Spatial autocorrelation analysis of health care hotspots in Taiwan in 2006

Abstract

BackgroundSpatial analytical techniques and models are often used in epidemiology to identify spatial anomalies (hotspots) in disease regions. These analytical approaches can be used to not only identify the location of such hotspots, but also their spatial patterns.MethodsIn this study, we utilize spatial autocorrelation methodologies, including Global Moran's I and Local Getis-Ord statistics, to describe and map spatial clusters, and areas in which these are situated, for the 20 leading causes of death in Taiwan. In addition, we use the fit to a logistic regression model to test the characteristics of similarity and dissimilarity by gender.ResultsGender is compared in efforts to formulate the common spatial risk. The mean found by local spatial autocorrelation analysis is utilized to identify spatial cluster patterns. There is naturally great interest in discovering the relationship between the leading causes of death and well-documented spatial risk factors. For example, in Taiwan, we found the geographical distribution of clusters where there is a prevalence of tuberculosis to closely correspond to the location of aboriginal townships.ConclusionsCluster mapping helps to clarify issues such as the spatial aspects of both internal and external correlations for leading health care events. This is of great aid in assessing spatial risk factors, which in turn facilitates the planning of the most advantageous types of health care policies and implementation of effective health care services.

Understanding wetlands reclamation and soil-transmitted helminths and schistosomiasis incidence patterns in Rwanda (2001-2012)

“…In East African countries people living in rural areas are commonly infected with STH . In Rwanda, after malaria, schistosomiasis and STHs are a significant public health problem (TRAC+, 2008), as illustrated in Figure 4. Rwandan wetlands are rapidly converted from natural reserves with rich biodiversity to agricultural wetlands due to population pressure, which has increased demand for food production.…”

“…More than 75% of children are infected with intestinal worms (TRAC+, 2008). Children heavily infected are often physically and intellectually compromised by anemia, leading to attention deficits, learning disabilities, school absenteeism, and higher dropout rates.…”

“…Detection and visualization of the spatial pattern of S. mansoni Appropriate spatial and statistical approaches for detecting spatial clustering and relationships with risk factors are provided by current advances in spatial epidemiology (Osei, 2014;Tsai, Lin, Chu, & Perng, 2009). …”

“…The Local Gi*(d) statistic is useful for identifying individual members of local clusters by determining the spatial dependence and neighbouring observations (Tsai et al, 2009;Wu et al, 2004). It can be written as follows:…”

“…The burden of STH infections is well known in Rwanda. After malaria, STH represent the most important parasitic diseases in terms of public health and economic impact (TRAC+, 2008 (Ruxin & Negin, 2012).…”