A Formal Specification of a Data Model for Malaria Surveillance in the Developing World

The fourth Industrial Revolution(4IR), together with the COVID-19 pandemic have made a loud call for digitizing diagnosis processes. The world is now convinced that it is imperative to digitize the diagnosis of long standing diseases such as malaria for more efficient treatment and control. It has been seen that malaria control would benefit a lot from digitizing its diagnosis processes such as data gathering. We propose, in this paper, the architecture of a digital data collection system and how it is used to gather data for malaria awareness. The system is formally specified using Z notation, and based on the capability of the system, possible malaria determinants are defined and their retrieving mechanisms are discussed.
Comment: This paper has been accepted at 2024 The 7th International Conference on Information and Computer Technologies. Due to funding constraints, the paper cannot be published