Data availability is key for modeling of wastewater treatment processes. However, process data are characterized by missing values and outliers. This study applied a self-organizing map (SOM), to fill in missing values and replace outliers in wastewater treatment data from Kauma Sewage Treatment Plant in Lilongwe, Malawi. We used primary and secondary wastewater data and executed the SOM algorithm to fill missing values and replace outliers in effluent pH, biochemical oxygen demand, and dissolved oxygen. The results suggest that SOM algorithm is reliable in filling gaps in wastewater time series data with less than 50% missing values with correlation coefficient (R) values of >0.90. The SOM algorithm failed to reliably fill gaps and replace outliers in time series data with >50% missing values. For instance, high mean square error (MSE) values of 3,655.57, 10.62, and 2,153.34 for pH, DO, and BOD, respectively, were registered in datasets with more than 50% missing values, while very small MSE values (MSE ≈ 0) were associated with effluent pH, BOD, and DO data with missing values of >50%. Practitioners can use this approach to improve the planning and management of wastewater treatment facilities where available data records are riddled with missing observations.

This study is based on the evidence collected during the “Technical e-Learning Course on Wastewater Treatment”, an international training project developed in 2020 in Italy by the Hydroaid Association, in collaboration with Turin Polytechnic. This work intended to address the sustainability of urban sanitation in various African countries, which the world of international cooperation has been looking at in recent years with growing interest. A comparative analysis of the current strategies and technological solutions was conducted. Data and information reported by the project participants were elaborated and verified. Four African countries—Benin, Egypt, Ethiopia, and Malawi—were considered and two relevant case studies among those proposed by the participants were presented. Starting from this analysis, significant elements about the status and coverage of wastewater management were extracted and reported. The analysis of existing wastewater treatment plants (WWTPs) allowed evaluating their design features and current status of operation. Considerations about the environmental, economic, social, and technical sustainability of wastewater treatment and management were finally reported. Conducting such an analysis provided support in identifying the best practices and the most recurrent problems linked to the various African contexts, which need to be considered for a complete definition of the planning strategy for accessible, efficient, and sustainable sanitation infrastructures.