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Projections of Ebola outbreak size and duration with and without vaccine use in Équateur, Democratic Republic of Congo, as of May 27, 2018
- Source :
- PLoS ONE, Vol 14, Iss 3, p e0213190 (2019), PLoS ONE, PLOS ONE, PloS one, vol 14, iss 3
- Publication Year :
- 2019
- Publisher :
- Public Library of Science (PLoS), 2019.
-
Abstract
- As of May 27, 2018, 6 suspected, 13 probable and 35 confirmed cases of Ebola virus disease (EVD) had been reported in Équateur Province, Democratic Republic of Congo. We used reported case counts and time series from prior outbreaks to estimate the total outbreak size and duration with and without vaccine use. We modeled Ebola virus transmission using a stochastic branching process model that included reproduction numbers from past Ebola outbreaks and a particle filtering method to generate a probabilistic projection of the outbreak size and duration conditioned on its reported trajectory to date; modeled using high (62%), low (44%), and zero (0%) estimates of vaccination coverage (after deployment). Additionally, we used the time series for 18 prior Ebola outbreaks from 1976 to 2016 to parameterize the Thiel-Sen regression model predicting the outbreak size from the number of observed cases from April 4 to May 27. We used these techniques on probable and confirmed case counts with and without inclusion of suspected cases. Probabilistic projections were scored against the actual outbreak size of 54 EVD cases, using a log-likelihood score. With the stochastic model, using high, low, and zero estimates of vaccination coverage, the median outbreak sizes for probable and confirmed cases were 82 cases (95% prediction interval [PI]: 55, 156), 104 cases (95% PI: 58, 271), and 213 cases (95% PI: 64, 1450), respectively. With the Thiel-Sen regression model, the median outbreak size was estimated to be 65.0 probable and confirmed cases (95% PI: 48.8, 119.7). Among our three mathematical models, the stochastic model with suspected cases and high vaccine coverage predicted total outbreak sizes closest to the true outcome. Relatively simple mathematical models updated in real time may inform outbreak response teams with projections of total outbreak size and duration.
- Subjects :
- RNA viruses
and promotion of well-being
Viral Diseases
Epidemiology
medicine.disease_cause
Pathology and Laboratory Medicine
law.invention
Disease Outbreaks
0302 clinical medicine
Mathematical and Statistical Techniques
Theoretical
Models
law
Statistics
Medicine and Health Sciences
Public and Occupational Health
030212 general & internal medicine
Vaccines
Multidisciplinary
Mathematical Models
Vaccination
Regression analysis
General Medicine
Vaccination and Immunization
3. Good health
Transmission (mechanics)
Infectious Diseases
3.4 Vaccines
Medical Microbiology
Filoviruses
Viral Pathogens
Ebola
Viruses
Physical Sciences
Democratic Republic of the Congo
Medicine
Pathogens
Infection
General Agricultural and Biological Sciences
Ebola Virus
Research Article
Neglected Tropical Diseases
medicine.medical_specialty
Infectious Disease Control
General Science & Technology
Science
030231 tropical medicine
Immunology
Biology
Research and Analysis Methods
Microbiology
Ebola Hemorrhagic Fever
General Biochemistry, Genetics and Molecular Biology
Vaccine Related
03 medical and health sciences
Virology
medicine
Humans
Microbial Pathogens
Viral Hemorrhagic Fevers
Ebola virus
Hemorrhagic Fever Viruses
Prevention
Organisms
Prediction interval
Outbreak
Biology and Life Sciences
Viral Vaccines
Hemorrhagic Fever, Ebola
Models, Theoretical
Prevention of disease and conditions
Tropical Diseases
Probability Theory
Probability Distribution
Good Health and Well Being
Emerging Infectious Diseases
Hemorrhagic Fever
Immunization
Preventive Medicine
Mathematics
Subjects
Details
- Language :
- English
- ISSN :
- 19326203
- Volume :
- 14
- Issue :
- 3
- Database :
- OpenAIRE
- Journal :
- PLoS ONE
- Accession number :
- edsair.doi.dedup.....5ebc52936fb1f45eebf5e728a38e3f8c