Modeling freshwater snail habitat suitability and areas of potential snail-borne disease transmission in Uganda

TY - JOUR

T1 - Modeling freshwater snail habitat suitability and areas of potential snail-borne disease transmission in Uganda

AU - Stensgaard, Anna-Sofie

AU - Jørgensen, Aslak

AU - Kabatereine, N B

AU - Rahbek, Carsten

AU - Kristensen, Thomas K.

PY - 2006

Y1 - 2006

N2 - Geographic information system (GIS-based modeling of an intermediate host snail species environmental requirements using known occurrence records can provide estimates of its spatial distribution. When other data are lacking, this can be used as a rough spatial prediction of potential snail-borne disease transmission areas. Furthermore, knowledge of abiotic factors affecting intra-molluscan parasitic development can be used to make "masks" based on remotely sensed climatic data, and these can in turn be used to refine these predictions. We used data from a recent freshwater snail survey from Uganda, environmental data and the genetic algorithm for rule-set prediction (GARP) to map the potential distribution of snail species known to act as intermediate hosts of several human and animal parasites. The results suggest that large areas of Uganda are suitable habitats for many of these snail species, indicating a large potential for disease transmission. The lack of parasitological data still makes it difficult to determine the magnitude of actual disease transmission, but the predicted snail distributions might be used as indicators of potential present and future risk areas. Some of the predicted snail distribution maps were furthermore combined with temperature masks delineating suitable temperature regimes of the parasites they host. This revealed the coinciding suitable areas for snail and parasite, but also areas suitable for host snails, but apparently not for the parasites. Assuming that the developed models correctly reflect areas suitable for transmission, the applied approach could prove useful for targeting control interventions.

AB - Geographic information system (GIS-based modeling of an intermediate host snail species environmental requirements using known occurrence records can provide estimates of its spatial distribution. When other data are lacking, this can be used as a rough spatial prediction of potential snail-borne disease transmission areas. Furthermore, knowledge of abiotic factors affecting intra-molluscan parasitic development can be used to make "masks" based on remotely sensed climatic data, and these can in turn be used to refine these predictions. We used data from a recent freshwater snail survey from Uganda, environmental data and the genetic algorithm for rule-set prediction (GARP) to map the potential distribution of snail species known to act as intermediate hosts of several human and animal parasites. The results suggest that large areas of Uganda are suitable habitats for many of these snail species, indicating a large potential for disease transmission. The lack of parasitological data still makes it difficult to determine the magnitude of actual disease transmission, but the predicted snail distributions might be used as indicators of potential present and future risk areas. Some of the predicted snail distribution maps were furthermore combined with temperature masks delineating suitable temperature regimes of the parasites they host. This revealed the coinciding suitable areas for snail and parasite, but also areas suitable for host snails, but apparently not for the parasites. Assuming that the developed models correctly reflect areas suitable for transmission, the applied approach could prove useful for targeting control interventions.

KW - Animals

KW - Disease Transmission, Infectious

KW - Disease Vectors

KW - Ecosystem

KW - Environmental Monitoring

KW - Geographic Information Systems

KW - Humans

KW - Models, Theoretical

KW - Schistosomiasis

KW - Snails

KW - Uganda

U2 - 10.4081/gh.2006.284

DO - 10.4081/gh.2006.284

M3 - Journal article

C2 - 18686235

SN - 1827-1987

VL - 1

SP - 93

EP - 104

JO - Geospatial health

JF - Geospatial health

IS - 1

ER -