Telecommunication Infrastructure Development and Economic Growth: A Panel Data Approach

The present study empirically investigate the dynamic relationship between telecommunication infrastructure and economic growth, using data from twenty-four low income, middle income and high income countries for a 18 years period, from 1985– 2003. With a panel data set, this study uses dynamic fixed effect and random effect models for estimation, which allows us to test the relationship between country’s economic growth with initial economic condition, fixed investment, population growth, government consumption as well as telecommunication infrastructure. The results show that telecommunication is both statistically significant and positively correlated to the real GDP per capita of these countries included in the study. The results are robust even after controlling for investment, population growth, past level of GDP per capita and lagged growth. The results further indicate that the telecommunication investment is subject to increasing returns, suggesting thereby that countries gain more and more with the increase in telecommunication investment. The second test, Granger’s causality test confirms the causal relationship between telecommunication infrastructure and economic growth, but the relationship is significant from telecommunication to GDP per capita side but insignificant on GDP per capita to telecommunication development side.Telecommunication Growth, Panel Data, Fixed and Random Effect, Granger Causality

HIV and AIDS in Bangladesh

Bangladesh initiated an early response to the HIV epidemic starting in the mid-1980s. Since then, the res-ponse has been enhanced considerably, and many HIV-prevention interventions among the most at-risk populations and the general youth are being undertaken. Alongside prevention activities, gathering of data has been a key activity fostered by both the Government and individual development partners. This paper reviews available sources of data, including routine surveillance (HIV and behavioural among most at-risk populations), general population surveys, and various research studies with the aim to understand the dynamics of the HIV epidemic in Bangladesh. Available data show that the HIV epidemic is still at relatively low levels and is concentrated mainly among injecting drug users (IDUs) in Dhaka city. In addition, when the passively-reported cases were analyzed, another population group that appears to be especially vulnerable is migrant workers who leave their families and travel abroad for work. However, all sources of data confirm that risk behaviours that make individuals vulnerable to HIV are high—this is apparent within most at-risk populations and the general population (adult males and youth males and females). Based on the current activities and the sources of data, modelling exercises of the future of the HIV epidemic in Dhaka suggest that, if interventions are not enhanced further, Bangladesh is likely to start with an IDU-driven epidemic, similar to other neighbouring countries, which will then move to other population groups, including sex workers, males who have sex with males, clients of sex workers, and ultimately their families. This review reiterates the often repeated message that if Bangladesh wants to be an example of how to avert an HIV epidemic, it needs to act now using evidence-based programming

HIV and AIDS in Bangladesh

Bangladesh initiated an early response to the HIV epidemic starting in the mid-1980s. Since then, the res-ponse has been enhanced considerably, and many HIV-prevention interventions among the most at-risk populations and the general youth are being undertaken. Alongside prevention activities, gathering of data has been a key activity fostered by both the Government and individual development partners. This paper reviews available sources of data, including routine surveillance (HIV and behavioural among most at-risk populations), general population surveys, and various research studies with the aim to understand the dynamics of the HIV epidemic in Bangladesh. Available data show that the HIV epidemic is still at relatively low levels and is concentrated mainly among injecting drug users (IDUs) in Dhaka city. In addition, when the passively-reported cases were analyzed, another population group that appears to be especially vulnerable is migrant workers who leave their families and travel abroad for work. However, all sources of data confirm that risk behaviours that make individuals vulnerable to HIV are high-this is apparent within most at-risk populations and the general population (adult males and youth males and females). Based on the current activities and the sources of data, modelling exercises of the future of the HIV epidemic in Dhaka suggest that, if interventions are not enhanced further, Bangladesh is likely to start with an IDU-driven epidemic, similar to other neighbouring countries, which will then move to other population groups, including sex workers, males who have sex with males, clients of sex workers, and ultimately their families. This review reiterates the often repeated message that if Bangladesh wants to be an example of how to avert an HIV epidemic, it needs to act now using evidence-based programming

Characteristics and predictors of death among hospitalized HIV-infected patients in a low HIV prevalence country: Bangladesh.

Predictors of death in hospitalized HIV-infected patients have not been previously reported in Bangladesh.The primary aim of this study was to determine predictors of death among hospitalized HIV-infected patients at a large urban hospital in Bangladesh.A study was conducted in the HIV in-patient unit (Jagori Ward) of icddr,b's Dhaka Hospital. Characteristics of patients who died during hospitalization were compared to those of patients discharged from the ward. Bivariate analysis was performed to determine associations between potential risk factors and death. Multivariable logistic regression was used to identify factors independently associated with death.Of 293 patients admitted to the Jagori Ward, 57 died during hospitalization. Most hospitalized patients (67%) were male and the median age was 35 (interquartile range: 2-65) years. Overall, 153 (52%) patients were diagnosed with HIV within 6 months of hospitalization. The most common presumptive opportunistic infections (OIs) identified were tuberculosis (32%), oesophageal candidiasis (9%), Pneumocystis jirovecii pneumonia (PJP) (8%), and histoplasmosis (7%). On multivariable analysis, independent predictors of mortality were CD4 count ≤200 cells/mm3 (adjusted odds ratio [aOR]: 16.6, 95% confidence interval [CI]: 3.7-74.4), PJP (aOR: 18.5, 95% CI: 4.68-73.3), oesophageal candidiasis (aOR: 27.5, 95% CI: 5.5-136.9), malignancy (aOR:15.2, 95% CI: 2.3-99.4), and bacteriuria (aOR:7.9, 95% CI: 1.2-50.5). Being on antiretroviral therapy prior to hospitalization (aOR: 0.2, 95% CI: 0.06-0.5) was associated with decreased mortality.This study showed that most patients who died during hospitalization on the Jagori Ward had HIV-related illnesses which could have been averted with earlier diagnosis of HIV and proper management of OIs. It is prudent to develop a national HIV screening programme to facilitate early identification of HIV

Independent predictors of death in hospitalized HIV-infected patients.

<p><b>Adjustment variables:</b> New HIV diagnosis, presumptive TB, presumptive histoplasma, bacteremia and isolation of multiple organisms in blood.</p><p>OR indicates odds ratio. CI indicates confidence interval.</p><p>Independent predictors of death in hospitalized HIV-infected patients.</p

Baseline characteristics of the HIV-infected patients stratified by outcome.

<p>Figures represent n (%), unless specified. OR: odds ratio. CI: confidence interval. IQR: interquartile range.</p><p>Baseline characteristics of the HIV-infected patients stratified by outcome.</p

Distribution of Nadir CD4 cell counts of HIV-infected patients stratified by outcome.

<p>Distribution of Nadir CD4 cell counts of HIV-infected patients stratified by outcome.</p

Diagnoses of HIV-infected patients stratified by outcome.

<p>*Non-Hodgkin's lymphoma (4 cases), central nervous system tumors (2 cases), and Kaposi's sarcoma (1 case), mediastinal sarcoma (1 case), cervical cancer (1 case), carcinoma of the tongue (1 case) and adenocarcinoma of the colon (1 case).</p><p>Figures represent n (%), unless specified. OR: odds ratio. CI: confidence interval. IQR: interquartile range.</p><p>Diagnoses of HIV-infected patients stratified by outcome.</p