Although the presence of Schistosomiasis haematobium and S. mansoni infection in Nigeria has been known since 1881 from the account of the German traveller, Nachitigal, through the eastern region of Borno (Houmsou  et. al., 2012),  the infection has since been spreading. Initially it was through the Fulani herdsmen arriving from the Upper Nile valley (Houmsou et. al., 2012),  a pathway confirmed in the report of the National Health Services for 1929. It noted that urinary schistosomiasis was highly endemic in Katsina and Ibadan regions. Since the late 1980s infection with Schistosoma haematobium, Schistosoma mansoni, and Schistosoma intercalatum has been endemic in Nigeria, which led to the formation of a National Schistosomiasis Control programme (Ugochukwu et. al,. 2013). The disease results from an interaction between parasite, intermediate host, and definitive host. The abundance of the parasite is strongly dependent on the reciprocal transmission between intermediate and definitive host. With the relationship between parasite, the intermediate and the definitive host, lots of data have been generated mostly for epidemiological control of the disease. This requires more effective analysis and interpretation for effective decision making in the control of schistosomiasis.

Nigeria has high prevalence figures for schistosomiasis in communities that have fast flowing rivers such as Eggua with little alternative access to other water sources.

Most epidemiological evaluation done in areas such as Eggua utilizes statistical tools for analysis. The schistoso prevalence was obtained from primary data from our studies and secondary data of several studies with significance in the prevalence of schistosomiasis in Eggua.

Although, several issues limit the adoption of interactive exploratory analysis of data, logistics is a major problem in gathering and interpreting the data. Limited technical knowledge exist in this area of bio-statistical and bioinformatics analysis. The decision making process for the control of schistosomiasis greatly depend on the epidemiological data and this was addresses in this study.

We used interactive maps to provide information that could help to control the disease.

We are providing this Visual Analytics tool which will integrate epidemiology and molecular data with analysis for decision making and control options

Eggua Communities

This is a community made of five major provinces and other settlement that are unique and strategic with reference to their location, economic viability and geographical features. The river confluences and the annual flood is a major concern of high epidemiological significance.

The awareness about Schistosomiasis was established more than a decade ago but there is no proactive preventive measure other than Mass Drug Action.

This is one of the first communities visited after the Eggua Central.

Sagbon is well known for high deposit of lime stone and irrigated Rice farmland. It also has just one Health Center just like other communities in Eggua.

This is one of the places where the prevalence is least.

Ohumbe is closer to the border and the impact of immigrants was part of the paramerters considered in the spread and control of Schisto in this area.

Map of Eggua Community