Evaluating the Demand for Nucleic Acid Testing in Different Scenarios of COVID-19 Transmission: A Simulation Study

Abstract

Abstract Introduction The 2019 novel coronavirus (COVID-19) has been recognized as the most severe human infectious disease pandemic in the past century. To enhance our ability to control potential infectious diseases in the future, this study simulated the influence of nucleic acid testing on the transmission of COVID-19 across varied scenarios. Additionally, it assessed the demand for nucleic acid testing under different circumstances, aiming to furnish a decision-making foundation for the implementation of nucleic acid screening measures, the provision of emergency materials, and the allocation of human resources. Methods Considering the transmission dynamics of COVID-19 and the preventive measures implemented by countries, we explored three distinct levels of epidemic intensity: community transmission, outbreak, and sporadic cases. Integrating the theory of scenario analysis, we formulated six hypothetical epidemic scenarios, each corresponding to possible occurrences during different phases of the pandemic. We developed an improved SEIR model, validated its accuracy using real-world data, and conducted a comprehensive analysis and prediction of COVID-19 infections under these six scenarios. Simultaneously, we assessed the testing resource requirements associated with each scenario. Results We compared the predicted number of infections simulated by the modified SEIR model with the actual reported cases in Israel to validate the model. The root mean square error (RMSE) was 350.09, and the R-squared (R 2) was 0.99, indicating a well-fitted model. Scenario 4 demonstrated the most effective prevention and control outcomes. Strengthening non-pharmaceutical interventions and increasing nucleic acid testing frequency, even under low testing capacity, resulted in a delayed epidemic peak by 78 days. The proportion of undetected cases decreased from 77.83% to 31.21%, and the overall testing demand significantly decreased, meeting maximum demand even with low testing capacity. The initiation of testing influenced case detection probability. Under high testing capacity, increasing testing frequency elevated the detection rate from 36.40% to 77.83%. Nucleic acid screening proved effective in reducing the demand for testing resources under diverse epidemic prevention and control strategies. While effective interventions and nucleic acid screening measures substantially diminished the demand for testing-related resources, varying degrees of insufficient testing capacity may still persist. Conclusions The nucleic acid detection strategy proves effective in promptly identifying and isolating infected individuals, thereby mitigating the infection peak and extending the time to peak. In situations with constrained testing capacity, implementing more stringent measures can notably decrease the number of infections and alleviate resource demands. The improved SEIR model demonstrates proficiency in predicting both reported and unreported cases, offering valuable insights for future infection risk assessments. Rapid evaluations of testing requirements across diverse scenarios can aptly address resource limitations in specific regions, offering substantial evidence for the formulation of future infectious disease testing strategies.

Keywords

• COVID-19
• Nucleic acid screening
• Dynamical model of infectious disease
• Demand assessment