Spatio-temporal propagation of COVID-19 pandemics

Abstract

<jats:p>The new coronavirus known as COVID-19 is spread world-wide since December 2019. Without any vaccination or medicine, the means of controlling it are limited to quarantine and social distancing. Here we study the spatio-temporal propagation of the first wave of the COVID-19 virus in China and compare it to other global locations. We provide a comprehensive picture of the spatial propagation from Hubei to other provinces in China in terms of distance, population size, and human mobility and their scaling relations. Since strict quarantine has been usually applied between cities, more insight about the temporal evolution of the disease can be obtained by analyzing the epidemic within cities, especially the time evolution of the infection, death, and recovery rates which affected by policies. We study and compare the infection rate in different cities in China and provinces in Italy and find that the disease spread is characterized by a two-stages process. At early times, at order of few days, the infection rate is close to a constant probably due to the lack of means to detect infected individuals before infection symptoms are observed. Then at later times it decays approximately exponentially due to quarantines. The time evolution of the death and recovery rates also distinguish between these two stages and reflect the health system situation which could be overloaded.</jats:p>

Calculation of epidemic arrival time distributions using branching processes

“…Arrival time distributions as observed in 15 000 simulations perfectly match survival probabilities as calculated numerically using Eq. (5). Unlike the γ 1 domain, where survival probabilities decay approximately logistically, here we observe roughly exponential decay.…”

“…Similarly, the 2009 H1N1 flu pandemic first reported in Mexico was able to reach both Europe and Asia within a fortnight [4]. Now, in 2020, we see that coronavirus SARS-CoV-2 has spread quickly throughout China [5] and across the world [6,7], reaching all but a handful of countries within a few short months.…”

COVID-19 case-fatality rate and demographic and socioeconomic influencers: worldwide spatial regression analysis based on country-level data

“…The spatial spread is one of the most important properties of COVID-19, a characteristic which mainly depends on the epidemic mechanism, human mobility and control strategy. 11 Spatial statistical methods are frequently used to uncover relationships between spatiotemporal patterns of infectious diseases and host or environmental characteristics, 12 to generate detailed maps to visualise the distribution of the diseases’ morbidity or mortality 13 14 and to identify hotspots, clusters and potential risk factors. 15–18 …”

The Spatio-Temporal Characteristics and Influencing Factors of Covid-19 Spread in Shenzhen, China—An Analysis Based on 417 Cases

“…One of the most important features of an epidemic is the spatial transmission, which mainly depends on epidemic mechanisms, human mobility, and control strategies [ 13 ]. When deciding on timetables for local reopening activities, the spatio-temporal characteristics and trends of COVID-19 need to be considered [ 14 ].…”