https://doi.org/10.4081/gh.2015.329

MALAREO: a user-driven project

Vol. 10 No. 2 (2015)
Submitted: 5 February 2015
Accepted: 22 April 2015
Published: 4 November 2015
MALAREO, Malaria, Earth observation, Lubombo Spatial Development Initiative, Southern Africa
Abstract Views: 2524
PDF: 982
HTML: 965
Publisher's note
All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.

Authors

Michael T. Gebreslasie
gebreslasie@ukzn.ac.za
School of Agricultural, Earth and Environmental Sciences, University of KwaZulu-Natal, Durban, South Africa.
Ides Bauwens
School of Agricultural, Earth and Environmental Sciences, University of KwaZulu-Natal, Durban, South Africa.
The aim of this study is to assess the capacity gaps and requirements of Earth observation (EO) and related technologies for malaria vector control and management in the Lubombo Spatial Development Initiative regions of South Africa, Swaziland and Mozambique. In order to achieve the core objective of this study, available EO data (including main characteristics and resources required to utilize them) and their potential applications for malaria epidemiology are reviewed. In addition, a survey was conducted to assess the availability of human and facility resources to operate EO and related technologies for control and management of the malaria control programs in these countries resulting in an analysis of capacity gaps, priorities and requirements. Earth observation in malaria vector control and management has two different applications: i) collection of relevant remotely sensed data for epidemiological use; and ii) direct support of ongoing malaria vector control activities. All malaria control programs and institutions recognize the significance of EO products to detect mosquito vector habitats, to monitor environmental parameters affecting mosquito vector populations as well as house mapping and distribution of information supporting residual spray planning and monitoring. It was found that only the malaria research unit (MRU) of the medical research council (MRC) in South Africa and the national malaria control program (MCP) in Swaziland currently have a fully functional geographic information systems (GIS), whereas the other surveyed MCPs in South Africa and Mozambique currently do not have this in place. Earth observation skills only exist in MRU of MRC, while spatial epidemiology is scarce in all institutions, which was identified as major gap. The survey has also confirmed that EO and GIS technologies have enormous potential as sources of spatial data and as analytical frameworks for malaria vector control. It is therefore evident that planning and management require capacity building with respect to GIS, EO and spatial epidemiology.

Dimensions

Altmetric

PlumX Metrics

Downloads

Download data is not yet available.

Citations

Crossref
Scopus
Google Scholar
Europe PMC
Michael T. Gebreslasie, School of Agricultural, Earth and Environmental Sciences, University of KwaZulu-Natal, Durban

Dr Michael Gebreslasie obtained a BA Geography degree (space and health specialization) from the University of Asmara, Eritrea. This was followed by MSc Applied Environmental Science degree with Geographic Information Systems (GIS) and Remote sensing specialization from university of KwaZulu Natal, South Africa. Michael then completed PhD Geography degree at University of KwaZulu Natal. This degree focused on testing, improving tools and methods for prediction of biophysical, biochemical, and canopy structural characteristics such as Leaf Area Index (LAI), Tree height, Basal area, Tree density, and Biomass using multi-spectral and multi-angle optical and active remote sensing. Better prediction of these characteristics is a key to sustainable management of forest ecosystem.

I teach Geographic Information Systems (GIS) and Remote Sensing subjects at both undergraduate and postgraduate levels.

ENVS 250 Introduction to Remote Sensing

ENVS 316 Introduction to GIS

ENVS 712 Analytical GIS and Advanced Spatial Modeling

ENVS 720 Advanced Remote Sensing

How to Cite

Gebreslasie, M. T., & Bauwens, I. (2015). MALAREO: a user-driven project. Geospatial Health, 10(2). https://doi.org/10.4081/gh.2015.329

PAGEPress has chosen to apply the Creative Commons Attribution NonCommercial 4.0 International License (CC BY-NC 4.0) to all manuscripts to be published.