Joint spatiotemporal modelling of tuberculosis and human immunodeficiency virus in Ethiopia using a Bayesian hierarchical approach
Abstract Background The aim of this paper was to evaluate the distribution of HIV and TB in Ethiopia during four years (2015-2018) at the district level, considering both spatial and temporal patterns. Methods Consolidated data on the count of TB case notifications and the number of patients with HI...
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2025-01-01
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| author | Legesse Kassa Debusho Leta Lencha Gemechu |
| author_facet | Legesse Kassa Debusho Leta Lencha Gemechu |
| author_sort | Legesse Kassa Debusho |
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| description | Abstract Background The aim of this paper was to evaluate the distribution of HIV and TB in Ethiopia during four years (2015-2018) at the district level, considering both spatial and temporal patterns. Methods Consolidated data on the count of TB case notifications and the number of patients with HIV for four years, 2015-2018, were provided by the Ethiopian Federal Ministry of Health. The data was analyzed using the Bayesian hierarchical approach, employing joint spatiotemporal modelling. The integrated nested Laplace approximation available in the R-INLA package was used to fit six models, each with different priors, for the precision parameters of the random effects variances. The best-fitting model with the best predictive capacity was selected using the Deviance Information Criterion and the negative sum of cross-validatory predictive log-likelihood. Results According to the findings of the selected model, about 53% of the variability in TB and HIV incidences in the study period was explained by the shared temporal component, disease-specific spatial effect of HIV, and space-time interaction effect. The shared temporal trend and disease-specific temporal trend of HIV risk showed a slight upward trend between 2015 and 2017, followed by a slight decrease in 2018. However, the disease-specific temporal trend of TB risk had almost constant trend with minimal variation over the study period. The distribution of the shared relative risks was similar to the distribution of disease-specific TB relative risk, whereas that of HIV had more districts as high-risk areas. Conclusions The study showed the spatial similarity in the distribution of HIV and TB case notifications in specific districts within various provinces. Moreover, the shared relative risks exhibit a temporal pattern and spatial distribution that closely resemble those of the relative risks specific to HIV illness. The existence of districts with shared relative risks implies the need for collaborative surveillance of HIV and TB, as well as integrated interventions to control the two diseases jointly. |
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| institution | Kabale University |
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| spelling | doaj-art-8b090638f4e4494fafc1a24fbab87d1b2025-02-02T12:45:38ZengBMCBMC Public Health1471-24582025-01-0125111610.1186/s12889-024-20996-7Joint spatiotemporal modelling of tuberculosis and human immunodeficiency virus in Ethiopia using a Bayesian hierarchical approachLegesse Kassa Debusho0Leta Lencha Gemechu1Department of Statistics, University of South AfricaDepartment of Statistics, University of South AfricaAbstract Background The aim of this paper was to evaluate the distribution of HIV and TB in Ethiopia during four years (2015-2018) at the district level, considering both spatial and temporal patterns. Methods Consolidated data on the count of TB case notifications and the number of patients with HIV for four years, 2015-2018, were provided by the Ethiopian Federal Ministry of Health. The data was analyzed using the Bayesian hierarchical approach, employing joint spatiotemporal modelling. The integrated nested Laplace approximation available in the R-INLA package was used to fit six models, each with different priors, for the precision parameters of the random effects variances. The best-fitting model with the best predictive capacity was selected using the Deviance Information Criterion and the negative sum of cross-validatory predictive log-likelihood. Results According to the findings of the selected model, about 53% of the variability in TB and HIV incidences in the study period was explained by the shared temporal component, disease-specific spatial effect of HIV, and space-time interaction effect. The shared temporal trend and disease-specific temporal trend of HIV risk showed a slight upward trend between 2015 and 2017, followed by a slight decrease in 2018. However, the disease-specific temporal trend of TB risk had almost constant trend with minimal variation over the study period. The distribution of the shared relative risks was similar to the distribution of disease-specific TB relative risk, whereas that of HIV had more districts as high-risk areas. Conclusions The study showed the spatial similarity in the distribution of HIV and TB case notifications in specific districts within various provinces. Moreover, the shared relative risks exhibit a temporal pattern and spatial distribution that closely resemble those of the relative risks specific to HIV illness. The existence of districts with shared relative risks implies the need for collaborative surveillance of HIV and TB, as well as integrated interventions to control the two diseases jointly.https://doi.org/10.1186/s12889-024-20996-7Bayesian hierarchicalHIVPoisson regressionRelative riskJoint spatiotemporal modellingTuberculosis |
| spellingShingle | Legesse Kassa Debusho Leta Lencha Gemechu Joint spatiotemporal modelling of tuberculosis and human immunodeficiency virus in Ethiopia using a Bayesian hierarchical approach BMC Public Health Bayesian hierarchical HIV Poisson regression Relative risk Joint spatiotemporal modelling Tuberculosis |
| title | Joint spatiotemporal modelling of tuberculosis and human immunodeficiency virus in Ethiopia using a Bayesian hierarchical approach |
| title_full | Joint spatiotemporal modelling of tuberculosis and human immunodeficiency virus in Ethiopia using a Bayesian hierarchical approach |
| title_fullStr | Joint spatiotemporal modelling of tuberculosis and human immunodeficiency virus in Ethiopia using a Bayesian hierarchical approach |
| title_full_unstemmed | Joint spatiotemporal modelling of tuberculosis and human immunodeficiency virus in Ethiopia using a Bayesian hierarchical approach |
| title_short | Joint spatiotemporal modelling of tuberculosis and human immunodeficiency virus in Ethiopia using a Bayesian hierarchical approach |
| title_sort | joint spatiotemporal modelling of tuberculosis and human immunodeficiency virus in ethiopia using a bayesian hierarchical approach |
| topic | Bayesian hierarchical HIV Poisson regression Relative risk Joint spatiotemporal modelling Tuberculosis |
| url | https://doi.org/10.1186/s12889-024-20996-7 |
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