Figure 3

Equality and allocation of resources in drug dissemination. To understand the roots of the dramatically improved performance of decentralized vs. centralized we examined the level of inequality in the local efficiencies \({{\epsilon }}_{{\rm{Res}},n}\) via the Gini coefficient (5). (a) Gini vs. C for centralized (yellow) and decentralized (green) mitigation. While the latter is egalitarian by nature, having a low Gini coefficient, the former is extremely uneven, with few nodes that benefit from high \({{\epsilon }}_{{\rm{Res}},n}\) and a majority of nodes that remain deprived. This indicates that uneven allocation of resources (Gini), and not the slower production/shipping rates (C), is the main obstacle for efficient mitigation. (b) The probability density \(P({{\epsilon }}_{{\rm{Res}}})\) under centralized mitigation, as obtained for different capacity levels C. We observe a coexistence of a minority of well treated nodes (peak around \({{\epsilon }}_{{\rm{Res}}}\approx 1\), see inset) and a majority of nodes with varying efficiency levels. (c) In contrast, under decentralized mitigation we observe a bounded \(P({{\epsilon }}_{{\rm{Res}}})\), whose mean efficiency (peak) approaches \({{\epsilon }}_{{\rm{Res}}}=1\) uniformly as C is increased. This represents an even allocation of benefits, in which most nodes witness a similar rise in efficiency as capacity is increased.