Global Health, Epidemiology and Genomics

Cardiovascular diseases (CVDs) have emerged as the leading cause of deaths worldwide in 2019. Globally, more than three-quarters of the total deaths due to CVDs occur in low- and middle-income countries like Nepal. Although increasing number of studies is available on the prevalence of CVDs, there is limited evidence presenting a complete picture on the burden of CVDs in Nepal. In this context, this study aims to provide comprehensive picture on the burden of CVDs in the country. This study is based on the Global Burden of Disease (GBD) study 2019, which is a multinational collaborative research covering 204 countries and territories across the world. The estimations made from the study are publicly available in the GBD Compare webpage operated by the Institute for Health Metrics and Evaluation (IHME), University of Washington. This article makes use of those data available on the GBD Compare page of IHME website to present the comprehensive picture of the burden of CVDs in Nepal. Overall, in 2019, there were an estimated 1,214,607 cases, 46,501 deaths, and 1,104,474 disability-adjusted life years (DALYs) due to CVDs in Nepal. The age-standardized mortality rates for CVDs witnessed a marginal reduction from 267.60 per 100,000 population in 1990 to 245.38 per 100,000 population in 2019. The proportion of deaths and DALYs attributable to CVDs increased from 9.77% to 24.04% and from 4.82% to 11.89%, respectively, between 1990 and 2019. Even though there are relatively stable rates of age-standardized prevalence, and mortality, the proportion of deaths and DALYs attributed to CVDs have risen sharply between 1990 and 2019. Besides implementing the preventive measures, the health system also needs to prepare itself for the delivery of long-term care of patients with CVDs which could have significant implications on resources and operations.

Enterococci are among the most common opportunistic hospital pathogens. This study used whole-genome sequencing (WGS) and bioinformatics to determine the antibiotic resistome, mobile genetic elements, clone and phylogenetic relationship of Enterococcus faecalis isolated from hospital environments in South Africa. This study was carried out from September to November 2017. Isolates were recovered from 11 frequently touched sites by patients and healthcare workers in different wards at 4 levels of healthcare (A, B, C, and D) in Durban, South Africa. Out of the 245 identified E. faecalis isolates, 38 isolates underwent whole-genome sequencing (WGS) on the Illumina MiSeq platform, following microbial identification and antibiotic susceptibility tests. The tet(M) (31/38, 82%) and erm(C) (16/38, 42%) genes were the most common antibiotic-resistant genes found in isolates originating from different hospital environments which corroborated with their antibiotic resistance phenotypes. The isolates harboured mobile genetic elements consisting of plasmids (n = 11) and prophages (n = 14) that were mostly clone-specific. Of note, a large number of insertion sequence (IS) families were found on the IS3 (55%), IS5 (42%), IS1595 (40%), and Tn3 transposons the most predominant. Microbial typing using WGS data revealed 15 clones with 6 major sequence types (ST) belonging to ST16 (n = 7), ST40 (n = 6), ST21 (n = 5), ST126 (n = 3), ST23 (n = 3), and ST386 (n = 3). Phylogenomic analysis showed that the major clones were mostly conserved within specific hospital environments. However, further metadata insights revealed the complex intraclonal spread of these E. faecalis major clones between the sampling sites within each specific hospital setting. The results of these genomic analyses will offer insights into antibiotic-resistantE. faecalis in hospital environments relevant to the design of optimal infection prevention strategies in hospital settings.

The coronavirus disease 2019 (COVID-19) has wreaked havoc globally, resulting in millions of cases and deaths. The objective of this study was to predict mortality in hospitalized COVID-19 patients in Zambia using machine learning (ML) methods based on factors that have been shown to be predictive of mortality and thereby improve pandemic preparedness. This research employed seven powerful ML models that included decision tree (DT), random forest (RF), support vector machines (SVM), logistic regression (LR), Naïve Bayes (NB), gradient boosting (GB), and XGBoost (XGB). These classifiers were trained on 1,433 hospitalized COVID-19 patients from various health facilities in Zambia. The performances achieved by these models were checked using accuracy, recall, F1-Score, area under the receiver operating characteristic curve (ROC_AUC), area under the precision-recall curve (PRC_AUC), and other metrics. The best-performing model was the XGB which had an accuracy of 92.3%, recall of 94.2%, F1-Score of 92.4%, and ROC_AUC of 97.5%. The pairwise Mann–Whitney U-test analysis showed that the second-best model (GB) and the third-best model (RF) did not perform significantly worse than the best model (XGB) and had the following: GB had an accuracy of 91.7%, recall of 94.2%, F1-Score of 91.9%, and ROC_AUC of 97.1%. RF had an accuracy of 90.8%, recall of 93.6%, F1-Score of 91.0%, and ROC_AUC of 96.8%. Other models showed similar results for the same metrics checked. The study successfully derived and validated the selected ML models and predicted mortality effectively with reasonably high performance in the stated metrics. The feature importance analysis found that knowledge of underlying health conditions about patients’ hospital length of stay (LOS), white blood cell count, age, and other factors can help healthcare providers offer lifesaving services on time, improve pandemic preparedness, and decongest health facilities in Zambia and other countries with similar settings.

Purpose. The purpose of the study was to assess the impact of an educational intervention on the level of knowledge and adherence to the treatment regimen among hemodialysis (HD) patients as well as to describe the association between these variables. Methods. In this randomized controlled trial, 160 HD patients at an HD centre of a 2030-bed tertiary teaching hospital in Southern India were randomly assigned into intervention (N = 80, received education and a booklet) and control (N = 80, received standard care) groups. Knowledge and adherence were measured preintervention and postintervention using a validated questionnaire for knowledge and the ESRD-AQ (End-Stage Renal Disease Questionnaire) for the level of adherence. The statistical analysis of the data was performed with the help of the Statistical Program SPSS version 19.0. The statistical significance level was set at 0.05. Results. The increase in knowledge on disease management, fluid adherence, and dietary adherence in the intervention group was significantly higher compared to the control group. There was no significant correlation between knowledge and adherence. Adherence improved for all the domains, i.e., dialysis attendance, episodes of shortening, adherence to medication, fluid restriction, and dietary restriction. Adherence to fluid and dietary restriction was statistically significant. This trail is registered with https://clinicaltrials.gov/ct2/show/CTRI/2018/05/014166.

The rabies virus, which belongs to the genus Lyssavirus, the family Rhabdoviridae, is the causative agent of rabies, a contagious, deadly, and progressive neurological infection. This illness is commonly distributed worldwide and affects all warm-blooded animals. Regarding the zoonotic aspects of rabies, the prevalence of rabies was investigated in this study. Over 2 years, 188 samples were examined via the direct fluorescent antibody test (DFAT) and mouse inoculation test (MIT) techniques by using brain tissue samples. Our findings showed that 73.94% of samples were rabies positive. The highest number of samples belonged to cows and dogs, respectively. The positivity rate in cows was 71.88%, followed by dogs with a 57.78% infection rate. These findings suggested that despite the heavy monitoring protocols in Iran, rabies is still a prevalent disease, and it is advised that vaccinations and screening programs should be carried out more frequently with heavier observation.

Knowing the health and nutritional status of older adults is crucial to helping them live healthier lives and limiting the need for pharmaceuticals and complicated medical procedures. The objective of this research was to analyze the eating habits (EH), physical activity (PA), and sleep quality (SQ) of older adults in the rural parish of San José de Minas in Quito, Ecuador. Three validated questionnaires were used: the Pittsburgh PSQI for SQ, IPAQ for PA, and frequency of consumption for EH. The results revealed high consumption of refined flours and sugar (70% at least once a day), low intake of whole grains, fish, and olive oil, and considerable consumption of fruits and water. Fifty percent of respondents engage in moderate physical activity and 24% in low physical activity, while 90% of older adults have poor sleep quality. These results indicate a problem in the integral health of the population that does not allow older adults to have a good old age. Health campaigns should be developed to increase physical activity, encourage a better diet, and thus, improve the quality of sleep.