# Ensemble Machine Learning Model to Predict the Waterborne Syndrome
###### Abstract  
The COVID-19 epidemic has highlighted the significance of sanitization and maintaining hygienic access to clean water to reduce mortality and morbidity cases worldwide. Diarrhea is one of the prevalent waterborne diseases caused due to contaminated water in many low-income countries with similar living conditions. According to the latest statistics from the World Health Organization (WHO), diarrhea is among the top five primary causes of death worldwide in low-income nations. The condition affects people in every age group due to a lack of proper water used for daily living. In this study, a stacking ensemble machine learning model was employed against traditional models to extract clinical knowledge for better understanding patients' characteristics; disease prevalence; hygienic conditions; quality of water used for cooking, bathing, and toiletries; chemicals used; therapist's medications; and symptoms that are reflected in the field study data. Results revealed that the ensemble model provides higher accuracy with 98.90% as part of training and testing phases when experimented against frequently used J48, Naive Bayes, SVM, NN, PART, Random Forest, and Logistic Regression models. Managing outcomes of this research in the early stages could assist people in low-income countries to have a better lifestyle, fewer infections, and minimize expensive hospital visits. waterborne disease; classification algorithm; machine learning; data mining; retrospective analysis; artificial intelligence; public health; prevalence and management  
1  
<ccs2012  
six out of ten do not have access to sufficiently managed sanitation facilities [3]. The statistic is particularly alarming in developing countries: poor water and sanitation conditions account for 80% of illnesses in developing countries. Furthermore, 88% of diarrheal diseases are linked to the unavailability of safe drinking water, inadequate sanitation, and lack of hygienic conditions [4]. Additionally, patients with a water-related disease occupy half of the world's hospital beds. One-tenth of the deaths in countries with low and middle-income earners are attributed to diarrhea-related diseases [5]. Although fever, cough, and shortness of breath were among the prevalent presenting symptoms during the COVID-19 pandemic, gastrointestinal symptoms such as diarrhea were frequently identified among COVID-19 patients [6]. Hence, the UN and other world health organizations are urging governments worldwide, particularly in low-income COVID-19-affected areas, to prioritize public health, which includes providing safe drinking water to their citizens [7]. To classify it as safe for daily use, water used for domestic purposes must be free from pathogenic agents, any unknown, harmful chemical substances, and have a pleasant taste. Unfortunately, during water distribution through the streets to homes, several physical, chemical, and biological transformations occur. Various water sources, including the supply pipelines, experience widespread contamination by microorganisms. Although the gap between urban and rural development of basic municipal necessities has reduced in recent years, urban areas still enjoy better supplies of drinking water and better sanitation facilities than rural areas [8]. Due to a lack of safe water supply management and inadequate sanitation facilities, many waterborne diseases, including diarrhea, are largely found to emerge in rural regions. These waterborne diseases that lead to diarrhea could be reduced from one-third to one-fourth simply through proper sanitation management practices. The authors in [9] discovered that the risk of diarrhea-related morbidity could be reduced by 25% by improving the water supply, by 31% by maintaining water quality, and by 32% by facilitating proper sanitation. To address these challenges, which are also part of the COVID-19 pandemic and hygienic requirements, we consider discovering the latest evidence on the characteristics, medications, and living conditions of diarrhea-infected patients in low-income nations.