Modelling the COVID-19 epidemic and implementation of population-wide interventions in Italy methods
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Main
Figure shows, if the lockdown is weakened, a sudden and strong increase of the spread of disease, a prolonged emergency and more deaths (0.12% of the population in the first 350 days). Figure shows the benefits of stricter lockdown measures: after 350 days, 0.41% of the population would contract the virus (0.30% diagnosed) and 0.04% of the population would die. Fig. 3 The effect of lockdown. a - d, Epidemic evolution predicted by the model for the COVID-19 outbreak in Italy when, after day 50, the social distancing countermeasures are weakened, leading to a larger R 0 = 0.98 ( a, b ), or strengthened, leading to a smaller R 0 = 0.50 ( c, d ). a, c, The difference between the actual (real cases) and perceived (diagnosed cases) evolution of the epidemics. The plots in b and d distinguish between the different categories of infected patients: non-diag...
Main
A policy of population-wide testing and contact tracing would help to rapidly end the epidemic, as suggested by Peto. Figure shows the effect of such measures: the peak would be reached sooner and, after 350 days, 0.43% of the population would contract the virus (0.33% diagnosed), with an estimated 0.05% dying. Figure shows the effect of combining a milder lockdown with widespread testing and contact tracing: after 350 days, 0.52% of the population would contract the virus (0.41% diagnosed) and 0.05% would die. Fig. 4 The effect of testing. a - d, Epidemic evolution predicted by the model for the COVID-19 outbreak in Italy when, after day 50, massive testing and contact tracing is enforced ( a, b ), leading to R 0 = 0.59, as well as in parallel with weakening social-distancing measures ( c, d ), leading to R 0 = 0.77. The plots in a and c show the d...
Fit of the model for the COVID-19 outbreak in Italy
Extended Data Fig. shows that, in the absence of further countermeasures after day 22 (just closing schools and hygiene recommendations), we have α = 0.422, γ = 0.285 and β = δ = 0.0057, hence R 0 = 1.66 and the model predicts an evolution that leads to 73% of the population having contracted the virus (and ~64% having been diagnosed) and ~5.2% of the population having died because of the contagion over a 300-day horizon (Extended Data Fig. ). The peak of the number of concurrently infected individuals occurs at around 76 days and amounts to ~44% of the population; however, the peak of concurrently diagnosed infected individuals occurs later, around 82 days, and amounts to 39% of the population. Extended Data Fig. shows how the different subpopulations of infected individuals evolve over time, and it...
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Figure shows, if the lockdown is weakened, a sudden and strong increase of the spread of disease, a prolonged emergency and more deaths (0.12% of the population in the first 350 days). Figure shows the benefits of stricter lockdown measures: after 350 days, 0.41% of the population would contract the virus (0.30% diagnosed) and 0.04% of the population would die. Fig. 3 The effect of lockdown. a - d, Epidemic evolution predicted by the model for the COVID-19 outbreak in Italy when, after day 50, the social distancing countermeasures are weakened, leading to a larger R 0 = 0.98 ( a, b ), or strengthened, leading to a smaller R 0 = 0.50 ( c, d ). a, c, The difference between the actual (real cases) and perceived (diagnosed cases) evolution of the epidemics. The plots in b and d distinguish between the different categories of infected patients: non-diagnosed asymptomatic (ND AS), diagnosed asymptomatic (D AS), non-diagnosed symptomatic (ND S), diagnosed symptomatic (D S) and diagnosed with life-threatening symptoms (D IC). Note that a, c and b, d have different scales.
A policy of population-wide testing and contact tracing would help to rapidly end the epidemic, as suggested by Peto. Figure shows the effect of such measures: the peak would be reached sooner and, after 350 days, 0.43% of the population would contract the virus (0.33% diagnosed), with an estimated 0.05% dying. Figure shows the effect of combining a milder lockdown with widespread testing and contact tracing: after 350 days, 0.52% of the population would contract the virus (0.41% diagnosed) and 0.05% would die. Fig. 4 The effect of testing. a - d, Epidemic evolution predicted by the model for the COVID-19 outbreak in Italy when, after day 50, massive testing and contact tracing is enforced ( a, b ), leading to R 0 = 0.59, as well as in parallel with weakening social-distancing measures ( c, d ), leading to R 0 = 0.77. The plots in a and c show the difference between the actual (real cases) and the perceived (diagnosed cases) evolution of the epidemics. The plots in b and d distinguish between the different categories of infected patients: non-diagnosed asymptomatic (ND AS), diagnosed asymptomatic (D AS), non-diagnosed symptomatic (ND S), diagn...
Extended Data Fig. shows that, in the absence of further countermeasures after day 22 (just closing schools and hygiene recommendations), we have α = 0.422, γ = 0.285 and β = δ = 0.0057, hence R 0 = 1.66 and the model predicts an evolution that leads to 73% of the population having contracted the virus (and ~64% having been diagnosed) and ~5.2% of the population having died because of the contagion over a 300-day horizon (Extended Data Fig. ). The peak of the number of concurrently infected individuals occurs at around 76 days and amounts to ~44% of the population; however, the peak of concurrently diagnosed infected individuals occurs later, around 82 days, and amounts to 39% of the population. Extended Data Fig. shows how the different subpopulations of infected individuals evolve over time, and it is interesting to notice that each subpopulation reaches its peak at a different time. In particular, the fraction of infected who need intensive care reaches its peak, almost 16.5% of the population, after 107 days.
Machine-readable layer
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