A trend analysis and sub-regional distribution in number of people living with HIV and dying with TB in Africa, 1991 to 2006

Abstract

BackgroundThe tuberculosis (TB) bacillus and the Human Immunodeficiency Virus (HIV) have formed a powerful alliance and are together responsible for more than five million deaths per year. TB is leading to increased mortality rates among people living with HIV/acquired immunodeficiency syndrome (AIDS). The aim of this study was to investigate the geographical and temporal distribution of TB-HIV deaths in Africa in order to identify possible high-risk areas.MethodsTime trends in the 16-year study period from 1990 to 2005 were analyzed by multilevel Poisson growth curve models. Moran global and local indicators of spatial associations were used to test for evidence of global and local spatial clustering respectively.ResultsEastern, Southern, Western, and Middle Africa experienced an upward trend in the number of reported TB-HIV deaths. The spatial distribution of TB cases was non-random and clustered, with a Moran's I = 0.454 (p = .001). Spatial clustering suggested that 13 countries were at increased risk of TB-HIV deaths, and six countries could be grouped as "hot spots".ConclusionEvidence shows that there is no decline in growth in the number of deaths due to TB among HIV positive in most Africa countries. There is presence of 'hot-spots' and very large differences persist between sub-regions. Only by tackling TB and HIV together will progress be made in reversing the burden of both diseases. There is a great need for scale-up of preventive interventions such as the World Health Organization '3I's strategy' (intensified case finding, isoniazid preventive therapy and infection control).

Distribuição espacial de casos de tuberculose em Santa Cruz do Sul, município prioritário do Estado do Rio Grande do Sul, Brasil, 2000 a 2010

“…22 A tuberculose é comum no curso da infecção pelo HIV. 23 Ela é responsável pelo aumento da mortalidade em soropositivos, sendo um dos motivos pelos quais a sorologia de cada paciente diagnosticado com TB é recomendada. O registro de sorologias não foi verificado em grande parcela dos dados averiguados, contra a lógica necessária à estruturação de um plano de Saúde Pública que previna e reduza as mortes por TB-HIV.…”

Trends and Predictors of Mortality among HIV Positive Patients in the Era of Highly Active Antiretroviral Therapy in Uganda

“… 2-8 However, the greatest challenge for sub-Saharan Africa has been that most HIV-infected patients present late for ARVS thereby increasing the risk of death in spite of the increasing availability of effective treatment. 2 , 6 , 7 The recent changes in WHO treatment guidelines, 9 , 10 recommending treatment initiation at 350-500 cells/µL, were meant to address this challenge in these settings.…”

“…Some authors have attributed the main causes of high mortality in African HIV patients starting HAART were low CD4 cell counts and co-morbidities especially tuberculosis at HAART initiation. 2 A study that investigated the geographical and temporal distribution of TB-HIV deaths in Africa, in the period from 1991 to 2006, 6 showed that Eastern, Southern, Western, and Middle Africa experienced an upward trend in the number of reported TB-HIV deaths. Eastern Africa was ranked first in absolute upward trend in number of reported TB-HIV deaths, followed by Southern and Western Africa.…”

“…Uganda and Kenya were categorized as high risk areas for TB-HIV related deaths. 6 In Botswana, the first 633 patients initiated on public HAART were followed for 5 years (2002-2007) and results showed that 86% of all the deaths occurred in the first 12 months. The majority of deaths were due to advanced HIV disease at HAART initiation, with only a small fraction was attributed to ARV-related toxicities.…”

Spatial Distribution and Trend Analysis of Current Status of COVID-19 in Nepal and Global Future Preventive Perspectives

“…In relation to the spatial analysis of certain information, it is possible to evaluate the risks of disease, trends in outbreaks over time and space, and hotspots of infection. In addition, these methods may relate to the design, planning, and distribution of international health resources for treatment, control and prevention facilities and may help mitigate the impact of interference [20][21][22][23]. This study aimed to investigate the dynamics of the trend to predict the spread of diseases with the help of GIS software and spatial patterns of RT-PCR positive SARS-CoV-2 infected people at the provincial level in Nepal from 23rd January to 13th July, 2020.…”