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Modeling future spread of infections via mobile geolocation data and population dynamics. An application to COVID-19 in Brazil
- Source :
- PLoS ONE, Vol 15, Iss 7, p e0235732 (2020), PLoS ONE, Repositório Institucional da USP (Biblioteca Digital da Produção Intelectual), Universidade de São Paulo (USP), instacron:USP, PLOS ONE, 15(7):e0235732
- Publication Year :
- 2020
- Publisher :
- Public Library of Science (PLoS), 2020.
-
Abstract
- Mobile geolocation data is a valuable asset in the assessment of movement patterns of a population. Once a highly contagious disease takes place in a location the movement patterns aid in predicting the potential spatial spreading of the disease, hence mobile data becomes a crucial tool to epidemic models. In this work, based on millions of anonymized mobile visits data in Brazil, we investigate the most probable spreading patterns of the COVID-19 within states of Brazil. The study is intended to help public administrators in action plans and resources allocation, whilst studying how mobile geolocation data may be employed as a measure of population mobility during an epidemic. This study focuses on the states of São Paulo and Rio de Janeiro during the period of March 2020, when the disease first started to spread in these states. Metapopulation models for the disease spread were simulated in order to evaluate the risk of infection of each city within the states, by ranking them according to the time the disease will take to infect each city. We observed that, although the high-risk regions are those closer to the capital cities, where the outbreak has started, there are also cities in the countryside with great risk. The mathematical framework developed in this paper is quite general and may be applied to locations around the world to evaluate the risk of infection by diseases, in special the COVID-19, when geolocation data is available.
- Subjects :
- Geographic mobility
Epidemiology
Economics
Social Sciences
Geographical locations
Consumer Electronics
Disease Outbreaks
COVID-19
Brazil
Infectious disease epidemiology
Simulation and modeling
Health economics
Musculoskeletal system
Cell phones
Consumer electronics
k means clustering
0302 clinical medicine
Mathematical and Statistical Techniques
Medicine and Health Sciences
Cluster Analysis
Health Status Indicators
030212 general & internal medicine
Musculoskeletal System
0303 health sciences
education.field_of_study
Travel
Multidisciplinary
Risk of infection
Simulation and Modeling
Environmental resource management
Mobile Applications
Contagious disease
Geography
Infectious Diseases
Engineering and Technology
Medicine
Anatomy
Coronavirus Infections
Research Article
DISTRIBUIÇÃO ESPACIAL
Science
Population
Pneumonia, Viral
Equipment
Research and Analysis Methods
Models, Biological
Infectious Disease Epidemiology
03 medical and health sciences
Health Economics
medicine
Humans
Computer Simulation
Asset (economics)
Cities
education
Pandemics
030304 developmental biology
Communication Equipment
Population Density
business.industry
Mobile broadband
Biology and Life Sciences
South America
medicine.disease
Health Care
Geolocation
K Means Clustering
Rural area
People and places
Cell Phones
Electronics
business
Subjects
Details
- Language :
- English
- ISSN :
- 19326203
- Volume :
- 15
- Issue :
- 7
- Database :
- OpenAIRE
- Journal :
- PLoS ONE
- Accession number :
- edsair.doi.dedup.....eaba9f646d5331598a1887d2fe75ecb7