Online Advanced Analytical Service: Profiles for Dengue Hemorrhagic Fever Transmission in Southern Thailand
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Abstract
Background: Southern Thailand has the highest Dengue Hemorrhagic Fever (DHF) incidence and fatality rate in Thailand. Geographic Information Systems (GIS) technology and spatial analysis techniques are powerful tools to describe epidemiological patterns. The aim of this study was to develop an Online Advanced Analytical Service: Profiles for Dengue Hemorrhagic Fever Transmission (OSD) in Southern Thailand.
Methods: The system was developed using JavaServer Pages (JSP) and Database Management System (DBMS) with Structured Query Language (SQL) technology as the web database tool for data entry and data access, web Mathematica technology for data analysis and Google Maps™ API technology for online data display as the map service implementing GIS technology.
Results: The OSD system has been available online at URL http://www.s-cm.co/dengue. Users performed data entry using the web-service with login by social network (i.e. Facebook) account, used data analysis tools with online real-time statistical analysis and data display with transparent color circles overlaid on Google Maps™.
Conclusion: The OSD system display represents the distribution of DHF cases with spatial information. This system enables health planners to provide interventions for DHF focusing on prevention, control, and strategic planning.
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2. WHO (2009). Dengue: Guidelines for diag-nosis, treatment, prevention and control. France: World Health Organization and TDR Publication.
3. Hay SI, Myers MF, Burke DS et al (2000). Ethology of interepidemic periods of mosquito-borne disease. Proc Natl Acad Sci U S A, 97: 9335-9.
4. Stephenson I, Roper J, Fraser M et al (2003). Dengue fever in febrile returning travel-lers to a UK regional infectious diseases unit. Travel Med Infect Dis, 1(2): 89-93.
5. WHO (2016). Dengue and Severe Dengue. http://www.who.int/mediacentre/factsheets/fs117/en/
6. Reyes-Castro PA, Harris RB, Brown HE et al (2017). Spatio-temporal and neighbor-hood characteristics of two dengue out-breaks in two arid cities of Mexico. Acta Trop, 167: 174-82.
7. Coudeville L, Baurin N, L’Azou M, Guy B (2016). Potential impact of dengue vac-cination: Insights from two large-scale phase III trials with a tetravalent dengue vaccine. Vaccine, 34: 6426-35.
8. Strickman D, Sithiprasasna R, Kittayapong P, Innis BL (2000). Distribution of den-gue and Japanese encephalitis among children in rural and suburban Thai vil-lages. Am J Trop Med Hyg, 63: 27-35.
9. Bureau of Epidemiology (2016). DHF Situa-tion in Thailand. Department of Disease Control, Ministry of Public Health, Thai-land.
10. WHO (2017). Immunization, Vaccines and Biologicals. http://www.who.int/immunization/research/development/dengue_q_and_a/en/
11. Vannice KS, Durbin A, Hombach J (2016). Status of vaccine research and develop-ment of vaccines for dengue. Vaccine, 34: 2934-8.
12. Li Z, Yin W, Clements A et al (2012). Spa-tiotemporal analysis of indigenous and imported dengue fever cases in Guang-dong province, China. BMC Infect Dis, 12: 132.
13. Wongkoon S, Jaroensutasinee M, Jaroensutasinee K (2013). The Mosquito Online Advanced Analytic Service: A Case Study for School Research Projects in Thailand. Southeast Asian J Trop Med Public Health, 44(4): 574-85.
14. Wongkoon S, Jaroensutasinee M, Jaroensutasinee K (2016). Spatio-temporal climate-based model of dengue infection in Southern, Thailand. Trop Bio-med, 33(1): 55-70.
15. Dominkovics P, Granell C, Pérez-Navarro A et al (2011). Development of spatial density maps based on geoprocessing web services: application to tuberculosis incidence in Barcelona, Spain. Int J Health Geogr, 10(1): 62.
16. Kienberger S, Hagenlocher M, Delmelle E, Casas I (2013). A WebGIS tool for visu-alizing and exploring socioeconomic vul-nerability to dengue fever in Cali, Colom-bia. Geospat Health, 8(1): 313-6.
17. Morrison AC, Getis A, Santiago M et al (1998). Exploratory space-time analysis of reported dengue cases during an out-break in Florida, Puerto Rico, 1991–1992. Am J Trop Med Hyg, 58: 287-98.
18. Sharma KD, Mahabir RS, Curtin KM et al (2014). Exploratory space-time analysis of dengue incidence in Trinidad: a retro-spective study using travel hubs as dis-persal points, 1998–2004. Parasites Vectors, 7: 341.
19. Boulos MN (2005). Web GIS in practice III: creating a simple interactive map of Eng-land’s Strategic Health Authorities using Google Maps API, Google Earth KML, and MSN Virtual Earth Map Control. Int J Health Geogr, 4: 22.
20. Google Developer (2016). Google Maps API Technology. https://enterprise.google.com/intl/en/maps/products/mapsapi.html
21. Lozano-Fuentes S, Elizondo-Quiroga D, Farfan-Ale JA et al (2008). Use of Google Earth™ to strengthen public health ca-pacity and facilitate management of vec-tor-borne diseases in resource-poor envi-ronments. Bull World Health Organ, 86: 718-25.
22. Oracle Corporation (2016). JavaServer Pages Technology http://docs.oracle.com/javaee/5/tutorial/doc/bnagx.html
23. Wolfram Research (2016). Powered by Mathematica, webMathematica adds dy-namic content to your website. http://www.wolfram.com/products/webmathematica/
24. Bureau of Epidemiology (2013). The dengue fever cases in Thailand. Department of Disease Control, Ministry of Public Health, Thailand.
25. Delmelle EM, Zhu H, Tang W, Casas I (2014). A Web-based geospatial toolkit for the monitoring of dengue fever. Appl Geogr, 52:144-52.
26. Mao L, Yin L, Song X, Mei S (2016). Map-ping intra-urban transmission risk of dengue fever with big hourly cellphone data. Acta Trop, 162: 188-95.
27. Wongkoon S, Jaroensutasinee M, Jaroensu-tas-inee K (2012). Assessing the temporal modelling for prediction of dengue infec-tion in northern and northeastern, Thai-land. Trop Biomed, 29(3): 339-48.
28. Nagao Y, Thavara U, Chitnumsup P et al (2003). Climatic and social risk factors for Aedes infestation in rural Thailand. Trop Med Int Health, 8: 650-9.
29. Mammen PM Jr, Chusak P, Constantianus JMK et al (2008). Spatial and temporal clustering of dengue virus transmission in Thai villages. PLOS Med, 5: e205.
30. Hu W, Clements A, Williams G, Tong S (2011). Spatial analysis of notified dengue fever infections. Epidemiol Infect, 139: 391-9.
| Files | ||
| Issue | Vol 48 No 11 (2019) | |
| Section | Original Article(s) | |
| DOI | https://doi.org/10.18502/ijph.v48i11.3516 | |
| Keywords | ||
| Dengue Hemorrhagic Fever (DHF); Spatio-temporal Advanced analytic Google Maps™ | ||
| Rights and permissions | |
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This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License. |
How to Cite
1.
KAJORNKASIRAT S, MUANGPRATHUB J, BOONNAM N. Online Advanced Analytical Service: Profiles for Dengue Hemorrhagic Fever Transmission in Southern Thailand. Iran J Public Health. 2019;48(11):1979-1987.
