Abstract
We present a complex SIR syndemic model for misdiagnoses and missed diagnoses between
COVID-19 and malaria. The objective of the study was to design and analyse a quasi-steady
state deterministic mathematical model to determine the effect of COVID-19 and malaria
misdiagnoses and missed diagnoses. We then designed and analysed the stochastic equivalent
model in order to compute the probability of disease extinction and disease outbreak. We
carried out mathematical analysis and numerical simulations to further understand the impact
of misdiagnoses and missed diagnoses on both infections. We also computed the probability of
disease extinction or outbreak when R0 > 1 for different disease initial states. We presented
the numerical data and estimated the impact of misdiagnoses and missed diagnoses between
COVID-19 and malaria. The probability of disease outbreak increases when more misdiagnoses
and missed diagnoses between malaria and COVID-19 occur. The more members with COVID-
19 are misdiagnosed with malaria or the COVID-19 diagnosis is missed, the more COVID-19
cases persist and there is a high chance of a COVID-19 outbreak. The more members with
malaria are misdiagnosed with COVID-19 or the malaria diagnosis is missed, the more malaria
cases persist and there is a high chance of a malaria outbreak.