Add to ORKGSpatial estimation of the burden of schistosome infection, West Africa Use of Bayesian geostatistical prediction to estimate local variations in Schistosoma haematobium infection in Wes
Background: Schistosomiasis is a water-based disease that is believed to affect over 200 million peo...
Schistosomiasis is a water-based disease that is believed to affect over 200 million people with an ...
Multiple parasite infections are widespread in the developing world and understanding their geograph...
Simon and Fenwick, Alan (2009) Use of Bayesian geostatistical prediction to estimate local variation...
Objective To predict the subnational spatial variation in the number of people infected with Schisto...
A Bayesian geostatistical model was developed to predict the intensity of infection with Schistosoma...
Objective: To predict the subnational spatial variation in the number of people infected with Schist...
Objective: To predict the subnational spatial variation in the number of people infected with Schist...
We aimed to map the probability of Schistosoma haematobium infection being >50%, a threshold for ann...
We aimed to map the probability of Schistosoma haematobium infection being >50%, a threshold for ann...
Schistosomiasis remains one of the most prevalent parasitic diseases in the tropics and subtropics, ...
OBJECTIVE: To predict the spatial distributions of Schistosoma haematobium and S. mansoni infections...
A Bayesian geostatistical model was developed to predict the intensity of infection with Schistosoma...
Objective To predict the subnational spatial variation in the number of people infected with Schisto...
The increased interest of reducing the infection rates of neglected tropical diseases like schistoso...
Background: Schistosomiasis is a water-based disease that is believed to affect over 200 million peo...
Schistosomiasis is a water-based disease that is believed to affect over 200 million people with an ...
Multiple parasite infections are widespread in the developing world and understanding their geograph...
Simon and Fenwick, Alan (2009) Use of Bayesian geostatistical prediction to estimate local variation...
Objective To predict the subnational spatial variation in the number of people infected with Schisto...
A Bayesian geostatistical model was developed to predict the intensity of infection with Schistosoma...
Objective: To predict the subnational spatial variation in the number of people infected with Schist...
Objective: To predict the subnational spatial variation in the number of people infected with Schist...
We aimed to map the probability of Schistosoma haematobium infection being >50%, a threshold for ann...
We aimed to map the probability of Schistosoma haematobium infection being >50%, a threshold for ann...
Schistosomiasis remains one of the most prevalent parasitic diseases in the tropics and subtropics, ...
OBJECTIVE: To predict the spatial distributions of Schistosoma haematobium and S. mansoni infections...
A Bayesian geostatistical model was developed to predict the intensity of infection with Schistosoma...
Objective To predict the subnational spatial variation in the number of people infected with Schisto...
The increased interest of reducing the infection rates of neglected tropical diseases like schistoso...
Background: Schistosomiasis is a water-based disease that is believed to affect over 200 million peo...
Schistosomiasis is a water-based disease that is believed to affect over 200 million people with an ...
Multiple parasite infections are widespread in the developing world and understanding their geograph...