Evaluating local vegetation cover as a risk factor for malaria transmission: a new analytical approach using ImageJ.

BACKGROUND: In places where malaria transmission is unstable or is transmitted under hypoendemic conditions, there are periods where limited foci of cases still occur and people become infected. These residual "hot spots" are likely reservoirs of the parasite population and so are fundamental to the seasonal spread and decline of malaria. It is, therefore, important to understand the ecological conditions that permit vector mosquitoes to survive and forage in these specific areas. Features such as local waterways and vegetation, as well as local ecology, particularly nocturnal temperature, humidity, and vegetative sustainability, are important for modeling local mosquito behavior. Vegetation around a homestead likely provides refuge for outdoor resting of these insects and may be a risk factor for malaria transmission. Analysis of this vegetation can be done using satellite information and mapping programs, such as Google Earth, but manual quantification is difficult and can be tedious and subjective. A more objective method is required. METHODS: Vegetation cover in the environment is reasonably static, particularly in and around homesteads. In order to evaluate and enumerate such information, ImageJ, an image processing software, was used to analyse Google Earth satellite imagery. The number of plants, total amount of vegetation around a homestead and its percentage of the total area were calculated and related to homesteads where cases of malaria were recorded. RESULTS: Preliminary results were obtained from a series of field trials carried out in South East Zambia in the Choma and Namwala districts from a base at the Macha District Hospital. CONCLUSIONS: This technique is objective, clear and simple to manipulate and has potential application to determine the role that vegetation proximal to houses may play in affecting mosquito behaviour, foraging and subsequent malaria incidence.

Measuring malaria by passive case detection: a new perspective based on Zambian experience.

Most measurements of malaria are based on cross-sectional data and do not reflect the dynamic nature of transmission, particularly when interventions require timely data for planning strategies. Such data can be collected from local rural health centres (RHCs) where the infrastructure is sufficiently developed and where rapid diagnostics are in use. Because in rural areas, the population served by RHC is reasonably static, the regular use of malaria rapid diagnosis in RHCs can provide data to assess local weekly incidence rates, and such data are easily dispersed by cell phones. Essentially each RHC is a potential sentinel site that can deliver critical information to programme planners. Data collected during this process of passive case detection over a five-year period in the Macha area of Zambia show the importance of ecological zones and refugia in the seasonal fluctuation of malaria cases. If this process is implemented nationally it can assist in planning efficient use of resources and may contribute to local management and even elimination of malaria in this region.