Using an Eigenvector Spatial Filtering-Based Spatially Varying Coefficient Model to Analyze the Spatial Heterogeneity of COVID-19 and Its Influencing Factors in Mainland China

The COVID-19 pandemic has led to many deaths and economic disruptions across the world. Several studies have examined the effect of corresponding health risk factors in different places, but the problem of spatial heterogeneity has not been adequately addressed. The purpose of this paper was to explore how selected health risk factors are related to the pandemic infection rate within different study extents and to reveal the spatial varying characteristics of certain health risk factors. An eigenvector spatial filtering-based spatially varying coefficient model (ESF-SVC) was developed to find out how the influence of selected health risk factors varies across space and time. The ESF-SVC was able to take good control of over-fitting problems compared with ordinary least square (OLS), eigenvector spatial filtering (ESF) and geographically weighted regression (GWR) models, with a higher adjusted R2 and lower cross validation RMSE. The impact of health risk factors varied as the study extent changed: In Hubei province, only population density and wind speed showed significant spatially constant impact; while in mainland China, other factors including migration score, building density, temperature and altitude showed significant spatially varying impact. The influence of migration score was less contributive and less significant in cities around Wuhan than cities further away, while altitude showed a stronger contribution to the decrease of infection rates in high altitude cities. The temperature showed mixed correlation as time passed, with positive and negative coefficients at 2.42 °C and 8.17 °C, respectively. This study could provide a feasible path to improve the model fit by considering the problem of spatial autocorrelation and heterogeneity that exists in COVID-19 modeling. The yielding ESF-SVC coefficients could also provide an intuitive method for discovering the different impacts of influencing factors across space in large study areas. It is hoped that these findings improve public and governmental awareness of potential health risks and therefore influence epidemic control strategies.

A study on awareness of hearing health, risk factors, prevention, and intervention of hearing impairment-among pregnant women and mothers of newborn in urban area, Bhubaneswar

Background: The study was aimed at investigating the knowledge of awareness of hearing health, risk factors causing hearing loss and preventive measures for hearing disability at natal stages and awareness regarding the intervention among the pregnant women and mothers of newborn in urban area i.e. in Bhubaneswar.Methods: 53 pregnant women and 103 mothers of newborn had participated in the present study and were agreed to provide their awareness regarding the questionnaire related to selected parameters their responses were scored and documented for the statistics.Results: Results indicates that mothers were more aware of the selected parameters like risk factors during natal stages, intervention as compared to pregnant women. Mothers (66.01%) and pregnant women (56.22%) were more aware of prenatal risk factors as compared to peri and postnatal. Almost 60% of total participants were aware of hearing health and intervention for hearing loss. Two-way ANOVA was computed. p<0.0001, indicates statistically significant difference between the selected parameters i.e. awareness of hearing health and intervention and awareness of risk factors and prevention for hearing impairment at natal stages. Post hoc analysis (using unpaired t test by applying Bonferroni correction) suggestive of statistically significant difference of selected parameters from each other among pregnant women and mothers with p=0.0002.Conclusions: It is very much important to utilize the existing knowledge of the grass root level people like mothers and pregnant women by acquiring their ideas and information regarding the awareness of occurrence of hearing impairment in children which can be done only by spreading adequate information regarding hearing disability.

HEALTH RISK FACTORS: BODY MASS INDEX, BLOOD PRESSURE AND BLOOD GLUCOSE AMONG ROMA IN BULGARIA

Roma communities suffer from higher rates of diabetes, cardiovascular disease, hypertension and related impairments and limitations in daily activities. Purpose of the article is to study and analyze health risk factors: body mass index, blood pressure and blood glucose among the Roma population in small cities in Bulgaria. Material/Methods: In May 2015, a community-based approach was applied, and all adult residents of the Roma neighborhood of the town of Knezha, district of Pleven, were invited to participate. Only the persons who agreed to participate (59) or about 9% of the adult residents of Roma origin are included. By measuring BMI, blood pressure and blood glucose, the collection of primary data was done. The statistical processing of the data with Microsoft Office Excel 2010 and STATGRAPHICS-19 centurion software packages was performed. The significance of the results and conclusions was determined at p<0.05. Results: The Roma population is characterized by an unfavorable risk constellation and a health profile. Over two thirds (77.1%) of the participants in the study have BMI values above the normal. There is a high relative share of people with hypertension – 42.3% of Roma people covered. Elevated levels of blood sugar were found in almost 40% of the people observed: in equal relative shares are presented the persons with impaired glucose tolerance (prediabetic) and diabetes mellitus – respectively 18.7%. Conclusions: The study found a wide distribution of unhealthy factors of lifestyle among Roma population, and particularly alarming results are established regarding to the health of the Roma women.

Beta Inflated Regression Models on the Physical and Mental Health of Nigerian Stroke Survivors

Background: Stroke is one of the major public health problems worldwide. Physical and mental health data of stroke survivors are often expressed in proportions. Therefore, the Beta Regression models family for data between zero and one will be appropriate. Objectives: To identify a suitable model and the likely risk factors of physical and mental health of stroke survivors. Method: Secondary data of stroke survivors from two tertiary health Institutions in Ogun State, Nigeria, were analysed. Inflated Beta (BEINF) and Inflated-at-one-Beta (BEINF1) models were compared using Deviance (DEV), Akaike Information Criterion (AIC) and Bayesian Information Criteria (BIC) for model selection. The model with minimum DEV, AIC and BIC was considered to be better. Results: The deviance (-86.0604,), AIC (-46.0604) and BIC (6.4391) values of the BEINF1 model for physical health and the deviance (-20.1217), AIC (19.8783) and BIC (72.3778) values of BEINF1 model for mental health were smaller than BEINF models. Therefore, BEINF1 was the better model to identify the health risk factors of stroke survivors. Age, marital status, diastolic blood pressure, disability duration and systolic blood pressure had a significant association with physical health, while BMI had a significant positive association with mental health. Conclusion: The beta-inflated-at-one (BEINF1) model is suitable for identifying health risk factors of stroke survivors when the outcome variable is a proportion. Both demographic and clinical characteristics were significantly associated with the health of stroke survivors. This study would assist researchers in knowing the appropriate model for analysing proportion or percentage response variables.