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Open Access Highly Accessed Research

Modern geographical reconnaissance of target populations in malaria elimination zones

Gerard C Kelly1*, Jeffrey Hii2, William Batarii3, Wesley Donald4, Erick Hale3, Johnny Nausien4, Scott Pontifex5, Andrew Vallely1, Marcel Tanner6 and Archie Clements1

Author Affiliations

1 Pacific Malaria Initiative Support Centre, Australian Centre for International and Tropical Health, School of Population Health, University of Queensland, Brisbane, Australia

2 Malaria, Other Vectorborne and Parasitic Diseases, Regional Office for the Western Pacific, World Health Organization, San Lazaro Hospital Compound, Manila, Philippines

3 National Vector Borne Disease Control Programme, Ministry of Health, Honiara, Solomon Islands

4 National Vector Borne Disease Control Programme, Ministry of Health, Port Vila, Republic of Vanuatu

5 Statistics and Demography Programme, Secretariat of the Pacific Community, Noumea, New Caledonia

6 Swiss Tropical & Public Health Institute, 4002 Basel, Switzerland & University of Basel, Basel, Switzerland

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Malaria Journal 2010, 9:289  doi:10.1186/1475-2875-9-289

Published: 20 October 2010

Abstract

Background

Geographical Reconnaissance (GR) operations using Personal Digital Assistants (PDAs) and Global Positioning Systems (GPS) have been conducted in the elimination provinces of Temotu, Solomon Islands and Tafea, Republic of Vanuatu. These operations aimed to examine modern approaches to GR to define the spatial distribution of target populations to support contemporary malaria elimination interventions.

Methods

Three GR surveys were carried out covering the outer islands of Temotu Province (October - November, 2008); Santa Cruz Island, Temotu Province (February 2009) and Tanna Island, Tafea Province (July - September 2009). Integrated PDA/GPS handheld units were used in the field to rapidly map and enumerate households, and collect associated population and household structure data to support priority elimination interventions, including bed net distribution, indoor residual spraying (IRS) and malaria case surveillance. Data were uploaded and analysed in customized Geographic Information System (GIS) databases to produce household distribution maps and generate relevant summary information pertaining to the GR operations. Following completion of field operations, group discussions were also conducted to review GR approaches and technology implemented.

Results

10,459 households were geo-referenced and mapped. A population of 43,497 and 30,663 household structures were recorded during the three GR surveys. The spatial distribution of the population was concentrated in coastal village clusters. Survey operations were completed over a combined total of 77 field days covering a total land mass area of approximately 1103.2 km2. An average of 45 households, 118 structures and a population of 184 people were recorded per handheld device per day. Geo-spatial household distribution maps were also produced immediately following the completion of GR fieldwork. An overall high acceptability of modern GR techniques and technology was observed by both field operations staff and communities.

Conclusion

GR implemented using modern techniques has provided an effective and efficient operational tool for rapidly defining the spatial distribution of target populations in designated malaria elimination zones in Solomon Islands and Vanuatu. The data generated are being used for the strategic implementation and scaling-up of priority interventions, and will be essential for establishing future surveillance using spatial decision support systems.