Patient and healthcare delays in critical and non-critical pulmonary tuberculosis incidence areas in Portugal: are there differences?

Public Health ◽  
2021 ◽  
Vol 201 ◽  
pp. 41-47
Author(s):  
J. Almeida Santos ◽  
P. Soares ◽  
A. Leite ◽  
R. Duarte ◽  
C. Nunes
Keyword(s):  
Pulmonary Tuberculosis ◽  
Tuberculosis Incidence

scholarly journals Contribution of Smoking to Pulmonary Tuberculosis Incidence in Bandung, Indonesia

2020 ◽  
pp. 451-457
Author(s):  
Raspati Cundarani Koesoemadinata ◽  
◽  
Panji Fortuna Hadisoemarto ◽  
Manik Intan Gumilang ◽  
Ida Parwati Santoso ◽  
...  
Keyword(s):  
Pulmonary Tuberculosis ◽  
Tuberculosis Incidence

Pulmonary tuberculosis incidence in Turkish prisons: importance of screening and case finding strategies

2013 ◽  
Vol 61 (1) ◽  
pp. 21-27 ◽  
Author(s):  
Gül ÖNGEN ◽  
Şermin BÖREKÇİ ◽  
Özlem Saniye İÇMELİ ◽  
Nur BİRGEN ◽  
Gülsüm KARAGÜL ◽  
...  
Keyword(s):  
Pulmonary Tuberculosis ◽  
Case Finding ◽  
Tuberculosis Incidence

Time Series Analysis of Pulmonary Tuberculosis Incidence: Forecasting by Applying the Time Series Model

2013 ◽  
Vol 709 ◽  
pp. 819-822 ◽  
Author(s):  
Yin Ping Chen ◽  
Ai Ping Wu ◽  
Cui Ling Wang ◽  
Hai Ying Zhou ◽  
Shu Xiu Feng
Keyword(s):  
Time Series ◽  
Pulmonary Tuberculosis ◽  
Moving Average ◽  
Arima Model ◽  
Autoregressive Integrated Moving Average ◽  
Tuberculosis Incidence ◽  
Short Lead Time ◽  
White Noise Sequence ◽  
Noise Sequence ◽  
Residual Sequence

The main objective of this study is to identify the stochastic autoregressive integrated moving average (ARIMA) model to predict the pulmonary tuberculosis incidence in Qianan. Considering the Box-Jenkins modeling approach, the incidence of pulmonary tuberculosis was collected monthly from 2004 to 2010. The model ARIMA(0,1,1)12 was established finally and the residual sequence was a white noise sequence. Then, this model was used for calculating dengue incidence for the last 6 observations compared with observed data, and performed to predict the monthly incidence in 2011. It is necessary and practical to apply the approach of ARIMA model in fitting time series to predict pulmonary tuberculosis within a short lead time.

scholarly journals Pulmonary Tuberculosis Incidence and Risk Factors in Rural Areas of China: A Cohort Study

PLoS ONE ◽  
2013 ◽  
Vol 8 (3) ◽  
pp. e58171 ◽  
Author(s):  
Wei Chen ◽  
Wen Shu ◽  
Min Wang ◽  
Yongchun Hou ◽  
Yinyin Xia ◽  
...  
Keyword(s):  
Risk Factors ◽  
Cohort Study ◽  
Pulmonary Tuberculosis ◽  
Rural Areas ◽  
Tuberculosis Incidence
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