Integration of Different Epidemiologic Perspectives and Applications to Spatial Epidemiology

2016 ◽  
pp. 21-56
Keyword(s):  
Spatial Epidemiology

The development of spatial epidemiology

2016 ◽  
Vol 19 ◽  
pp. 100-102 ◽  
Author(s):  
Dawei Zhao ◽  
Zhenghong Deng ◽  
Lianhai Wang
Keyword(s):  
Spatial Epidemiology

scholarly journals Spatial epidemiology of hospital-diagnosed brucellosis in Kampala, Uganda

2011 ◽  
Vol 10 (1) ◽  
pp. 52 ◽  
Author(s):  
Kohei Makita ◽  
Eric M Fèvre ◽  
Charles Waiswa ◽  
Winyi Kaboyo ◽  
Mark C Eisler ◽  
...  
Keyword(s):  
Spatial Epidemiology

scholarly journals The spatial epidemiology of alcohol-related mortality among the Czech adult population

2020 ◽  
Vol 30 (Supplement_5) ◽  
Author(s):  
L Kazmer ◽  
I Kulhanova ◽  
M Lustigova
Keyword(s):  
Local Community ◽  
Spatial Epidemiology ◽  
Adult Population ◽  
Age Groups ◽  
Health Determinants ◽  
Mortality Data ◽  
Annual Data ◽  
Cross Sectional ◽  
Inequalities In Health ◽  
Related Mortality

Abstract Background In Czechia, alcohol-induced deaths account for a significant portion of preventable mortality. As inequalities in health are both socially and spatially determined, the paper aims at the detailed examination of socio-geographic inequalities of this phenomenon. Methods The 2011-2015 annual data on both ICD-10 cause-specific deaths (K70; F10; X45/64; Y15) and mid-year population were obtained from the official Czech registries - the data were cross-classified by gender, 5-year age-groups, and permanent residence (N = 6,302 small area spatial units). The selected socio-demographic indicators (education, unemployment, religious population) from the Czech 2011 Census were spatially merged to the mortality dataset. From the data on education and unemployment, composite deprivation index (DI) was derived. In the adult population aged 25+, the age-standardised mortality ratios (SMR) were computed for each of the spatial units, separately by genders. The SMRs were spatially modelled by the Besag-York-Mollié (BYM) autoregressive approach, applying a fully bayesian framework integrated within the INLA R-package. The study applied cross-sectional design and employed ecological regression conducted on observational data. Results Compared to the Czech average, the highest SMRs were located in the historical regions of Moravia [SMR=1.15; 95%CI: 1.11-1.19] and Silesia [SMR=1.59; 95%CI: 1.52-1.66]. The SMRs were significantly correlated with DI among males [Rel.Risk=1.15; 95%CI: 1.11-1.19], and with religiousness rate among females [Rel.Risk=0.83; 95%CI: 0.77-0.90]. Conclusions Significant socio-geographic inequalities were detected, particularly with respect to the Czech historical regions. Among males, higher mortality was associated with a structural deprivation. Among females, protective effect of religiousness rate was found to be significant. The results highlight an importance of both socially and spatially integrated efforts for public health promotion. Key messages The inequalities in health are both socially and spatially contextualised. The paper presents robust empirical evidence in favour of the proposition, as examined on alcohol-related mortality data. The health determinants may be gender sensitive. Males might be more responsive to a structural disadvantage. Among females, cultural factors related to a local community might be more relevant.

scholarly journals A Spatial Analysis of Tuberculosis Related Mortality in South Africa

2021 ◽  
Vol 18 (22) ◽  
pp. 11865
Author(s):  
Dan Kibuuka ◽  
Charles Mpofu ◽  
Penny Neave ◽  
Samuel Manda
Keyword(s):  
Public Health ◽  
South Africa ◽  
Mortality Rate ◽  
Spatial Epidemiology ◽  
Hot Spot ◽  
Mortality Rates ◽  
Cold Spot ◽  
The South ◽  
Female Population ◽  
Death Rates

Background: South Africa, with an estimated annual tuberculosis (TB) incidence of 360,000 cases in 2019, remains one of the countries with the largest burden of TB in the world. The identification of highly burdened TB areas could support public health policy planners to optimally target resources and TB control and prevention interventions. Objective: To investigate the spatial epidemiology and distribution of TB mortality in South Africa in 2010 and its association with area-level poverty and HIV burden. Methods: The study analysed a total of 776,176 TB deaths for the period 2005–2015. Local and global and spatial clustering of TB death rates were investigated by Global and Local Moran’s Indices methods (Moran’s I). The spatial regression analysis was employed to assess the effect of poverty and HIV on TB mortality rates. Results: There was a significant decrease in TB mortality rate, from 179 per 100,000 population in 2005 to 60 per 100,000 population in 2015. The annual TB mortality rate was higher among males (161.5 per 100,000 male population; (95% confidence interval (CI) 132.9, 190.0) than among females (123.2 per 100,000 female population; (95% CI 95.6, 150.8)). The 35–44 age group experienced higher TB mortality rates, regardless of gender and time. Hot spot clusters of TB mortality were found in the South-Eastern parts of the country, whereas cold spot clusters were largely in the north-eastern parts. Tuberculosis death rates were positively associated with poverty, as measured by the South African Multidimension Poverty Index (SAMPI) as well TB death rates in the neighbouring districts. Conclusion: The findings of this study revealed a statistically significant decrease in TB deaths and a disproportionate distribution of TB deaths among certain areas and population groups in South Africa. The existence of the identified inequalities in the burden of TB deaths calls for targeted public health interventions, policies, and resources to be directed towards the most vulnerable populations in South Africa.

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