Year: 2024 | Month: January-March | Volume: 9 | Issue: 1 | Pages: 58-66
DOI: https://doi.org/10.52403/ijshr.20240110
Use of Mapping Technologies to Study the Spatial Distribution of Malaria Incidence in Vietnam
Thi-Quynh Nguyen1, Thi-Hien Cao2
1,2Faculty of Nursing, East Asia University of Technology, Hanoi, Vietnam
Corresponding Author: Thi-Quynh Nguyen
ABSTRACT
Background: Malaria is one of the major public health issues globally. Malaria infection spreads through mosquito bites from infected female Anopheles mosquitoes. This study aims to apply mapping technologies to investigate the spatial distribution of malaria cases and incidence in Vietnam.
Materials and Methods: Malaria cases in 2019 were first collected from the websites of the Vietnam Ministry of Health (VMH). The incidence of malaria will be then computed. The histogram is employed to study the distribution of malaria cases and incidence. Mapping technologies is then used to study the spatial distribution of malaria cases and incidence. In addition, a scatter plot is also used to investigate the relationship between population density and the incidence of malaria. Finally, results and findings will be discussed and summarised.
Results: the study results showed that the highest rate of malaria infection was detected in Gia Lai, followed by Phu Yen, Dak Lak, and Binh Phuoc. Areas of high malaria infection rates were mainly concentrated in rural areas in the south-central region having with high vegetation coverage. Whereas, areas with no or low malaria infection rates were mainly concentrated in urban areas in the northeastern and southeastern regions of Vietnam. In addition, there was a negative correlation between population density and the incidence of malaria.
Conclusion: It can be concluded that the combination of histograms, mapping technologies and a scatter plot prove their effectiveness in the study of malaria. Findings in this study provide an insight into how to apply mapping technologies to study and prevent the spread of such an infectious disease as malaria.
Keywords: Spatial distribution, Malaria cases, Malaria incidence, Histogram, Scatter plot, Mapping technologies.