Diffusive process under Lifshitz scaling and pandemic scenarios

TL;DR

This paper introduces a novel continuous diffusion model based on Lifshitz scaling to describe COVID-19 spread, successfully fitting data from Germany, Spain, and specific Brazilian cities, and predicting effects of lockdown measures.

Contribution

The paper develops a new diffusion model with a dynamic diffusion coefficient under Lifshitz scaling, capturing complex virus spread behaviors and fitting real pandemic data.

Findings

Successfully modeled COVID-19 active cases in Germany and Spain.

Predicted pandemic evolution in Brazil with different scenarios.

Showed how lockdown measures can flatten infection curves.

Abstract

We here propose to model active and cumulative cases data from COVID-19 by a continuous effective model based on a modified diffusion equation under Lifshitz scaling with a dynamic diffusion coefficient. The proposed model is rich enough to capture different aspects of a complex virus diffusion as humanity has been recently facing. The model being continuous it is bound to be solved analytically and/or numerically. So, we investigate two possible models where the diffusion coefficient associated with possible types of contamination are captured by some specific profiles. The active cases curves here derived were able to successfully describe the pandemic behavior of Germany and Spain. Moreover, we also predict some scenarios for the evolution of COVID-19 in Brazil. Furthermore, we depicted the cumulative cases curves of COVID-19, reproducing the spreading of the pandemic between the cities of S\~ao Paulo and S\~ao Jos\'e dos Campos, Brazil. The scenarios also unveil how the lockdown measures can flatten the contamination curves. We can find the best profile of the diffusion coefficient that better fit the real data of pandemic.