Modeling And Simulation of Covid-19 Base Triage Algorithm using Coloured Petri Nets
Keywords:
COVID-19, Coronaviruses, Coloured Petri Nets, Infectious Disease Modeling, pandemicAbstract
The confirmation of a new coronavirus disease (COVID-19) case by the Cross River
State Ministry of Health, Nigeria, on 17 April 2026 underscores the continued threat
posed by emerging and re-emerging infectious diseases. Although there has been a
substantial decline in global transmission since the 2019 pandemic. The confirmed case
involved a Chinese national who arrived in Nigeria on 17 March 2026, subsequently
developed symptoms, and tested positive for SARS-CoV-2, prompting the activation of
emergency public health response measures. This incident highlights the persistent
need for robust preparedness, rapid case detection, and efficient triage systems to
prevent future outbreaks. During the 2019 pandemic, Nigeria recorded 3,155 COVID
19-related deaths, emphasizing the devastating impact of delayed detection and
response. This study presents the modelling and simulation of a COVID-19-based triage
algorithm using Coloured Petri Nets (CPN). It formally represents and validates patient
screening, clinical decision-making, isolation, referral, testing, and treatment
workflows. The proposed CPN model captures the dynamic behaviour, concurrency,
synchronization, and resource-sharing characteristics inherent in hospital triage
processes while enabling formal verification of workflow correctness. Through
simulation, the model provides a reliable framework for evaluating patient flow,
optimizing triage decisions, and minimizing delays that could facilitate disease
transmission. The developed model serves as a decision-support tool for ministries of
health, hospital management boards, emergency response teams, and frontline
healthcare workers involved in outbreak preparedness, patient triage, and COVID-19
case management across Nigeria. Beyond COVID-19, the framework offers a scalable
and adaptable platform for modelling and evaluating triage processes for future
infectious disease outbreaks. This would strengthen national public health
preparedness and emergency response capacity.
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