Bayesian spatial modeling of transfusion-dependent β-thalassemia incidence rate in Fars Province, Southern Iran. (February 2021)
- Record Type:
- Journal Article
- Title:
- Bayesian spatial modeling of transfusion-dependent β-thalassemia incidence rate in Fars Province, Southern Iran. (February 2021)
- Main Title:
- Bayesian spatial modeling of transfusion-dependent β-thalassemia incidence rate in Fars Province, Southern Iran
- Authors:
- Haghpanah, Sezaneh
Asmarian, Naeimehossadat
Zekavat, Omid Reza
Bordbar, Mohammadreza
Karimi, Mehran
Zareifar, Soheila
Ramzi, Mani
Safaei, Sanaz - Abstract:
- Highlights: Iran is one of the most affected region by β-thalassemia worldwide. β-thalassemia is a chronic disorder with the requirement to lifelong supports. Accurate disease distribution can be an essential prerequisite in the regional health system resources allocation. In this study, disease mapping of β-thalassemia was demonstrated in Fars Province by spatial analysis. The relative risk of transfusion-dependent β-thalassemia in different counties was determined. Abstract: 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 systemHighlights: Iran is one of the most affected region by β-thalassemia worldwide. β-thalassemia is a chronic disorder with the requirement to lifelong supports. Accurate disease distribution can be an essential prerequisite in the regional health system resources allocation. In this study, disease mapping of β-thalassemia was demonstrated in Fars Province by spatial analysis. The relative risk of transfusion-dependent β-thalassemia in different counties was determined. Abstract: 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. … (more)
- Is Part Of:
- Spatial and spatio-temporal epidemiology. Volume 36(2021)
- Journal:
- Spatial and spatio-temporal epidemiology
- Issue:
- Volume 36(2021)
- Issue Display:
- Volume 36, Issue 2021 (2021)
- Year:
- 2021
- Volume:
- 36
- Issue:
- 2021
- Issue Sort Value:
- 2021-0036-2021-0000
- Page Start:
- Page End:
- Publication Date:
- 2021-02
- Subjects:
- β-thalassemia -- Anemia -- Transfusion -- Spatial Bayesian analysis -- Iran
Epidemiology -- Statistical methods -- Periodicals
Epidemiology -- Periodicals
614.4072 - Journal URLs:
- http://www.sciencedirect.com/science/journal/18775845/ ↗
http://www.sciencedirect.com/ ↗ - DOI:
- 10.1016/j.sste.2020.100389 ↗
- Languages:
- English
- ISSNs:
- 1877-5845
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - BLDSS-3PM
British Library HMNTS - ELD Digital store - Ingest File:
- 15534.xml