Research

Spatial and temporal distribution of the malaria mosquito Anopheles arabiensis in northern Sudan: influence of environmental factors and implications for vector control

Tellal B Ageep¹ , Jonathan Cox² , M'oawia M Hassan¹ , Bart GJ Knols^3,7 , Mark Q Benedict⁴ , Colin A Malcolm⁵ , Ahmed Babiker⁶ and Badria B El Sayed¹

¹  Epidemiology Department, Tropical Medicine Research Institute, PO Box 1304, Khartoum, Sudan

²  Department of Tropical and Infectious Diseases, London School of Hygiene and Tropical Medicine, London, WC1E 7HT, UK

³  Laboratory of Entomology, Wageningen University and Research Centre, PO Box 8031, 6700 EH, Wageningen, the Netherlands

⁴  International Atomic Energy Agency, Seibersdorf Laboratory, A-2444 Seibersdorf, Austria

⁵  School of Biological and Chemical Sciences, Queen Mary University of London, London, E1 4NS, UK

⁶  National Centre for Research, Ministry of Science and Technology PO Box 2404, Khartoum, Sudan

⁷  K&S Consulting, Kalkestraat 20, 6669CP, Dodewaard, the Netherlands

author email corresponding author email

Malaria Journal 2009, 8:123doi:10.1186/1475-2875-8-123

Published:	7 June 2009

Abstract

Background

Malaria is an important public health problem in northern Sudan, but little is known about the dynamics of its transmission. Given the characteristic low densities of Anopheles arabiensis and the difficult terrain in this area, future vector control strategies are likely to be based on area-wide integrated pest management (AW-IPM) that may include the sterile insect technique (SIT). To support the planning and implementation of future AW-IPM activities, larval surveys were carried out to provide key data on spatial and seasonal dynamics of local vector populations.

Methods

Monthly cross-sectional larval surveys were carried out between March 2005 and May 2007 in two localities (Dongola and Merowe) adjacent to the river Nile. A stratified random sampling strategy based on the use of Remote Sensing (RS), Geographical Information Systems (GIS) and the Global Positioning System (GPS) was used to select survey locations. Breeding sites were mapped using GPS and data on larval density and breeding site characteristics were recorded using handheld computers. Bivariate and multivariate logistic regression models were used to identify breeding site characteristics associated with increased risk of presence of larvae. Seasonal patterns in the proportion of breeding sites positive for larvae were compared visually to contemporaneous data on climate and river height.

Results

Of a total of 3,349 aquatic habitats sampled, 321 (9.6%) contained An. arabiensis larvae. The frequency with which larvae were found varied markedly by habitat type. Although most positive sites were associated with temporary standing water around the margins of the main Nile channel, larvae were also found at brickworks and in areas of leaking pipes and canals – often far from the river. Close to the Nile channel, a distinct seasonal pattern in larval populations was evident and appeared to be linked to the rise and fall of the river level. These patterns were not evident in vector populations breeding in artificial water sources away from the river.

Conclusion

The GIS-based survey strategy developed in this study provides key data on the population dynamics of An. arabiensis in Northern State. Quantitative estimates of the contributions of various habitat types and their proximity to settlements provide a basis for planning a strategy for reducing malaria risk by elimination of the vector population.