Back to Search
Start Over
Forecasting the novel coronavirus COVID-19
- Source :
- PLoS ONE, Vol 15, Iss 3, p e0231236 (2020), Petropoulos, F & Makridakis, S 2020, ' Forecasting the novel coronavirus COVID-19 ', PLoS ONE, vol. 15, no. 3, e0231236 . https://doi.org/10.1371/ journal.pone.0231236, PLoS ONE, PLOS ONE, 15(3):e0231236
- Publication Year :
- 2020
- Publisher :
- Public Library of Science (PLoS), 2020.
-
Abstract
- What will be the global impact of the novel coronavirus (COVID-19)? Answering this question requires accurate forecasting the spread of confirmed cases as well as analysis of the number of deaths and recoveries. Forecasting, however, requires ample historical data. At the same time, no prediction is certain as the future rarely repeats itself in the same way as the past. Moreover, forecasts are influenced by the reliability of the data, vested interests, and what variables are being predicted. Also, psychological factors play a significant role in how people perceive and react to the danger from the disease and the fear that it may affect them personally. This paper introduces an objective approach to predicting the continuation of the COVID-19 using a simple, but powerful method to do so. Assuming that the data used is reliable and that the future will continue to follow the past pattern of the disease, our forecasts suggest a continuing increase in the confirmed COVID-19 cases with sizable associated uncertainty. The risks are far from symmetric as underestimating its spread like a pandemic and not doing enough to contain it is much more severe than overspending and being over careful when it will not be needed. This paper describes the timeline of a live forecasting exercise with massive potential implications for planning and decision making and provides objective forecasts for the confirmed cases of COVID-19.
- Subjects :
- Viral Diseases
Research Validity
Computer science
Emotions
Social Sciences
02 engineering and technology
medicine.disease_cause
Global Health
Animal Diseases
Geographical Locations
Mathematical and Statistical Techniques
Cognition
Sociology
Zoonoses
Pandemic
0202 electrical engineering, electronic engineering, information engineering
Global health
Medicine and Health Sciences
Psychology
Reliability (statistics)
0303 health sciences
Multidisciplinary
Agricultural and Biological Sciences(all)
Viral Epidemiology
Statistics
Uncertainty
Social Communication
Fear
Research Assessment
Infectious Diseases
COVID-19
Decision making
Research validity
China
SARS
Forecasting
Avian influenza
Social media
Social Networks
Physical Sciences
Medicine
020201 artificial intelligence & image processing
Coronavirus Infections
Network Analysis
Research Article
Avian Influenza
2019-20 coronavirus outbreak
Computer and Information Sciences
Asia
Coronavirus disease 2019 (COVID-19)
Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)
Science
Decision Making
Pneumonia, Viral
Research and Analysis Methods
03 medical and health sciences
Betacoronavirus
Animal Influenza
medicine
Humans
Statistical Methods
General
Pandemics
030304 developmental biology
Actuarial science
Models, Statistical
SARS-CoV-2
Biochemistry, Genetics and Molecular Biology(all)
Cognitive Psychology
Reproducibility of Results
Biology and Life Sciences
Influenza A virus subtype H5N1
Communications
People and Places
Cognitive Science
Zoology
Social Media
Mathematics
Neuroscience
Subjects
Details
- Language :
- English
- ISSN :
- 19326203
- Volume :
- 15
- Issue :
- 3
- Database :
- OpenAIRE
- Journal :
- PLoS ONE
- Accession number :
- edsair.doi.dedup.....e246d1d797c5fd8bc80fe6a4336d5c9a