Day: November 23, 2010

Spatial Analysis of Tuberculosis/HIV Coinfection: Its Relation with Socioeconomic Levels in a City in South-eastern Brazil

/ Matt Artz / 1 Comment

Revista da Sociedade Brasileira de Medicina Tropical, 2010 Oct;43(5):536-541.

Vendramini SH, Santos NS, Santos MD, Chiaravalloti-Neto F, Ponce MA, Gazetta CE, Villa TC, Ruffino Netto A.

“INTRODUCTION: Spatial analysis of the distribution of tuberculosis/HIV coinfection was performed and associated with socioeconomic indicators in São José do Rio Preto, from 1998 to 2006.

“METHODS: New TB/HIV coinfection cases were georeferenced and incidence coefficients were calculated for spatial units. Moran’s index was used to evaluate spatial associations of incidences. Multiple regressions selected variables that could best explain the spatial association of incidences. The local indicator of spatial association was used to identify significant spatial groupings.

“RESULTS: Moran’s index was 0.0635 (p=0.0000) indicating that the incidence association occurred. The variable that best explained the spatial association of incidence was the percentage of heads of families with up to three years of education. The LISA cluster map for TB/HIV coinfection incidence coefficients showed groups with high incidence rates in the North and low incidence in the South and West regions of the municipality.

“CONCLUSIONS: The study elucidated the spatial geographic distribution of TB/HIV coinfection and determined its association with socioeconomic variables, thus providing data for oriented planning, prioritizing socially disadvantaged regions that present a higher incidence of the disease.”

Varying the Variable: Presenting Different Cases for Visualizing the Relative Attractiveness of Retail Business Centers in New Britain, Connecticut

/ Matt Artz / 1 Comment

International Journal of Applied Geospatial Research, Vol. 1, Issue 4, 2010

Zachary Klaas

“It is common practice in business geography to use gravity models such as the Reilly’s Retail Law of Gravitation model to gauge the extent of presumed trade areas for retail sites based on a variable that models the general demographic attractiveness of the site in question. In the Huff retail model, an exponent represents additional attractiveness factors that differentially affect certain sites; however, it is less common practice to vary the attractiveness of one site alone and to visually inspect in a series of maps the differences in other trade areas given the variation of assumptions about the attractiveness of that site. The idea behind this form of analysis is that business managers benefit from being able to visualize a range of possible contingencies to which they may have to respond. The city of New Britain, Connecticut, is used as a demonstration model in this article to provide these kinds of visualization maps.”