ABSTRACT
Objective To analyze the spatial point pattern distribution characteristics of hemorrhagic fever with renal syndrome (HFRS) in Jingzhou city, Hubei province during the two seasons spring- summer and autumn-winter of 2017, to discuss its high incidence area and reason, and to provide basis for the resource allocation of public health. Methods The analytical data was collected from Infectious Disease Reporting Information System in China, and the spring-summer season was from March to August of 2017, while the autumn-winter was from the September of 2017 to the February of 2018. The Ripley's K-function and kernel density estimation were applied to analyze the spatial point pattern distribution and compare the distribution characteristics of spatial point pattern between the two seasons. Results In 2017, 133 cases of HFRS were reported in Jingzhou city, including the spring- summer and autumn-winter two pick incidences. The strongest aggregation distance was 17.77km in spring-summer season, and 14.40 km in autumn-winter season. The spatial gathering center was located in the north of Jianli County in spring-summer, and it moved to the south of Jiangling County and Shashi District in autumn-winter. Conclusions The key areas for the prevention and control of HFRS in Jingzhou City are Jiangling County, the southern part of Shashi District and the northern part of jianli county. The key groups are the residents of the urban-rural junction in the southern part of Shashi City, residents along the route of large-scale projects, and farmers engaged in agricultural planting or crayfish breeding in the gathering areas.
ABSTRACT
Objective: To provide optimal decision making for military health service and to increase the speed for and efficiency for health service decision-making. Methods: The optimized decision-making was achieved based on the geographic information system, decision making support system and related decision-making model. Results: Every subsystem had the functions of searching, counting, and analysis. For example, the optimal decision-making function was achieved by selecting the shortest evacuation path. Conclusion: Each subsystem provides the health service commanding officers with the optimized decision-making scheme, which can be of great help in improving the quality and speed of military medical service commanding.
ABSTRACT
Objective To detect the spatial point pattern distribution rules of neural tube defects.Methods The kernel density estimation and Ripley's K-function were used to analyze the spatial point pattern of the neural tube birth defects in Heshun county in 1998-2001.Results The kernel density estimation result showed that there was two clusters' distribution in central area and southeastern area respectively.In addition,the result by the Ripley's K-function presented that the location of neural tube birth defects had a significant cluster tendency in the spatial distance from 3.17 to 10.41 kilometers in the investigated area.Conclusion These results can provide an important clue for identifying the relations between environment risk factors and birth defects in this area in the future.