Spatial and non-spatial determinants of successful tuberculosis treatment outcomes: An implication of Geographical Information Systems in health policy-making in a developing country

Abstract

This retrospective study aimed to address whether or to what extent spatial and non-spatial factors with a focus on a healthcare delivery system would influence successful tuberculosis (TB) treatment outcomes in Urmia, Iran. In this cross-sectional study, data of 452 new TB cases were extracted from Urmia TB Management Center during a 5-year period. Using the Geographical Information System (GIS), health centers and study subjects' locations were geocoded on digital maps. To identify the statistically significant geographical clusters, Average Nearest Neighbor (ANN) index was used. Logistic regression analysis was employed to determine the association of spatial and non-spatial variables on the occurrence of adverse treatment outcomes. The spatial clusters of TB cases were concentrated in older, impoverished and outskirts areas. Although there was a tendency toward higher odds of adverse treatment outcomes among urban TB cases, this finding after adjusting for distance from a given TB healthcare center did not reach statistically significant. This article highlights effects of spatial and non-spatial determinants on the TB adverse treatment outcomes, particularly in what way the policies of healthcare services are made. Accordingly, non-spatial determinants in terms of low socio-economic factors need more attention by public health policy makers, and then more focus should be placed on the health delivery system, in particular men's health.

Analysis on spatial-temporal distribution characteristics of smear positive pulmonary tuberculosis in China, 2004–2015

“…Previous studies have demonstrated that the characteristics of pulmonary tuberculosis (PTB)exist an obvious spatial-temporal heterogeneity at the national level or the provincial level (Tweya et al, 2013;Ribeiro et al, 2015;Kolifarhood et al, 2015;Hassarangsee et al, 2015), and it is believed that a better understanding of the patterns on spatial-temporal heterogeneity of smear positive PTB are important to formulate effective national prevention and control strategies, and allocate the limited health resources of national TB program (NTP) (Areias et al, 2015;Wubuli et al, 2015). As the most infectious form of TB and the main source of infection, prolonged exposure to smear positive PTB patient are highly susceptible to infect with TB, meanwhile, the longer, the more dangerous (Chen et al, 2016;Shi et al, 2013).…”

Road safety data collection systems in Iran: A comparison based on relevant organizations

“…36 A system approach also is needed by more focus on information about speed management to develop both activities and surveillance system. 37 , 38 …”

Spatial data analysis and the use of maps in scientific health articles

“…Among these techniques, it is worth highlighting: remote mapping, data digitization, automation of mapping work, the Global Positioning System (GPS) and Geographic Information Systems (GIS). 6,[21][22][23] In recent decades, with increased access to computers, the storage and processing of data has been streamlined, facilitating the dissemination and realization of works with spatial reference or georeferenced information. Even so, in the case of Brazil, only municipalities that have invested heavily in the construction of GISs have managed to develop them in a satisfactory and detailed manner.…”