Visual analytics of COVID-19 dissemination in S\~ao Paulo state, Brazil

TL;DR

This paper introduces a visual analytics tool that monitors COVID-19 spread in São Paulo, Brazil, by analyzing city neighborhoods and time periods to support decision-making and policy assessment.

Contribution

The paper presents a novel visual analytics approach using k-nearest neighbors to analyze COVID-19 dissemination across cities and time periods.

Findings

Effective visualization of COVID-19 spread in São Paulo

Insights into the impact of isolation policies

Potential to assist decision-makers in epidemic control

Abstract

Visual analytics techniques are useful tools to support decision-making and cope with increasing data, which is particularly important when monitoring natural or artificial phenomena. When monitoring disease progression, visual analytics approaches help decision-makers choose to understand or even prevent dissemination paths. In this paper, we propose a new visual analytics tool for monitoring COVID-19 dissemination. We use k-nearest neighbors of cities to mimic neighboring cities and analyze COVID-19 dissemination based on the comparison of a city under consideration and its neighborhood. Moreover, such analysis is performed based on periods, which facilitates the assessment of isolation policies. We validate our tool by analyzing the progression of COVID-19 in neighboring cities of S\~ao Paulo state, Brazil.