Mapping malaria risk using environmental and anthropic variables

Abstract

Despite much research in the identification of areas with malaria, it is urgent to further investigate mapping techniques to achieve better approaches in strategies to prevent, mitigate, and eradicate the mosquito and the illness eventually. By using spatial distributed modeling techniques with Geographical Information Systems (GIS), the study proposes methodology to map malaria risk zoning for the municipality of Buenaventura in Colombia. The model proposed by Craig et al.¹ using climatic information was adapted to the conditions of the study area regarding scale and spatial resolution. Geomorphologic and anthropic variables were added to improve spatial allocation of areas with higher risk of contracting the illness, refining zoning. Then, they were contrasted with the locations reported by health entities², taking into account spatial distribution. The comparison of results shows a decrease in the area obtained initially using the Craig et al. model¹ (1999), from 5,422.4 km² (89.1% of the municipality's territory) to 624.3km² (approximately 10% of the municipality's area), yielding a total reduction of 78.8% when environmental and anthropic variables were included in the model. Data show that of the 9,863 cases reported during 2001 to 2005 for 20 selected towns as basis for the amount of surveyed malaria cases², 1,132 were located in the very high-risk areas, 7,662 were in the areas of moderate risk, and 1,066 cases in low-risk areas, showing that 89% of the cases reported fell into the areas with higher risk for malaria.

Remote Sensing and Multi-Criteria Evaluation for Malaria Risk Mapping to Support Indoor Residual Spraying Prioritization in the Central Highlands of Madagascar

“…Several methods have been used to map malaria risk. GIS-based spatial modeling techniques were adopted by Rincón-Romero and Londoño for malaria risk mapping in Columbia and by Ferrao et al in Mozambique [14,15]. Others promote spatial statistical approaches to map malaria risk.…”

Spatial fine‐resolution model of malaria risk for the Colombian Pacific region

“…In Latin America, few studies have attempted to categorise and map malaria risk. One of them used environmental and anthropic variables to design a malaria risk map for Buenaventura municipality in the Colombian Pacific region and showed that 89% of the cases corresponded to areas with moderate/high malaria risk [25]. Later, risk maps for Colombia and surrounding areas [26], and for northern South America [22] were produced based on expert opinion of key environmental and population risk factors.…”

Downscaling incidence risk mapping for a Colombian malaria endemic region

“…Two of them focused on the effects of climatic change associated with El Niño/Southern Oscillation‐ENSO on the number of malaria cases . Another study that mapped malaria risk for the Pacific Coast municipality of Buenaventura and showed a 78.8% reduction in areas under malaria risk when environmental and anthropic variables were included in the model . In addition, a high spatial resolution (90 × 90 m) malaria risk map for Colombia, based on environmental and human population data, helped to demonstrate the relationship between mean risk scores with total cases by the municipality, and provided an accurate spatial representation of risk potential to vector exposure .…”