Spatial Patterns of Malaria Reported Deaths in Yunnan Province, China

Abstract

Abstract. Malaria has been a heavy social and health burden in the remote and poor areas in southern China. Analyses of malaria epidemic patterns can uncover important features of malaria transmission. This study identified spatial clusters, seasonal patterns, and geographic variations of malaria deaths at a county level in Yunnan, China, during 1991-2010. A discrete Poisson model was used to identify purely spatial clusters of malaria deaths. Logistic regression analysis was performed to detect changes in geographic patterns. The results show that malaria mortality had declined in Yunnan over the study period and the most likely spatial clusters (relative risk [RR] = 23.03-32.06, P 0.001) of malaria deaths were identified in western Yunnan along the China-Myanmar border. The highest risk of malaria deaths occurred in autumn (RR = 58.91, P 0.001) and summer (RR = 31.91, P 0.001). The results suggested that the geographic distribution of malaria deaths was significantly changed with longitude, which indicated there was decreased mortality of malaria in eastern areas over the last two decades, although there was no significant change in latitude during the same period. Public health interventions should target populations in western Yunnan along border areas, especially focusing on floating populations crossing international borders.

Prevalence and Molecular Study of G6PD Deficiency in the Dai and Jingpo Ethnic Groups in the Dehong Prefecture of the Yunnan Province

“…The number of malaria cases accounts for 44.16% of the total number of reported infectious diseases in the whole prefecture [6] . The highest incidence rate of malaria in the Yunnan province occurs along the border between China and Myanmar [17] . Malaria is currently the strongest known selection pressure for genetic mutation [18] , and it is an evolutionary driver for diseases, including G6PD deficiency [9] , sickle cell anemia, and thalassemia [19] .…”

Space-time scan statistics of 2007-2013 dengue incidence in Cimahi city, Indonesia

“…Applications of this software has been used for various purposes and accordingly documented (Kulldorff et al, 1998;Schmidt et al, 2011;Bi et al, 2013;SaTScan, 2015). In our study, we used retrospective space-time analysis with a Poisson model to identify villages at high risk for DF during between 1 January 2007 and 31 December 2013.…”

“…This approach for various health-related matters has been documented, both for infectious diseases (DF, malaria, tuberculosis) and non-communicable diseases epidemiology (i.e. cancer) (Kulldorff et al, 1998;Morrison et al, 1998;Touray et al, 2010;Jeefoo et al, 2010;Schmidt et al, 2011;Wu et al, 2011;Bi et al, 2013). Surveillance and early detection should be prioritized in the face of the global DF threat (Guzman et al, 2010).…”

Seasonal dynamics and microgeographical spatial heterogeneity of malaria along the China–Myanmar border

“…Therefore, timely, detailed mapping of malaria epidemiology in the border regions is essential for identifying malaria transmission hotspots and guiding targeted control efforts. However, malaria epidemiology studies conducted so far in this region mostly focused on malaria in China on large scales (Bi et al, 2013a; Clements et al, 2009; Hui et al, 2009; Li et al, 2013; Lin et al, 2009; Xu et al, 2015; Zhou et al, 2014a). Though these studies depicted the overall trends of malaria situation, better understanding of malaria transmission on a microgeographic level (e.g., villages) would provide unprecedented opportunities for local health department officials to execute targeted control efforts.…”