A Poisson Autoregressive Model to Understand COVID-19 Contagion Dynamics
Current Language EN
English English Türkçe Türkçe Español Español Português Português Pусский Pусский Filipino Filipino Tiếng Việt Tiếng Việt हिन्दी हिन्दी العربية العربية বাংলা বাংলা Deutsch Deutsch 中文 中文

A Poisson Autoregressive Model to Understand COVID-19 Contagion Dynamics

Arianna Agosto;Paolo Giudici;Agosto, Arianna;Giudici, Paolo;
risks 2020 Vol. 8 pp. 77-
161
agosto2020risksa

Abstract

We present a statistical model which can be employed to understand the contagion dynamics of the COVID-19, which can heavily impact health, economics and finance. The model is a Poisson autoregression of the daily new observed cases, and can reveal whether contagion has a trend, and where is each country on that trend. Model results are exemplified from some observed series.

Keywords

contagion poisson autoregressive models predictive monitoring

Access

DOI:
10.3390/risks8030077
URL:
https://www.mdpi.com/2227-9091/8/3/77/htm

Citation

ID: 114841
Ref Key: agosto2020risksa
Use this key to autocite in SciMatic or Thesis Manager

References

References

No Bibliography

Blockchain Verification

Account:
NFT Contract Address:
0x95644003c57E6F55A65596E3D9Eac6813e3566dA
Article ID:
114841
Unique Identifier:
10.3390/risks8030077
Network:
Scimatic Chain (ID: 481)
Blockchain Readiness Checklist
Authors
Abstract
Journal Name
Year
Title
5/5
Creates 1,000,000 NFT tokens for this article
Token Features:
  • ERC-1155 Standard NFT
  • 1 Million Supply per Article
  • Transferable via MetaMask
  • Permanent Blockchain Record
Blockchain QR Code
Scan with Saymatik Web3.0 Wallet
Gas fees required in SCI Coins
Buy SCI

Saymatik Web3.0 Wallet

Google Play
App Store