A modelling study highlights the power of detecting and isolating asymptomatic or very mildly affected individuals for COVID-19 epidemic management

MAYORGA, LÍA; GARCÍA SAMARTINO, CLARA; FLORES, GABRIEL; MASUELLI, SOFÍA; SÁNCHEZ, MARÍA V.; MAYORGA, LUIS S.; SÁNCHEZ, CRISTIÁN G.

BMC PUBLIC HEALTH

BIOMED CENTRAL LTD

Año: 2020 vol. 20

1471-2458

Background: Mathematical modelling of infectious diseases is a powerful tool for the design of managementpolicies and a fundamental part of the arsenal currently deployed to deal with the COVID-19 pandemic.Methods: We present a compartmental model for the disease where symptomatic and asymptomatic individualsmove separately. We introduced healthcare burden parameters allowing to infer possible containment andsuppression strategies. In addition, the model was scaled up to describe different interconnected areas, giving thepossibility to trigger regionalized measures. It was specially adjusted to Mendoza-Argentina?s parameters, but iseasily adaptable for elsewhere.Results: Overall, the simulations we carried out were notably more effective when mitigation measures were notrelaxed in between the suppressive actions. Since asymptomatics or very mildly affected patients are the vastmajority, we studied the impact of detecting and isolating them. The removal of asymptomatics from the infectiouspool remarkably lowered the effective reproduction number, healthcare burden and overall fatality. Furthermore,different suppression triggers regarding ICU occupancy were attempted. The best scenario was found to be thecombination of ICU occupancy triggers (on: 50%, off: 30%) with the detection and isolation of asymptomaticindividuals. In the ideal assumption that 45% of the asymptomatics could be detected and isolated, there would beno need for complete lockdown, and Mendoza?s healthcare system would not collapse.Conclusions: Our model and its analysis inform that the detection and isolation of all infected individuals, withoutleaving aside the asymptomatic group is the key to surpass this pandemic.