Spatial distribution and clusters of pancreatic cancer mortality in Shandong Province, China

A raster-based spatial clustering method with robustness to spatial outliers

Spatial clustering is an essential method for the comprehensive understanding of a region. Spatial clustering divides all spatial units into different clusters. The attributes of each cluster of the spatial units are similar, and simultaneously, they are as continuous as spatially possible. In spatial clustering, the handling of spatial outliers is important. It is necessary to improve spatial integration so that each cluster is connected as much as possible, while protecting spatial outliers can help avoid the excessive masking of attribute differences This paper proposes a new spatial clustering method for raster data robust to spatial outliers. The method employs a sliding window to scan the entire region to determine spatial outliers. Additionally, a mechanism based on the range and standard deviation of the spatial units in each window is designed to judge whether the spatial integration should be further improved or the spatial outliers should be protected. To demonstrate the usefulness of the proposed method, we applied it in two case study areas, namely, Changping District and Pinggu District in Beijing. The results show that the proposed method can retain the spatial outliers while ensuring that the clusters are roughly contiguous. This method can be used as a simple but powerful and easy-to-interpret alternative to existing geographical spatial clustering methods.

Epidemiological Characteristics of Pancreatic Cancer in China From 1990 to 2019

Background

Pancreatic cancer is an aggressive cancer and is predicted to become the second leading cause of cancer-related deaths in China. To understand the epidemic trend of pancreatic cancer and formulate targeted preventive measures, it is important to analyze the incidence and mortality of pancreatic cancer.

Methods

The incidence and mortality data of pancreatic cancer in China were obtained from Global Burden of Disease (GBD) data. We used joinpoint regression analysis to calculate the magnitude and direction of trends, and the age-period-cohort method to analyze the effects of chronological age, time period, and birth cohort.

Results

The age-standardized rates (ASRs) for both incidence and mortality of pancreatic cancer increased from 1990 to 2019, and were higher in males than females. The incidence and mortality rates have increased year by year in the age group above 25 years. The most common age group was 55–79 years, accounting for approximately 50% of all incident cases. In terms of incidence and mortality rates, the overall net drifts were above 0. The local drifts in all age groups were above 0 in both sexes and males, while the local drifts in the 15–39 age groups were below 0 in females. The longitudinal age curves increased with age, with higher incidence and mortality rates, mainly in older age groups. The period rate ratios increased by year. The cohort rate ratios showed an upward trend before 1970 and fluctuated after 1975.

Conclusions

The burden of pancreatic cancer is still very high in China, and attention should be paid to the key population that is, males and older people. The results of our study can be used by policy makers to allocate resources efficiently to improve early diagnosis and treatment, improving the awareness of self-protection, and advocating a healthy lifestyle to prevent pancreatic cancer.

Spatiotemporal Variability of Zoonotic Cutaneous Leishmaniasis Based on Sociodemographic Heterogeneity. The Case of Northeastern Iran, 2011-2016

Zoonotic cutaneous leishmaniasis (ZCL) is one of the most prevalent zoonoses in Iran, especially in central and northeastern Iran. This research aimed to examine whether there were spatiotemporal clusters of ZCL cases, and if so, whether there were differences in clustering according to age, sex, area of residence, and occupation. Spatial analysis, including global and local spatial autocorrelations, inverse distance weighting, and space-time scan statistics, were used to determine potential clusters in the villages of Golestan from 2011-2016. Several spatially significant (p < 0.05) clusters were observed in the north and northeastern regions, and most persisted until the last year of the study period. Children (0-10 years) living in rural settings were more likely to have an infection than those living in other areas. Although the disease was centered in the northern regions, housekeepers, females, and patients aged 21-30 and 41-50 years were found to be the high-risk groups in the southern areas. The seasonal pattern indicated that the outbreak mainly began in late summer, peaked in October, and diminished in December. By exploring spatiotemporal variations of ZCL by sociodemographic information, this study was able to identify priority areas for decision-makers in healthcare and resource allocation.