Biostatistics and Epidemiology最新文献_第2页

Modeling time taken to HIV testing and uptake of test results: application of extended PWP model HIV测试的建模时间和测试结果的吸收:扩展PWP模型的应用

Biostatistics and Epidemiology Pub Date : 2022-01-02 DOI: 10.1080/24709360.2021.2017637

M. Suranga, S. Samita

{"title":"Modeling time taken to HIV testing and uptake of test results: application of extended PWP model","authors":"M. Suranga, S. Samita","doi":"10.1080/24709360.2021.2017637","DOIUrl":"https://doi.org/10.1080/24709360.2021.2017637","url":null,"abstract":"Improving HIV testing among the most at risk populations (MARP) is one of the first steps to achieve the Sustainable Development Goal target of ending AIDS by 2030. Factors affecting time taken to HIV testing and subsequent clinic visits to uptake the test result are important inputs for development of HIV prevention programmes. This study aims to develop multivariate statistical models to describe HIV testing behavior of MARP. HIV testing data of 5667 Female Sex Workers registered with the National HIV Prevention Programme in 10 districts of Sri Lanka during 2016 and 2017 were modelled using univariate and multivariate survival analysis techniques. Results showed that the Prentice, Williams & Peterson gap time model (PWPGTM), and all univariate Cox Proportional Hazard Models together generated consistent results. However, higher number of effects of the factors and interaction effects were detected in the PWPGTM compared to other models. Further, PWPGTM generated more precise estimates with lower standard errors. In all the models, most of the factors were identified as time dependent covariates. Study concludes that the extended PWPGTM is the more appropriate technique to model time taken to HIV testing and subsequent clinic visit to uptake of test results among MARP.","PeriodicalId":37240,"journal":{"name":"Biostatistics and Epidemiology","volume":"6 1","pages":"97 - 112"},"PeriodicalIF":0.0,"publicationDate":"2022-01-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48753315","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}

引用次数: 0

Estimation of highly heterogeneous multinomial probabilities observed at the beginning of COVID-19 新冠肺炎开始时观察到的高度异质多项式概率的估计

Biostatistics and Epidemiology Pub Date : 2022-01-02 DOI: 10.1080/24709360.2022.2064693

T. Ogura, T. Yanagimoto

引用次数: 0

A comparison of single imputation and multiple imputation methods for missing data in different oncogene expression profiles 不同癌基因表达谱中缺失数据的单一插补和多重插补方法的比较

Biostatistics and Epidemiology Pub Date : 2022-01-02 DOI: 10.1080/24709360.2021.2023805

W. Ye, Ling Zhang, Wenqing Zhang, Xiaojiao Wu, Dong Yi, Yazhou Wu

{"title":"A comparison of single imputation and multiple imputation methods for missing data in different oncogene expression profiles","authors":"W. Ye, Ling Zhang, Wenqing Zhang, Xiaojiao Wu, Dong Yi, Yazhou Wu","doi":"10.1080/24709360.2021.2023805","DOIUrl":"https://doi.org/10.1080/24709360.2021.2023805","url":null,"abstract":"To evaluate the effects of multiple-imputation (MI) method for missing data in gene expression profiles with different datasets and percentages of missing values compared with 3 single-imputation (SI) methods. Based on 3 gene expression profiles datasets from human colon cancer, non-small cell lung cancer, and lymph cancer, different deletion rates and different imputation numbers of MI were compared. The imputation and clustering effects of different methods were evaluated using the NRMSE and the gene clustering accuracy (F value). The NRMSE of the 4 methods gradually increased as the percentage of missing values in the 3 datasets increased, whereas the F value gradually decreased. In all datasets with different percentage of missing values settings, the NRMSEs of MI was consistently lower than those of the 3 SI methods, whereas the F value of MI was highest. The NRMSEs of MI gradually decreased as the number of imputations increased and increased as the variability in the original datasets increased, and the datasets imputed by MI showed the best clustering results. The results showed that the application of MI develops and enriches imputation-model approaches and provides a solid foundation for subsequent establishment of imputation strategies for gene expression profiles with missing data.","PeriodicalId":37240,"journal":{"name":"Biostatistics and Epidemiology","volume":"6 1","pages":"113 - 127"},"PeriodicalIF":0.0,"publicationDate":"2022-01-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46745736","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}

引用次数: 1

Bayesian inference of the basic reproduction number for a SIR epidemic model SIR流行病模型基本繁殖数的贝叶斯推断

Biostatistics and Epidemiology Pub Date : 2022-01-02 DOI: 10.1080/24709360.2022.2031721

Abdelaziz Qaffou, Hamid El Maroufy, Mokhtar Zbair

{"title":"Bayesian inference of the basic reproduction number for a SIR epidemic model","authors":"Abdelaziz Qaffou, Hamid El Maroufy, Mokhtar Zbair","doi":"10.1080/24709360.2022.2031721","DOIUrl":"https://doi.org/10.1080/24709360.2022.2031721","url":null,"abstract":"This paper is concerned with the Bayesian estimation for the basic reproduction number , defined as the expected number of new infectious from one infected individual in a fully susceptible population through the entire duration of the infectious period. This parameter is of great importance within epidemic modeling because no epidemic can occur if and an epidemic occurs if . Estimation of , or equivalent parameters in more complex models, can usually be achieved via Markov chain Monte Carlo (MCMC) methods. We will adopt the Bayesian method proposed by Eraker [MCMC analysis of diffusion models with application to finance. J Bus Econ Statist. 2001;19(2):177–191] in the context of financial models. The method consists of augmenting the low-frequency observations by the insertion of a finite number of latent data between two consecutive observations. We develop MCMC methods for inference to explore a posterior distribution of and of missing data. We illustrate the performance of the estimators on both synthetic data and real epidemic from the SIR (Susceptible-Infective-Removed) epidemic model and compare the results with the maximum likelihood (ML) method.","PeriodicalId":37240,"journal":{"name":"Biostatistics and Epidemiology","volume":"6 1","pages":"128 - 143"},"PeriodicalIF":0.0,"publicationDate":"2022-01-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44710149","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}

引用次数: 1

Abstract PO-166: Geographic distribution of the cervical cancer incidence in the northeast region of the state of São Paulo, Brazil 摘要PO-166:巴西<s:1>圣保罗州东北部地区宫颈癌发病率的地理分布

Biostatistics and Epidemiology Pub Date : 2022-01-01 DOI: 10.1158/1538-7755.disp21-po-166

A. Ribeiro, A. M. Costa, J. Fregnani

引用次数: 0

Abstract PO-165: Prevalence of metabolic syndrome among cancer survivors: An NHANES study PO-165:癌症幸存者中代谢综合征的患病率:一项NHANES研究

Biostatistics and Epidemiology Pub Date : 2022-01-01 DOI: 10.1158/1538-7755.disp21-po-165

A. Ezeani, T. Agurs-Collins

引用次数: 0

Estimation of missing total number of trials in binomial time series analysis by a BDLM process with an illustration of the COVID-19 pandemic data 用BDLM过程估计二项时间序列分析中缺失的试验总数，并举例说明COVID-19大流行数据

Biostatistics and Epidemiology Pub Date : 2021-12-31 DOI: 10.1080/24709360.2021.2006397

Massoud Nakhkoob

{"title":"Estimation of missing total number of trials in binomial time series analysis by a BDLM process with an illustration of the COVID-19 pandemic data","authors":"Massoud Nakhkoob","doi":"10.1080/24709360.2021.2006397","DOIUrl":"https://doi.org/10.1080/24709360.2021.2006397","url":null,"abstract":"The criteria used for sample size determination are generally developed based on applying averaging techniques to the possible values a variable can take on. This paper presented new methods for estimation of sample size, in particular for binomial distribution, when an observation on number of successes is available. In this paper, first, the general criteria for the determination of sample size were reviewed. Next, the BDLM process was concisely introduced and fit to the first real-world dataset. Then, based on the model, four new methods for the estimation of the missing total number of trials in binomial time series were developed with the illustrated small dataset, where number of successes at any specific time point was known. In addition, the worst outcome criterion was evaluated based on the highest probability density (HPD) confidence set by using the illustrated data and the results were compared with those of the new methods developed in the present paper. Later, an illustration of COVID-19 trinomial data was presented in which BDLM was fit to the time series of cured cases infected due to COVID-19 disease. Finally, the new methods of estimation of missing total confirmed cases evaluated by the relatively large dataset.","PeriodicalId":37240,"journal":{"name":"Biostatistics and Epidemiology","volume":"6 1","pages":"74 - 96"},"PeriodicalIF":0.0,"publicationDate":"2021-12-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42963328","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}

引用次数: 0

TBEV analyzer platform for evolutionary analysis and monitoring tick-borne encephalitis virus: 2020 update 进化分析和监测蜱传脑炎病毒的bev分析平台:2020年更新

Biostatistics and Epidemiology Pub Date : 2021-10-29 DOI: 10.1080/24709360.2021.1985392

M. Forghani, S. Kovalev, M. Bolkov, M. Khachay, P. Vasev

{"title":"TBEV analyzer platform for evolutionary analysis and monitoring tick-borne encephalitis virus: 2020 update","authors":"M. Forghani, S. Kovalev, M. Bolkov, M. Khachay, P. Vasev","doi":"10.1080/24709360.2021.1985392","DOIUrl":"https://doi.org/10.1080/24709360.2021.1985392","url":null,"abstract":"Viral surveillance is an essential task in public health that yields specific data, such as biological and epidemiological characteristics, crucial in the fight against viruses. We have recently developed an online platform for monitoring of Tick-Borne Encephalitis Virus, TBEV Analyzer, equipped with phylogenetic analysis and geographic map visualization functions. The phylogenetic analysis employs the clusteron approach, which has been earlier proposed by one of the authors of this paper. The analysis is based on a genetic pattern and provides three-fold hierarchical information about subtype, phylogenetic lineage, and clusteron. A clusteron is a group of TBEV strains with identical amino acid sequences of the glycoprotein E fragment, as a rule phylogeographically close, and having a certain type of territorial distribution. We enhance the algorithms and quality of visualization by integrating our platform with the GenBank database, adding a heat map distribution, and providing more details in the analysis report. To demonstrate the performance of the upgraded system, we analyze recent strains published in GenBank and compare them with the results of the manual analysis performed by a specialist. The results show that the system can rapidly and accurately determine query strain characteristics. This suggests possible applications in the field of public health.","PeriodicalId":37240,"journal":{"name":"Biostatistics and Epidemiology","volume":"6 1","pages":"57 - 73"},"PeriodicalIF":0.0,"publicationDate":"2021-10-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46403222","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}

引用次数: 4

A comparative study of design-based and analysis-based approaches to causal inference with observational data 基于设计和基于分析的方法对观测数据进行因果推理的比较研究

Biostatistics and Epidemiology Pub Date : 2021-10-28 DOI: 10.1080/24709360.2021.1992246

Junni L. Zhang

引用次数: 0

Reproduction number, discrete forecasting model, and chaos analytics for Coronavirus Disease 2019 outbreak in India, Bangladesh, and Myanmar 2019年印度、孟加拉国和缅甸冠状病毒疫情的再现数、离散预测模型和混沌分析

Biostatistics and Epidemiology Pub Date : 2021-08-10 DOI: 10.1080/24709360.2021.1960122

R. Sunthornwat, Y. Areepong

引用次数: 2