Present study focuses on the attitudes/perceptions regarding negative attitudes, hesitancy (uncertainty, unwillingness) and anxiety towards COVID-19 within the Saudian context. A cross-sectional web-based study uses convenience sampling technique for data collection through self-administrated validated questionnaire translated in Arabic language. Outcomes of the study revealed that more than 3/4th (80%) of respondents expressed intermediate to high levels of negative attitude towards vaccines, in general. The most common reasons for vaccine hesitancy were the concerns about the vaccine's possible side effects, not taking it as a serious infection, and its efficacy in preventing the infection. Regarding anxiety towards coronavirus, it was found to be quite low. Decision tree analysis was used to assess the relationship between hesitancy and demographic characteristics of the respondents. Findings of the study pinpoint specific areas, on which to focus on, for the health care administrators in case of resurgence of the pandemic. The health administrators may incorporate the suggestions of the present study when framing their future policies for enhancing confidence and alleviating fears of the populace at large to receive COVID-19 vaccination.
{"title":"HESITANCY viz-a-viz COVID-19 VACCINE: A CASE STUDY OF SAUDI ARABIA","authors":"A. Almarashi, K. Khan","doi":"10.17654/0973514323002","DOIUrl":"https://doi.org/10.17654/0973514323002","url":null,"abstract":"Present study focuses on the attitudes/perceptions regarding negative attitudes, hesitancy (uncertainty, unwillingness) and anxiety towards COVID-19 within the Saudian context. A cross-sectional web-based study uses convenience sampling technique for data collection through self-administrated validated questionnaire translated in Arabic language. Outcomes of the study revealed that more than 3/4th (80%) of respondents expressed intermediate to high levels of negative attitude towards vaccines, in general. The most common reasons for vaccine hesitancy were the concerns about the vaccine's possible side effects, not taking it as a serious infection, and its efficacy in preventing the infection. Regarding anxiety towards coronavirus, it was found to be quite low. Decision tree analysis was used to assess the relationship between hesitancy and demographic characteristics of the respondents. Findings of the study pinpoint specific areas, on which to focus on, for the health care administrators in case of resurgence of the pandemic. The health administrators may incorporate the suggestions of the present study when framing their future policies for enhancing confidence and alleviating fears of the populace at large to receive COVID-19 vaccination.","PeriodicalId":40703,"journal":{"name":"JP Journal of Biostatistics","volume":null,"pages":null},"PeriodicalIF":0.1,"publicationDate":"2023-01-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44672426","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}
Vaccination against COVID-19 is designed to provide herd immunity. However, there are cases of SARS-CoV-2 infection after vaccination. Using Python software, we calculated the number of SARS-CoV-2 infections per 100,000 adults after the first and second vaccinations as at July 23, 2021, conducted in St. Petersburg, Russian Federation. After the first vaccination with Gam-COVID-Vac (Sputnik V) vaccine, 544 infections were determined, and after the second vaccination -1,643 cases. After the first vaccination with the EpiVacCorona vaccine, 1,600 infections were calculated, and after the second vaccination -6,073 cases. After the first vaccination with CoviVac vaccine, 1,162 infections were determined, and after the second vaccination -886 cases. Cluster analysis revealed the similarity of epidemiological indicators due to Gam-COVID-Vac and CoviVac vaccines, with EpiVacCorona vaccine isolated in a separate cluster, which is associated with significant differences in the calculated epidemiological parameters.
{"title":"CLUSTERING OF COVID-19 VACCINES BY SARS-CoV-2 INFECTION LEVEL AFTER TWO VACCINATIONS","authors":"A. B. Kiladze","doi":"10.17654/0973514323001","DOIUrl":"https://doi.org/10.17654/0973514323001","url":null,"abstract":"Vaccination against COVID-19 is designed to provide herd immunity. However, there are cases of SARS-CoV-2 infection after vaccination. Using Python software, we calculated the number of SARS-CoV-2 infections per 100,000 adults after the first and second vaccinations as at July 23, 2021, conducted in St. Petersburg, Russian Federation. After the first vaccination with Gam-COVID-Vac (Sputnik V) vaccine, 544 infections were determined, and after the second vaccination -1,643 cases. After the first vaccination with the EpiVacCorona vaccine, 1,600 infections were calculated, and after the second vaccination -6,073 cases. After the first vaccination with CoviVac vaccine, 1,162 infections were determined, and after the second vaccination -886 cases. Cluster analysis revealed the similarity of epidemiological indicators due to Gam-COVID-Vac and CoviVac vaccines, with EpiVacCorona vaccine isolated in a separate cluster, which is associated with significant differences in the calculated epidemiological parameters.","PeriodicalId":40703,"journal":{"name":"JP Journal of Biostatistics","volume":null,"pages":null},"PeriodicalIF":0.1,"publicationDate":"2023-01-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43650958","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":"APPLICATIONS OF STATISTICAL TECHNIQUES IN CARDIOVASCULAR DISEASE RISK ESTIMATION FOR INDIAN POPULATION: A SYSTEMATIC REVIEW","authors":"Abha Marathe, Virendra Shete, D. Upasani","doi":"10.17654/0973514322029","DOIUrl":"https://doi.org/10.17654/0973514322029","url":null,"abstract":"","PeriodicalId":40703,"journal":{"name":"JP Journal of Biostatistics","volume":null,"pages":null},"PeriodicalIF":0.1,"publicationDate":"2022-12-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49646217","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":"PATIENTS SATISFACTION WITH OPD SERVICES: A CASE STUDY OF SAUDI ARABIA","authors":"A. Almarashi, K. Khan","doi":"10.17654/0973514322028","DOIUrl":"https://doi.org/10.17654/0973514322028","url":null,"abstract":"","PeriodicalId":40703,"journal":{"name":"JP Journal of Biostatistics","volume":null,"pages":null},"PeriodicalIF":0.1,"publicationDate":"2022-12-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48906312","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":"PARAMETRIC REGRESSION MODELING OF COMPETING RISK USING CARDIOVASCULAR DISEASE PATIENT’S SURVIVAL DATA","authors":"G. Jayakodi, N. Sundaram, P. Venkatesan","doi":"10.17654/0973514322027","DOIUrl":"https://doi.org/10.17654/0973514322027","url":null,"abstract":"","PeriodicalId":40703,"journal":{"name":"JP Journal of Biostatistics","volume":null,"pages":null},"PeriodicalIF":0.1,"publicationDate":"2022-12-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48808251","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}
COVID-19 is the biggest threat to the life of humankind around the globe. Vaccination became an important protective system against COVID-19 infection. The geographical aspect is an important factor in infection spreading. This study explores the effect of the vaccination on COVID-19 in India using the estimate of the spatial effects. Since the distribution of vaccination started in the middle of study period, time-interrupted spatial panel models were used. SDM model was selected as the best one. The spatial effect coefficients are statistically significant in SDM models (rho = 0.4057;p < 0.01 , rho = 0.3132;p < 0.01) and the spillover effect of second dose vaccination rate is statistically significant on both confirmed rate and deceased rate. The vaccination has a significant negative impact on deceased rate. There is a clear evidence for the requirement of second dose vaccination
{"title":"UNDERSTANDING THE IMPACT OF VACCINATION ON COVID-19 IN INDIA USING TIME INTERRUPTED SPATIAL PANEL DATA MODELS","authors":"J. P. Antony, T. Prabakaran","doi":"10.17654/0973514322026","DOIUrl":"https://doi.org/10.17654/0973514322026","url":null,"abstract":"COVID-19 is the biggest threat to the life of humankind around the globe. Vaccination became an important protective system against COVID-19 infection. The geographical aspect is an important factor in infection spreading. This study explores the effect of the vaccination on COVID-19 in India using the estimate of the spatial effects. Since the distribution of vaccination started in the middle of study period, time-interrupted spatial panel models were used. SDM model was selected as the best one. The spatial effect coefficients are statistically significant in SDM models (rho = 0.4057;p < 0.01 , rho = 0.3132;p < 0.01) and the spillover effect of second dose vaccination rate is statistically significant on both confirmed rate and deceased rate. The vaccination has a significant negative impact on deceased rate. There is a clear evidence for the requirement of second dose vaccination","PeriodicalId":40703,"journal":{"name":"JP Journal of Biostatistics","volume":null,"pages":null},"PeriodicalIF":0.1,"publicationDate":"2022-12-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41981668","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":"MODELING AGE SPECIFIC FERTILITY RATES OF PAKISTAN WITH HADWIGER FUNCTION MODEL","authors":"H. Waseem, Farah Yasmeen","doi":"10.17654/0973514322025","DOIUrl":"https://doi.org/10.17654/0973514322025","url":null,"abstract":"","PeriodicalId":40703,"journal":{"name":"JP Journal of Biostatistics","volume":null,"pages":null},"PeriodicalIF":0.1,"publicationDate":"2022-12-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42452087","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}
In Covid-19 pandemic, countries have developed various policies to get over this period with minimum damage. These policies have been updated and are still being updated at each stage of the pandemic to maximize benefit to the society. Vaccination policies of countries have become crucial after vaccine was developed. Some inequalities such as opportunity of developed countries and inability of other countries to access vaccine and anti-vaccination are considerable hinders to prevent spread of the pandemic. We used Covid-19 data to cluster European Union Countries, Candidate Countries and Potential Candidate Countries. At the first stage of the study, optimum algorithm was determined with use of internal and stability validation indexes for clustering of countries. At the second stage of the study, model algorithm was applied and it was determined that there are 20 countries in the first cluster and 14 countries in the second cluster. In conclusion of the study, cluster-based variables analysis shows that deaths and positive rate are lower since vaccination rate is high no matter how high is the number of new cases and the reproduction rate.
{"title":"APPLICATION OF MODEL-BASED CLUSTERING ALGORITHM TO COVID-19 VACCINE DATA","authors":"Seda Bağdatlı Kalkan, Ö. Başar","doi":"10.17654/0973514322024","DOIUrl":"https://doi.org/10.17654/0973514322024","url":null,"abstract":"In Covid-19 pandemic, countries have developed various policies to get over this period with minimum damage. These policies have been updated and are still being updated at each stage of the pandemic to maximize benefit to the society. Vaccination policies of countries have become crucial after vaccine was developed. Some inequalities such as opportunity of developed countries and inability of other countries to access vaccine and anti-vaccination are considerable hinders to prevent spread of the pandemic. We used Covid-19 data to cluster European Union Countries, Candidate Countries and Potential Candidate Countries. At the first stage of the study, optimum algorithm was determined with use of internal and stability validation indexes for clustering of countries. At the second stage of the study, model algorithm was applied and it was determined that there are 20 countries in the first cluster and 14 countries in the second cluster. In conclusion of the study, cluster-based variables analysis shows that deaths and positive rate are lower since vaccination rate is high no matter how high is the number of new cases and the reproduction rate.","PeriodicalId":40703,"journal":{"name":"JP Journal of Biostatistics","volume":null,"pages":null},"PeriodicalIF":0.1,"publicationDate":"2022-09-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45207411","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":"IMPACT OF GEOLOGICAL FACTOR ON CATARACT EYE DISEASE USING COM-POISSON REGRESSION MODEL","authors":"Vyasa Rao Prasanna, S. A. Ahmed","doi":"10.17654/0973514322023","DOIUrl":"https://doi.org/10.17654/0973514322023","url":null,"abstract":"","PeriodicalId":40703,"journal":{"name":"JP Journal of Biostatistics","volume":null,"pages":null},"PeriodicalIF":0.1,"publicationDate":"2022-09-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49212243","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}
H. Okagbue, T. Olawande, O. A. Odetunmibi, A. Opanuga
{"title":"MEAN AGE OF MENARCHE AND THE PROBABILITY OF ATTAINING MENARCHE FOR NIGERIAN GIRLS","authors":"H. Okagbue, T. Olawande, O. A. Odetunmibi, A. Opanuga","doi":"10.17654/0973514322022","DOIUrl":"https://doi.org/10.17654/0973514322022","url":null,"abstract":"","PeriodicalId":40703,"journal":{"name":"JP Journal of Biostatistics","volume":null,"pages":null},"PeriodicalIF":0.1,"publicationDate":"2022-08-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43851396","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}
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