Spatial and multidimensional visualization of Indonesia's village health statistics
2008

Using SOVAT for Community Health Assessment in Indonesia

Sample size: 60000 publication Evidence: moderate

Author Information

Author(s): Parmanto Bambang, Paramita Maria V, Sugiantara Wayan, Pramana Gede, Scotch Matthew, Burke Donald S

Primary Institution: University of Pittsburgh

Hypothesis

Can the Spatial OLAP Visualization and Analysis Tool (SOVAT) facilitate community health assessments in developing countries like Indonesia?

Conclusion

The case studies demonstrate that SOVAT can effectively support community health assessments in developing countries by providing timely and comprehensive health data analysis.

Supporting Evidence

  • SOVAT integrates various health and demographic data to enhance community health assessments.
  • The tool allows for rapid analysis and visualization of health data.
  • Case studies showed significant disparities in healthcare resource distribution across Indonesia.
  • Malaria mortality rates were found to be higher in rural areas compared to urban areas.

Takeaway

This study shows that a special tool called SOVAT can help health workers in Indonesia quickly understand health data to make better decisions.

Methodology

The study used case studies to demonstrate the application of SOVAT in analyzing health, population, and spatial data from Indonesia.

Limitations

The study is limited by the availability and accuracy of spatial data, which may not be up-to-date due to administrative changes.

Participant Demographics

The study involved data from 60,000 villages across Indonesia.

Digital Object Identifier (DOI)

10.1186/1476-072X-7-30

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