Bayesian Modelling of Tuberculosis Risk Factors in South Africa 2014

Abstract

Background: Although the number of deaths has declined since 2007, Tuberculosis (TB) continues to be the number one cause of death in South Africa. To create a country free of TB, there is need for continued research to explore models that will provide the Department of Health with new interventions.Aim: This study was aimed at identifying the risk factors of active self-reported TB prevalence for South Africa in 2014. Methods:The Frequentist Logistic Regression (FLR) approach was applied on a sample of 19213 individuals taken from the National Income Dynamics Survey (NIDS) wave data. Bayesian analysis with non-informative priors were used to model Wave 1 to 3 data and elicitation of the obtained posterior density parameters by averaging done to obtain the informative priors used to model wave 4. The wave 4 results obtained under the two estimation approaches were compared as well as the results for non-informative and informative priors. Results:The findings show that self-reported TB prevalence is higher than the reported 1%, Human Immuno Deficiency Virus (HIV) remains a major threat to TB and Eastern Cape is the province mostly affected by TB with Limpopo recording the least prevalence. Poor living conditions and lower socio-economic conditions continue to be drivers of TB whilst English illiteracy, lack of Secondary/Tertiary education, alcohol consumption, marital status, gender and age groups also influence TB progression to disease. FLR yielded similar results to Bayesian with non-informative priors whilst the results are more precise for informative priors. Conclusion:This study identified individuals and communities at risk of developing active TB disease in South Africa.

A Multilevel Analysis of the Associated and Determining Factors of TB among Adults in South Africa: Results from National Income Dynamics Surveys 2008 to 2017

“…Our overall findings revealed that the significant variables associated with TB were marital status, age, gender, race, unemployment, suffering from other diseases, regular exercise, regular smoking consult about health, diagnosis with asthma, diabetes, housing, household income, and geotype. This research conforms with previous findings that report unemployment [ 5 ] and poor living conditions [ 7 , 8 , 9 ] as the risk factors for TB. We did not take households as a level, but households with income above the median were more at risk of being diagnosed with TB.…”

“…In this regard, ref [ 11 ] used transmission models to determine if these targets were reachable in a bid to eradicate TB in South Africa. They also concur with refs [ 7 , 12 ] that eradicating this disease will only occur if other interventions apart from treatment are implemented. Therefore, it is vital to include social, economic, and environmental determinants of TB in the strategy to stop TB deaths and new infections.…”

“…Therefore, although some households have income and expenditure above median, they could still be living under poor economic conditions where TB is rife. Smoking is a known risk factor for TB infection [ 7 , 27 ].…”

“…[ 6 ] on identifying risk factors of TB/HIV in South Africa, 2006 reported those married or have surviving partners to be at lower risk of TB/HIV. A National study [ 7 ] said that Eastern Cape Province is the hardest hit by TB and Limpopo province the least. They also listed poor living conditions, lower socio-economic status, English illiteracy, lack of Secondary/Tertiary education, alcohol consumption, marital status, age groups, and gender as drivers of TB.…”

Tuberculosis risk factors in South Africa, 2008 to 2017: A Generalised Estimating Equations approach

“…The number one global strategy to eradicate TB starts with early diagnosis and effective treatment [1,3]. However, research has shown that there is a need for social interventions [14,17] yet there have been few analyses of the social determinants of tuberculosis, particularly in high-burden settings. We conducted a multilevel analysis of self-reported tuberculosis disease in a nationally representative sample of South Africans based on the 1998 Demographic and Health Survey (DHS.…”