Molecular detection and prevalence of Rotavirus with acute gastroenteritis among the children of rural and urban areas

Rotavirus is the main infective agent of acute gastroenteritis (AGE) in children under the age of five years and causing significant morbidity as well as mortality throughout the world. The study was carried out to detect the prevalence rate, genotypes strain and risk factors of Rotavirus among the children of rural and urban areas of district Bannu Khyber Pakhtunkhwa Pakistan. A total of 180 stool samples were collected from children under the age of 5 years from two major hospitals of Bannu from January to December (2015). The samples were analyzed by Reverse-transcriptase Polymerase Chain Reaction (RT-PCR) for the detection of Rotavirus, positive samples were further processed for genotyping (G and P type) through specific PCR. Of the total, 41 (23%) samples were positive for Rotavirus. The most prevalent G genotypes found were: G3, G8, G9 (each 29%), followed by G10 (15%), and G11 (10%). Whereas the prevalent P genotypes were: P-8 (25%), P-4 and P-10 (each 20%), P-9 (15%), followed by P-6 and P-11 (each 10%). Moreover, Rotavirus infection was more prevalent in summer (23.73%) and winter (22.7%) than spring (20%) and autumn (21.4%). Rotavirus infection exhibited high frequency in June (14%), October (8%) and November (6%). It is concluded that Rotavirus is more prevalent in children and various genotypes (G and P) of Rotavirus are present in the study area. Lack of studies, awareness and rarer testing of Rotavirus are the principal reasons of virus prevalence in district Bannu, Pakistan.

Customer Churn in Retail E-Commerce Business: Spatial and Machine Learning Approach

This study is a comprehensive and modern approach to predict customer churn in the example of an e-commerce retail store operating in Brazil. Our approach consists of three stages in which we combine and use three different datasets: numerical data on orders, textual after-purchase reviews and socio-geo-demographic data from the census. At the pre-processing stage, we find topics from text reviews using Latent Dirichlet Allocation, Dirichlet Multinomial Mixture and Gibbs sampling. In the spatial analysis, we apply DBSCAN to get rural/urban locations and analyse neighbourhoods of customers located with zip codes. At the modelling stage, we apply machine learning extreme gradient boosting and logistic regression. The quality of models is verified with area-under-curve and lift metrics. Explainable artificial intelligence represented with a permutation-based variable importance and a partial dependence profile help to discover the determinants of churn. We show that customers’ propensity to churn depends on: (i) payment value for the first order, number of items bought and shipping cost; (ii) categories of the products bought; (iii) demographic environment of the customer; and (iv) customer location. At the same time, customers’ propensity to churn is not influenced by: (i) population density in the customer’s area and division into rural and urban areas; (ii) quantitative review of the first purchase; and (iii) qualitative review summarised as a topic.

Risk Factors of Mild and Severe Stunting Children in Rural and Urban Areas in Indonesia

The article's abstract is not available.

Trends in the Incidence of New‐Onset Hypertensive Disorders of Pregnancy Among Rural and Urban Areas in the United States, 2007 to 2019

Background Hypertensive disorders of pregnancy are growing public health problems that contribute to maternal morbidity, mortality, and future risk of cardiovascular disease. Given established rural‐urban differences in maternal cardiovascular health, we described contemporary trends in new‐onset hypertensive disorders of pregnancy in the United States. Methods and Results We conducted a serial, cross‐sectional analysis of 51 685 525 live births to individuals aged 15 to 44 years from 2007 to 2019 using the Centers for Disease Control and Prevention Natality Database. We included gestational hypertension and preeclampsia/eclampsia in individuals without chronic hypertension and calculated the age‐adjusted incidence (95% CI) per 1000 live births overall and by urbanization status (rural or urban). We used Joinpoint software to identify inflection points and calculate rate of change. We quantified rate ratios to compare the relative incidence in rural compared with urban areas. Incidence (95% CI) of new‐onset hypertensive disorders of pregnancy increased from 2007 to 2019 in both rural (48.6 [48.0–49.2] to 83.9 [83.1–84.7]) and urban (37.0 [36.8–37.2] to 77.2 [76.8–77.6]) areas. The rate of annual increase in new‐onset hypertensive disorders of pregnancy was more rapid after 2014 with greater acceleration in urban compared with rural areas. Rate ratios (95% CI) comparing incidence of new‐onset hypertensive disorders of pregnancy in rural and urban areas decreased from 1.31 (1.30–1.33) in 2007 to 1.09 (1.08–1.10) in 2019. Conclusions Incidence of new‐onset hypertensive disorders of pregnancy doubled from 2007 to 2019 with persistent rural‐urban differences highlighting the need for targeted interventions to improve the health of pregnant individuals and their offspring.

Measuring Treatment Attrition at Various Stages of Engagement in Opioid Agonist Treatment in Ontario Canada Using a Cascade of Care Framework

Background The cascade of care framework is an effective way to measure attrition at various stages of engagement in Opioid Agonist Treatment (OAT). The primary objective of the study was to describe the cascade of care for individuals who have accessed OAT from a network of specialized addiction clinics in Ontario, Canada. The secondary objectives were to evaluate correlates associated with retention in OAT at various stages and the impact of patients' location of the residence on retention in OAT. Design: A multi-clinic retrospective cohort study was conducted using electronic medical record (EMR) data from the largest network of OAT clinics in Canada (70 clinics) from 2014-2020. Study participants included all individuals who received OAT from the network of clinics during the study period. Measurements: In this study, four stages of the cascade of care framework were operationalized to identify treatment engagement patterns, including patients retained within 90 days, 90 to 365 days, one to two years, and more than two years. Correlates associated with OAT retention for 90 days, 90 to 365 days, one to two years, and more than two years were also evaluated and compared across rural and urban areas in northern and southern Ontario. Results A total of 32,487 individuals were included in the study. Compared to individuals who were retained in OAT for 90 days, individuals who were retained for 90 to 365 days, one to two years, or more than two years were more likely to have a higher number of treatment attempts, a higher number of average monthly urine drug screening and a lower proportion of positive urine drug screening results for other drug use. Conclusion Distinct sociodemographic and clinical factors are likely to influence treatment retention at various stages of engagement along the OAT continuum. Research is required to determine if tailored strategies specific to people at different stages of engagement have the potential to improve outcomes of OAT.

Institutional Differences in Individual Wellbeing in China

An imbalanced distribution of income and welfare characterizes a developing or transitional economy such as China’s. Even after forty years of reform and rapid economic growth, there is still considerable disparity in wellbeing across different institutional settings in China. Major inequalities exist between rural and urban areas, public and for profit sectors, and state-owned and private enterprises. This paper presents the descriptive differences in individual wellbeing across these kinds of institutional settings from objective and subjective perspectives, enabled by the five waves of the Chinese General Social Survey (CGSS; the years of 2010, 2011, 2012, 2013 and 2015). The results show that: (1) people in urban China enjoy more objective wellbeing than people in rural China, but less subjective wellbeing; (2) people who work for the public sector enjoy more objective and subjective wellbeing than those for the for profit sector; (3) people who work for the state owned enterprises enjoy more objective wellbeing than those for the for profit sector, but subjective happiness is not significantly different. Furthermore, people’s perception of subjective wellbeing not only relies upon substantive objective wellbeing, but also an affiliation with a certain type of institution.

The Quality of Life of Coronavirus Disease Survivors Living in Rural and Urban Area of Riau Province, Indonesia

This study assesses the status of health-related quality of life (HRQOL) among coronavirus survivors living in rural and urban districts in Riau province, Indonesia. The cross-sectional study was conducted among 468 and 285 Coronavirus disease (COVID-19) survivors living in rural and urban areas, respectively in August 2021. The St. George Respiratory Questionnaire (SGRQ) was used to measure the HRQOL of COVID-19 survivors. A higher total score domain corresponds to worse quality of life status. Quantile regression with the respect to 50th percentile found a significant association for the factors living in rural areas, being female, having comorbidities, and being hospitalized during treatment, with total score of 4.77, 2.43, 7.22, and 21.27 higher than in their contra parts, respectively. Moreover, having received full vaccination had the score 3.96 in total score. The HRQOL of COVID-19 survivors living in rural areas was significantly lower than in urban areas. Factors such as living in rural areas, female sex, having comorbidities, and history of symptomatic COVID-19 infection were identified as significant predictors for lower quality of life. Meanwhile, having full vaccination is a significant predictor for a better quality of life. The results of this study can provide the targeted recommendations for improvement of HRQOL of COVID-19 survivors.

Discrimination Against People With HIV and AIDS in the Workplace

The main thrust of the chapter was to explore the discrimination experienced by people living with HIV and AIDS (PLHIV) in the workplace in Lagos State. A purposive sample of 80 PLHIV was selected from two local government areas (LGAs) of Lagos state: Epe, a rural setting, and Lagos Mainland, an urban one. Secondary data were obtained from internet sources while primary data were collected through structured interviews September 2005–April 2006. Data were analyzed using SPSS versions 11 and 13. Data between and within the rural and urban areas were also analyzed comparatively. The results indicate that PLHIV experienced instant dismissal from offices, mandatory HIV tests, alienation, denial of promotion, and exclusion from insurance schemes. This indicates that PLHIV's rights were violated. The study recommends intensive HIV education and enforcement of national HIV policy and international legal instruments in the workplace to protect PLHIV's rights.

Cutaneous leishmaniasis–Awareness, knowledge and practices among general population in rural and urban areas in Malakand region, Pakistan

Malakand region is an endemic area for cutaneous leishmaniasis (CL). However, there are limited number of studies of this disease in Pakistan. Therefore, a study was conducted to understand the level of awareness attitude and practice among the residents of Makaland towards CL and the disease vectors. This study adopted a cross-sectional approach with a total of 400 respondents (n=93 rural and n= 307 urban). Overall, the population in Malakand region (61.2%) were well-informed in the role of sand fly in transmitting diseases, but most lack knowledge on the vector’s behavior and almost a quarter (24.5%) were unable to provide knowledge on proper control measures. Alarmingly, the practice and attitudes of the general population was not satisfactory as close to half (49.8%) of the population did adopt any control method. This study calls for increase in awareness through health education campaign to reduce the risk of cutaneous leishmaniasis outbreaks in the future.

Predictive Analytics for Healthcare

The healthcare scheme in India has a lot of differences between rural and urban areas in terms of quality along with changes in private and public healthcare systems. The healthcare system is massive in India and full of inconsistencies and complexities like the other countries. Predictive analytics will help to improve the healthcare systems by providing valuable insight in healthcare. A huge amount of different data sets is generated because of the digitization of healthcare. This digitization allows us to use predictive analytics for better patient outcomes. Predictive analytics is utilized in decision-making activities and prediction making about the future events which are unknown. In this chapter, a brief overview of the Indian healthcare systems is given, along with data representations, challenges, issues, and risks associated with applying predictive analytics in healthcare and case studies with respect to regression and classification models.