Fuzzy expert systems and GIS for cholera health risk
Cholera is listed as an internationally quarantinable disease by the International Health Organization, and it is one of the most researched communicable diseases, yet it is still wreaking havoc on countries in Southern and Eastern Africa. Outbreaks in 2000 were traced to the uMhlathuze River in the northern part of the KwaZulu-Natal Province. Risk factors for cholera outbreaks include a hot and humid climate and socio-economic factors. The CSIR, Council for Scientific and Industrial Research, has used GIS tools to assess likely locations for outbreaks. Their models use the assumption that environmental conditions like algal blooms trigger Vibrio, the bacteria that cause cholera, growth. If there is Vibrio in the water, spread of the disease then depends on human access to safe water. This risk potential model was designed to predict cholera outbreaks and hopefully prevent them in the future.
By researching the environment that cholera outbreaks occur in and assessing the risk of outbreaks, they hope to reduce the spread of cholera through well planned resource allocation. The model below describes how a cholera outbreak can be caused by an algal bloom.
The cholera outbreak potential model takes into account average annual rainfall, mean maximum daily temperature on a monthly basis and ‘month of first rains’ per pixel (salts from the first rain run into the river affecting the salinity). Results from the model show long term cholera outbreak risk. However, results do not show location and time of the outbreaks. Expanding the model will incorporate remote sensing data to supply input information for data like phytoplankton levels and the spread of algal blooms. Field data will need to be taken for data like temperature, daily rainfall, dissolved oxygen levels, salinity, oxidization, reduction potential, presence of bacteria, and pH. The model will take into account the weather data around the time of past cholera outbreaks, and predictions of future outbreaks can be made. Funding has been given to this project to make remote sensing possible.
Fleming, Gavin; Merwe, Marna van der; McFerren, Graeme. (2006). Fuzzy expert systems and GIS for cholera health risk prediction in southern Africa. Science Direct. Retrieved from