Issues in the Current Practices of Spatial Cluster Detection and Exploring Alternative Methods

A Spatial Autocorrelation Method for Taenia solium Risk Mapping: The Case of Lao PDR

BACKGROUND

The World Health Organization has identified Taenia solium mapping tools as an important development for intensifying control in hyperendemic areas. Taenia solium has also been identified as a priority by the Lao PDR government. There is a limited understanding of the distribution of T. solium due to inherent diagnostic challenges.

METHOD

Global and local autocorrelation statistics were applied to available risk factor data sourced from national censuses to map the risk of Taenia solium in Lao PDR.

RESULTS

Approximately 50% of villages could be considered hot spots for one or more risk factors. Different risk factor hot spots co-occurred in 30% of villages. Twenty per cent of villages were classified as hot spots for the proportion of households owning pigs and another risk factor. Northern Lao PDR was the dominant high-risk area. This is consistent with passive reports, limited surveys, and anecdotal reports. One smaller area in southern Lao PDR was also identified as high-risk. This is of particular interest because T. solium has not previously been investigated in this area.

CONCLUSIONS

The methods applied provide a simple, rapid, and versatile approach that allows endemic countries to begin mapping the risk of T. solium at a sub-national level.

Prediction of the Old-Age Dependency Ratio in Chinese Cities Using DMSP/OLS Nighttime Light Data

The old-age dependency ratio (ODR) is an important indicator reflecting the degree of a regional population’s aging. In the context of aging, this study provides a timely and effective method for predicting the ODR in Chinese cities. Using the provincial ODR from the Seventh National Population Census and Defense Meteorological Satellite Program/Operational Linescan System (DMSP/OLS) nighttime light data, this study aims to predict and analyze the spatial correlation of the municipal ODR in Chinese cities. First, the prediction model of the ODR was established with curve regression. Second, the spatial structure of the municipal ODR was investigated using the Moran’s I method. The experimental results show the following: (1) the correlation between the sum of the nighttime light and ODR is greater than the mean of nighttime light in the study areas; (2) the Sigmoid model fits better than other regression models using the provincial ODR in the past ten years; and (3) there exists an obvious spatial agglomeration and dependence on the municipal ODR. The findings indicate that it is reasonable to use nighttime light data to predict the municipal ODR in large and medium-sized cities. Our approach can provide support for future regional censuses and spatial simulations.