Data-Driven Study of the the COVID-19 Pandemic via Age-Structured Modelling and Prediction of the Health System Failure in Brazil amid Diverse Intervention Strategies

Askery Canabarro; Elayne Tenorio; Renato Martins; Lais Martins; Samurai Brito; Rafael Chaves

The parameter g i represents the NPI policies and, as in [9] , they are not supposed to have full compliance of the individuals. Further, as a by-product such NPIs might generated other kinds of social contacts, for instance, those due to the essential services that continue running even in a mandatory quarantine. For a combination of NPIs, one should take the lowest value in each corresponding row of Table II . So, g i influences directly the spread of the disease, having strong effect on the efficacy of the infection process and can be interpreted as alterations of the β i parameter, resulting in an effective β ef f i = g i β i due to the imposed control measure. It comes from the reasonable assumption that in the early stage of the infection S ≈ N , therefore it fights the infection by reducing the number of susceptible persons. In our approach it reflects the amount of susceptible individuals undergoing the specific control measure and g i S i represents the fraction of S i not complying with the policy g i . Ahead we discussed the NPIs considered in this work along with the expected response from the population to these measures. In all cases, the compliance is not 100% effective [9] since that, for instance, many essential services are needed, so even in an intense and mandatory quarantine we supposed that 25% of the susceptible individuals are still well exposed to the infection (see the fraction 0.25 in the last column of Table II ).