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Hoffmann Dahl E, Mbala P, Juchet S, Touré A, Montoyo A, Serra B, Kojan R, D'Ortenzio E, Blomberg B, Jaspard M. Improving Ebola virus disease outbreak control through targeted post-exposure prophylaxis. Lancet Glob Health 2024; 12:e1730-e1736. [PMID: 39270687 DOI: 10.1016/s2214-109x(24)00255-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/29/2024] [Revised: 05/24/2024] [Accepted: 06/05/2024] [Indexed: 09/15/2024]
Abstract
Ebola virus disease kills more than half of people infected. Since the disease is transmitted via close human contact, identifying individuals at the highest risk of developing the disease is possible on the basis of the type of contact (correlated with viral exposure). Different candidates for post-exposure prophylaxis (PEP; ie, vaccines, antivirals, and monoclonal antibodies) each have their specific benefits and limitations, which we discuss in this Viewpoint. Approved monoclonal antibodies have been found to reduce mortality in people with Ebola virus disease. As monoclonal antibodies act swiftly by directly targeting the virus, they are promising candidates for targeted PEP in contacts at high risk of developing disease. This intervention could save lives, halt viral transmission, and, ultimately, help curtail outbreak propagation. We explore how a strategic integration of monoclonal antibodies and vaccines as PEP could provide both immediate and long-term protection against Ebola virus disease, highlighting ongoing clinical research that aims to refine this approach, and discuss the transformative potential of a successful PEP strategy to help control viral haemorrhagic fever outbreaks.
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Affiliation(s)
- Elin Hoffmann Dahl
- Médecins Sans Frontières, Oslo, Norway; Department of Infectious Diseases, Haukeland University Hospital, Bergen, Norway; Department of Clinical Science, University of Bergen, Bergen, Norway
| | - Placide Mbala
- Kingebeni Institut National de Recherche Biomédicale and University of Kinshasa, Kinshasa, Democratic Republic of the Congo
| | - Sylvain Juchet
- The Alliance for International Medical Action, Dakar, Senegal; UMR 1219 GHiGS unit, University of Bordeaux, National Institute for Health and Medical Research, Research Institute for Sustainable Development, Bordeaux Population Health Center, Bordeaux, France
| | - Abdoulaye Touré
- Centre de recherche et de formation en infectiologie de Guinea, University Gamal Abdel Nasser de Conakry, Conakry, Guinée
| | - Alice Montoyo
- The Alliance for International Medical Action, Dakar, Senegal; UMR 1219 GHiGS unit, University of Bordeaux, National Institute for Health and Medical Research, Research Institute for Sustainable Development, Bordeaux Population Health Center, Bordeaux, France
| | - Beatrice Serra
- The Alliance for International Medical Action, Dakar, Senegal; UMR 1219 GHiGS unit, University of Bordeaux, National Institute for Health and Medical Research, Research Institute for Sustainable Development, Bordeaux Population Health Center, Bordeaux, France
| | - Richard Kojan
- The Alliance for International Medical Action, Dakar, Senegal
| | - Eric D'Ortenzio
- ANRS Emerging infectious diseases, National Institute for Health and Medical Research, Paris, France; Infectious and Tropical Diseases Department, Bichat-Claude-Bernard Hospital, Assistance Publique-Hôpitaux de Paris, Paris, France
| | - Bjorn Blomberg
- Department of Clinical Science, University of Bergen, Bergen, Norway; National Centre for Tropical Infectious Diseases, Haukeland University Hospital, Bergen, Norway
| | - Marie Jaspard
- UMR 1136 IPLESP unit, Sorbonne Université, Paris, France; Infectious Disease Department, Hopital Saint Antoine, Paris, France.
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Charniga K, Park SW, Akhmetzhanov AR, Cori A, Dushoff J, Funk S, Gostic KM, Linton NM, Lison A, Overton CE, Pulliam JRC, Ward T, Cauchemez S, Abbott S. Best practices for estimating and reporting epidemiological delay distributions of infectious diseases. PLoS Comput Biol 2024; 20:e1012520. [PMID: 39466727 PMCID: PMC11516000 DOI: 10.1371/journal.pcbi.1012520] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/30/2024] Open
Abstract
Epidemiological delays are key quantities that inform public health policy and clinical practice. They are used as inputs for mathematical and statistical models, which in turn can guide control strategies. In recent work, we found that censoring, right truncation, and dynamical bias were rarely addressed correctly when estimating delays and that these biases were large enough to have knock-on impacts across a large number of use cases. Here, we formulate a checklist of best practices for estimating and reporting epidemiological delays. We also provide a flowchart to guide practitioners based on their data. Our examples are focused on the incubation period and serial interval due to their importance in outbreak response and modeling, but our recommendations are applicable to other delays. The recommendations, which are based on the literature and our experience estimating epidemiological delay distributions during outbreak responses, can help improve the robustness and utility of reported estimates and provide guidance for the evaluation of estimates for downstream use in transmission models or other analyses.
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Affiliation(s)
- Kelly Charniga
- Mathematical Modelling of Infectious Diseases Unit, Institut Pasteur, Université Paris Cité, CNRS UMR 2000, Paris, France
| | - Sang Woo Park
- Department of Ecology and Evolutionary Biology, Princeton University, Princeton, New Jersey, United States of America
| | | | - Anne Cori
- MRC Centre for Global Infectious Disease Analysis, School of Public Health, Imperial College London, London, United Kingdom
| | - Jonathan Dushoff
- Departments of Mathematics & Statistics and Biology, McMaster University, Hamilton, Ontario, Canada
- Department of Biology, McMaster University, Hamilton, Ontario, Canada
- M. G. DeGroote Institute for Infectious Disease Research, McMaster University, Hamilton, Ontario, Canada
| | - Sebastian Funk
- Department of Infectious Disease Epidemiology and Dynamics, London School of Hygiene & Tropical Medicine, London, United Kingdom
- Centre for Mathematical Modelling of Infectious Diseases, London School of Hygiene & Tropical Medicine, London, United Kingdom
| | - Katelyn M. Gostic
- Center for Forecasting and Outbreak Analytics, U.S. Centers for Disease Control and Prevention, Atlanta, Georgia, United States of America
| | - Natalie M. Linton
- Graduate School of Medicine, Hokkaido University, Sapporo-shi, Hokkaido, Japan
| | - Adrian Lison
- Department of Biosystems Science and Engineering, ETH Zurich, Zurich, Switzerland
| | - Christopher E. Overton
- Department of Mathematical Sciences, University of Liverpool, Liverpool, United Kingdom
- All Hazards Intelligence, Infectious Disease Modelling Team, Data Analytics and Surveillance, UK Health Security Agency, United Kingdom
- Department of Mathematics, University of Manchester, Manchester, United Kingdom
| | - Juliet R. C. Pulliam
- Center for Forecasting and Outbreak Analytics, U.S. Centers for Disease Control and Prevention, Atlanta, Georgia, United States of America
| | - Thomas Ward
- All Hazards Intelligence, Infectious Disease Modelling Team, Data Analytics and Surveillance, UK Health Security Agency, United Kingdom
| | - Simon Cauchemez
- Mathematical Modelling of Infectious Diseases Unit, Institut Pasteur, Université Paris Cité, CNRS UMR 2000, Paris, France
| | - Sam Abbott
- Department of Infectious Disease Epidemiology and Dynamics, London School of Hygiene & Tropical Medicine, London, United Kingdom
- Centre for Mathematical Modelling of Infectious Diseases, London School of Hygiene & Tropical Medicine, London, United Kingdom
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Ahmad B, Sagide M, Ntamwinja S, Byiringiro E, Kihanduka E, Rugendabanga E, Hangi S, Bhattacharjee P, Ali B, Nkundakozera M, Kanda MS, Guruka L, Onesime J, Tague C, Langat AK, Akilimali A. National burden of Ebola virus disease in Democratic Republic of the Congo: the urgency to act. Ann Med Surg (Lond) 2024; 86:4579-4585. [PMID: 39118744 PMCID: PMC11305799 DOI: 10.1097/ms9.0000000000002213] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/09/2024] [Accepted: 05/15/2024] [Indexed: 08/10/2024] Open
Abstract
Ebola virus disease (EVD) has long been a major public health concern for Democratic Republic of the Congo (DR Congo). First identified in DR Congo in 1976, the country has witnessed more than 25 outbreaks of this deadly disease, which has a case fatality rate of nearly 90% and manifesting with symptoms such as diarrhoea, vomiting, stomachache and haemorrhagic fever. African fruit bats have been speculated to be the reservoir of this virus. DR Congo is currently facing another EVD outbreak simultaneously with other communicable diseases, rendering it vulnerable to a shortage of medical and paramedical staff along with distrust among remote communities towards local authorities due to armed conflict and political instability. Moreover, lack of ring vaccinations and inefficient surveillance of suspected individuals are some other significant hurdles in disease control. Despite the availability of rVSV-ZEBOV/Erbevo vaccine and many antibody-based vaccines, challenges including politicization, low access to remote communities, and illiteracy have limited their effectiveness. Recently, the Congolese govt. has put in efforts such as building local capacities at the health zone level, outbreak control intervention, community engagement and social mobilization to counter the rising EVD cases. Four successive Strategic Response Plans have been implemented to increase resource mobilization by DR Congo and her partners. The Spread of zoonotics such as EVD can be confronted by implementing the One Health approach, which involves medical staff, veterinarians and public health officials.
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Affiliation(s)
- Bilal Ahmad
- Department of Community Medicine and Public Health, Shaikh Khalifa bin Zayed Al Nahyan Medical and Dental College
| | - Martin Sagide
- Jomo Kenyatta University of Agriculture and Technology, Juja
| | | | - Elysée Byiringiro
- Department of Internal Medicine, Kibagabaga District Hospital, Kigali, Rwanda
- Department of Research, Medical Research Circle (MedReC), Bukavu
| | - Elie Kihanduka
- Department of Research, Medical Research Circle (MedReC), Bukavu
| | | | - Samson Hangi
- Department of Research, Medical Research Circle (MedReC), Bukavu
- Faculty of Medicine, La Sapientia Catholic University
| | | | - Babar Ali
- The University of Lahore
- University Institute of Radiological Sciences and Medical Imaging Technology, Lahore, Pakistan
| | | | | | | | - Jones Onesime
- Department of Research, Medical Research Circle (MedReC), Bukavu
| | - Christian Tague
- Faculty of Medicine, Université Libre des Pays des Grands Lacs, Goma
| | - Amos Kipkorir Langat
- Pan African University for Basic Sciences Technology and innovation, Nairobi, Kenya
| | - Aymar Akilimali
- Department of Research, Medical Research Circle (MedReC), Bukavu
- SCORE, Medical Students Association of DR Congo
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Obeng-Kusi M, Martin J, Abraham I. The economic burden of Ebola virus disease: a review and recommendations for analysis. J Med Econ 2024; 27:309-323. [PMID: 38299454 DOI: 10.1080/13696998.2024.2313358] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/29/2023] [Accepted: 01/30/2024] [Indexed: 02/02/2024]
Abstract
BACKGROUND Ebola virus disease (EVD) continues to be a major public health threat globally, particularly in the low-and-middle-income countries (LMICs) of Africa. The social and economic burdens of EVD are substantial and have triggered extensive research into prevention and control. We aim to highlight the impact and economic implications, identify research gaps, and offer recommendations for future economic studies pertaining to EVD. METHOD We conducted a comprehensive librarian-led search in PubMed/Medline, Embase, Google Scholar, EconLit and Scopus for economic evaluations of EVD. After study selection and data extraction, findings on the impact and economics of EVD were synthesized using a narrative approach, while identifying gaps, and recommending critical areas for future EVD economic studies. RESULTS The economic evaluations focused on the burden of illness, vaccine cost-effectiveness, willingness-to-pay for a vaccine, EVD funding, and preparedness costs. The estimated economic impact of the 2014 EVD outbreak in Guinea, Liberia, and Sierra Leone across studies ranged from $30 billion to $50 billion. Facility construction and modification emerged as significant cost drivers for preparedness. The EVD vaccine demonstrated cost-effectiveness in a dynamic transmission model; resulting in an incremental cost-effectiveness ratio of about $96 per additional disability adjusted life year averted. Individuals exhibited greater willingness to be vaccinated if it incurred no personal cost, with a minority willing to pay about $1 for the vaccine. CONCLUSIONS The severe impact of EVD puts pressure on governments and the international community for better resource utilization and re-allocation. Several technical and methodological issues related to economic evaluation of EVD remain to be addressed, especially for LMICs. We recommend conducting cost-of-sequelae and cost-of-distribution analyses in addition to adapting existing economic analytical methods to EVD. Characteristics of the affected regions should be considered to provide evidence-based economic plans and economic-evaluation of mitigations that enhance resource allocation for prevention and treatment.
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Affiliation(s)
- Mavis Obeng-Kusi
- Center for Health Outcomes and PharmacoEconomic Research, University of Arizona, Tucson, AZ, USA
| | - Jennifer Martin
- Arizona Health Sciences Library, 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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