Hu Xuefeng, Chen Lin, Zhang Rong, Tian Lingling, Zhou Pengcheng, Shi Dan, Wu Hailei, Han Hui. Temporal-spatial epidemiological characteristics of malaria cases in Jiangsu province, 2012−2019[J]. Disease Surveillance, 2023, 38(9): 1059-1066. DOI: 10.3784/jbjc.202302190049
Citation: Hu Xuefeng, Chen Lin, Zhang Rong, Tian Lingling, Zhou Pengcheng, Shi Dan, Wu Hailei, Han Hui. Temporal-spatial epidemiological characteristics of malaria cases in Jiangsu province, 2012−2019[J]. Disease Surveillance, 2023, 38(9): 1059-1066. DOI: 10.3784/jbjc.202302190049

Temporal-spatial epidemiological characteristics of malaria cases in Jiangsu province, 2012−2019

  •   Objective  To analyze the temporal-spatial distribution characteristics of malaria cases in Jiangsu province from 2012 to 2019, to analyze the temporal-spatial clustering of malaria cases, in order to provide theoretical basis for prevention and control of imported cases.
      Methods  The epidemic data of malaria cases in Jiangsu province was collected. The global and local spatial autocorrelation of malaria cases was carried out respectively by ArcGIS 10.2. The temporal-spatial clustering was analyzed by spatial-temporal scanning by SatScan 9.5.
      Results  A total of 2333 malaria cases were reported in Jiangsu province from 2012 to 2019. 2329 (99.83%) cases were imported. 2317 (99.31%) cases were Chinese. 1939 (83.11%) cases were Chinese migrant workers. 2279 (97.85%) cases were imported from African. 43 (1.85%) cases were imported from south-east Asia. The top 5 cities were Nantong (350, 15.00%), Taizhou (277, 11.87%), Lianyungang (276, 11.83%), Yangzhou (268, 11.49%), Huai'an (258, 11.06%). There was a trend in spatial distribution. January-February and April-July were annual bimodal periods. Spatial autocorrelation analysis results showed that there was no obvious global spatial correlation from 2012 to 2019. But there were in hot areas and cold areas in local spatial autocorrelation analysis. Three high risk clustering areas were detected by year-by-year spatial-temporal scanning, involved in Huai’an, Lianyungang, Taizhou, Yangzhou, Nantong.
      Conclusion  There is a certain level of spatial-temporal clustering in malaria cases in Jiangsu province from 2012 to 2019. The targeted measures should be taken to prevent and control the epidemic.
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