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APPLICATION OF GIS TECHNOLOGY IN ESTABLISHING DATABASE FOR GEOSPATIAL EPIDEMIOLOGY AND ANALYSIS OF RELATED FACTORS TO INFECTIOUS DISEASE IN THE NORTHERN MIDLANDS AND MOUNTAINOUS REGIONS (2014 - 2023)
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Abstract
Objectives: To set up a geospatial epidemiological database of infectious diseases and factors related to infectious diseases in the northern midland and mountainous provinces in the period from 2014 to 2023. Methods: Data were processed using Excel and MapInfo software, a mapping method for creating thematic maps. Results: 2,080 survey forms of all kinds were edited and processed; 353,635 database data records of geospatial epidemiological map attributes of infectious diseases and factors related to infectious diseases in the northern midland and mountainous provinces were digitized and updated in the period from 2014 to 2023 using MapInfo software. Exploiting and applying MapInfo software to build thematic maps of a number of infectious diseases including: respiratory transmission, gastrointestinal transmission, bloodborne pathogen transmission under the national expanded immunisation programme. Conclusion: Building a geospatial epidemiological database of infectious diseases in the northern midland and mountainous regions has provided an overall picture including information on morbidity and mortality of infectious diseases along with the relevance of certain natural features; socio-economic; animals, plants, microorganisms and infectious diseases in strategic areas of the Fatherland.
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Keywords
Infectious diseases, Related factors, Geographic Information Systems (GIS)
References
2. Cục Đo đạc, Bản đồ và Thông tin địa lý Việt Nam. Cơ sở dữ liệu nền địa lý quốc gia. Truy cập tại: https://bandovn.vn/ vi/co-so-du-lieu-nen-dia-ly-quoc-gia-6 ngày 06/3/2025. 2025.
3. Umuhoza T, Oyugi J, Mancuso JD, et al. Spatial and spatio-temporal distribution of human respiratory syncytial virus, human parainfluenza virus, and human adenoviruses cases in Kenya 2007 - 2013. East African Health Research Journal. 2022; 6(1):52-63.
4. Zhu H, Zhao H, Ou R, et al. Spatiotemporal epidemiology of Varicella in Chongqing, China, 2014 - 2018. International Journal of Environmental Research and Public Health. 2020; 17(2):662.
5. Zhu H, Zhao H, Ou R, et al. Epidemiological characteristics and spatiotemporal analysis of mumps from 2004 to 2018 in Chongqing, China. International Journal of Environmental Research and Public Health. 2019; 16(17):3052.
6. Jaya I, Chadidjah A, Andriyana Y, et al. Bayesian hierarchical spatiotemporal modeling for forecasting diarrhea risk among children under 5 in Bandung city, Indonesia. International Journal of Data & Network Science. 2023; 7(4)
7. Nguyễn Văn Chuyên, Nguyễn Trọng Chính, Nguyễn Văn Ba. Thực trạng bệnh truyền nhiễm tại khu vực Tây Nguyên (2008 - 2014). Tạp chí Y Dược học Quân sự. 2017; 3:117-125.
8. Yao HW, Yang Y, Liu K, et al. The spatiotemporal expansion of human rabies and its probable explanation in mainland China, 2004 - 2013. PLoS Neglected Tropical Diseases. 2015; 9(2):e0003502.
9. Paireau J, Mainassara HB, Jusot J-F, et al. Spatio-temporal factors associated with meningococcal meningitis annual incidence at the health centre level in Niger, 2004 - 2010. PLoS Neglected Tropical Diseases. 2014; 8(5):e2899.
10. Umaru E, Ludin A, Sabri S. Spatiotemporal analysis of the spread of meningococcal meningitis in kaduna metropolis, 2007 - 2011. IOP Publishing; 2014:012056.