5 results on '"Cyrus Sinai"'
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2. Estimating the impact of violent events on transmission in Ebola virus disease outbreak, Democratic Republic of the Congo, 2018–2019
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S. Rae Wannier, Lee Worden, Nicole A. Hoff, Eduardo Amezcua, Bernice Selo, Cyrus Sinai, Mathias Mossoko, Bathe Njoloko, Emile Okitolonda-Wemakoy, Placide Mbala-Kingebeni, Steve Ahuka-Mundeke, Jean Jacques Muyembe-Tamfum, Eugene T. Richardson, George W. Rutherford, James H Jones, Thomas M. Lietman, Anne W. Rimoin, Travis C. Porco, and J. Daniel Kelly
- Subjects
Infectious and parasitic diseases ,RC109-216 - Abstract
Introduction: As of April 2019, the current Ebola virus disease (EVD) outbreak in the Democratic Republic of the Congo (DRC) is occurring in a longstanding conflict zone and has become the second largest EVD outbreak in history. It is suspected that after violent events occur, EVD transmission will increase; however, empirical studies to understand the impact of violence on transmission are lacking. Here, we use spatial and temporal trends of EVD case counts to compare transmission rates between health zones that have versus have not experienced recent violent events during the outbreak. Methods: We collected daily EVD case counts from DRC Ministry of Health. A time-varying indicator of recent violence in each health zone was derived from events documented in the WHO situation reports. We used the Wallinga-Teunis technique to estimate the reproduction number R for each case by day per zone in the 2018–2019 outbreak. We fit an exponentially decaying curve to estimates of R overall and by health zone, for comparison to past outbreaks. Results: As of 16 April 2019, the mean overall R for the entire outbreak was 1.11. We found evidence of an increase in the estimated transmission rates in health zones with recently reported violent events versus those without (p = 0.008). The average R was estimated as between 0.61 and 0.86 in regions not affected by recent violent events, and between 1.01 and 1.07 in zones affected by violent events within the last 21 days, leading to an increase in R between 0.17 and 0.53. Within zones with recent violent events, the mean estimated quenching rate was lower than for all past outbreaks except the 2013–2016 West African outbreak. Conclusion: The difference in the estimated transmission rates between zones affected by recent violent events suggests that violent events are contributing to increased transmission and the ongoing nature of this outbreak. Keywords: Ebola virus disease, Outbreak, Mathematical modeling, Geospatial, Democratic Republic of Congo, Africa
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- 2019
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3. Projections of Ebola outbreak size and duration with and without vaccine use in Équateur, Democratic Republic of Congo, as of May 27, 2018.
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J Daniel Kelly, Lee Worden, S Rae Wannier, Nicole A Hoff, Patrick Mukadi, Cyrus Sinai, Sarah Ackley, Xianyun Chen, Daozhou Gao, Bernice Selo, Mathais Mossoko, Emile Okitolonda-Wemakoy, Eugene T Richardson, George W Rutherford, Thomas M Lietman, Jean Jacques Muyembe-Tamfum, Anne W Rimoin, and Travis C Porco
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Medicine ,Science - 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.
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- 2019
- Full Text
- View/download PDF
4. Projections of Ebola outbreak size and duration with and without vaccine use in Équateur, Democratic Republic of Congo, as of May 27, 2018
- Author
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Cyrus Sinai, Travis C. Porco, Patrick Mukadi, Mathais Mossoko, Lee Worden, Anne W. Rimoin, S. Rae Wannier, Nicole A. Hoff, Sarah F Ackley, Bernice Selo, Emile Okitolonda-Wemakoy, George W. Rutherford, Jean Jacques Muyembe-Tamfum, Thomas M. Lietman, Eugene T Richardson, Xianyun Chen, Daozhou Gao, J. Daniel Kelly, and Schieffelin, John
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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 - 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.
- Published
- 2019
5. Real-time projections of Ebola outbreak size and duration with and without vaccine use in Équateur, Democratic Republic of Congo, as of May 27, 2018
- Author
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Cyrus Sinai, Rae Wannier, Thomas M. Lietman, George W. Rutherford, Nicole A. Hoff, Bernice Selo, Patrick Mukadi, Sarah F Ackley, Mathais Mossoko, Xianyun Chen, Anne W. Rimoin, Jean Jacques Muyembe-Tamfum, Eugene T Richardson, Daozhou Gao, J. Daniel Kelly, Travis C. Porco, Emile Okitolonda-Wemakoy, and Lee Worden
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medicine.medical_specialty ,Ebola virus ,030231 tropical medicine ,Prediction interval ,Outbreak ,Regression analysis ,medicine.disease_cause ,3. Good health ,law.invention ,03 medical and health sciences ,0302 clinical medicine ,Transmission (mechanics) ,Geography ,law ,Epidemiology ,medicine ,Credible interval ,030212 general & internal medicine ,Duration (project management) ,Demography - Abstract
BackgroundAs of May 27, 2018, 54 cases of Ebola virus disease (EVD) were reported in Équateur Province, Democratic Republic of Congo. We used reported case counts and time series from prior outbreaks to estimate the current outbreak size and duration with and without vaccine use.MethodsWe modeled Ebola virus transmission using a stochastic branching process model with a negative binomial distribution, using both estimates of reproduction number R declining from supercritical to subcritical derived from past Ebola outbreaks, as well as a particle filtering method to generate a probabilistic projection of the future course of the outbreak conditioned on its reported trajectory to date; modeled using 0%, 44%, and 62% estimates of vaccination coverage. Additionally, we used the time series for 18 prior Ebola outbreaks from 1976 to 2016 to parameterize a regression model predicting the outbreak size from the number of observed cases from April 4 to May 27.ResultsWith the stochastic transmission model, we projected a median outbreak size of 78 EVD cases (95% credible interval: 52, 125.4), 86 cases (95% credible interval: 53, 174.3), and 91 cases (95% credible interval: 52, 843.5), using 62%, 44%, and 0% estimates of vaccination coverage. With the regression model, we estimated a median size of 85.0 cases (95% prediction interval: 53.5, 216.6).ConclusionsThis outbreak has the potential to be the largest outbreak in DRC since 2007. Vaccines are projected to limit outbreak size and duration but are only part of prevention, control, and care strategies.
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- 2018
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