Utilizing supervised machine learning algorithms to develop a surveillance and response system based on symptoms of diarrhoea, contingent on the Support Vector Machine (SVM) to predict the probable disease using labelled data. Diarrhoea is amongst the top ten diseases which kill. A prototype system is developed based on the SVM algorithm. The prototype system takes six patient symptoms that which is input, from the user and the output result becomes the prognosis which may likely occur based solely on the given symptoms. Two other supervised learning models have been utilized in the prediction process, Random Forest Model (RFC) and Naïve Bayes Model (NB). Furthermore, a visualization on google maps (my maps) on the area in which a diarrhoea outbreak would likely occur. The constituency and the region of the patient will be used to place a pin on my maps, giving a visualization on the map, with a mapping structure this allows for a vivid demonstration of how diarrhoea is spreading in Eswatini. SVM received an average of 100% accuracy. The other two supervised learning models, random forest model and naïve Bayes model received 97.62% average accuracy on the same dataset. It shows that the SVM does well in data classification and with a small dataset.INDEX TERMS Diarrhoea, prognosis, supervised machine learning. I. INTRODUCTIONThis research explores ways in which acute diarrhoea can be detected at early stages within communities in Eswatini to widely reduce the chances of an outbreak, mostly in children under the age of 5. When it comes to experiencing acute diarrhoea [7] it should be short-lived. When acute diarrhoea spans over weeks, there is a major concern.The World Health organization defines acute diarrhoea ''as the passage of three or more loose or liquid stools per day'', [7]. There has been nearly 1.7 billion annually recorded global cases of childhood diarrhoeal diseases [7]. A Global Burden of Disease Study which was conducted in 2017 showed that, there have been 22167 total deaths due to diarrhoea for the past 27 year, from 1990 to 2017. The death toll of children under 5 has been 12454 in these years.The associate editor coordinating the review of this manuscript and approving it for publication was Yudong Zhang .