Vendramini Silvia Helena Figueiredo, Santos Natália Sperli Geraldes Marin Dos, Santos Maria de Lourdes Sperli Geraldes, Chiaravalloti-Neto Francisco, Ponce Maria Amélia Zanon, Gazetta Claudia Eli, Villa Tereza Cristina Scatena, Netto Antonio Ruffino
Departamento de Enfermagem em Saúde Coletiva e Orientação Profissional, Faculdade de Medicina de São José do Rio Preto, São José do Rio Preto, SP.
Rev Soc Bras Med Trop. 2010 Sep-Oct;43(5):536-41. doi: 10.1590/s0037-86822010000500013.
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.
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.
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.
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.
对1998年至2006年里约普雷图河畔圣若泽市结核病/艾滋病病毒合并感染分布情况进行了空间分析，并将其与社会经济指标相关联。
对新的结核病/艾滋病病毒合并感染病例进行地理定位，并计算各空间单元的发病率系数。使用莫兰指数评估发病率的空间关联。多元回归选择最能解释发病率空间关联的变量。利用空间关联局部指标识别显著的空间聚类。
莫兰指数为0.0635（p = 0.0000），表明存在发病率关联。最能解释发病率空间关联的变量是受教育年限达三年的家庭户主百分比。结核病/艾滋病病毒合并感染发病率系数的局部空间关联聚类图显示，该市北部地区发病率高，南部和西部地区发病率低。
该研究阐明了结核病/艾滋病病毒合并感染的空间地理分布，并确定了其与社会经济变量之间的关联，从而为定向规划提供数据，优先关注该病发病率较高的社会弱势群体地区。
