{"title":"Phases 1 and 2 of Covid-19 Epidemic in the Three Geographical Areas of Italy: An Estimation of Italian Government Measures Based on a Bayesian Changepoint Detection Method","authors":"M. Manca, F. Russo, V. Georgiev, S. Taddei","doi":"10.18502/jbe.v6i2.4877","DOIUrl":"https://doi.org/10.18502/jbe.v6i2.4877","url":null,"abstract":"Background: Based on data from the Ministry of Health, which highlighted the earlier onset of Covid-19 epidemic in Italy, compared with the Europe, we would like to present a statistical elaboration on the impact of measures taken by the Government, during the phase 1 and the start of phase 2. \u0000Methods: After the implementation of a Bayesian changepoint detection method, we looked for a best fit model, based on the first part of time series data, in order to observe the progress of the data in the presence and absence of the restriction measures introduced. \u0000Results: Both the implementation of changepoint detection method and the analysis of the curves showed that the decree that marked the start of lockdown has had the effect of slowing down the epidemic by allowing thestart of a plateau between 21 and 25 March. Moreover, the decree that decided the beginning of phase 2 on 4 May did not have a negative impact. \u0000Conclusion: This statistical analysis supports the hypothesis that stringent measures decreased hospitalization, thanks to a slowing down in the evolution of the epidemic compared with what was expected. \u0000 ","PeriodicalId":34310,"journal":{"name":"Journal of Biostatistics and Epidemiology","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2020-12-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44703605","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Developing a Questionnaire to Investigate the Reasons for Ignoring Home Quarantine by Some Iranians","authors":"Elham Nazari, M. Shahriari, H. Tabesh","doi":"10.18502/jbe.v6i2.4876","DOIUrl":"https://doi.org/10.18502/jbe.v6i2.4876","url":null,"abstract":"Background: The rapid outbreak of Coronavirus has led to the worrying situation. Prevention strategies such as a stay at home offer great opportunities for transmission reduction of the virus. Therefore, the purpose of current study has developed a questionnaire to investigate the reasons for not staying at home in Iran. \u0000Methods: In this study a self-administered questionnaire was designed in two Delphi rounds and based on 50 expert and 10 expert opinions from different fields of study. \u0000Results: In the first Delphi round 11 questions were obtained and in the second round 14 questions were confirmed. The mean of CVR and CVI for the questionnaire was 95.33 and 94.67, respectively. A questionnaire was designed and developed according to the purpose. \u0000Conclusion: Using the designed questionnaire, the reasons why some people do not pay attention to home quarantine can be examined and solutions can be considered for them. This can prevent further corona spread.","PeriodicalId":34310,"journal":{"name":"Journal of Biostatistics and Epidemiology","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2020-12-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46659385","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Negin Badrooj, S. Keshavarz, M. Yekaninejad, K. Mirzaei
{"title":"Association Between Circadian Rhythm with Resting Metabolic Rate in OverweightObese Women","authors":"Negin Badrooj, S. Keshavarz, M. Yekaninejad, K. Mirzaei","doi":"10.18502/jbe.v6i2.4873","DOIUrl":"https://doi.org/10.18502/jbe.v6i2.4873","url":null,"abstract":"Aim: The aim of this study was to investigate the association between circadian rhythm with resting metabolic rate (RMR) in overweightobese women \u0000Methods: This cross-sectional study included 232 obese and overweight women. Morningness-Eveningness Questionnaire (MEQ) was used to assess the level of circadian rhythm. RMR was measured by indirect calorimetry after a 10-12 hour overnight fasting period by a trained nutritionist. We assessed body composition using multi-frequency bioelectrical impedance analyzer (BIA). \u0000Results: The percentage of overweight and obese women were 48.7% (113) and 51.3% (119), respectively. The number of participants who were morningness, intermediate and eveningness was 28(12.1%), 135(58.2%) and 69(29.7%) respectively. A significant relationship was found between MEQ and RMR.normal (p=0.011). According to linear regression model non-eveningness participants had 81.92 higher RMR compared to eveningness participants (p=0.027). \u0000Conclusion: We found that non-eveningness participants had higher RMR compared to eveningness participants that can lead to obesity, diabetes type2 and other health disorders.","PeriodicalId":34310,"journal":{"name":"Journal of Biostatistics and Epidemiology","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2020-12-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47494076","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Erythropoietin in COVID-19-Induced Neuroinflammation; EPO Plus Losartan Might be Promising","authors":"Reza Nejat, A. S. Sadr, David J. Najafi","doi":"10.18502/jbe.v6i2.4879","DOIUrl":"https://doi.org/10.18502/jbe.v6i2.4879","url":null,"abstract":"Introduction: Neuroinflammation is the inflammatory reaction in the central nervous system (CNS) provoked by diverse insults. This phenomenon results in a cascade of release of inflammatory mediators and intracellular messengers such as reactive oxygen species. The elicited responses are the cause of many neurological and neurodegenerative disorders. Erythropoietin (EPO) has been considered effective in attenuating this inflammatory process in the CNS, yet its administration in COVID-19 needs meticulously designed studies. \u0000Discussion: Neuroinflammation in COVID-19 due to probable contribution of renin-angiotensin system dysregulation resulting in surplus of Ang II and owing to the synergistic interaction between this octapeptide and EPO needs special consideration. Both of these compounds increase intracellular Ca2+ which may induce release of cytokine and inflammatory mediators leading to aggravation of neuroinflammation. In addition, Ang II elevates HIF even in normoxia which by itself increases EPO. It is implicated that EPO and HIF may likely increase in patients with COVID-19 which makes administration of EPO to these patients hazardous. Furthermore, papain-like protease of SARS-CoV2 as a deubiquitinase may also increase HIF. \u0000Conclusion: It is hypothesized that administration of EPO to patients with COVID-19-induced neuroinflammation may not be safe and in case EPO is needed for any reason in this disease adding of losartan may block AT1R-mediated post-receptor harmful effects of Ang II in synergism with EPO. Inhibition of papain-like protease might additionally decrease HIF in this disease. More in vitro, in vivo and clinical studies are needed to validate these hypotheses.","PeriodicalId":34310,"journal":{"name":"Journal of Biostatistics and Epidemiology","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2020-12-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47727687","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Competing Risk Analysis of the Health Status of Neonates with Respiratory Distress Syndrome","authors":"Z. Ayele, Mekonnen Tadesse, Zelalem Tazu","doi":"10.18502/jbe.v6i2.4878","DOIUrl":"https://doi.org/10.18502/jbe.v6i2.4878","url":null,"abstract":"Introduction: Respiratory distress syndrome (RDS) is not only the most common respiratory disorder in premature infants but also the main cause of neonatal mortality. \u0000Methods: Competing risk framework was used to examine and identify potential prognostic factors of the health status of preterm infants with respiratory distress syndrome. Preterm infants with RDS admitted to the neonatal intensive care units (NICUs) of selected hospitals in Ethiopia were followed for 28 days and only neonates with complete cases were included in the analysis. The Fine-Gray or sub-distribution hazard model was used to identify significant prognostic factors. Three outcome variables (death due to RDS, death due to other causes and discharged alive) were considered. \u0000Results: The Fine-Gray model fit results revealed that anemia, multiple pregnancies, birth-weight and gestational age were the prognostic factors significantly associated with the death of neonates due to Respiratory distress syndrome problem while Pneumonia, meningitis, anemia and gestational age of neonates were the significant prognostic factors for death of neonates due to other causes. Moreover, pneumonia, birth weight and gestational age were identified as the prognostic factors associated with neonates being discharged alive. \u0000Conclusion: Offering intensive and adequate treatments for neonates with lowest birth-weights and gestational age may be useful to reduce neonatal mortality and increase the incidence of being discharged alive.","PeriodicalId":34310,"journal":{"name":"Journal of Biostatistics and Epidemiology","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2020-12-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44201630","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Multidimensional item response theory to assess psychometric properties of GHQ-12 in parents of school children","authors":"Elham Haem, Marziyeh Doostfatemeh","doi":"10.21203/rs.3.rs-62439/v2","DOIUrl":"https://doi.org/10.21203/rs.3.rs-62439/v2","url":null,"abstract":"\u0000 Background: Multidimensional item response theory (MIRT) model provides an ideal foundation to assess psychological properties of a questionnaire designed with multidimensional structure. This study aimed to present the first use of MIRT models to investigate psychometric properties of general health questionnaire (GHQ-12) in parents of school children. Methods: A total of 1104 parents of school children completed the Persian version of GHQ-12 questionnaire. Unidimensional IRT model and MIRT models with two and three factors were applied to model the observed scores for each GHQ-12 item as a function of the subject’s latent traits while taking the correlation between dimensions of the questionnaire into account. The goodness of fit indices were reported for the three models, and items fit were assessed for the best model. Individual items were described in detail through item characteristic curves, and the amount of information carried by different items was presented using information curves. Results: The MIRT analysis with two factors corresponding to psychological distress and social dysfunction provided the best account of the GHQ-12 data. The model showed that all items were fitted adequately. Items varied in their discrimination ranged from 0.86 to 2.35 and 1.18 to 2.41 for psychological distress and social dysfunction, respectively. Moreover, items 8 and 2 provided the least information in psychological distress and social dysfunction dimensions, respectively. Conclusions: The developed framework to evaluate psychometric properties of GHQ-12 can be a suitable alternative to traditional approaches and also unidimensional IRT models, the use of which has been restricted due to multidimensional structure of the questionnaire.","PeriodicalId":34310,"journal":{"name":"Journal of Biostatistics and Epidemiology","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2020-11-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48084129","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Investigating the Challenges of Big Data Analytics from the Viewpoints of Students in Mashhad in 2019","authors":"Elham Nazari, Marziyeh Afkanpour, H. Tabesh","doi":"10.18502/jbe.v5i4.3870","DOIUrl":"https://doi.org/10.18502/jbe.v5i4.3870","url":null,"abstract":"Introduction: Nowadays Big Data Analytics has attracted students for research due to its very high capabilities, but there are also obstacles to analyses that need to be addressed. Therefore, the purpose of this study is to investigate the viewpoints of students of different disciplines at Mashhad universities on the challenges of this analysis. \u0000Method: This study is a cross-sectional study conducted on students of different universities and fields such as computer engineering, pharmacy, industry and biology in Mashhad, Iran. A questionnaire based on literature review in Pubmed, Google scholar, and science direct databases was designed by 10 experts from different disciplines using Delphi method. 185 students participated in the study. Students' viewpoints on the challenges were also collected. Descriptive and analytical results were reported using SPSS 21 and Maxqda software. \u0000Results: The age range of most students was 25 - 34 years. 54.2% were female. Most of the participants in this study were students of engineering and medical informatics. Of the participants in this study, 96.4% considered big data analytics necessary, 50.6% were familiar with the benefits of analytics. Lack of awareness, inadequate management, lack of managers' knowledge, lack of expertise, and lack of priority were the most important challenges for students. \u0000Conclusion: Despite the importance and benefits of big data analytics, challenges are a major barrier to use that need to be addressed.","PeriodicalId":34310,"journal":{"name":"Journal of Biostatistics and Epidemiology","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2020-08-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41494323","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"SARS Virus Papain-Like Protease: A Mysterious Weapon","authors":"Reza Nejat, A. S. Sadr","doi":"10.18502/jbe.v5i4.3873","DOIUrl":"https://doi.org/10.18502/jbe.v5i4.3873","url":null,"abstract":"Introduction: Papain-like protease (PLpro) of SARS-CoV in association with 3Chemotrypsin-like protease (3CLpro or Mpro) are two proteases which auto-proteolyze replicase polyproteins pp1a/pp1ab. These polyproteins are translated from ORF1a/ORF1b of the virus genome. Cleavage of pp1a/pp1ab releases nonstructural proteins of the virus which orchestrate viral replication. In addition, PLpro as a deubiquitinase and deISGylase modifies the proteins involved in recognition of the virus by the sensors of host cell innate immunity system. In this manner, the virus reforms the ubiquitination and ISGylation of the cell proteins to progress its own replication without any interference from host cell restrictive strategies against the viruses. Furthermore, PLpro blocks IRF3 activation independent of deubiquinating processes. Besides, PLpro induces pulmonary fibrosis through pathways involving ROS and MAPK. \u0000Conclusion: Inhibition of PLpro allows innate immunity to sense and react against the invasion of SARSCoV and to activate IRF3 to induce type I IFN expression. Thenceforth, proper development and signaling of innate immunity result in a long-term efficient cell/humoral adaptive immunity. Moreover, suppression of PLpro prevents cleavage of nsp3 and hence replication of the virus and through abolishing ubiquitinproteasome/MAPK/ERK- and ROS/MAPK-mediated pathways prevent pulmonary fibrosis.","PeriodicalId":34310,"journal":{"name":"Journal of Biostatistics and Epidemiology","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2020-08-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46337420","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Elham Nazari, M. Shahriari, M. Khodabandeh, H. Tabesh
{"title":"Create Frameworks from Software Engineering to Health Care: A Survey","authors":"Elham Nazari, M. Shahriari, M. Khodabandeh, H. Tabesh","doi":"10.18502/jbe.v5i3.3619","DOIUrl":"https://doi.org/10.18502/jbe.v5i3.3619","url":null,"abstract":"Background & Aims: One of the challenges of multidisciplinary disciplines such as Medical Informatics, Health Information Technology, etc., especially for those who have just begun research in this field, is the lack of familiarity with some of the key terms and applications of software concepts, including frameworks. \u0000Methods: This study is based on search of databases (ProQuest, PubMed, Google Scholar, Science Direct, Scopus, IranMedex, Irandoc, Magiran, Pars Medline and Scientific Information Database (SID)). This investigation has done with the websites and the specialized books with standard key words. After a careful study, 56 sources were selected and used in the final article. \u0000Results: Frameworks are widely used in the field of health care and have produced valuable results. Considering the framework advantages in the health care sector among designing and estimating the systems in standard ways and comparing the systems in principle for identifying the gaps and introducing the capabilities, avoidance of reworking seem necessary. Therefore, after reviewing the literature we will explain about meaning, overlapping to the other meanings, components, steps, advantages, challenges, and the types of frameworks in general and their applications in the healthcare sector. \u0000Conclusions: The results of this research can help the researchers for doing the new research and understand the important concepts of that, thus it can be useful in designing and researching projects for researchers and health care providers as well. \u0000 ","PeriodicalId":34310,"journal":{"name":"Journal of Biostatistics and Epidemiology","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2020-07-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49281459","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Saeed Shirazi, Hamed Baziyad, N. Ahmadi, A. Albadvi
{"title":"A New Application of Louvain Algorithm for Identifying Disease Fields Using Big Data Techniques","authors":"Saeed Shirazi, Hamed Baziyad, N. Ahmadi, A. Albadvi","doi":"10.18502/jbe.v5i3.3613","DOIUrl":"https://doi.org/10.18502/jbe.v5i3.3613","url":null,"abstract":"Background and aim: Recently, the use of data science techniques in healthcare has been increased remarkably. Community detection as one the important methods of data science is utilized in the health domain. \u0000Methods: This paper detects disease areas based on combination of big data and graph mining methods on drug prescriptions. At first, network of prescription is designed, and Louvain algorithm is applied for community detection of 50000 Iranian prescriptions in 2014 gathered from the Iranian Health Insurance Organization. We use modularity metric for validation of the results and the experts’ opinion as the external validation of communities. \u0000Results: The outputs are consist of six communities. These communities are labeled based on experts’ opinion that present the disease fields. \u0000Conclusion: The Louvain algorithm has the ability to detect the major communities of the prescription database with an acceptable accuracy. We have proven that these communities present the disease fields.","PeriodicalId":34310,"journal":{"name":"Journal of Biostatistics and Epidemiology","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2020-07-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47375951","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}