COVID-19 most vulnerable Mexican cities lack the public health infrastructure to face the pandemic: a new temporally-explicit model

Wesley Dattilo; Alcides Castro e Silva; Roger Guevara; Ian MacGregor-Fors; Servio Pontes Ribeiro

We modeled the time that would take to overload the intensive care units available in the public healthcare system of each focal city under the COVID-19 scenario that assumed no social distancing. Data regarding the existing public healthcare infrastructure was taken from the Mexican Health Secretary (19) . This calculation was performed for every simulated day by balancing the number of people that would require an intensive care unit, as well as those that recover or die (estimated by our SIR-Net model). For this case, ΔN represents the variation of the amount of hospitalized patients in a given intensive care unit, in such way that ΔN = (I1-I2) Δt, where I1 is the rate of occupation of intensive care units and I2 the rate at which the units are made available either because of recovery or death of patients. Given that the unit of time in our models is the day, Δt = 1, and ΔN = Nt+1-Nt = I1-I2, or Nt+1 = Nt + (I1-I2). In this case, factor I1 was calculated as a fraction of infected patients (5%) that would require intensive care units, and to estimate I2 and Nt, we considered an average of 10 days in intensive care for each patient admitted at this level (following 20). Therefore, overloads occur at day t in which Nt is higher than the number of intensive care units available in the public healthcare system of a given city.