Prevalence of latent tuberculosis infection in persons with and without human immunodeficiency virus infection using two interferon-gamma release assays and tuberculin skin test in a low human immunodeficiency virus prevalence, intermediate tuberculosis-burden country

Lin, Wei; Lin, Hsi Hsun; Lee, Susan Shin Jung; Sy, Cheng Len; Wu, Kang; Chen, Jui Kuang; Tsai, Hung Chin; Chen, Yao Shen

doi:10.1016/j.jmii.2014.08.010

Cited by 19 publications

(28 citation statements)

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“…The prevalence of LTBI recorded in South Omo pastoral communities was higher than that documented by a previous study conducted on Addis Ababa University male students in Ethiopia [ 23 ] and lower than a study conducted on Afar pastoral communities in Ethiopia [ 12 ]. The prevalence was higher than those documented in surveys of village doctors in China [ 24 ], people living in border areas in Nuevo Leon and Tamaulipasin Mexico [ 25 ], individuals attending health care centers in Southern Taiwan [ 26 ], a population living in Danyang County, Jiangsu Province inChina [ 27 ] and immigrants in the USA [ 28 ]. Moreover, the estimated prevalence of LTBI in South Omo was higher than the estimated 23% worldwide prevalence of LTBI [ 29 ].…”

Section: Discussionmentioning

confidence: 99%

Latent tuberculosis infection and associated risk indicators in pastoral communities in southern Ethiopia: a community based cross-sectional study

et al. 2018

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BackgroundResearch pertaining to the community-based prevalence of latent tuberculosis infection (LTBI) is important to understand the magnitude of this infection. This study was conducted to estimate LTBI prevalence and to identify associated risk factors in the Omo Zone of Southern Ethiopia.MethodsA community-based cross-sectional study was conducted in six South Omo districts from May 2015 to February 2016. The sample size was allocated to the study districts proportional to their population sizes. Participants were selected using a multi-stage sampling approach. A total of 497 adult pastoralists were recruited. Blood samples were collected from the study participants and screened for LTBI using a U.S. Food and Drug Administration approved interferon-gamma release assay (IGRA). Logistic regression was used to model the likelihood of LTBI occurrence and to identify risk factors associated with LTBI.ResultsThe prevalence of LTBI was 50.5% (95% CI: 46%, 55%) with no significant gender difference (49.8% among males versus 51.2% among females; Chi-square (χ2) = 0.10; P = 0.41) and marginally non-significant increasing trends with age (44.6% among those below 24 years and 59.7% in the age range of 45-64 years; χ2 = 6.91; P = 0.075). Being residence of the Dasanech District (adjusted odds ratio, AOR = 2.62, 95% CI: 1.30, 5.28; P = 0.007) and having a habit of eating raw meat (AOR = 2.89, 95% CI: 1.09, 7.66; P = 0.033) were significantly associated with an increased odds of being positive for LTBI. A large family size (size of 5 to 10) has significant protective effect against associated a reduced odds of being positive for LTBI compared to a family size of below 5 (AOR = 0.65, 95% CI: 0.42, 0.99; P = 0.045).ConclusionsA high prevalence of LTBI in the South Omo Zone raises the concern that elimination of TB in the pastoral communities of the region might be difficult. Screening for and testing individuals infected with TB, independent of symptoms, may be an effective way to minimize the risk of disease spread.

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Section: Discussionmentioning

confidence: 99%

Latent tuberculosis infection and associated risk indicators in pastoral communities in southern Ethiopia: a community based cross-sectional study

et al. 2018

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“…Globally, sub-Saharan Africa accounts for the largest percentage of the dual epidemic with co-morbidity from TB-HIV remaining a critical public health challenge [14]. In essence, more people die from TB than HIV associated infections [17]. In 2016 alone, the SSA region accounted for an estimated 86% of HIV-linked TB deaths [18].…”

Section: Introductionmentioning

confidence: 99%

Bayesian modeling of spatiotemporal patterns of TB-HIV co-infection risk in Kenya

Otiende¹,

Achia

Mwambi

2019

BMC Infect Dis

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BackgroundTuberculosis (TB) and Human Immunodeficiency Virus (HIV) diseases are globally acknowledged as a public health challenge that exhibits adverse bidirectional relations due to the co-epidemic overlap. To understand the co-infection burden we used the case notification data to generate spatiotemporal maps that described the distribution and exposure hypotheses for further epidemiologic investigations in areas with unusual case notification levels.MethodsWe analyzed the TB and TB-HIV case notification data from the Kenya national TB control program aggregated for forty-seven counties over a seven-year period (2012–2018). Using spatiotemporal poisson regression models within the Integrated Nested Laplace Approach (INLA) paradygm, we modeled the risk of TB-HIV co-infection. Six competing models with varying space-time formulations were compared to determine the best fit model. We then assessed the geographic patterns and temporal trends of coinfection risk by mapping the posterior marginal from the best fit model.ResultsOf the total 608,312 TB case notifications, 194,129 were HIV co-infected. The proportion of TB-HIV co-infection was higher in females (39.7%) than in males (27.0%). A significant share of the co-infection was among adults aged 35 to 44 years (46.7%) and 45 to 54 years (42.1%). Based on the Bayesian Defiance Information (DIC) and the effective number of parameters (pD) comparisons, the spatiotemporal model allowing space-time interaction was the best in explaining the geographical variations in TB-HIV coinfection. The model results suggested that the risk of TB-HIV coinfection was influenced by infrastructure index (Relative risk (RR) = 5.75, Credible Interval (Cr.I) = (1.65, 19.89)) and gender ratio (RR = 5.81e−04, Cr. I = (1.06e−04, 3.18e−03). The lowest and highest temporal relative risks were in the years 2016 at 0.9 and 2012 at 1.07 respectively. The spatial pattern presented an increased co-infection risk in a number of counties. For the spatiotemporal interaction, only a few counties had a relative risk greater than 1 that varied in different years.ConclusionsWe identified elevated risk areas for TB/HIV co-infection and fluctuating temporal trends which could be because of improved TB case detection or surveillance bias caused by spatial heterogeneity in the co-infection dynamics. Focused interventions and continuous TB-HIV surveillance will ensure adequate resource allocation and significant reduction of HIV burden amongst TB patients.

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“…Globally, sub-Saharan Africa accounts for the largest percentage of the dual epidemic with co-morbidity from TB-HIV remaining a critical public health challenge (14). In essence, more people die from TB than HIV associated infections (17). In 2016 alone, the SSA region accounted for an estimated 86% of HIVlinked TB deaths (18).…”

Section: Introductionmentioning

confidence: 99%

Bayesian Modeling of Spatiotemporal patterns of TB-HIV co-infection risk in Kenya

Otiende

Achia

Mwambi

2019

Preprint

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Background Tuberculosis (TB) and Human Immunodeficiency Virus (HIV) diseases are globally acknowledged as a public health challenge that exhibits adverse bidirectional relations due to the co-epidemic overlap. To understand the co-infection burden we used the case notification data to generate spatiotemporal maps that described the distribution and exposure hypotheses for further epidemiologic investigations in areas with unusual case notification levels. Methods We analyzed the TB and TB-HIV case notification data from the Kenya national TB control program aggregated for forty-seven counties over a seven-year period (2012 – 2018). Using the Integrated Nested Laplace Approach (INLA), we modeled the risk of TB-HIV co-infection. Six competing models with varying space-time formulations were compared to determine the best fit model. We then assessed the geographic patterns and temporal trends of coinfection risk by mapping the posterior marginal from the best fit model. Results Of the total 608312 TB case notifications, 194129 were HIV co-infected. The proportion of TB-HIV co-infection was higher in females (39.7%) than in males (27.0%). A significant share of the co-infection was among adults aged 35 to 44 years (46.7%) and 45 to 54 years (42.1%). Based on the Bayesian Defiance Information (DIC) and the effective number of parameters comparisons, the spatiotemporal model 3b was the best in explaining the geographical variations in TB-HIV coinfection. The model results suggested that the risk of TB-HIV coinfection was influenced by infrastructure index (Relative risk (RR)=5.75, Credible Interval (Cr.I) = (1.65, 19.89)) and gender ratio . The lowest and highest temporal relative risks were in the years 2016 at 0.9 and 2012 at 1.07 respectively. The spatial pattern presented an increased co-infection risk in a number of counties. For the spatiotemporal interaction, only a few counties had a relative risk greater than 1 that varied in different years. Conclusions We identified elevated risk areas for TB/HIV co-infection and fluctuating temporal trends which could be because of improved TB case detection or surveillance bias caused by spatial heterogeneity in the co-infection dynamics. Focused interventions and continuous TB-HIV surveillance will ensure adequate resource allocation and significant reduction of HIV burden amongst TB patients

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Prevalence of latent tuberculosis infection in persons with and without human immunodeficiency virus infection using two interferon-gamma release assays and tuberculin skin test in a low human immunodeficiency virus prevalence, intermediate tuberculosis-burden country

Abstract: HIV-infected persons had a significantly lower response to both IGRAs and TST. High discordance was found between the two generations of IGRAs and between IGRAs and TST. Increasing age, a known risk factor for LTBI, was significantly associated with IGRAs, but not with TST.

Cited by 19 publications

References 28 publications

Latent tuberculosis infection and associated risk indicators in pastoral communities in southern Ethiopia: a community based cross-sectional study

Latent tuberculosis infection and associated risk indicators in pastoral communities in southern Ethiopia: a community based cross-sectional study

Bayesian modeling of spatiotemporal patterns of TB-HIV co-infection risk in Kenya

Bayesian Modeling of Spatiotemporal patterns of TB-HIV co-infection risk in Kenya

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