Low-code development platform for modeling and implementation of business processes to support outbreak investigations

Abstract: This article describes the functional scope of a low-code development platform for modeling and implementation of business processes to support outbreak investigations.LCDP (Low-Code Development Platforms) are development tools that allow you to create applications using a minimum amount of traditional programming code. They help speed up the software development process by reducing the need to write manual code and enabling the development of applications using visual interfaces, ready-made components, and configuration rules. They can also support business process management through various mechanisms. LCDP platforms can help build applications that support Business Process Management through visual modeling of processes, the use of ready-made components, automation mechanisms that enable the performance of specific activities or decisions as part of a business process, easy integration of various external systems, which may be necessary for business processes that require cooperation with multiple tools and applications, providing mechanisms for monitoring the course of business processes and generating reports on performance, duration and other parameters, and enabling business analysts to participate in the application development process, because they do not require deep programming knowledge.The article presents the basic functionality of the platform and refers to such architectural assumptions as integrated process management, remote access, security, reliability, flexibility, openness to integration, reporting, registers, and monitoring.Particular attention was paid to the issues of modeling business processes and building applications to support activities related to epidemic investigation during an epidemic of poisonings and foodborne diseases.Epidemiological investigation to cut the paths of epidemics of poisoning and foodborne diseases is an important process to identify, control, and prevent the further spread of the disease. This process aims to understand where the infection came from, what factors led to the outbreak, and how it can be stopped. The first step is to recognize and report an outbreak or increase in foodborne illness. This can be done by analyzing epidemiological data, e.g. reports on illnesses and hospitalizations. Detailed information is then collected from patients about their symptoms, food history, places visited, food eaten, contacts with others, etc. It is important to identify common factors and sources that may be related to the disease. The next phase is analyzing the collected data to identify trends, patterns, and potential sources of the outbreak. This may include the analysis of time-disease curves, the identification of geographic disease clusters, or the analysis of consumption clusters of specific products. Based on the analysis of data, epidemiologists create hypotheses about the possible sources of infection or ways of transmitting the disease. This may include identifying specific foods, restaurants, suppliers, or water sources. To verify the hypotheses and identify the source of the epidemic, field studies are carried out, including microbiological tests of food samples, the environment, and samples from patients and people suspected of being infected. Once the source of the outbreak has been identified, action is taken to control and disrupt transmission routes. These actions consist of withdrawing contaminated products from the market, closing the source of contamination (e.g. a restaurant), and implementing hygiene and safety measures. After an epidemic intervention, monitoring of the situation continues to confirm the effectiveness of the actions and to ensure that the epidemic has been stopped. Investigation, intervention, and outcome information is also reported to relevant public health agencies.The developed platform was used as a programming base to develop a support system for the above-mentioned activities of the State Sanitary Inspection, allowing for the detection of threats and cutting the paths of spreading the epidemic.

Keywords: human-computer interaction, monitoring, outbreak investigation, system design, LCDP, Low-code development platform, Aurea BPM

DOI: 10.54941/ahfe1004326

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