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Ren H, Xu R. Prevention and control of Ebola virus transmission: mathematical modelling and data fitting. J Math Biol 2024; 89:25. [PMID: 38963509 DOI: 10.1007/s00285-024-02122-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/04/2022] [Revised: 08/16/2023] [Accepted: 06/23/2024] [Indexed: 07/05/2024]
Abstract
The Ebola virus disease (EVD) has been endemic since 1976, and the case fatality rate is extremely high. EVD is spread by infected animals, symptomatic individuals, dead bodies, and contaminated environment. In this paper, we formulate an EVD model with four transmission modes and a time delay describing the incubation period. Through dynamical analysis, we verify the importance of blocking the infection source of infected animals. We get the basic reproduction number without considering the infection source of infected animals. And, it is proven that the model has a globally attractive disease-free equilibrium when the basic reproduction number is less than unity; the disease eventually becomes endemic when the basic reproduction number is greater than unity. Taking the EVD epidemic in Sierra Leone in 2014-2016 as an example, we complete the data fitting by combining the effect of the media to obtain the unknown parameters, the basic reproduction number and its time-varying reproduction number. It is shown by parameter sensitivity analysis that the contact rate and the removal rate of infected group have the greatest influence on the prevalence of the disease. And, the disease-controlling thresholds of these two parameters are obtained. In addition, according to the existing vaccination strategy, only the inoculation ratio in high-risk areas is greater than 0.4, the effective reproduction number can be less than unity. And, the earlier the vaccination time, the greater the inoculation ratio, and the faster the disease can be controlled.
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Affiliation(s)
- Huarong Ren
- Complex Systems Research Center, Shanxi University, Taiyuan, 030006, Shanxi, China
- School of Mathematical Sciences, Shanxi University, Taiyuan, 030006, Shanxi, China
| | - Rui Xu
- Complex Systems Research Center, Shanxi University, Taiyuan, 030006, Shanxi, China.
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Bisanzio D, Davis AE, Talbird SE, Van Effelterre T, Metz L, Gaudig M, Mathieu VO, Brogan AJ. Targeted preventive vaccination campaigns to reduce Ebola outbreaks: An individual-based modeling study. Vaccine 2023; 41:684-693. [PMID: 36526505 DOI: 10.1016/j.vaccine.2022.11.036] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/26/2022] [Revised: 11/16/2022] [Accepted: 11/17/2022] [Indexed: 12/15/2022]
Abstract
INTRODUCTION Nonpharmaceutical interventions (NPI) and ring vaccination (i.e., vaccination that primarily targets contacts and contacts of contacts of Ebola cases) are currently used to reduce the spread of Ebola during outbreaks. Because these measures are typically initiated after an outbreak is declared, they are limited by real-time implementation challenges. Preventive vaccination may provide a complementary option to help protect communities against unpredictable outbreaks. This study aimed to assess the impact of preventive vaccination strategies when implemented in conjunction with NPI and ring vaccination. METHODS A spatial-explicit, individual-based model (IBM) that accounts for heterogeneity of human contact, human movement, and timing of interventions was built to represent Ebola transmission in the Democratic Republic of the Congo. Simulated preventive vaccination strategies targeted healthcare workers (HCW), frontline workers (FW), and the general population (GP) with varying levels of coverage (lower coverage: 30% of HCW/FW, 5% of GP; higher coverage: 60% of HCW/FW, 10% of GP) and efficacy (lower efficacy: 60%; higher efficacy: 90%). RESULTS The IBM estimated that the addition of preventive vaccination for HCW reduced cases, hospitalizations, and deaths by ∼11 % to ∼25 % compared with NPI + ring vaccination alone. Including HCW and FW in the preventive vaccination campaign yielded ∼14 % to ∼38 % improvements in epidemic outcomes. Further including the GP yielded the greatest improvements, with ∼21 % to ∼52 % reductions in epidemic outcomes compared with NPI + ring vaccination alone. In a scenario without ring vaccination, preventive vaccination reduced cases, hospitalizations, and deaths by ∼28 % to ∼59 % compared with NPI alone. In all scenarios, preventive vaccination reduced Ebola transmission particularly during the initial phases of the epidemic, resulting in flatter epidemic curves. CONCLUSIONS The IBM showed that preventive vaccination may reduce Ebola cases, hospitalizations, and deaths, thus safeguarding the healthcare system and providing more time to implement additional interventions during an outbreak.
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Affiliation(s)
- Donal Bisanzio
- RTI International, 701 13th St NW #750, Washington, DC 20005, USA
| | - Ashley E Davis
- RTI Health Solutions, 3040 East Cornwallis Road, Research Triangle Park, NC 27709, USA
| | - Sandra E Talbird
- RTI Health Solutions, 3040 East Cornwallis Road, Research Triangle Park, NC 27709, USA
| | | | - Laurent Metz
- Johnson & Johnson Global Public Health, One Johnson and Johnson Plaza, New Brunswick, NJ 08901, USA
| | - Maren Gaudig
- Johnson & Johnson Global Public Health, One Johnson and Johnson Plaza, New Brunswick, NJ 08901, USA
| | | | - Anita J Brogan
- RTI Health Solutions, 3040 East Cornwallis Road, Research Triangle Park, NC 27709, USA.
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Potluri R, Kumar A, Oriol-Mathieu V, Van Effelterre T, Metz L, Bhandari H. Model-based evaluation of the impact of prophylactic vaccination applied to Ebola epidemics in Sierra Leone and Democratic Republic of Congo. BMC Infect Dis 2022; 22:769. [PMID: 36192683 PMCID: PMC9529325 DOI: 10.1186/s12879-022-07723-6] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/19/2022] [Accepted: 09/11/2022] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND Protection by preventive Ebola vaccines has been demonstrated in clinical trials, but a complete picture of real-world effectiveness is lacking. Our previous study modeling the impact of preventively vaccinating healthcare workers (HCW) alone or with a proportion of the general population (GP) estimated significant reductions in incidence and mortality. The model assumed 100% vaccine efficacy, which is unlikely in the real world. We enhanced this model to account for lower vaccine efficacy and to factor in reduced infectiousness and lower case fatality rate in vaccinated individuals with breakthrough infections. METHODS The previous model was enhanced to still permit a risk, although lower, for vaccinated individuals to become infected. The enhanced model, calibrated with data from epidemics in Sierra Leone (SL) and North Kivu, Democratic Republic of the Congo, helped evaluate the impact of preventive Ebola vaccination in different scenarios based on different vaccine efficacy rates (90% and 30% reductions in infection risk in the base and conservative scenarios, respectively; additionally, both scenarios with 50% reductions in infectiousness and mortality) and vaccination coverage among HCWs (30%, 90%) and GP (0%, 5%, and 10%). RESULTS The base scenario estimated that, depending upon the proportions of vaccinated HCWs and GP, 33-85% of cases and 34-87% of deaths during the 2014 SL epidemic and 42-89% of cases and 41-89% of deaths during the 2018 North Kivu epidemic would be averted versus no vaccination. Corresponding estimates for the conservative scenario were: 23-74% of cases and 23-77% of deaths averted during the SL epidemic and 31-80% of both cases and deaths averted during the North Kivu epidemic. CONCLUSIONS Preventive vaccination targeting HCW alone or with GP may significantly reduce the size and mortality of an EVD outbreak, even with modest efficacy and coverage. Vaccines may also confer additional benefits through reduced infectiousness and mortality in breakthrough cases.
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Affiliation(s)
- Ravi Potluri
- SmartAnalyst Inc., 300 Vesey Street, 10th Floor, New York, NY, 10282, USA.
| | - Amit Kumar
- SmartAnalyst India Pvt. Ltd., Gurugram, India
| | | | | | - Laurent Metz
- Johnson & Johnson Global Public Health, New Brunswick, NJ, USA
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OUEMBA TASSÉ AJ, TSANOU B, LUBUMA J, WOUKENG JEANLOUIS, SIGNING FRANCIS. EBOLA VIRUS DISEASE DYNAMICS WITH SOME PREVENTIVE MEASURES: A CASE STUDY OF THE 2018–2020 KIVU OUTBREAK. J BIOL SYST 2022. [DOI: 10.1142/s0218339022500048] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022]
Abstract
To fight against Ebola virus disease, several measures have been adopted. Among them, isolation, safe burial and vaccination occupy a prominent place. In this paper, we present a model which takes into account these three control strategies as well as the indirect transmission through a polluted environment. The asymptotic behavior of our model is achieved. Namely, we determine a threshold value [Formula: see text] of the control reproduction number [Formula: see text], below which the disease is eliminated in the long run. Whenever the value of [Formula: see text] ranges from [Formula: see text] and 1, we prove the existence of a backward bifurcation phenomenon, which corresponds to the case, where a locally asymptotically stable positive equilibrium co-exists with the disease-free equilibrium, which is also locally asymptotically stable. The existence of this bifurcation complicates the control of Ebola, since the requirement of [Formula: see text] below one, although necessary, is no longer sufficient for the elimination of Ebola, more efforts need to be deployed. When the value of [Formula: see text] is greater than one, we prove the existence of a unique endemic equilibrium, locally asymptotically stable. That is the disease may persist and become endemic. Numerically, we fit our model to the reported data for the 2018–2020 Kivu Ebola outbreak which occurred in Democratic Republic of Congo. Through the sensitivity analysis of the control reproduction number, we prove that the transmission rates of infected alive who are outside hospital are the most influential parameters. Numerically, we explore the usefulness of isolation, safe burial combined with vaccination and investigate the importance to combine the latter control strategies to the educational campaigns or/and case finding.
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Affiliation(s)
- A. J. OUEMBA TASSÉ
- Department of Mathematics and Computer Science, University of Dschang, P. O. Box 67, Dschang, Cameroon
| | - B. TSANOU
- Department of Mathematics and Computer Science, University of Dschang, P. O. Box 67, Dschang, Cameroon
- Department of Science, Mathematics and Applied Mathematics, University of Pretoria, Private Bag X20, Pretoria 0028, South Africa
- IRD Sorbonne University, UMMISCO, F-93143, Bondy, France
| | - J. LUBUMA
- School of Computer Science and Applied Mathematics, University of the Witwatersrand, Johannesburg, South Africa
| | - JEAN LOUIS WOUKENG
- Department of Mathematics and Computer Science, University of Dschang, P. O. Box 67, Dschang, Cameroon
| | - FRANCIS SIGNING
- Department of Mathematics and Computer Science, University of Dschang, P. O. Box 67, Dschang, Cameroon
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Obeng-Kusi M, Habila MA, Roe DJ, Erstad B, Abraham I. Economic evaluation using dynamic transition modeling of ebola virus vaccination in lower-and-middle-income countries. J Med Econ 2021; 24:1-13. [PMID: 34866541 DOI: 10.1080/13696998.2021.2002092] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 10/19/2022]
Abstract
BACKGROUND With the increasing occurrence of infectious diseases in lower-and-middle-income countries (LMICs), emergency preparedness is essential for rapid response and mitigation. Economic evaluations of mitigation technologies and strategies have been recommended for inclusion in emergency preparedness plans. We aimed to perform an economic evaluation using dynamic transition modeling of ebola virus disease (EVD) vaccination in a hypothetical community of 1,000 persons in the Democratic Republic of Congo (DRC). METHOD Using a modified SEIR (Susceptible, Exposed, Infectious, Recovered, with Death added [SEIR-D]) model that accounted for death and epidemiological data from an EVD outbreak in the DRC, we modeled the transmission of EVD in a hypothetical population of 1,000. With our model, we estimated the cost-effectiveness of an EVD vaccine and an EVD vaccination intervention. RESULTS The results showed vaccinating 50% of the population at risk prevented 670 cases, 538 deaths, and 22,022 disability-adjusted life years (DALYs). The vaccine was found to be cost-effective with an incremental cost-effectiveness ratio (ICER) of $95.63 per DALY averted. We also determined the minimum required vaccination coverage for cost-effectiveness to be 40%. Sensitivity analysis showed our model to be fairly robust, assuring relatively consistent results even with variations in such input parameters as cost of screening, as well as transmission, infection, incubation, and case fatality rates. CONCLUSION EVD vaccination in our hypothetical population was found to be cost-effective from the payer perspective. Our model presents an efficient and reliable approach for conducting economic evaluations of infectious disease interventions as part of an emergency preparedness plan.
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Affiliation(s)
- Mavis Obeng-Kusi
- Center for Health Outcomes and PharmacoEconomic Research, University of Arizona, Tucson, AZ, USA
| | - Magdiel A Habila
- Center for Health Outcomes and PharmacoEconomic Research, University of Arizona, Tucson, AZ, USA
- Mel & Enid Zuckerman College of Public Health, University of Arizona, Tucson, AZ, USA
| | - Denise J Roe
- Mel & Enid Zuckerman College of Public Health, University of Arizona, Tucson, AZ, USA
| | - Brian Erstad
- Pharmacy Practice and Science, University of Arizona, Tucson, AZ, USA
| | - Ivo Abraham
- Center for Health Outcomes and PharmacoEconomic Research, University of Arizona, Tucson, AZ, USA
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A hybrid simulation model to study the impact of combined interventions on Ebola epidemic. PLoS One 2021; 16:e0254044. [PMID: 34228758 PMCID: PMC8259970 DOI: 10.1371/journal.pone.0254044] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/06/2020] [Accepted: 06/21/2021] [Indexed: 12/01/2022] Open
Abstract
Pandemics have been recognized as a serious global threat to humanity. To effectively prevent the spread and outbreak of the epidemic disease, theoretical models intended to depict the disease dynamics have served as the main tools to understand its underlying mechanisms and thus interrupt its transmission. Two commonly-used models are mean-field compartmental models and agent-based models (ABM). The former ones are analytically tractable for describing the dynamics of subpopulations by cannot explicitly consider the details of individual movements. The latter one is mainly used to the spread of epidemics at a microscopic level but have limited simulation scale for the randomness of the results. To overcome current limitations, a hierarchical hybrid modeling and simulation method, combining mean-field compartmental model and ABM, is proposed in this paper. Based on this method, we build a hybrid model, which takes both individual heterogeneity and the dynamics of sub-populations into account. The proposed model also investigates the impact of combined interventions (i. e. vaccination and pre-deployment training) for healthcare workers (HCWs) on the spread of disease. Taking the case of 2014-2015 Ebola Virus Disease (EVD) in Sierra Leone as an example, we examine its spreading mechanism and evaluate the effect of prevention by our parameterized and validated hybrid model. According to our simulation results, an optimal combination of pre-job training and vaccination deployment strategy has been identified. To conclude, our hybrid model helps informing the synergistic disease control strategies and the corresponding hierarchical hybrid modeling and simulation method can further be used to understand the individual dynamics during epidemic spreading in large scale population and help inform disease control strategies for different infectious disease.
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Impact of prophylactic vaccination strategies on Ebola virus transmission: A modeling analysis. PLoS One 2020; 15:e0230406. [PMID: 32339195 PMCID: PMC7185698 DOI: 10.1371/journal.pone.0230406] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/19/2019] [Accepted: 03/01/2020] [Indexed: 01/18/2023] Open
Abstract
Ebola epidemics constitute serious public health emergencies. Multiple vaccines are under development to prevent these epidemics and avoid the associated morbidity and mortality. Assessing the potential impact of these vaccines on morbidity and mortality of Ebola is essential for devising prevention strategies. A mean-field compartmental stochastic model was developed for this purpose and validated by simulating the 2014 Sierra Leone epidemic. We assessed the impacts of prophylactic vaccination of healthcare workers (HCW) both alone and in combination with the vaccination of the general population (entire susceptible population other than HCW). The model simulated 8,706 (95% confidence intervals [CI]: 478–21,942) cases and 3,575 (95%CI: 179–9,031) deaths in Sierra Leone, in line with WHO-reported statistics for the 2014 epidemic (8,704 cases and 3,587 deaths). Relative to this base case, the model then estimated that prophylactic vaccination of only 10% of HCW will avert 12% (95% CI: 6%-14%) of overall cases and deaths, while vaccination of 30% of HCW will avert 34% of overall cases (95% CI: 30%-64%) and deaths (95% CI: 30%-65%). Prophylactic vaccination of 1% and 5% of the general population in addition to vaccinating 30% of HCW was estimated to result in reduction in cases by 44% (95% CI: 39%-61%) and 72% (95% CI: 68%-84%) respectively, and deaths by 45% (95% CI: 40%-61%) and 74% (95% CI: 70%-85%) respectively. Prophylactic vaccination of even small proportions of HCW is estimated to significantly reduce incidence of Ebola and associated mortality. The effect is greatly enhanced by the additional vaccination even of small percentages of the general population. These findings could be used to inform the planning of prevention strategies.
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Worden L, Wannier R, Hoff NA, Musene K, Selo B, Mossoko M, Okitolonda-Wemakoy E, Muyembe Tamfum JJ, Rutherford GW, Lietman TM, Rimoin AW, Porco TC, Kelly JD. Projections of epidemic transmission and estimation of vaccination impact during an ongoing Ebola virus disease outbreak in Northeastern Democratic Republic of Congo, as of Feb. 25, 2019. PLoS Negl Trop Dis 2019; 13:e0007512. [PMID: 31381606 PMCID: PMC6695208 DOI: 10.1371/journal.pntd.0007512] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/28/2018] [Revised: 08/15/2019] [Accepted: 06/03/2019] [Indexed: 01/24/2023] Open
Abstract
BACKGROUND As of February 25, 2019, 875 cases of Ebola virus disease (EVD) were reported in North Kivu and Ituri Provinces, Democratic Republic of Congo. Since the beginning of October 2018, the outbreak has largely shifted into regions in which active armed conflict has occurred, and in which EVD cases and their contacts have been difficult for health workers to reach. We used available data on the current outbreak, with case-count time series from prior outbreaks, to project the short-term and long-term course of the outbreak. METHODS For short- and long-term projections, we modeled Ebola virus transmission using a stochastic branching process that assumes gradually quenching transmission rates estimated from past EVD outbreaks, with outbreak trajectories conditioned on agreement with the course of the current outbreak, and with multiple levels of vaccination coverage. We used two regression models to estimate similar projection periods. Short- and long-term projections were estimated using negative binomial autoregression and Theil-Sen regression, respectively. We also used Gott's rule to estimate a baseline minimum-information projection. We then constructed an ensemble of forecasts to be compared and recorded for future evaluation against final outcomes. From August 20, 2018 to February 25, 2019, short-term model projections were validated against known case counts. RESULTS During validation of short-term projections, from one week to four weeks, we found models consistently scored higher on shorter-term forecasts. Based on case counts as of February 25, the stochastic model projected a median case count of 933 cases by February 18 (95% prediction interval: 872-1054) and 955 cases by March 4 (95% prediction interval: 874-1105), while the auto-regression model projects median case counts of 889 (95% prediction interval: 876-933) and 898 (95% prediction interval: 877-983) cases for those dates, respectively. Projected median final counts range from 953 to 1,749. Although the outbreak is already larger than all past Ebola outbreaks other than the 2013-2016 outbreak of over 26,000 cases, our models do not project that it is likely to grow to that scale. The stochastic model estimates that vaccination coverage in this outbreak is lower than reported in its trial setting in Sierra Leone. CONCLUSIONS Our projections are concentrated in a range up to about 300 cases beyond those already reported. While a catastrophic outbreak is not projected, it is not ruled out, and prevention and vigilance are warranted. Prospective validation of our models in real time allowed us to generate more accurate short-term forecasts, and this process may prove useful for future real-time short-term forecasting. We estimate that transmission rates are higher than would be seen under target levels of 62% coverage due to contact tracing and vaccination, and this model estimate may offer a surrogate indicator for the outbreak response challenges.
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Affiliation(s)
- Lee Worden
- F. I. Proctor Foundation, University of California, San Francisco (UCSF), San Francisco, California, United States of America
| | - Rae Wannier
- F. I. Proctor Foundation, University of California, San Francisco (UCSF), San Francisco, California, United States of America
- School of Medicine, UCSF, San Francisco, California, United States of America
| | - Nicole A. Hoff
- Department of Epidemiology, Fielding School of Public Health, University of California, Los Angeles, Los Angeles, California, United States of America
| | - Kamy Musene
- Department of Epidemiology, Fielding School of Public Health, University of California, Los Angeles, Los Angeles, California, United States of America
| | - Bernice Selo
- Ministry of Health, Directorate of Primary Health Care Development, Kinshasa, Democratic Republic of Congo
| | - Mathias Mossoko
- Ministry of Health, Directorate of Primary Health Care Development, Kinshasa, Democratic Republic of Congo
| | | | | | | | - Thomas M. Lietman
- F. I. Proctor Foundation, University of California, San Francisco (UCSF), San Francisco, California, United States of America
- School of Medicine, UCSF, San Francisco, California, United States of America
| | - Anne W. Rimoin
- Department of Epidemiology, Fielding School of Public Health, University of California, Los Angeles, Los Angeles, California, United States of America
| | - Travis C. Porco
- F. I. Proctor Foundation, University of California, San Francisco (UCSF), San Francisco, California, United States of America
- School of Medicine, UCSF, San Francisco, California, United States of America
| | - J. Daniel Kelly
- F. I. Proctor Foundation, University of California, San Francisco (UCSF), San Francisco, California, United States of America
- School of Medicine, UCSF, San Francisco, California, United States of America
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Berge T, Ouemba Tassé AJ, Tenkam HM, Lubuma J. Mathematical modeling of contact tracing as a control strategy of Ebola virus disease. INT J BIOMATH 2018. [DOI: 10.1142/s1793524518500936] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/25/2022]
Abstract
More than 20 outbreaks of Ebola virus disease have occurred in Africa since 1976, and yet no adequate treatment is available. Hence, prevention, control measures and supportive treatment remain the only means to avoid the disease. Among these measures, contact tracing occupies a prominent place. In this paper, we propose a simple mathematical model that incorporates imperfect contact tracing, quarantine and hospitalization (or isolation). The control reproduction number [Formula: see text] of each sub-model and for the full model are computed. Theoretically, we prove that when [Formula: see text] is less than one, the corresponding model has a unique globally asymptotically stable disease-free equilibrium. Conversely, when [Formula: see text] is greater than one, the disease-free equilibrium becomes unstable and a unique globally asymptotically stable endemic equilibrium arises. Furthermore, we numerically support the analytical results and assess the efficiency of different control strategies. Our main observation is that, to eradicate EVD, the combination of high contact tracing (up to 90%) and effective isolation is better than all other control measures, namely: (1) perfect contact tracing, (2) effective isolation or full hospitalization, (3) combination of medium contact tracing and medium isolation.
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Affiliation(s)
- T. Berge
- Department of Science, Mathematics and Applied Mathematics, University of Pretoria, Private Bag X20, Pretoria 0028, South Africa
- Department of Mathematics and Computer Science, University of Dschang, P. O. Box 67, Dschang, Cameroon
| | - A. J. Ouemba Tassé
- Department of Mathematics and Computer Science, University of Dschang, P. O. Box 67, Dschang, Cameroon
| | - H. M. Tenkam
- Department of Mathematics and Applied Mathematics, North-West University, Private Bag X1290, Potchefstroom 2520, South Africa
| | - J. Lubuma
- Department of Mathematics and Computer Science, University of Dschang, P. O. Box 67, Dschang, Cameroon
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Kabli K, El Moujaddid S, Niri K, Tridane A. Cooperative system analysis of the Ebola virus epidemic model. Infect Dis Model 2018; 3:145-159. [PMID: 30839882 PMCID: PMC6326236 DOI: 10.1016/j.idm.2018.09.004] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/30/2018] [Revised: 09/03/2018] [Accepted: 09/16/2018] [Indexed: 11/27/2022] Open
Abstract
This paper aims to study the global stability of an Ebola virus epidemic model. Although this epidemic ended in September 2015, it devastated several West African countries and mobilized the international community. With the recent cases of Ebola in the Democratic Republic of the Congo (DRC), the threat of the reappearance of this fatal disease remains. Therefore, we are obligated to be prepared for a possible re-emerging of the disease. In this work, we investigate the global stability analysis via the theory of cooperative systems, and we determine the conditions that lead to global stability diseases free and endemic equilibrium.
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Affiliation(s)
- Karima Kabli
- Department of Mathematics and Computing, Ain Chock Science Faculty, Hassan II University, Casablanca, Morocco
| | - Soumia El Moujaddid
- Department of Mathematics and Computing, Ain Chock Science Faculty, Hassan II University, Casablanca, Morocco
| | - Khadija Niri
- Department of Mathematics and Computing, Ain Chock Science Faculty, Hassan II University, Casablanca, Morocco
| | - Abdessamad Tridane
- Department of Mathematical Sciences, United Arab Emirates University, P.O. Box 15551, Al Ain, United Arab Emirates
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