common bacterial pathogens, but data remain limited in many low and middle-income countries including Indonesia. We systematically searched Embase, PubMed and Global Health Database and three Indonesian databases for original peer-reviewed articles in English and Indonesian, published between January 1, 2000 and May 25, 2023, that reported antimicrobial susceptibility for the 12 GLASS target pathogens from human samples. Pooled AMR prevalence estimates were calculated for relevant pathogen-antimicrobial combinations accounting for the sampling weights of the studies (PROSPERO: CRD42019155379). Of 2182 search hits, we included 102 papers, comprising 19,517 bacterial isolates from hospitals (13,647) and communities (5870). In hospital settings, 21.6% of Klebsiella pneumoniae isolates, 18.3% of Escherichia coli isolates, 35.8% of Pseudomonas aeruginosa isolates and 70.7% of Acinetobacter baumannii isolates were carbapenem-resistant; 29.9% of Streptococcus pneumoniae isolates were penicillin-resistant; and 22.2% of Staphylococcus aureus isolates were methicillin-resistant. Hospital prevalence of carbapenem-resistant K.pneumoniae and E.coli, and penicillin-resistant S.pneumoniae increased over time. In communities, 28.3% of K.pneumoniae isolates and15.7% of E.coli isolates were carbapenem-resistant, 23.9% of S.pneumoniae isolates were penicillin-resistant, and 11.1% of S.aureus isolates were methicillin-resistant. Data were limited for the other pathogens. AMR prevalence estimates were high for critical gram-negative bacteria. However, data were insufficient to draw robust conclusions about the full contemporary AMR situation in Indonesia. Implementation of national AMR surveillance is a priority to address these gaps and inform context-specific interventions. Wellcome Africa Asia Programme Vietnam.

Estimating Prevalence and Infection Intensity of Soil-Transmitted Helminths Using Quantitative Polymerase Chain Reaction and Kato-Katz in School-Age Children in Angola.

Quantitative polymerase chain reaction (qPCR) is gaining recognition in soil-transmitted helminth (STH) diagnostics, especially for Strongyloides stercoralis and differentiating hookworm species. However, sample preservation and DNA extraction may influence qPCR performance. We estimated STH prevalence and infection intensity by using qPCR in schoolchildren from Huambo, Uige, and Zaire, Angola, and compared its performance with that of the Kato-Katz technique (here termed Kato-Katz). Stool samples from 3,063 children (219 schools) were preserved in 96% ethanol and analyzed by qPCR, of which 2,974 children (215 schools) had corresponding Kato-Katz results. Cluster-adjusted prevalence and infection intensity estimates were calculated by qPCR and Kato-Katz, with cycle threshold values converted to eggs per gram for qPCR. Cohen's kappa statistic evaluated agreement between qPCR and Kato-Katz. DNA extraction and qPCR were repeated on 191 (of 278) samples that were initially qPCR negative but Kato-Katz positive, of which 112 (58.6%) became positive. Similar prevalence for Ascaris lumbricoides (37.5% versus 34.6%) and Trichuris trichiura (6.5% versus 6.1%) were found by qPCR and Kato-Katz, respectively, while qPCR detected a higher hookworm prevalence (11.9% versus 2.9%). The prevalence of moderate- or high-intensity infections was higher by Kato-Katz than by qPCR. Agreement between qPCR and Kato-Katz was very good for A. lumbricoides, moderate for T. trichiura, and fair for hookworm. Strongyloides stercoralis prevalence was 4.7% (municipality range, 0-14.3%), and no Ancylostoma ceylanicum was detected by qPCR. Despite suboptimal performance, presumably due to fixative choice, qPCR was fundamental in detecting S. stercoralis and excluding zoonotic A. ceylanicum. Further evaluations on sample fixatives and DNA extraction methods are needed to optimize and standardize the performance of qPCR.

Tracking the Global Burden of Neural Tube Defects and Assessing Disparities Across World Health Organization Regions: A Scoping Literature Review.

Neural tube defects (NTDs) are an important cause of global morbidity worldwide. Well-planned global neurosurgery and public health efforts can aid vulnerable communities, but there is a need to elucidate the global burden of NTDs and identify regions without available data to better target interventions. A scoping review to quantify worldwide NTD prevalence using the PubMed/Medline and birth defects surveillance registries was conducted. Data published after January 1, 1990, encompassing prevalence values of at least the 2 most prevalent NTDs-spina bifida and encephalocele-were abstracted. Average NTD prevalence rates were aggregated by World Health Organization (WHO) region and World Bank classification, and differences were determined using the analysis of variance test. Differences in availability of nationally representative data by WHO region and World Bank classification were determined using χ2 tests. This review captured 140 studies from a total of 93 of 194 WHO member countries. The percentage of countries within a geographic region with available NTD prevalence data was highest in the Eastern Mediterranean (EMR) (85.7%) and lowest in Africa (AFR) (31.3%). The NTD prevalence range was 0.9-269.6 per 10 000 births. Statistically significant differences in reported NTD prevalence rates existed by WHO Region (P = .00027) and World Bank income level of study country (P = .00193). Forty countries (43%) had conducted national-level studies assessing NTD prevalence. There was a statistically significant difference in the availability of nationally representative prevalence data depending on the WHO region (P = .0081) and World Bank classification of study country (P = .0017). There is a gap in availability of NTD prevalence data worldwide, with many WHO member states lacking national-level NTD prevalence estimates. These findings highlight the need for greater NTD surveillance efforts to identify the countries with the greatest need for targeted global intervention.

Prevalence Estimate for Adjustment Disorders in the South African Navy

Introduction and Aim Adjustment Disorder is among the most commonly diagnosed mental disorders in the armed forces, with a mean prevalence estimated at 7.4% across military populations. The prevalence in South African military populations is not known. This study aimed to estimate the prevalence of Adjustment Disorders in the South African Navy and to explore potential risk factors. Methods In this cross-sectional study, a representative sample of 714 sailors completed the International Adjustment Disorder Questionnaire, and also provided information from their biennial occupational health assessment mental health screening, which included other clinical screeners of mental health and adjustment history. Results The estimated prevalence of Adjustment Disorders in the South African Navy was 6.9%, and was proportionally distributed across gender and age categories. Depression and PTSD were the main comorbid conditions. Risk factors included a) history of adjustment difficulties during military deployment or family adjustment difficulties, b) domestic discord (difficulties in relationship with spouse/partner or immediate family), and c) the experience of stress overload (i.e., that the demands of life are overwhelming available resources). Conclusion The estimated prevalence was similar to the expectation of military personnel generally, although the self-report data needs to be interpreted cautiously. The contributing risk factors offer possible direction for targeted intervention, e.g., skills training and relationship counselling to enhance coping with military service and family challenges, and cognitive behaviour therapy generally to address sailors’ experience of stress overload.

A Two‐stage Bayesian Small Area Estimation Approach for Proportions

SummaryWith the rise in popularity of digital Atlases to communicate spatial variation, there is an increasing need for robust small area estimates. However, current small area estimation methods suffer from various modelling problems when data are very sparse or when estimates are required for areas with very small populations. These issues are particularly heightened when modelling proportions. Additionally, recent work has shown significant benefits in modelling at both the individual and area levels. We propose a two‐stage Bayesian hierarchical small area estimation approach for proportions that can account for survey design, reduce direct estimate instability and generate prevalence estimates for small areas with no survey data. Using a simulation study, we show that, compared with existing Bayesian small area estimation methods, our approach can provide optimal predictive performance (Bayesian mean relative root mean squared error, mean absolute relative bias and coverage) of proportions under a variety of data conditions, including very sparse and unstable data. To assess the model in practice, we compare modelled estimates of current smoking prevalence for 1,630 small areas in Australia using the 2017–2018 National Health Survey data combined with 2016 census data.

Prevalence and associated Factors of Anemia in Diabetic Patients

Introduction: Diabetes presents a significant global health challenge due to its association with a range of pathological changes, such as metabolic, cellular, and blood disturbances, that lead to long-term microvascular and macrovascular complications. Healthcare providers often underestimate anemia as a co-morbidity in diabetes, despite the wide range of prevalence estimates reported in the literature. Addressing anemia in diabetes patients early can reduce the incidence of these complications, as has been demonstrated. Aim of the study: The study aimed to estimate the prevalence of anemia and its associated factors among patients with type 2 diabetes mellitus (T2DM). Methods: This is a cross-sectional prospective study with a retrospective review of diabetic patient medical records attending family medicine clinics at four military hospitals (King Hussien Medical Center, Prince Rashed Military Hospital, Queen Aliah Military Hospital, and Prince Hashem Military Hospital) at Royal Medical Services. Adult patients over the age of 18 diagnosed with type 2 diabetes mellitus for more than one year will be included in the study. However, those patients with diseases (such as thalassemia and leukemia) or other systemic disorders (such as infectious diseases) that could result in anemia, those with acute conditions such as acute hemorrhage, those who received blood transfusions in the last three months, pregnant women, or type 1 diabetes will be excluded. Anemia will be defined as hemoglobin level < 13 g/dl in men and 12g/dl in females (Harrison TR, 2011). Type 2 DM will be defined glycated hemoglobin (HbA1c > 6.5%), fasting blood glucose (FBG > 126 mg/dl), random blood glucose (RBG > 200 mg/dl) (American Diabetes Association, 2012). Patients’ medical records will be reviewed for patient medications, duration of diabetes, diabetic complications, and glycemic control. Furthermore, to exclude any patients who have one or more of the aforementioned conditions reported in the exclusion criteria. Meanwhile, researcher will collect the following data in the clinic after patients’ agreement to participate in the study which include: age, sex, marital status, smoking status, comorbidities, anthropometric measurements including weight, height and body mass index (BMI). Moreover, patient will ask to withdraw complete blood count (CBC) blood sample which include hemoglobin, mean corpuscular volume (MCV), mean corpuscular hemoglobin (MCH) and mean corpuscular hemoglobin concentration (MCHC) for diagnosing anemia if its present. Patients will be divided into two groups based on the presence of anemia; anemic group and non-anemic group. Regarding study variables. Glycemic control will be classified into two categories based on HbA1c result (controlled diabetic group comprised those whose HbA1c level was equal to or <7.5% and poorly controlled diabetic group comprised those whose HbA1c level was >7.5%). Body mass index will classify according to Center of Disease Control (CDC) as follow: BMI score < 18.5 Kg/m2 is underweight, 18.5–24.9 Kg/m2 is normal, 25–29.9 Kg/m2 is overweight and BMI ≥ 30 Kg/m2 is obese. The sample size will be calculated based on Cohran’s sample size formula as: n=Z2 pq /e2. Here, p will be the anticipation of anemia prevalence in the diabetic population, q=1 - p; e is an acceptable error (5%); and Z= 1.96. A simple random sampling (systematic procedure) will be used to choose patients with type 2 diabetes in order to reduce the possibility of selection bias. With this technique, we randomly choose the first subject and then select the next subjects in a periodic manner according to K (interval). K will be determined based on the sampling frame prepared by researchers divided by n. Descriptive analysis will be used with the mean (standard deviation) for normally distributed variables and the median (inter-quartile range) for highly skewed distributions. The t-test and the Mann-Whitney test will be used to compare the baseline characteristics of quantitative variables between anemic and non-anemic groups for variables with a normal and highly skewed distribution, respectively. Categorical variables will be compared between the groups using the chi-square test. Logistic regression analyses will be employed to find out how these variables are associated with anemia. The results will be given as odds ratios (ORs) with a 95% confidence interval (CI). We will select only covariates with a p-value <0.20 in the univariate analysis to enter the logistic analysis.

Prevalence of ALS in all 50 states in the United States, data from the National ALS Registry, 2011–2018

Objective: To summarize the prevalence of ALS in all 50 states and Washington, DC in the United States from 2011 to 2018 using data collected and analyzed by the National ALS Registry. In October 2010, the federal Agency for Toxic Substances and Disease Registry (ATSDR) launched the congressionally mandated Registry to determine the incidence and prevalence of ALS within the USA, characterize the demographics of persons with ALS, and identify the potential risk factors for the disease. This is the first analysis of state-level ALS prevalence estimates. Methods: ALS is not a notifiable disease in the USA, so the Registry uses a two-pronged approach to identify cases. The first approach uses existing national administrative databases (Medicare, Veterans Health Administration, and Veterans Benefits Administration). The second method uses a secure web portal to gather voluntary participant data and identify cases not included in the national administrative databases. Results: State-level age-adjusted average prevalence from 2011–2018 ranged from 2.6 per 100,000 persons (Hawaii) to 7.8 per 100,000 persons (Vermont), with an average of 4.4 per 100,000 persons in the US. New England and Midwest regions had higher prevalence rates than the national average. Conclusions: These findings summarize the prevalence of ALS for all 50 states from 2011 to 2018. This is a continuing effort to identify ALS cases on a national population basis. The establishment of the National ALS Registry has allowed for epidemiological trends of this disease and the assessment of potential risk factors that could cause ALS.

Prevalence and correlates of alcohol and drug harms to others: Findings from the 2020 U.S. National Alcohol Survey.

Measure prevalence and overlap of secondhand harms from other people's use of alcohol, cannabis, opioid, or other drugs and examine sociodemographic and other correlates of these secondhand harms. This cross-sectional analysis used data from 7,799 respondents (51.6% female; 12.9% Black, 15.6% Hispanic/Latiné; mean age: 47.6) in the 2020 U.S. National Alcohol Survey. Secondhand harms included family/marriage difficulties, traffic accidents, vandalism, physical harm, and financial difficulties. Weighted prevalence estimates provided nationally representative estimates of these harms. Logistic regression assessed associations between individual characteristics and secondhand harms. Lifetime prevalence of secondhand harms from alcohol, cannabis, opioid, or other drugs was 34.2%, 5.5%, 7.6%, and 8.3%, respectively. There was substantial overlap among lifetime harms: almost 30% of those reporting secondhand alcohol harms also reported secondhand drug harms. Significant correlates of secondhand substance harms included female sex (alcohol, other drug); white (alcohol, opioid), American Indian/Alaska Native (opioid), and Black (cannabis) race/ethnicity; and separated/divorced/widowed marital status (opioid). Those reporting family history of alcohol problems had significantly higher odds of reporting secondhand harms across substance types. Individuals who reported frequent cannabis use had higher odds of reporting secondhand alcohol and opioid harms compared to those with no cannabis use, (aOR=1.55; aOR=2.38), but lower odds of reporting secondhand cannabis harms (aOR=0.51). Although less prevalent than secondhand alcohol harms, 14% of participants reported secondhand harms from someone else's drug use and frequently experienced secondhand harms attributed to multiple substances. Population-focused interventions are needed to reduce the total burden of alcohol and drug use.

Herd-level prevalence of bovine leukemia virus, Salmonella Dublin and Neospora caninum in Alberta, Canada, dairy herds using ELISA on bulk tank milk samples

Endemic infectious diseases remain a major challenge for dairy producers worldwide. For effective disease control programs, up-to-date prevalence estimates are of utmost importance. The objective of this study was to estimate the herd-level prevalence of bovine leukemia virus (BLV), Salmonella Dublin, and Neospora caninum in dairy herds in Alberta, Canada using a serial cross-sectional study design. Bulk tank milk samples from all Alberta dairy farms were collected 4 times, in December 2021 (n = 489), April 2022 (n = 487), July 2022 (n = 487), and October 2022 (n = 480), and tested for antibodies against BLV, S. Dublin, and N. caninum using ELISAs. Herd-level apparent prevalence was calculated as positive samples divided by total tested samples at each time point. A mixed effect modified Poisson regression model was employed to assess the association of prevalence with region, herd size, herd type, and type of milking system. Apparent prevalence of BLV was 89.4, 88.7, 86.9 and 86.9% in December, April, July, and October, respectively, whereas for S. Dublin apparent prevalence was 11.2, 6.6, 8.6, and 8.5%, and for N. caninum apparent prevalence was 18.2, 7.4, 7.8, and 15.0%. For BLV, S. Dublin and N. caninum, a total of 91.7, 15.6, and 28.1% of herds, respectively, were positive at least once, whereas 82.5, 3.6, and 3.0% of herds were ELISA-positive at all 4 times. Compared with the north region, central Alberta had a high prevalence (prevalence ratio (PR) = 1.13) of BLV-antibody positive herds, whereas south Alberta had a high prevalence (PR = 2.56) of herds positive for S. Dublin antibodies. Furthermore, central (PR = 0.52) and south regions (PR = 0.46) had low prevalence of N. caninum-positive herds compared with the north. Hutterite colony herds were more frequently BLV-positive (PR = 1.13) but less frequently N. caninum-positive (PR = 0.47). Large herds (>7,200 L/day milk delivered ∼ > 250 cows) were 1.1 times more often BLV-positive, whereas small herds (≤3,600 L/day milk delivered ∼ ≤ 125 cows) were 3.2 times more often N. caninum-positive. For S. Dublin, Hutterite-colony herds were less frequently (PR = 0.07) positive than non-colony herds only in medium and large stratum but not in small stratum. Moreover, larger herds were more frequently (PR = 2.20) S. Dublin-positive than smaller herds only in non-colony stratum but not in colony stratum. Moreover, N. caninum prevalence was 1.6 times higher on farms with conventional milking systems compared with farms with an automated milking system. These results provide up-to-date information of the prevalence of these infections that will inform investigations of within-herd prevalence of these infections and help in devising evidence-based disease control strategies.

A longitudinal analysis of COVID-19 prevention strategies implemented among US K-12 public schools during the 2021-2022 school year

PurposeExamine how school-based COVID-19 prevention strategy implementation varied over time, including by local characteristics. MethodsSchool administrators (n = 335) from a nationally representative sample of K-12 public schools completed four surveys assessing COVID-19 prevention strategies at two-month intervals between October 2021 and June 2022. We calculated weighted prevalence estimates by survey wave. Generalized estimating equations (GEE) were used to model longitudinal changes in strategy implementation, accounting for school and county covariates. ResultsOpening doors/windows, daily cleaning, and diagnostic testing were reported by ≥ 50 % of schools at each survey wave. Several strategies were consistently implemented across the 2021–2022 school year (i.e., daily cleaning, opening doors and windows, diagnostic testing) while other strategies increased initially and then declined (i.e., contact tracing, screening testing, on-campus vaccination) or declined consistently throughout the school year (i.e., mask requirement, classroom distancing, quarantine). Although longitudinal changes in strategy implementation did not vary by school characteristics, strategy implementation varied by urban-rural classification and school level throughout the school year. ConclusionsStrategies that were consistently implemented throughout the school year were also reported by a majority of schools, speaking toward their feasibility for school-based infection control and prevention and potential utility in future public health emergencies.

How Generalizable Are Findings from a Community-Based Prospective Cohort Study? Extending Estimates from the Adult Changes in Thought Study to Its Source Population

Background: The Adult Changes in Thought (ACT) study is a cohort of Kaiser Permanente Washington members ages 65+ that began in 1994. Objective: We wanted to know how well ACT participants represented all older adults in the region, and how well ACT findings on eye disease and its relationship with Alzheimer’s disease generalized to all older adults in the Seattle Metropolitan Region. Methods: We used participation weights derived from pooling ACT and Behavioral Risk Factor Surveillance System (BRFSS) data to estimate prevalences of common eye diseases and their associations with Alzheimer’s disease incidence. Cox proportional hazards models accounted for age, education, smoking, sex, and APOE genotype. Confidence intervals for weighted analyses were bootstrapped to account for error in estimating the weights. Results: ACT participants were fairly similar to older adults in the region. The largest differences were more self-reported current cholesterol medication use in BRFSS and higher proportions with low education in ACT. Incorporating the weights had little impact on prevalence estimates for age-related macular degeneration or glaucoma. Weighted estimates were slightly higher for diabetic retinopathy (weighted 5.7% (95% Confidence Interval 4.3, 7.1); unweighted 4.1% (3.6, 4.6)) and cataract history (weighted 51.8% (49.6, 54.3); unweighted 48.6% (47.3, 49.9)). The weighted hazard ratio for recent diabetic retinopathy diagnosis and Alzheimer’s disease was 1.84 (0.34, 4.29), versus 1.32 (0.87, 2.00) in unweighted ACT. Conclusions: Most, but not all, associations were similar after participation weighting. Even in community-based cohorts, extending inferences to broader populations may benefit from evaluation with participation weights.

Invited Commentary: Raising a High-Pressure Alarm About Pediatric Hypertension.

Hypertension is a common "silent killer" in adult medicine, but epidemiologic estimates of elevated blood pressure in children and adolescents are challenged by under-diagnosis and resultant low utilization of relevant administrative or billing codes. In the article by Horgan et al (Am J Epidemiol 2024), children and adolescents with hypertension and elevated blood pressure were identified using direct assessment of blood pressure measurements available in the electronic health record from both inpatient and outpatient visits ("clinical cohort") in comparison to diagnosis codes ("claims-based cohort"). The study population included 3.75 million pediatric healthcare visits available in the US Food and Drug Administration's Sentinel System. While the study applied a relatively novel methodology to interrogate available clinical data within the EHR to better understand the prevalence of pediatric hypertension and raised concern for a higher occurrence of hypertension among children and adolescents than previously realized using claims codes, the utility of the prevalence estimates may be limited by the potential for misclassification bias inherent in EHR data. However, these data raise important concerns about relaying solely on ICD-9-CM/ICD-10-CM codes to quantify the epidemiology of pediatric hypertension and highlight opportunities to address elevated blood pressure in children that could improve long-term cardiovascular health.

A panel network analysis of posttraumatic stress disorder and obsessive-compulsive disorder symptoms across the perinatal period.

The perinatal period is marked by a higher risk of experiencing depressive, anxiety, and/or trauma-related symptoms, a phenomenon that affects millions of individuals each year. Obsessive-compulsive disorder (OCD) and posttraumatic stress disorder (PTSD) symptoms commonly co-occur but have rarely been examined together beyond prevalence estimates in the perinatal period. Our study aimed to explore patterns of associations among OCD and PTSD symptoms to elucidate within- and between-person effects and how these effects may change over time. Participants (N = 270) were recruited during pregnancy from an academic medical center affiliated with a midwestern university. PTSD, OCD, and depressive symptoms were assessed at pregnancy, 4, 8, and 12 weeks postpartum. A panel graphical vector autoregression model was used to estimate networks. The temporal network provided information regarding directed predictive effects between symptoms, and hyperarousal, neutralizing, and ordering were the most stable and predictive symptoms across time. The contemporaneous network, which yields undirected partial correlations between symptoms at a given moment, indicated that there were positive associations between intrusions and avoidance, hyperarousal and negative alterations in cognitions and mood, as well as between hyperarousal and dysphoria. This study identified hyperarousal and neutralizing as the PTSD and OCD symptoms with the strongest stability, predictive power, and association with other symptoms. Clinically, this indicates that screening for hyperarousal and neutralizing symptoms may identify individuals who could maximally benefit from treatment in the perinatal period. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Halitosis occurrence due to systemic disease and medication

Background: Halitosis, a term originating from "halitisus" and the Greek suffix "osis," refers to malodorous breath. It is a common problem impacting individuals globally, with prevalence estimates ranging from 24% to 65%. Dental issues, dry mouth, infections, medications, and systemic diseases can contribute to halitosis. Notably, systemic conditions like kidney and liver diseases, diabetes, respiratory infections, and gastritis can produce distinct odors in the mouth. The management of halitosis focuses on identifying and addressing underlying causes, with intraoral interventions like oral hygiene measures and extraoral treatments such as medical management based on the etiology. Objectives: To review and clarify association between halitosis with systemic diseases and medication. Conclusion: This study reveals a notable correlation between halitosis and systemic diseases or medication. Halitosis, a common occurrence influenced by various factors, appears to have a strong association with systemic ailments and medication usage.

Gestational Diabetes Prevalence Estimates from Three Data Sources, 2018.

We investigated 2018 gestational diabetes mellitus (GDM) prevalence estimates in three surveillance systems (National Vital Statistics System, State Inpatient Database, and Pregnancy Risk Assessment Monitoring Survey). We calculated GDM prevalence for jurisdictions represented in each system; a subset of data was analyzed for people 18-39 years old in 22 jurisdictions present in all three systems to observe dataset-specific demographics and GDM prevalence using comparable categories. GDM prevalence estimates varied widely by data system and within the data subset despite comparable demographics. Understanding the differences between GDM surveillance data systems can help researchers better identify people and places at higher risk of GDM.

Prevalence of HCV infection in Europe in the DAA era: Review.

In 2016, the Global Health Sector Strategy, ratified by the 69th World Health Assembly, set the ambitious goal of eliminating hepatitis C virus (HCV) and hepatitis B virus infections by 2030, emphasizing the importance of national screening programmes. Achieving this goal depends on each country's ability to identify and treat 80% of chronic hepatitis C cases, a critical threshold set by the World Health Organization. Traditionally, estimates of HCV prevalence have been based on interferon era studies that focused on high-risk subgroups rather than the general population. In addition, the incomplete data available from national registries also limited the understanding of HCV prevalence. The 2016 report from the European Centre for Disease Prevention and Control highlighted that HCV rates varied across European counties, ranging from .1% to 5.9%. However, data were only available for 13 countries, making the overall picture less clear. Additionally, the epidemiological data may have underestimated the true burden of HCV due to lack of awareness among those with chronic infection. The main objective of this review is to provide a comprehensive summary of HCV epidemiology in Europe in the current era of direct-acting antivirals (DAAs). The data included in the analysis range from the end of 2013 to December 2023 and have been categorised according to the United Nations Geoscheme. The resulting synthesis underscores the noteworthy impact of DAA treatment on the epidemiological situation.

Socioeconomic inequalities in pandemic-induced psychosocial stress in different life domains among the working-age population

BackgroundPsychosocial stress is considered a risk factor for physical and mental ill-health. Evidence on socioeconomic inequalities with regard to the psychosocial consequences of the COVID-19 pandemic in Germany is still limited. We aimed to investigate how pandemic-induced psychosocial stress (PIPS) in different life domains differed between socioeconomic groups.MethodsData came from the German Corona-Monitoring nationwide study – wave 2 (RKI-SOEP-2, November 2021–February 2022). PIPS was assessed using 4-point Likert scales with reference to the following life domains: family, partnership, own financial situation, psychological well-being, leisure activity, social life and work/school situation. Responses were dichotomised into “not stressed/slightly stressed/rather stressed” (0) versus “highly stressed” (1). The sample was restricted to the working-age population in Germany (age = 18–67 years, n = 8,402). Prevalence estimates of high PIPS were calculated by sex, age, education and income. Adjusted prevalence ratios (PRs) were estimated using Poisson regression to investigate the association between education/income and PIPS; high education and income were the reference groups.ResultsThe highest stress levels were reported in the domains social life and leisure activity. Women and younger participants reported high stress levels more frequently. The highest inequalities were found regarding people’s own financial situation, and PIPS was higher in low vs. high income groups (PR 5.54, 95% CI 3.61–8.52). Inequalities were also found regarding partnerships with higher PIPS in low vs. high education groups (PR 1.68, 95% CI 1.13–2.49) – and psychological well-being with higher PIPS in low vs. high income groups (PR 1.52, 95% CI 1.14–2.04).ConclusionSocioeconomic inequalities in PIPS were found for different life domains. Generally, psychosocial support and preventive interventions to help people cope with stress in a pandemic context should be target-group-specific, addressing the particular needs and circumstances of certain socioeconomic groups.

Antibiotic resistance of Escherichia coli isolated from food and clinical environment in China from 2001 to 2020

Antibiotics are widely used in China's aquaculture, agricultural, and clinical settings and can lead to antibiotic resistance in various pathogens. Although the pooled prevalence estimate (PPE) and antibiotic resistance of Escherichia coli (E. coli) in food and clinical settings has been extensively studied, a comprehensive analysis of the published literature is lacking. We conducted a comprehensive search for research indicators for 2001–2020 in eight major Chinese and English literature databases. Antibiotic PPE and resistance trends of 5933 and 29,451 E. coli isolates were screened and analysed in 35 food studies (total 1821) and 62 clinical studies (total 5159). E. coli strains derived from food had the highest antibiotic resistance rate to tetracycline (TET, 71.3 %), followed by trimethoprim-sulfamethoxazole (SXT, 62.5 %) and cefazolin (CFZ, 36.2 %). E. coli strains isolated from clinical environments were highly resistant to piperacillin (PIP, 71.7 %), TET (68.3 %) and CFZ (60.9 %), consistent with foodborne E. coli drug resistance patterns. E. coli strains isolated from food and clinical samples collected in laboratories carry multiple antibiotic resistance genes (ARGs), such as blaTEM, gryA, gryB, sul1, and tetA, making E. coli a reservoir of ARGs. This study highlights the presence of drug-resistant E. coli pathogens and ARGs in food and clinical environments.

Prevalence of Mild Cognitive Impairment and Alzheimer's Disease Identified in Veterans in the United States.

Diagnostic codes can be instrumental for case identification in Alzheimer's disease (AD) research; however, this method has known limitations and cannot distinguish between disease stages. Clinical notes may offer more detailed information including AD severity and can complement diagnostic codes for case identification. To estimate prevalence of mild cognitive impairment (MCI) and AD using diagnostics codes and clinical notes available in the electronic healthcare record (EHR). This was a retrospective study in the Veterans Affairs Healthcare System (VAHS). Health records from Veterans aged 65 years or older were reviewed during Fiscal Years (FY) 2010-2019. Overall, 274,736 and 469,569 Veterans were identified based on a rule-based algorithm as having at least one clinical note for MCI and AD, respectively; 201,211 and 149,779 Veterans had a diagnostic code for MCI and AD, respectively. During FY 2011-2018, likely MCI or AD diagnosis was defined by≥2 qualifiers (i.e., notes and/or codes)≥30 days apart. Veterans with only 1 qualifier were considered as suspected MCI/AD. Over the 8-year study, 147,106 and 207,225 Veterans had likely MCI and AD, respectively. From 2011 to 2018, yearly MCI prevalence increased from 0.9% to 2.2%; yearly AD prevalence slightly decreased from 2.4% to 2.1%; mild AD changed from 22.9% to 26.8%, moderate AD changed from 26.5% to 29.1%, and severe AD changed from 24.6% to 30.7. The relative distribution of AD severities was stable over time. Accurate prevalence estimation is critical for healthcare resource allocation and facilitating patients receiving innovative medicines.

Prevalence of PTSD in Active Duty Members with Mild Traumatic Brain Injury: Systematic Review and Meta-analysis.

Traumatic brain injury (TBI), particularly mild TBI (mTBI), is a significant health concern for U.S. active duty service members (ADSMs), with potential implications for psychiatric outcomes including PTSD. Despite recognizing this association, the prevalence of PTSD among ADSMs with mTBI remains unclear. The review followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. A thorough search in PubMed, CINAHL, Embase, and PsycINFO databases from 2008 to 2024 focused on identifying studies involving ADSMs with PTSD and mTBI. The R software (version 4.3.2) was employed for meta-analysis with the "meta" and "meta prop" packages. Eight reviewed studies revealed a pooled prevalence estimate of PTSD among ADSMs with mTBI at 36% (95% CI, 30%-41%, P < .01, I2 = 96%). Cohort studies indicated a slightly higher prevalence of 38% (95% CI, 19%-59%, P < .01, I2 = 98%), whereas cross-sectional studies provided a marginally lower prevalence of 34% (95% CI, 27%-40%, P < .01, I2 = 92%). Methodological differences, including diagnostic criteria variability, contribute to the observed variability in prevalence estimates. Despite methodological challenges, this study provides crucial insights into the pooled prevalence of comorbid PTSD and mTBI within the military, emphasizing the need for standardized methodologies and further research to refine understanding and support strategies for affected individuals.