scholarly journals MODELLING THE NUMBER OF NEW PULMONARY TUBERCULOSIS CASES WITH GEOGRAPHICALLY WEIGHTED NEGATIVE BINOMIAL REGRESSION METHOD

2018 ◽  
Vol 2 (2) ◽  
pp. 77-92
Author(s):  
Tsuraya Mumtaz ◽  
Agung Priyo Utomo
Keyword(s):  
Diabetes Mellitus ◽  
Infectious Disease ◽  
Developing Countries ◽  
Mycobacterium Tuberculosis ◽  
Negative Binomial ◽  
Negative Binomial Regression ◽  
Regression Method ◽  
Pulmonary Tb ◽  
Binomial Regression ◽  
The World

Tuberculosis (TB) is an infectious disease caused by Mycobacterium Tuberculosis. Untill now, TB is still one of the main problems in many countries, especially developing countries. Indonesia ranked second as the country with the highest TB cases in the world in 2015, where most cases were found in Java. This study was conducted to model the number of new pulmonary TB cases in Java by considering the spatial aspects using Geographically Weighted Negative Binomial Regression (GWNBR). GWNBR method was chosen  because the data used in this study are overdispered. The result showed that the population density and percentage of healty homes were not significantly influential in each region. While the number of puskesmas, the percentage of smokers, the percentage of good PHBS, the percentage of diabetes mellitus, and the percentage of less IMT were significant in some regions. In general, the GWNBR model was better for modelling the number of new pulmonary TB cases than negative binomial regression and GWPR.

scholarly journals MODELLING THE NUMBER OF NEW PULMONARY TUBERCULOSIS CASES WITH GEOGRAPHICALLY WEIGHTED NEGATIVE BINOMIAL REGRESSION METHOD

2018 ◽  
Author(s):  
Tsuraya Mumtaz ◽  
Agung Priyo Utomo
Keyword(s):  
Diabetes Mellitus ◽  
Infectious Disease ◽  
Developing Countries ◽  
Mycobacterium Tuberculosis ◽  
Negative Binomial ◽  
Negative Binomial Regression ◽  
Regression Method ◽  
Pulmonary Tb ◽  
Binomial Regression ◽  
The World

Tuberculosis (TB) is an infectious disease caused by Mycobacterium Tuberculosis. Untill now, TB is still one of the main problems in many countries, especially developing countries. Indonesia ranked second as the country with the highest TB cases in the world in 2015, where most cases were found in Java. This study was conducted to model the number of new pulmonary TB cases in Java by considering the spatial aspects using Geographically Weighted Negative Binomial Regression (GWNBR). GWNBR method was chosen  because the data used in this study are overdispered. The result showed that the population density and percentage of healty homes were not significantly influential in each region. While the number of puskesmas, the percentage of smokers, the percentage of good PHBS, the percentage of diabetes mellitus, and the percentage of less IMT were significant in some regions. In general, the GWNBR model was better for modelling the number of new pulmonary TB cases than negative binomial regression and GWPR.

scholarly journals STUDI PENGARUH STATUS PERKAWINAN DAN PEKERJAAN PADA PASIEN TUBERKULOSIS DI RUMAH SAKIT DKT PURWOKERTO

2019 ◽  
Vol 10 (2) ◽  
pp. 46-51
Author(s):  
Peppy Octaviani
Keyword(s):  
Infectious Disease ◽  
Developing Countries ◽  
Pulmonary Tuberculosis ◽  
Descriptive Study ◽  
World Health ◽  
P Value ◽  
Cross Sectional ◽  
Pulmonary Tb ◽  
The World ◽  
Health Organization

ABSTRACT Pulmonary tuberculosis (TB) is a contagious pulmonary infectious disease that is still a health problem in the world, especially developing countries. Tuberculosis has been proclaimed by WHO (World Health Organization) as Global Emergency since 1992. The purpose of this study is to find out what physical characteristics are at risk of tuberculosis in DKT Hospital Purwokerto. The research design used in this study was a descriptive study with a cross-sectional approach to determine the characteristics of pulmonary TB patients who were adherent to treatment and those who did not comply with treatment at the DKT Hospital in Purwokerto. This research was conducted at the DKT Purwokerto Hospital in May 2018. The samples studied in this study were pulmonary TB patients who were obedient to treatment and non-compliance with treatment at the DKT Purwokerto Hospital for the period of 1 January - 30 December 2017 that met the sample criteria. The results of the study have no relationship between age and the results of sputum examination at the Purwokerto DKT Hospital (p value = 0.286), there is no relationship between sex with the results of sputum examination at DKT Purwokerto Hospital (p value = 0.261).                                                                                                                           Keywords: Pulmonary TBC, Characteristics, Phlegm Examination  

Gender, Marital Status, and Mental Health: A Test of the Sex Role Hypothesis in India

2016 ◽  
Vol 38 (13) ◽  
pp. 1899-1922 ◽  
Author(s):  
Lisa Strohschein ◽  
Usha Ram
Keyword(s):  
Mental Health ◽  
Developing Countries ◽  
Marital Status ◽  
Gender Inequality ◽  
Regression Models ◽  
Negative Binomial ◽  
Sex Role ◽  
Negative Binomial Regression ◽  
Developed Countries ◽  
Binomial Regression

Received wisdom says marriage correlates with better health, but men derive a greater benefit than do women. These perceptions persist even though the latter, known as the sex role hypothesis, no longer receives unqualified support. Some researchers attribute declining evidence for the sex role hypothesis to greater gender equality. Such arguments, however, may best apply to Western, developed countries where gains in women’s status have been largest. To date, few researchers have explored these issues in non-Western, developing countries. This study is the first to explore sex-specific differences in the association between marital status and mental health in India, a country with high levels of gender inequality. Data come from the Youth in India Situation and Needs survey, with analysis restricted to 19,163 young adults aged 20 to 24. Results from negative binomial regression models supported the sex role hypothesis. The implications of these findings are discussed.

scholarly journals STUDI PENGARUH UMUR DAN JENIS KELAMIN PADA PASIEN TUBERKULOSIS DI RUMAH SAKIT DKT PURWOKERTO

2019 ◽  
Vol 10 (2) ◽  
pp. 40-45
Author(s):  
Peppy Octaviani
Keyword(s):  
Infectious Disease ◽  
Developing Countries ◽  
Pulmonary Tuberculosis ◽  
Descriptive Study ◽  
World Health ◽  
P Value ◽  
Cross Sectional ◽  
Pulmonary Tb ◽  
The World ◽  
Health Organization

ABSTRACT Pulmonary tuberculosis (TB) is a contagious pulmonary infectious disease that is still a health problem in the world, especially developing countries. Tuberculosis has been proclaimed by WHO (World Health Organization) as Global Emergency since 1992. The purpose of this study is to find out what physical characteristics are at risk of tuberculosis in DKT Hospital Purwokerto. The research design used in this study was a descriptive study with a cross-sectional approach to determine the characteristics of pulmonary TB patients who were adherent to treatment and those who did not comply with treatment at the DKT Hospital in Purwokerto. This research was conducted at the DKT Purwokerto Hospital in May 2018. The samples studied in this study were pulmonary TB patients who were obedient to treatment and non-compliance with treatment at the DKT Purwokerto Hospital for the period of 1 January - 30 December 2017 that met the sample criteria. The results of the study have no relationship between age and the results of sputum examination at the Purwokerto DKT Hospital (p value = 0.286), there is no relationship between sex with the results of sputum examination at DKT Purwokerto Hospital (p value = 0.261).                                                                                                                           Keywords: Pulmonary TBC, Characteristics, Phlegm Examination  

scholarly journals Pemodelan Zero Inflated Negative Binomial (ZINB) Pada Kasus Jumlah Bepergian Penduduk Provinsi Sulawesi Tengah

2020 ◽  
Vol 17 (2) ◽  
pp. 202-211
Author(s):  
I T Utami
Keyword(s):  
Regression Model ◽  
Negative Binomial ◽  
Negative Binomial Regression ◽  
Regression Method ◽  
Poisson Regression Model ◽  
Factors Affecting ◽  
The People ◽  
Binomial Regression ◽  
Zero Values ◽  
Central Sulawesi

Traveling is something that has been done by every resident, especially the people of Central Sulawesi province. The people of Central Sulawesi province who travel have a certain purpose either because of their own desires or following others. The number of people traveling from Central Sulawesi Province can be analyzed using the zero inflated negative binomial regression method (ZINB). ZINB regression is a method used to model calculated or discrete data with many zero values ​​on the response variable (zero inflation) and overdispersion occurs. The result shows that the factors affecting the number of people traveling population from the Central Sulawesi Province are age (X1), the people who have jobs in mining and quarrying (X32), the people who have jobs in electricity and gas (X34). The zero inflated negative binomial (ZINB) regression model is better at modeling cases of the number of people traveling in Central Sulawesi Province in 2016 compared to the Poisson regression model because it has the smallest AIC value.

scholarly journals Is area deprivation associated with greater impacts of COVID-19 in care homes across England? A preliminary analysis of COVID-19 outbreaks and deaths

2021 ◽  
pp. jech-2020-215039 ◽  
Author(s):  
Anders Malthe Bach-Mortensen ◽  
Michelle Degli Esposti
Keyword(s):  
Negative Binomial ◽  
Care Home ◽  
Negative Binomial Regression ◽  
Population Characteristics ◽  
Care Homes ◽  
Future Research ◽  
Area Deprivation ◽  
Binomial Regression ◽  
Index Of Multiple Deprivation

IntroductionThe COVID-19 pandemic has disproportionately impacted care homes and vulnerable populations, exacerbating existing health inequalities. However, the role of area deprivation in shaping the impacts of COVID-19 in care homes is poorly understood. We examine whether area deprivation is linked to higher rates of COVID-19 outbreaks and deaths among care home residents across upper tier local authorities in England (n=149).MethodsWe constructed a novel dataset from publicly available data. Using negative binomial regression models, we analysed the associations between area deprivation (Income Deprivation Affecting Older People Index (IDAOPI) and Index of Multiple Deprivation (IMD) extent) as the exposure and COVID-19 outbreaks, COVID-19-related deaths and all-cause deaths among care home residents as three separate outcomes—adjusting for population characteristics (size, age composition, ethnicity).ResultsCOVID-19 outbreaks in care homes did not vary by area deprivation. However, COVID-19-related deaths were more common in the most deprived quartiles of IDAOPI (incidence rate ratio (IRR): 1.23, 95% CI 1.04 to 1.47) and IMD extent (IRR: 1.16, 95% CI 1.00 to 1.34), compared with the least deprived quartiles.DiscussionThese findings suggest that area deprivation is a key risk factor in COVID-19 deaths among care home residents. Future research should look to replicate these results when more complete data become available.

scholarly journals Association between fatality rate of COVID-19 and selenium deficiency in China

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Hai-Yang Zhang ◽  
An-Ran Zhang ◽  
Qing-Bin Lu ◽  
Xiao-Ai Zhang ◽  
Zhi-Jie Zhang ◽  
...  
Keyword(s):  
Negative Binomial ◽  
Viral Infections ◽  
Case Fatality ◽  
Selenium Deficiency ◽  
Negative Binomial Regression ◽  
Negative Binomial Regression Model ◽  
Fatality Rate ◽  
Selenium Content ◽  
Individual Level ◽  
Binomial Regression

Abstract Background COVID-19 has impacted populations around the world, with the fatality rate varying dramatically across countries. Selenium, as one of the important micronutrients implicated in viral infections, was suggested to play roles. Methods An ecological study was performed to assess the association between the COVID-19 related fatality and the selenium content both from crops and topsoil, in China. Results Totally, 14,045 COVID-19 cases were reported from 147 cities during 8 December 2019–13 December 2020 were included. Based on selenium content in crops, the case fatality rates (CFRs) gradually increased from 1.17% in non-selenium-deficient areas, to 1.28% in moderate-selenium-deficient areas, and further to 3.16% in severe-selenium-deficient areas (P = 0.002). Based on selenium content in topsoil, the CFRs gradually increased from 0.76% in non-selenium-deficient areas, to 1.70% in moderate-selenium-deficient areas, and further to 1.85% in severe-selenium-deficient areas (P < 0.001). The zero-inflated negative binomial regression model showed a significantly higher fatality risk in cities with severe-selenium-deficient selenium content in crops than non-selenium-deficient cities, with incidence rate ratio (IRR) of 3.88 (95% CIs: 1.21–12.52), which was further confirmed by regression fitting the association between CFR of COVID-19 and selenium content in topsoil, with the IRR of 2.38 (95% CIs: 1.14–4.98) for moderate-selenium-deficient cities and 3.06 (1.49–6.27) for severe-selenium-deficient cities. Conclusions Regional selenium deficiency might be related to an increased CFR of COVID-19. Future studies are needed to explore the associations between selenium status and disease outcome at individual-level.

scholarly journals Statistical models for analyzing count data: predictors of length of stay among HIV patients in Portugal using a multilevel model

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Ahmed Nabil Shaaban ◽  
Bárbara Peleteiro ◽  
Maria Rosario O. Martins
Keyword(s):  
Length Of Stay ◽  
Regression Model ◽  
Random Effects ◽  
Count Data ◽  
Negative Binomial ◽  
Negative Binomial Regression ◽  
Comprehensive Approach ◽  
Negative Binomial Regression Model ◽  
Hiv Patients ◽  
Binomial Regression

Abstract Background This study offers a comprehensive approach to precisely analyze the complexly distributed length of stay among HIV admissions in Portugal. Objective To provide an illustration of statistical techniques for analysing count data using longitudinal predictors of length of stay among HIV hospitalizations in Portugal. Method Registered discharges in the Portuguese National Health Service (NHS) facilities Between January 2009 and December 2017, a total of 26,505 classified under Major Diagnostic Category (MDC) created for patients with HIV infection, with HIV/AIDS as a main or secondary cause of admission, were used to predict length of stay among HIV hospitalizations in Portugal. Several strategies were applied to select the best count fit model that includes the Poisson regression model, zero-inflated Poisson, the negative binomial regression model, and zero-inflated negative binomial regression model. A random hospital effects term has been incorporated into the negative binomial model to examine the dependence between observations within the same hospital. A multivariable analysis has been performed to assess the effect of covariates on length of stay. Results The median length of stay in our study was 11 days (interquartile range: 6–22). Statistical comparisons among the count models revealed that the random-effects negative binomial models provided the best fit with observed data. Admissions among males or admissions associated with TB infection, pneumocystis, cytomegalovirus, candidiasis, toxoplasmosis, or mycobacterium disease exhibit a highly significant increase in length of stay. Perfect trends were observed in which a higher number of diagnoses or procedures lead to significantly higher length of stay. The random-effects term included in our model and refers to unexplained factors specific to each hospital revealed obvious differences in quality among the hospitals included in our study. Conclusions This study provides a comprehensive approach to address unique problems associated with the prediction of length of stay among HIV patients in Portugal.

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