Space and time predictions of schistosomiasis snail host population dynamics across hydrologic regimes in Burkina Faso

Geospat Health. 2019 Nov 6;14(2). doi: 10.4081/gh.2019.796.


The ecology of the aquatic snails that serve as obligatory intermediate hosts of human schistosomiasis is driven by climatic and hydrological factors which result in specific spatial patterns of occurrence and abundance. These patterns in turn affect, jointly with other determinants, the geography of the disease and the timing of transmission windows, with direct implications for the success of control and elimination programmes in the endemic countries. We address the spatial distribution of the intermediate hosts and their seasonal population dynamics within a predictive ecohydrological framework developed at the national scale for Burkina Faso, West Africa. The approach blends river network-wide information on hydrological ephemerality which conditions snail habitat suitability together with ensembles of discrete time ecological models forced by remotely sensed estimates of temperature and precipitation. The models were validated against up to four years of monthly snail abundance data. Simulations of model ensembles accounting for the uncertainty in remotely sensed products adequately reproduce observed snail demographic fluctuations observed in the field across habitat types, and produce national scale predictions by accounting for spatial patterns of hydrological conditions in the country. Geospatial estimates of seasonal snail abundance underpin large-scale, spatially explicit predictions of schistosomiasis incidence. This work can therefore contribute to the development of disease control and elimination programmes.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Animals
  • Burkina Faso / epidemiology
  • Computer Simulation
  • Host-Parasite Interactions
  • Humans
  • Models, Theoretical
  • Population Dynamics
  • Schistosomiasis / veterinary*
  • Snails / parasitology*
  • Spatio-Temporal Analysis*