Hojjat Zeraati, PhD.
Knowledge, attitudes, and perceptions of the Greek population regarding the COVID-19 pandemic during the national lockdown (March 23 - May 03, 2020): A web-based cross-sectional study
Objective: The study assessed the knowledge, attitudes, and perceptions toward the COVID-19 pandemic during the total lockdown of spring 2020 in Greece.
Methods: A web-based cross-sectional study was conducted from April 13 to May 5, 2020 using snowball sampling method. Adult residents of Greece anonymously completed an online survey that was distributed through email and social media. Demographic questions, questions regarding the knowledge about the disease etiology, diagnosis and prevention, and questions related to the respondents’ attitude and perception toward the restriction measures and the confidence in different kinds of institutions were included in the survey items. The appropriate statistical analyses were conducted according to the type of variable and the research question.
Results: A total of 1396 fully complete questionnaires were collected. A moderate-high knowledge about COVID-19 was found in the study population (median 74.8%). The highest knowledge scores were found in females (74.8%, p = 0.015), individuals over 60 years old (77.3%, p < 0.001) and individuals having completed post-secondary or tertiary education (76.5%, p < 0.001). Five attitude patterns toward the pandemic were identified: “trust in institutions”, “trust in the restriction measures”, “trust in media and the internet”, “trust in traditional institutions”, and “measures deniers”. Age, education, and knowledge score were the factors defining the attitudinal patterns revealed.
Conclusions: Education and public awareness seem to be the factors defining the successful management of the pandemic’s first wave in Greece. Repeated observations of attitudinal patterns are important for eliminating irresponsible behaviors in periods of health crises.
The Study of Psychometric Properties of the Persian Version of Communication and Symbolic Behavior Scale Developmental Profile /Infant toddler Checklist: An Application of Confirmatory Factor Analysis with Skew Distribution
The importance of early detection and intervention of communication and language problems has increased the need for appropriate tools in this area.
This study with aim to evaluating the psychometric properties of Persian version of the Communication and Symbolic Behavior Scales Developmental Profile (CSBS DP) has been done.
Method and Materials:
In a cross-sectional study the Persian version of the CSBS DP was submitted to 157 participants randomly drawn from 2 district of Tehran city (Iran) in year 2020. Internal consistency, reliability, concurrent validity, and construct validity were evaluated. Concurrent validity was explored with respect to the Ages and Stages Questionnaire (ASQ) and MacArthur-Bates Communicative Development Inventory (CDI).
The correlation between CSBS DP questionnaire with ASQ-3 and CDI were 0.88 and 0.64 respectively. The test-re-test reliability and internal consistency were 0.78 and 0.77 respectively. The confirmatory factor analysis showed adequate construct validity of the Persian version of the CSBS DP questionnaire, RMSEA, GFI and AGFI were <0.000, >0.9 and >0.9 respectively; moreover other indexes were satisfactory.
The results of this research revealed the validity and reliability of Persian version of CSBSDP questioner at a very desirable level, thus making it a valid and reliable instrument in evaluating the communication and symbolic behavior
Statistical Considerations in Combining Multiple Biomarkers for Diagnostic Classification Logistic Regression Risk Score versus Discriminant Function Score
Introduction: In clinical practices, multiple biomarkers are frequently used on the same subjects for diagnosis of an adverse outcome. This study compares two alternative multiple linear regression approaches as the logistic regression model and the discriminant function score in combing several markers.
Methods: Ten thousand simulated data sets were generated from binormal and non-binormal pairs of distributions with different sample sizes and correlation structures. Each dataset underwent a logistic regression and the discriminant analysis simultaneously. The ROC analysis was performed with each marker alone and also their combining scores. For two alternative approaches, the average of AUC and its root mean square error (RMSE) were estimated over 10000 replications trials for all configurations and sample sizes used. The practical utility of the two methods is further illustrated with a clinical example of real data as well.
Results: The two approaches yielded identical accuracy in particular with binormal data. With non- binormal data, the logistic regression risk score produced an equal or a slightly better accuracy than the discriminate function score.
Conclusion: Overall, the two approaches yield rather identical results. However, adopting the logistic regression model may incorporate slightly better accuracy index than discriminant analysis with non-binormal data.
Introduction: Accidents and related injuries are the major public health problem and they have long been charged with being very destructive and deadly to the humans in the world. Regarding the widespread damage caused by accidents in Iran
Objectives: This study was conducted with the aim of determining the trend and epidemiological pattern of injuries caused by accidents in victims who referred to the emergency department of Iranian hospitals in 2016.
Methods: This study was performed based on secondary analysis of existing data. In order to collect the necessary information, all reports of the Iranian Ministry of Health and Medical Education on accidents and deaths in 2016 were used. Excel, SPSS and GIS software were used to analyze the results. Also, hierarchical analysis was used to cluster the provinces. Out of 1483425 cases in 2015, 68.6% were men.
Results: The highest frequency was related to the age group of ≥20 years (74%). Also, out of the total cases, 5013 people died and 358 others were disabled. The scene of the most accident was home (36%), followed by the street (32%). The highest rate of accidents per 100 000 population was related to trauma (598.72) followed by traffic accidents (570.53).The highest incidence rate per thousand population was related to Qazvin (46.30) and Kermanshah (38.10) provinces and Sistan and Baluchestan province had the lowest incidence rate (2.9 per thousand).
Conclusion: Organized policy-making and decision-making to prevent accidents is one of the important health priorities and an essential tool in promoting safety in Iran.
Factors associated with the incidence of coronary heart disease in the MASHAD cohort study: A six years follow upBackground
Coronary heart disease (CHD) is the leading cause of morbidity and mortality globally, and specifically in Iran. Accurate assessments of Coronary heart disease (CHD) incidence is very necessary for public health. In current study we aimed to investigate the incidence of CHD and
importance of several classical, modifiable and un-modifiable risk factors for CHD among an urban population in eastern Iran after 6 years of follow-up.Methods
The population of MASHAD cohort study were followed up for 6 years, every 3 years in two step by phone and who reported symptoms of CVD were asked to attend for a cardiac examination, to estimate the incidence of CHD with 95% confidence interval (95% CI) as well multiple logistic regression analysis was performed to assess the association of several baseline characteristics with incidence of CHD event. Evaluation of goodness-of-fit was done using ROC analysis. CHD cases divided into four different classes which include: stable angina, unstable angina pectoris, myocardial infarction and sudden cardiac death.Results In the six years' follow-up of Mashhad study, the incidence rate of all CHD event in men and women in 100,000 people-years with 95% confidence intervals were 1920 (810-3030) and 1160 (730-1590), respectively. The areas under ROC curve (AUC), based on multivariate predictors of CHD outcome, was 0.7825. Conclusion
Our findings indicated that the incidence rate of coronary heart diseases in MASHAD cohort study increases with age as well as our final model designed, was able to predict approximately 78% of CHD events in Iranian population.
Making the case for cross-border public health stratagies: a compartivie assessment of Covid-19 epidemiological trends in the Balkan countries across 17 months.
COVID-19 spread globally, including across the Balkans, resulting in different morbidity and mortality outcomes in different countries. The aim of this study was to review the impact of COVID-19 over 17 months with regards to pandemic progression, implemented mitigation strategies, and COVID-19 vaccination programs across the Balkan countries, while identifying any valuable pieces of information acquired serendipitously throughout the pandemic that can be implemented in future action plans.
Epidemiological data was obtained from Our World in Data databases, while Ministry of Health websites for each respective country as well as local newspapers were utilized to review COVID-19-related mitigations and vaccination strategies. Case, mortality, and vaccination incidence comparisons were made across neighbouring countries.
A similar trend in COVID morbidity and mortality outcomes were evident across neighbouring countries. A staggered vaccination rollout was observed, with various rollout speeds, although gradual decline in both morbidity and mortality occurred.
The COVID-19 outcome for a particular country is not only dependent on the country’s own level of viral transmission, mitigations, and vaccination rates but also on neighbouring countries’ COVID-19 situation. Hence, cross-border governance action and recovery plans are recommended along with targeting vaccination hesitance.
Measuring progress toward Universal Health Coverage in Iran: two years after the implementation of the Health Transformation Plan
Background and Objectives: One of the most important 2015-post agendas of countries’ health systems is achieving Universal Health Coverage (UHC), so the countries should monitor the taken activities. Ths study aimed to investigate the Universal UHC status two years after Health Transformation Plan in Iran.
Methods: Household Income and Expenditure Survey were used to estimate financial protection indicators in 2016. Estimation for service coverage index provided by international databases was applied at the country level. Indicators of financial protection and service coverage were evaluated in relation to each other using the World Health Organization joint levels assessment method, which indicates UHC attainment in terms of a plot with four zones. The relationship was estimated for the entire population, first quintile, and fifth quintile in 2000, 2017, and 2030.
Results: About 15.85% of households endured catastrophic health expenditures at the 10% threshold. Accordingly, Iran is on the border between zones 1 and 2 in 2017 in terms of achieving UHC and will move to zone 1 in 2030 with the current trend.
Conclusion: Iran did not attain UHC in 2000. It seems and has not achieved UHC in 2017 either. Even with improved service coverage, achieving UHC by 2030 may seem impossible with the current trends.
Introduction: Sarcopenia can be measured by a variety of indicators, and in many cases these indicators are quite positively correlated. With the aim of improving statistical model results, the objective of this study was to use multivariate methods to identify genetic variants affecting sarcopenia indices simultaneously.
Methods: GWAS analysis was performed based on data collected from 2426 Iranians aged 60 and over who were enrolled in the Bushehr Elderly Health program (BEH). DNA samples were collected from all subjects during this phase to measure prevalence of musculoskeletal disorders and risk factors. To analyze BEH DNA samples, we used a combination of Multiphen test, which is a linear combination of phenotypes most associated with genotypes, and GATES, a gene-based association test that can handle millions of SNP results efficiently and that can assess gene-level statistical significance.
Result: The upper and lower 50 kb of the IL10 gene are extracted from chromosome 1 at the position (206940947, 206945839). The next step was done to calculate P-values for SNPs in this gene of SMI and handgrip using Multiphen (joint model). In the Gates method, these P-values are used to calculate the overall P-value (0.046). Given the fact that this value is less than 5%, it is clear that this gene has been effective in preventing sarcopenia in the Iranian elderly population. The tutorial describes how Multiphen and Gates can be used to analyze sarcopenia, a multifactorial disease. In this study, the gene Il10 (P-value = 0.046) was analyzed as a risk gene for sarcopenia.
Conclusion: GWAS (Genome-wide association study) is a primary method for identifying genetic variants that influence the phenotype of a disease. Multi-phenotype analysis, which evaluates multiple phenotypes associated with the disease, can, however, identify additional genetic associations associated with the disease. An alternative to univariate GWAS, Multiphen tests the most related linear combinations of multifactorial diseases using a multi-phenotypic approach rather than univariate GWAS. The overall P-value of the selected gene is determined by using Gates, a gene-based analysis.
Introduction: Receiver Operating Characteristic (ROC) curve is one of the widely used supervised classification techniques to allocate/classify the individuals and also instrumental in comparing diagnostic tests. Generally to deal with classification problems we need to have knowledge of class labels. In most of the scenarios, data exhibit multi-model patterns in class labels which leads to multi-class classification problems.
Objective: The main aim of this study is to address the issue of constructing ROC models when there exist multi-models patterns in the class labels further, to classify the individuals for better diagnosis, and also to reduce the complexity of graphical representation of ROC curves in such classification problems.
Methods: A new version of univariate and multivariate ROC models are proposed in the framework of Finite Mixtures, due to the flexibility of identifying and modeling the subcomponents in the heterogeneous populations.
Results: Oral Glucose Tolerance Test and Disk Hernia datasets are used and simulation studies are also performed. Results show that the proposed models possess better accuracy when compared with Bi-Normal and MROC models with reasonable low 1-Specificity and higher Sensitivity. The ROC curves are depicted in a 2D space rather than a higher dimension for multi-class classification problems.
Conclusions: It is suggested that before one proceeds to model ROC curves, it is better to take a look at the density patterns of the study variable(s), which in turn help in explaining the true information between the classes and also provides a good amount of “true” accuracy.