Bayesian spatial modeling of transfusion-dependent β-thalassemia incidence rate in Fars Province, Southern Iran.

Background: Using maps and spatial analysis are technologies to evaluate the magnitude and spatial distribution of disease in epidemiology investigations. We aimed to conduct a Bayesian spatial analysis on epidemiologic data of transfusion-dependent β-thalassemia (TDT) patients.
Methods: In this cross-sectional study, data of all TDT patients diagnosed during 1955-2018 in all counties of Fars Province were obtained from data registry of the Organization of Special Diseases of Shiraz University of Medical Sciences in Shiraz, Fars Province, Iran. Besag, York, and Mollie's (BYM) model was used for mapping.
Results: The estimated relative risk ranged from 0.23 to 1.66 for TDT patients. The highest and lowest relative risks of TDT were observed in Larestan located in Southern and Abadeh in Northern Fars Province respectively.
Conclusions: Determining the accurate geographical distribution of a chronic disease such as β-thalassemia can be an essential prerequisite in allocation of regional health system resources.
Competing Interests: Declaration of Competing Interest The authors declare no conflict of interest.
(Copyright © 2020. Published by Elsevier Ltd.)