Space-time clustering characteristics of dengue based on ecological, socio-economic and demographic factors in northern Sri Lanka

  • Sumiko Anno | annou@sic.shibaura-it.ac.jp Shibaura Institute of Technology, Tokyo, Japan.
  • Keiji Imaoka Japan Aerospace Exploration Agency, Ibaraki, Japan.
  • Takeo Tadono Japan Aerospace Exploration Agency, Ibaraki, Japan.
  • Tamotsu Igarashi Remote Sensing Technology Center of Japan, Tokyo, Japan.
  • Subramaniam Sivaganesh Regional Epidemiologist, Jaffna, Sri Lanka.
  • Selvam Kannathasan University of Jaffna, Jaffna, Sri Lanka.
  • Vaithehi Kumaran University of Jaffna, Jaffna, Sri Lanka.
  • Sinnathamby Noble Surendran University of Jaffna, Jaffna, Sri Lanka.

Abstract

The aim of the present study was to identify geographical areas and time periods of potential clusters of dengue cases based on ecological, socio-economic and demographic factors in northern Sri Lanka from January 2010 to December 2013. Remote sensing (RS) was used to develop an index comprising rainfall, humidity and temperature data. Remote sensing data gathered by the AVNIR-2 instrument onboard the ALOS satellite were used to detect urbanisation, and a digital land cover map was used to extract land cover information. Other data on relevant factors and dengue outbreaks were collected through institutions and extant databases. The analysed RS data and databases were integrated into a geographical information system (GIS) enabling space-time clustering analysis. Our results indicate that increases in the number of combinations of ecological, socio-economic and demographic factors that are present or above the average contribute to significantly high rates of space-time dengue clusters. The spatio-temporal association that consolidates the two kinds of associations into one can ensure a more stable model for forecasting. An integrated spatiotemporal prediction model at a smaller level using ecological, socioeconomic and demographic factors could lead to substantial improvements in dengue control and prevention by allocating the right resources to the appropriate places at the right time.

Dimensions

Altmetric

PlumX Metrics

Downloads

Download data is not yet available.

Author Biography

Sumiko Anno, Shibaura Institute of Technology, Tokyo
Faculty of Engineering
Published
2015-11-26
Info
Issue
Section
Original Articles
Keywords:
Dengue, Space-time clustering analysis, Remote sensing, Sri Lanka
Statistics
  • Abstract views: 2491

  • PDF: 1401
  • HTML: 1250
How to Cite
Anno, S., Imaoka, K., Tadono, T., Igarashi, T., Sivaganesh, S., Kannathasan, S., Kumaran, V., & Surendran, S. N. (2015). Space-time clustering characteristics of dengue based on ecological, socio-economic and demographic factors in northern Sri Lanka. Geospatial Health, 10(2). https://doi.org/10.4081/gh.2015.376