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

TL;DR

This paper presents a formal Z notation specification of a digital data collection system designed for malaria surveillance, aiming to improve disease diagnosis and control through digitized data gathering.

Contribution

It introduces a formal architecture for a malaria data collection system and defines mechanisms for retrieving malaria determinants, enhancing digital disease monitoring.

Findings

Formal specification of the data collection system using Z notation

Identification of malaria determinants and retrieval mechanisms

Framework for digitizing malaria surveillance processes

Abstract

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.