Multivariate Prediction Network Model for epidemic progression to study the effects of lockdown time and coverage on a closed community on theoretical and real scenarios of COVID-19

The aim of this study was to develop a realistic network model to predict the relationship between lockdown duration and coverage in controlling the progression of the incidence curve of an epidemic with the characteristics of COVID-19 in two scenarios (1) a closed and non-immune population, and (2) a real scenario from State of Rio de Janeiro from May 6^th 2020.

Effects of lockdown time and rate on the progression of an epidemic incidence curve in a virtual population of 10 thousand subjects. Predictor variables were reproductive values established in the most recent literature (R0 =2.7 and 5.7, and Re = 1.28 from Rio de Janeiro State at May 6^th), without lockdown and with coverages of 25%, 50%, and 90% for 21, 35, 70, and 140 days in up to 13 different scenarios for each R0/Re, where individuals remained infected and transmitters for 14 days. We estimated model validity in theoretical and real scenarios respectively by applying an exponential model on the incidence curve with no lockdown with growth rate coefficient observed in realistic scenarios, and (2) fitting real data series from RJ upon simulated data, respectively.

For R0=5.7, the flattening of the curve occurs only with long lockdown periods (70 and 140 days) with a 90% coverage. For R0=2.7, coverages of 25 and 50% also result in curve flattening and reduction of total cases, provided they occur for a long period (70 days or more). For realistic scenario in Rio de Janeiro, lockdowns +25% or more from May 6^th during 140 days showed expressive flattening and number of COVID cases two to five times lower. If a more intense coverage lockdown (about +25 to +50% as much as the current one) will be implemented until June 6^th during at least 70 days, it is still possible reduce nearly 40-50% the impact of pandemy in state of Rio de Janeiro.

These data corroborate the importance of lockdown duration regardless of virus transmission and sometimes of intensity of coverage, either in realistic or theoretical scenarios of COVID-10 epidemics. Even later, the improvement of lockdown coverage can be effective to minimize the impact of epidemic.