Cholera epidemic remains a public threat throughout history, affecting vulnerable population living with unreliable water and substandard sanitary conditions. Various studies have observed that the occurrence of cholera has strong linkage with environmental factors such as climate change and geographical location. Climate change has been strongly linked to the seasonal occurrence and widespread of cholera through the creation of weather patterns that favor the disease’s transmission, infection, and the growth of Vibrio cholerae, which cause the disease. Over the past decades, there have been great achievements in developing epidemic models for the proper prediction of cholera. However, the integration of weather variables and use of machine learning techniques have not been explicitly deployed in modeling cholera epidemics in Tanzania due to the challenges that come with its datasets such as imbalanced data and missing information. This paper explores the use of machine learning techniques to model cholera epidemics with linkage to seasonal weather changes while overcoming the data imbalance problem. Adaptive Synthetic Sampling Approach (ADASYN) and Principal Component Analysis (PCA) were used to the restore sampling balance and dimensional of the dataset. In addition, sensitivity, specificity, and balanced-accuracy metrics were used to evaluate the performance of the seven models. Based on the results of the Wilcoxon sign-rank test and features of the models, XGBoost classifier was selected to be the best model for the study. Overall results improved our understanding of the significant roles of machine learning strategies in health-care data. However, the study could not be treated as a time series problem due to the data collection bias. The study recommends a review of health-care systems in order to facilitate quality data collection and deployment of machine learning techniques.

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Introduction 1.1Background introduction Cholera is an acute intestinal infectious disease caused by Vibrio cholerae (V. cholerae) [1]. It is an important public health problem worldwide [2]. The dynamics of cholera in most developing countries are related to several interactions between human beings, pathophysiological, and environmental [3, 4]. These environmental factors include geographical location and climatology factors. Climatology factors are climate variables such as temperature, rainfall, humidity, and wind. *Author for correspondenceEnvironmental and climatological factors affect cholera due to the facts that, V. cholerae are strongly controlled by water temperature, salinity, and the presence of copepods which in return, are controlled by climate variability [5] and seasonal dynamics of weather changes [6]. In order to counteract the climate water-borne epidemics, there have been a number of studies and reviews over the past fifty years on health and environmental related problems and policies on climate adaptation in Tanzania [7]. However, up to date, there is no single policy in the country addressing climate change impact on waterborne epidemics. Most initiatives and efforts have focused on providing medical interventions in response to the cholera outbreaks and much less attention has been directed towards investing in the

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