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June 25, 2026PLoS ONEOpen Access

Correction: Bayesian hierarchical modeling of joint spatiotemporal risk patterns for Human Immunodeficiency Virus (HIV) and Tuberculosis (TB) in Kenya

Verrah A. Otiende Thomas N. Achia Henry G. Mwambi

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Key Points

This article aims to correct previous findings on the joint spatiotemporal risk patterns for HIV and TB in Kenya.
Utilized Bayesian hierarchical modeling techniques to analyze spatiotemporal data
Focused on data related to human immunodeficiency virus (HIV) and tuberculosis (TB)
Analyzed the patterns of risk across different geographic and temporal scales.
Clarification of the joint risk patterns for HIV and TB in the specified region
Validation of the Bayesian modeling approach utilized in the analysis.

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Implication

Correction highlights joint spatiotemporal risk patterns for HIV and TB in Kenya using Bayesian modeling.

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Cite This Study

Otiende et al. (2026) studied this question.

synapsesocial.com/papers/6a40b8ed61bb0a67205c56c0 https://doi.org/10.1371/journal.pone.0352668

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Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context:

1Empirical Validation of an Adaptive Spatial Hierarchical Bayesian SEIR Model for HIV Transmission Dynamics in KenyaOriginal Research · 2026
2Bayesian Hierarchical Model Assessment in Public Health Surveillance Systems within Kenya: A Methodological ReviewReview · 2003
3Application of a joint multivariate probit model for mixed outcomes of CD4 cell count and tuberculosis using a Bayesian latent variable approach in KwaZulu-Natal2025 · 3 citations
4Spatial modelling of the relative risk of HIV/AIDS and associated risk factors in South Africa using integrated nested Laplace approximationsOriginal Research · 2026
5Bayesian Hierarchical Model in Public Health Surveillance Systems: Methodological Evaluation in KenyaOriginal Research · 2015

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