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Srivathsan A, Abdou A, Al-Khatib T, Apadinuwe SC, Badiane MD, Bucumi V, Chisenga T, Kabona G, Kabore M, Kanyi SK, Bella L, M’po N, Masika M, Minnih A, Sitoe HM, Mishra S, Olobio N, Omar FJ, Phiri I, Sanha S, Seife F, Sharma S, Tekeraoi R, Traore L, Watitu T, Bol YY, Borlase A, Deiner MS, Renneker KK, Hooper PJ, Emerson PM, Vasconcelos A, Arnold BF, Porco TC, Hollingsworth TD, Lietman TM, Blumberg S. District-Level Forecast of Achieving Trachoma Elimination as a Public Health Problem By 2030: An Ensemble Modelling Approach. Clin Infect Dis 2024; 78:S101-S107. [PMID: 38662700 PMCID: PMC11045026 DOI: 10.1093/cid/ciae031] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/28/2024] Open
Abstract
Assessing the feasibility of 2030 as a target date for global elimination of trachoma, and identification of districts that may require enhanced treatment to meet World Health Organization (WHO) elimination criteria by this date are key challenges in operational planning for trachoma programmes. Here we address these challenges by prospectively evaluating forecasting models of trachomatous inflammation-follicular (TF) prevalence, leveraging ensemble-based approaches. Seven candidate probabilistic models were developed to forecast district-wise TF prevalence in 11 760 districts, trained using district-level data on the population prevalence of TF in children aged 1-9 years from 2004 to 2022. Geographical location, history of mass drug administration treatment, and previously measured prevalence data were included in these models as key predictors. The best-performing models were included in an ensemble, using weights derived from their relative likelihood scores. To incorporate the inherent stochasticity of disease transmission and challenges of population-level surveillance, we forecasted probability distributions for the TF prevalence in each geographic district, rather than predicting a single value. Based on our probabilistic forecasts, 1.46% (95% confidence interval [CI]: 1.43-1.48%) of all districts in trachoma-endemic countries, equivalent to 172 districts, will exceed the 5% TF control threshold in 2030 with the current interventions. Global elimination of trachoma as a public health problem by 2030 may require enhanced intervention and/or surveillance of high-risk districts.
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Affiliation(s)
- Ariktha Srivathsan
- Francis I. Proctor Foundation, University of California, San Francisco, California, USA
| | - Amza Abdou
- Programme National de Santé Oculaire, Ministère De La Santé Publique, Niamey, Niger
| | - Tawfik Al-Khatib
- Prevention of Blindness Program, Ministry of Public Health & Population, Sana'a, Yemen
| | | | - Mouctar D Badiane
- Programme National de Promotion de La Santé Oculaire, Ministère de la Santé et de L'Action sociale, Dakar, Sénégal
| | - Victor Bucumi
- Département En Charge des Maladies Tropicales Négligées, Ministère De La Santé Publique Et De La Lutte Contre Le Sida, Bujumbura, Burundi
| | - Tina Chisenga
- Ministry of Health Public Health Department, Lusaka, Zambia
| | - George Kabona
- Neglected Tropical Disease Control Program, Ministry of Health and Social Welfare, Dar Es Salaam, United Republic of Tanzania
| | - Martin Kabore
- Programme national de lutte contre les maladies tropicales négligées, Ministère de la santé et de l'hygiène publique, Ouagadougou, Burkina Faso
| | - Sarjo Kebba Kanyi
- The National Eye Health Programme, Ministry of Health and Social Welfare, Banjul, Kanifing, The Gambia
| | - Lucienne Bella
- Programme National De Lutte Contre La Cécité, Ministère De La Santé Publique, Yaoundé, Cameroon
| | - Nekoua M’po
- Programme National De Lutte Contre Les Maladies Transmissibles, Ministère De La Santé, Cotonou, Benin
| | - Michael Masika
- Department of Clinical Services, Ministry of Health, Lilongwe, Malawi
| | - Abdellahi Minnih
- Département Des Maladies Transmissibles, Ministère De La Santé Nouakchott, Nouakchott, Mauritania
| | - Henis Mior Sitoe
- Direcção Nacional De Saúde Pública Ministerio Da Saude, Maputo, Mozambique
| | | | - Nicholas Olobio
- National Trachoma Elimination Programme, Federal Ministry of Health, Abuja, Nigeria
| | | | - Isaac Phiri
- Department of Epidemiology and Disease Control, Ministry of Health & Child Welfare, Harare, Zimbabwe
| | - Salimato Sanha
- Programa Nacional De Saúde De Visão, Minsap, Bissau, Guinea-Bissau
| | - Fikre Seife
- Federal Ministry of Health, Addis Ababa, Ethiopia
| | | | - Rabebe Tekeraoi
- Eye Department, Ministry of Health and Medical Services, South Tarawa, Kiribati
| | - Lamine Traore
- Programme National de la Santé Oculaire, Ministère de la Santé, Bamako, Mali
| | | | - Yak Yak Bol
- Neglected Tropical Diseases Programme, Ministry of Health, Juba, South Sudan
| | - Anna Borlase
- Department of Biology, University of Oxford, Oxford, United Kingdom
| | - Michael S Deiner
- Francis I. Proctor Foundation, University of California, San Francisco, California, USA
| | - Kristen K Renneker
- International Trachoma Initiative, The Task Force for Global Health, Decatur, Georgia, USA
| | - P J Hooper
- International Trachoma Initiative, The Task Force for Global Health, Decatur, Georgia, USA
| | - Paul M Emerson
- International Trachoma Initiative, The Task Force for Global Health, Decatur, Georgia, USA
| | - Andreia Vasconcelos
- Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, University of Oxford, Oxford, United Kingdom
| | - Benjamin F Arnold
- Francis I. Proctor Foundation, University of California, San Francisco, California, USA
| | - Travis C Porco
- Francis I. Proctor Foundation, University of California, San Francisco, California, USA
| | - T Déirdre Hollingsworth
- Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, University of Oxford, Oxford, United Kingdom
| | - Thomas M Lietman
- Francis I. Proctor Foundation, University of California, San Francisco, California, USA
| | - Seth Blumberg
- Francis I. Proctor Foundation, University of California, San Francisco, California, USA
- Department of Medicine, University of California, San Francisco, California, USA
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Vasconcelos A, King JD, Nunes-Alves C, Anderson R, Argaw D, Basáñez MG, Bilal S, Blok DJ, Blumberg S, Borlase A, Brady OJ, Browning R, Chitnis N, Coffeng LE, Crowley EH, Cucunubá ZM, Cummings DAT, Davis CN, Davis EL, Dixon M, Dobson A, Dyson L, French M, Fronterre C, Giorgi E, Huang CI, Jain S, James A, Kim SH, Kura K, Lucianez A, Marks M, Mbabazi PS, Medley GF, Michael E, Montresor A, Mutono N, Mwangi TS, Rock KS, Saboyá-Díaz MI, Sasanami M, Schwehm M, Spencer SEF, Srivathsan A, Stawski RS, Stolk WA, Sutherland SA, Tchuenté LAT, de Vlas SJ, Walker M, Brooker SJ, Hollingsworth TD, Solomon AW, Fall IS. Accelerating Progress Towards the 2030 Neglected Tropical Diseases Targets: How Can Quantitative Modeling Support Programmatic Decisions? Clin Infect Dis 2024; 78:S83-S92. [PMID: 38662692 PMCID: PMC11045030 DOI: 10.1093/cid/ciae082] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/28/2024] Open
Abstract
Over the past decade, considerable progress has been made in the control, elimination, and eradication of neglected tropical diseases (NTDs). Despite these advances, most NTD programs have recently experienced important setbacks; for example, NTD interventions were some of the most frequently and severely impacted by service disruptions due to the coronavirus disease 2019 (COVID-19) pandemic. Mathematical modeling can help inform selection of interventions to meet the targets set out in the NTD road map 2021-2030, and such studies should prioritize questions that are relevant for decision-makers, especially those designing, implementing, and evaluating national and subnational programs. In September 2022, the World Health Organization hosted a stakeholder meeting to identify such priority modeling questions across a range of NTDs and to consider how modeling could inform local decision making. Here, we summarize the outputs of the meeting, highlight common themes in the questions being asked, and discuss how quantitative modeling can support programmatic decisions that may accelerate progress towards the 2030 targets.
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Affiliation(s)
- Andreia Vasconcelos
- Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, Nuffield Department of Medicine, University of Oxford, Old Road Campus, Oxford, United Kingdom
- Centre for Global Health Research, Nuffield Department of Medicine, University of Oxford, Old Road Campus, Oxford, United Kingdom
| | - Jonathan D King
- Global Neglected Tropical Diseases Programme, World Health Organization, Geneva, Switzerland
| | - Cláudio Nunes-Alves
- Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, Nuffield Department of Medicine, University of Oxford, Old Road Campus, Oxford, United Kingdom
| | - Roy Anderson
- London Centre for Neglected Tropical Disease Research, London, United Kingdom
- Department of Infectious Disease Epidemiology, School of Public Health, Faculty of Medicine, St Mary's Campus, Imperial College London, London, United Kingdom
- MRC Centre for Global Infectious Disease Analysis, School of Public Health, Imperial College London, London, United Kingdom
| | - Daniel Argaw
- Global Neglected Tropical Diseases Programme, World Health Organization, Geneva, Switzerland
| | - Maria-Gloria Basáñez
- London Centre for Neglected Tropical Disease Research, London, United Kingdom
- Department of Infectious Disease Epidemiology, School of Public Health, Faculty of Medicine, St Mary's Campus, Imperial College London, London, United Kingdom
- MRC Centre for Global Infectious Disease Analysis, School of Public Health, Imperial College London, London, United Kingdom
| | - Shakir Bilal
- Department of Biological Sciences, University of Notre Dame, Notre Dame, Indiana, USA
| | - David J Blok
- Department of Public Health, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands
| | - Seth Blumberg
- Francis I. Proctor Foundation, University of California, San Francisco, California, USA
| | - Anna Borlase
- Department of Biology, University of Oxford, Oxford, United Kingdom
| | - Oliver J Brady
- Department of Infectious Disease Epidemiology, Faculty of Epidemiology and Population Health, London School of Hygiene & Tropical Medicine, London, United Kingdom
- Centre for the Mathematical Modelling of Infectious Diseases, London School of Hygiene & Tropical Medicine, London, United Kingdom
| | - Raiha Browning
- The Department of Statistics, The University of Warwick, Coventry, United Kingdom
| | - Nakul Chitnis
- Department of Epidemiology and Public Health, Swiss Tropical and Public Health Institute, Allschwil, Switzerland
- University of Basel, Basel, Switzerland
| | - Luc E Coffeng
- Department of Public Health, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands
| | - Emily H Crowley
- Zeeman Institute for System Biology and Infectious Disease Epidemiology Research, The University of Warwick, Coventry, United Kingdom
- Mathematics Institute, The University of Warwick, Coventry, United Kingdom
| | - Zulma M Cucunubá
- Departamento de Epidemiología Clínica y Bioestadística, Facultad de Medicina, Universidad Pontificia Javeriana, Bogotá, Colombia
| | - Derek A T Cummings
- Department of Biology, University of Florida, Gainesville, Florida, USA
- Emerging Pathogens Institute, University of Florida, Gainesville, Florida, USA
| | - Christopher Neil Davis
- Zeeman Institute for System Biology and Infectious Disease Epidemiology Research, The University of Warwick, Coventry, United Kingdom
- Mathematics Institute, The University of Warwick, Coventry, United Kingdom
| | - Emma Louise Davis
- Mathematics Institute, The University of Warwick, Coventry, United Kingdom
| | - Matthew Dixon
- London Centre for Neglected Tropical Disease Research, London, United Kingdom
- Department of Infectious Disease Epidemiology, School of Public Health, Faculty of Medicine, St Mary's Campus, Imperial College London, London, United Kingdom
- MRC Centre for Global Infectious Disease Analysis, School of Public Health, Imperial College London, London, United Kingdom
| | - Andrew Dobson
- Department of Ecology and Evolutionary Biology, Princeton University, Princeton, New Jersey, USA
| | - Louise Dyson
- Zeeman Institute for System Biology and Infectious Disease Epidemiology Research, The University of Warwick, Coventry, United Kingdom
- Mathematics Institute, The University of Warwick, Coventry, United Kingdom
| | - Michael French
- Schistosomiasis Control Initiative, Department of Infectious Disease Epidemiology, St Mary's Campus, Imperial College London, London, United Kingdom
- RTI International, Washington, D.C., USA
| | - Claudio Fronterre
- CHICAS, Lancaster Medical School, Lancaster University, Lancaster, United Kingdom
| | - Emanuele Giorgi
- CHICAS, Lancaster Medical School, Lancaster University, Lancaster, United Kingdom
| | - Ching-I Huang
- Zeeman Institute for System Biology and Infectious Disease Epidemiology Research, The University of Warwick, Coventry, United Kingdom
- Mathematics Institute, The University of Warwick, Coventry, United Kingdom
| | - Saurabh Jain
- Global Neglected Tropical Diseases Programme, World Health Organization, Geneva, Switzerland
| | - Ananthu James
- Department of Public Health, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands
| | - Sung Hye Kim
- Global Neglected Tropical Diseases Programme, World Health Organization, Geneva, Switzerland
| | - Klodeta Kura
- London Centre for Neglected Tropical Disease Research, London, United Kingdom
- Department of Infectious Disease Epidemiology, School of Public Health, Faculty of Medicine, St Mary's Campus, Imperial College London, London, United Kingdom
- MRC Centre for Global Infectious Disease Analysis, School of Public Health, Imperial College London, London, United Kingdom
| | - Ana Lucianez
- Communicable Diseases Prevention, Control, and Elimination, Pan American Health Organization, Washington D.C., USA
| | - Michael Marks
- Faculty of Infectious and Tropical Diseases, London School of Hygiene & Tropical Medicine, London, United Kingdom
| | - Pamela Sabina Mbabazi
- Global Neglected Tropical Diseases Programme, World Health Organization, Geneva, Switzerland
| | - Graham F Medley
- Department of Infectious Disease Epidemiology, Faculty of Epidemiology and Population Health, London School of Hygiene & Tropical Medicine, London, United Kingdom
| | - Edwin Michael
- College of Public Health, University of South Florida, Tampa, Florida, USA
| | - Antonio Montresor
- Global Neglected Tropical Diseases Programme, World Health Organization, Geneva, Switzerland
| | - Nyamai Mutono
- Centre for Epidemiological Modelling and Analysis, University of Nairobi, Nairobi, Kenya
- Paul G. Allen School for Global Health, Washington State University, Pullman, Washington, USA
| | - Thumbi S Mwangi
- Centre for Epidemiological Modelling and Analysis, University of Nairobi, Nairobi, Kenya
- Paul G. Allen School for Global Health, Washington State University, Pullman, Washington, USA
- Institute of Immunology and Infection Research, University of Edinburgh, Edinburgh, United Kingdom
| | - Kat S Rock
- Zeeman Institute for System Biology and Infectious Disease Epidemiology Research, The University of Warwick, Coventry, United Kingdom
- Mathematics Institute, The University of Warwick, Coventry, United Kingdom
| | - Martha-Idalí Saboyá-Díaz
- Communicable Diseases Prevention, Control, and Elimination, Pan American Health Organization, Washington D.C., USA
| | - Misaki Sasanami
- Lancaster Medical School, Lancaster University, Lancaster, United Kingdom
| | - Markus Schwehm
- ExploSYS GmbH, Interdisciplinary Institute for Exploratory Systems, Leinfelden-Echterdingen, Germany
| | - Simon E F Spencer
- Centre for the Mathematical Modelling of Infectious Diseases, London School of Hygiene & Tropical Medicine, London, United Kingdom
| | - Ariktha Srivathsan
- Francis I. Proctor Foundation, University of California, San Francisco, California, USA
| | - Robert S Stawski
- Institute of Public Health and Wellbeing, School of Health and Social Care, University of Essex, Essex, United Kingdom
| | - Wilma A Stolk
- Department of Public Health, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands
| | - Samuel A Sutherland
- Zeeman Institute for System Biology and Infectious Disease Epidemiology Research, The University of Warwick, Coventry, United Kingdom
- Warwick Medical School, The University of Warwick, Coventry, United Kingdom
| | | | - Sake J de Vlas
- Department of Public Health, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands
| | - Martin Walker
- London Centre for Neglected Tropical Disease Research, London, United Kingdom
- Department of Pathobiology and Population Sciences, Royal Veterinary College, University of London, London, United Kingdom
| | | | - T Déirdre Hollingsworth
- Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, Nuffield Department of Medicine, University of Oxford, Old Road Campus, Oxford, United Kingdom
| | - Anthony W Solomon
- Global Neglected Tropical Diseases Programme, World Health Organization, Geneva, Switzerland
| | - Ibrahima Socé Fall
- Global Neglected Tropical Diseases Programme, World Health Organization, Geneva, Switzerland
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Borlase A, Prada JM, Crellen T. Modelling morbidity for neglected tropical diseases: the long and winding road from cumulative exposure to long-term pathology. Philos Trans R Soc Lond B Biol Sci 2023; 378:20220279. [PMID: 37598702 PMCID: PMC10440174 DOI: 10.1098/rstb.2022.0279] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/14/2023] [Accepted: 07/13/2023] [Indexed: 08/22/2023] Open
Abstract
Reducing the morbidities caused by neglected tropical diseases (NTDs) is a central aim of ongoing disease control programmes. The broad spectrum of pathogens under the umbrella of NTDs lead to a range of negative health outcomes, from malnutrition and anaemia to organ failure, blindness and carcinogenesis. For some NTDs, the most severe clinical manifestations develop over many years of chronic or repeated infection. For these diseases, the association between infection and risk of long-term pathology is generally complex, and the impact of multiple interacting factors, such as age, co-morbidities and host immune response, is often poorly quantified. Mathematical modelling has been used for many years to gain insights into the complex processes underlying the transmission dynamics of infectious diseases; however, long-term morbidities associated with chronic or cumulative exposure are generally not incorporated into dynamic models for NTDs. Here we consider the complexities and challenges for determining the relationship between cumulative pathogen exposure and morbidity at the individual and population levels, drawing on case studies for trachoma, schistosomiasis and foodborne trematodiasis. We explore potential frameworks for explicitly incorporating long-term morbidity into NTD transmission models, and consider the insights such frameworks may bring in terms of policy-relevant projections for the elimination era. This article is part of the theme issue 'Challenges and opportunities in the fight against neglected tropical diseases: a decade from the London Declaration on NTDs'.
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Affiliation(s)
- Anna Borlase
- Department of Biology, University of Oxford, Oxford OX1 3SZ, UK
- Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, University of Oxford, Oxford OX3 7LF, UK
| | - Joaquin M. Prada
- Faculty of Health and Medical Sciences, University of Surrey, Guildford GU2 7XH, UK
| | - Thomas Crellen
- Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, University of Oxford, Oxford OX3 7LF, UK
- School of Biodiversity, One Health & Veterinary Medicine, Graham Kerr Building, University of Glasgow, Glasgow G12 8QQ, UK
- Wellcome Centre for Integrative Parasitology, Sir Graeme Davies Building, University of Glasgow, Glasgow G12 8TA, UK
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Calvo-Urbano B, Léger E, Gabain I, De Dood CJ, Diouf ND, Borlase A, Rudge JW, Corstjens PLAM, Sène M, Van Dam GJ, Walker M, Webster JP. Sensitivity and specificity of human point-of-care circulating cathodic antigen (POC-CCA) test in African livestock for rapid diagnosis of schistosomiasis: A Bayesian latent class analysis. PLoS Negl Trop Dis 2023; 17:e0010739. [PMID: 37216407 DOI: 10.1371/journal.pntd.0010739] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/16/2022] [Accepted: 04/29/2023] [Indexed: 05/24/2023] Open
Abstract
Schistosomiasis is a major neglected tropical disease (NTD) affecting both humans and animals. The morbidity and mortality inflicted upon livestock in the Afrotropical region has been largely overlooked, in part due to a lack of validated sensitive and specific tests, which do not require specialist training or equipment to deliver and interpret. As stressed within the recent WHO NTD 2021-2030 Roadmap and Revised Guideline for schistosomiasis, inexpensive, non-invasive, and sensitive diagnostic tests for livestock-use would also facilitate both prevalence mapping and appropriate intervention programmes. The aim of this study was to assess the sensitivity and specificity of the currently available point-of-care circulating cathodic antigen test (POC-CCA), designed for Schistosoma mansoni detection in humans, for the detection of intestinal livestock schistosomiasis caused by Schistosoma bovis and Schistosoma curassoni. POC-CCA, together with the circulating anodic antigen (CAA) test, miracidial hatching technique (MHT) and organ and mesentery inspection (for animals from abattoirs only), were applied to samples collected from 195 animals (56 cattle and 139 small ruminants (goats and sheep) from abattoirs and living populations) from Senegal. POC-CCA sensitivity was greater in the S. curassoni-dominated Barkedji livestock, both for cattle (median 81%; 95% credible interval (CrI): 55%-98%) and small ruminants (49%; CrI: 29%-87%), than in S. bovis-dominated Richard Toll ruminants (cattle: 62%; CrI: 41%-84%; small ruminants: 12%, CrI: 1%-37%). Overall, sensitivity was greater in cattle than in small ruminants. Small ruminants POC-CCA specificity was similar in both locations (91%; CrI: 77%-99%), whilst cattle POC-CCA specificity could not be assessed owing to the low number of uninfected cattle surveyed. Our results indicate that, whilst the current POC-CCA does represent a potential diagnostic tool for cattle and possibly for predominantly S. curassoni-infected livestock, future work is needed to develop parasite- and/or livestock-specific affordable and field-applicable diagnostic tests to enable determination of the true extent of livestock schistosomiasis.
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Affiliation(s)
- Beatriz Calvo-Urbano
- Royal Veterinary College, Department of Pathobiology and Population Sciences, University of London, Hatfield, United Kingdom
- London Centre for Neglected Tropical Disease Research, School of Public Health, Department of Infectious Disease Epidemiology, Imperial College Faculty of Medicine, London, United Kingdom
| | - Elsa Léger
- Royal Veterinary College, Department of Pathobiology and Population Sciences, University of London, Hatfield, United Kingdom
- London Centre for Neglected Tropical Disease Research, School of Public Health, Department of Infectious Disease Epidemiology, Imperial College Faculty of Medicine, London, United Kingdom
| | - Isobel Gabain
- Royal Veterinary College, Department of Pathobiology and Population Sciences, University of London, Hatfield, United Kingdom
- London Centre for Neglected Tropical Disease Research, School of Public Health, Department of Infectious Disease Epidemiology, Imperial College Faculty of Medicine, London, United Kingdom
| | | | - Nicolas D Diouf
- Unité de Formation et de Recherche des Sciences Agronomiques, d'Aquaculture et de Technologies Alimentaires, Université Gaston Berger, Saint Louis, Senegal
| | - Anna Borlase
- Royal Veterinary College, Department of Pathobiology and Population Sciences, University of London, Hatfield, United Kingdom
- Department of Biology, University of Oxford, Oxford, United Kingdom
| | - James W Rudge
- London Centre for Neglected Tropical Disease Research, School of Public Health, Department of Infectious Disease Epidemiology, Imperial College Faculty of Medicine, London, United Kingdom
- Communicable Diseases Policy Research Group, Department of Global Health and Development, London School of Hygiene and Tropical Medicine, London, United Kingdom
- Faculty of Public Health, Mahidol University, Bangkok, Thailand
| | | | - Mariama Sène
- Unité de Formation et de Recherche des Sciences Agronomiques, d'Aquaculture et de Technologies Alimentaires, Université Gaston Berger, Saint Louis, Senegal
| | | | - Martin Walker
- Royal Veterinary College, Department of Pathobiology and Population Sciences, University of London, Hatfield, United Kingdom
- London Centre for Neglected Tropical Disease Research, School of Public Health, Department of Infectious Disease Epidemiology, Imperial College Faculty of Medicine, London, United Kingdom
| | - Joanne P Webster
- Royal Veterinary College, Department of Pathobiology and Population Sciences, University of London, Hatfield, United Kingdom
- London Centre for Neglected Tropical Disease Research, School of Public Health, Department of Infectious Disease Epidemiology, Imperial College Faculty of Medicine, London, United Kingdom
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Borlase A, Le Rutte EA, Castaño S, Blok DJ, Toor J, Giardina F, Davis EL. Evaluating and mitigating the potential indirect effect of COVID-19 on control programmes for seven neglected tropical diseases: a modelling study. Lancet Glob Health 2022; 10:e1600-e1611. [PMID: 36240827 PMCID: PMC9579354 DOI: 10.1016/s2214-109x(22)00360-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/19/2022] [Revised: 07/25/2022] [Accepted: 08/03/2022] [Indexed: 11/06/2022]
Abstract
Background In line with movement restrictions and physical distancing essential for the control of the COVID-19 pandemic, WHO recommended postponement of all neglected tropical disease (NTD) control activities that involve community-based surveys, active case finding, and mass drug administration in April, 2020. Following revised guidance later in 2020, and after interruptions to NTD programmes of varying lengths, NTD programmes gradually restarted in the context of an ongoing pandemic. However, ongoing challenges and service gaps have been reported. This study aimed to evaluate the potential effect of the programmatic interruptions and strategies to mitigate this effect. Methods For seven NTDs, namely soil-transmitted helminths, schistosomiasis, lymphatic filariasis, onchocerciasis, trachoma, visceral leishmaniasis, and human African trypanosomiasis, we used mathematical transmission models to simulate the effect of programme interruptions on the dynamics of each of these diseases in different endemic settings. We also explored the potential benefit of implementing mitigation strategies, primarily in terms of minimising the delays to control targets. Findings We show that the effect of the COVID-19-induced interruption in terms of delay to achieving elimination goals might in some cases be much longer than the duration of the interruption. For schistosomiasis, onchocerciasis, trachoma, and visceral leishmaniasis, a mean delay of 2–3 years for a 1-year interruption is predicted in areas of highest prevalence. We also show that these delays can largely be mitigated by measures such as additional mass drug administration or enhanced case-finding. Interpretation The COVID-19 pandemic has brought infectious disease control to the forefront of global consciousness. It is essential that the NTDs, so long neglected in terms of research and financial support, are not overlooked, and remain a priority in health service planning and funding. Funding Bill & Melinda Gates Foundation, Medical Research Council, and the UK Foreign, Commonwealth & Development Office.
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Affiliation(s)
- Anna Borlase
- Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, University of Oxford, Oxford, UK
| | - Epke A Le Rutte
- Department of Public Health, Erasmus MC, University Medical Center Rotterdam, Rotterdam, Netherlands; Department of Epidemiology and Public Health, Swiss Tropical and Public Health Institute, Allschwil, Switzerland; University of Basel, Basel, Switzerland
| | - Soledad Castaño
- Department of Epidemiology and Public Health, Swiss Tropical and Public Health Institute, Allschwil, Switzerland; University of Basel, Basel, Switzerland; LYO-X, Allschwil, Switzerland
| | - David J Blok
- Department of Public Health, Erasmus MC, University Medical Center Rotterdam, Rotterdam, Netherlands
| | - Jaspreet Toor
- Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, University of Oxford, Oxford, UK; MRC Centre for Global Infectious Disease Analysis, Department of Infectious Disease Epidemiology, School of Public Health, Imperial College London, London, UK
| | - Federica Giardina
- Department of Public Health, Erasmus MC, University Medical Center Rotterdam, Rotterdam, Netherlands; Department of Health Evidence, Radboud University Medical Center, Nijmegen, Netherlands
| | - Emma L Davis
- Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, University of Oxford, Oxford, UK; Mathematics Institute, University of Warwick, Coventry, UK.
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Díaz AV, Lambert S, Neves MI, Borlase A, Léger E, Diouf ND, Sène M, Webster JP, Walker M. Modelling livestock test-and-treat: A novel One Health strategy to control schistosomiasis and mitigate drug resistance. Front Trop Dis 2022. [DOI: 10.3389/fitd.2022.893066] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/13/2022] Open
Abstract
Schistosomiasis, a neglected tropical disease, is a widespread chronic helminthiasis reported in 78 countries, predominantly those within sub-Saharan Africa, as well as Latin America, Asia, and most recently, even Europe. Species of the causative blood fluke infect not only humans but also animals, and hybrids between previously assumed human-specific and animal-specific schistosomes are being increasingly reported. Existing control programs across Africa focus on humans and rely heavily on mass drug administration of praziquantel, the sole drug available against schistosomiasis. Praziquantel is safe and highly efficacious but could become ineffective if resistance emerges. To reach the revised World Health Organization goal of elimination of schistosomiasis as a public health problem, and interruption of transmission within selected regions, by 2030, new consideration of the role of animal reservoirs in human transmission in general, and whether to also treat livestock with praziquantel in particular, has been raised. However, whilst there are no dedicated control programs targeting animals outside of Asia, there are emerging reports of the use and misuse of praziquantel in livestock across Africa. Therefore, to effectively treat livestock in Africa and to help mitigate against the potential evolution of praziquantel resistance, structured control strategies are required. Here, using a transmission modelling approach, we evaluate the potential effectiveness of a theoretical test-and-treat (TnT) strategy to control bovine schistosomiasis using a currently available point-of-care diagnostic test (developed for human use) to detect circulating cathodic antigen (POC-CCA). We show that implementing TnT at herd-level from 2022 to 2030 could be highly effective in suppressing infection in cattle and even, in lower prevalence settings, reaching nominal ‘elimination’ targets. We highlight the importance of enhancing the specificity of POC-CCA for use in livestock to avoid unnecessary treatments and discuss the outstanding challenges associated with implementing TnT as part of a holistic One Health approach to tackling human and animal schistosomiasis.
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Crellen T, Pi L, Davis EL, Pollington TM, Lucas TCD, Ayabina D, Borlase A, Toor J, Prem K, Medley GF, Klepac P, Déirdre Hollingsworth T. Dynamics of SARS-CoV-2 with waning immunity in the UK population. Philos Trans R Soc Lond B Biol Sci 2021; 376:20200274. [PMID: 34053264 PMCID: PMC8165597 DOI: 10.1098/rstb.2020.0274] [Citation(s) in RCA: 19] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 01/06/2021] [Indexed: 12/15/2022] Open
Abstract
The dynamics of immunity are crucial to understanding the long-term patterns of the SARS-CoV-2 pandemic. Several cases of reinfection with SARS-CoV-2 have been documented 48-142 days after the initial infection and immunity to seasonal circulating coronaviruses is estimated to be shorter than 1 year. Using an age-structured, deterministic model, we explore potential immunity dynamics using contact data from the UK population. In the scenario where immunity to SARS-CoV-2 lasts an average of three months for non-hospitalized individuals, a year for hospitalized individuals, and the effective reproduction number after lockdown ends is 1.2 (our worst-case scenario), we find that the secondary peak occurs in winter 2020 with a daily maximum of 387 000 infectious individuals and 125 000 daily new cases; threefold greater than in a scenario with permanent immunity. Our models suggest that longitudinal serological surveys to determine if immunity in the population is waning will be most informative when sampling takes place from the end of the lockdown in June until autumn 2020. After this period, the proportion of the population with antibodies to SARS-CoV-2 is expected to increase due to the secondary wave. Overall, our analysis presents considerations for policy makers on the longer-term dynamics of SARS-CoV-2 in the UK and suggests that strategies designed to achieve herd immunity may lead to repeated waves of infection as immunity to reinfection is not permanent. This article is part of the theme issue 'Modelling that shaped the early COVID-19 pandemic response in the UK'.
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Affiliation(s)
- Thomas Crellen
- Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, University of Oxford, Oxford OX3 7LF, UK
| | - Li Pi
- Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, University of Oxford, Oxford OX3 7LF, UK
| | - Emma L. Davis
- Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, University of Oxford, Oxford OX3 7LF, UK
| | - Timothy M. Pollington
- Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, University of Oxford, Oxford OX3 7LF, UK
- MathSys CDT, University of Warwick, Coventry CV4 7AL, UK
| | - Tim C. D. Lucas
- Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, University of Oxford, Oxford OX3 7LF, UK
| | - Diepreye Ayabina
- Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, University of Oxford, Oxford OX3 7LF, UK
| | - Anna Borlase
- Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, University of Oxford, Oxford OX3 7LF, UK
| | - Jaspreet Toor
- Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, University of Oxford, Oxford OX3 7LF, UK
| | - Kiesha Prem
- London School of Hygiene and Tropical Medicine, London WC1E 7HT, UK
| | - Graham F. Medley
- London School of Hygiene and Tropical Medicine, London WC1E 7HT, UK
| | - Petra Klepac
- London School of Hygiene and Tropical Medicine, London WC1E 7HT, UK
| | - T. Déirdre Hollingsworth
- Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, University of Oxford, Oxford OX3 7LF, UK
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8
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Blumberg S, Prada JM, Tedijanto C, Deiner MS, Godwin WW, Emerson PM, Hooper PJ, Borlase A, Hollingsworth TD, Oldenburg CE, Porco TC, Arnold BF, Lietman TM. Forecasting Trachoma Control and Identifying Transmission-Hotspots. Clin Infect Dis 2021; 72:S134-S139. [PMID: 33905484 PMCID: PMC8201580 DOI: 10.1093/cid/ciab189] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/17/2022] Open
Abstract
Background Tremendous progress towards elimination of trachoma as a public health problem has been made. However, there are areas where the clinical indicator of disease, trachomatous inflammation—follicular (TF), remains prevalent. We quantify the progress that has been made, and forecast how TF prevalence will evolve with current interventions. We also determine the probability that a district is a transmission-hotspot based on its TF prevalence (ie, reproduction number greater than one). Methods Data on trachoma prevalence come from the GET2020 global repository organized by the World Health Organization and the International Trachoma Initiative. Forecasts of TF prevalence and the percent of districts with local control is achieved by regressing the coefficients of a fitted exponential distribution for the year-by-year distribution of TF prevalence. The probability of a district being a transmission-hotspot is extrapolated from the residuals of the regression. Results Forecasts suggest that with current interventions, 96.5% of surveyed districts will have TF prevalence among children aged 1–9 years <5% by 2030 (95% CI: 86.6%–100.0%). Districts with TF prevalence < 20% appear unlikely to be transmission-hotspots. However, a district having TF prevalence of over 28% in 2016–2019 corresponds to at least 50% probability of being a transmission-hotspot. Conclusions Sustainable control of trachoma appears achievable. However there are transmission-hotspots that are not responding to annual mass drug administration of azithromycin and require enhanced treatment in order to reach local control.
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Affiliation(s)
- Seth Blumberg
- Francis I Proctor Foundation, University of California San Francisco, San Francisco, CA, USA.,Department of Medicine, University of California San Francisco, San Francisco, CA, USA
| | - Joaquin M Prada
- Faculty of Health and Medical Sciences, School of Veterinary Medicine, University of Surrey, Guildford, UK
| | - Christine Tedijanto
- Francis I Proctor Foundation, University of California San Francisco, San Francisco, CA, USA
| | - Michael S Deiner
- Francis I Proctor Foundation, University of California San Francisco, San Francisco, CA, USA
| | - William W Godwin
- Francis I Proctor Foundation, University of California San Francisco, San Francisco, CA, USA
| | - Paul M Emerson
- International Trachoma Initiative, The Task Force for Global Health, Decatur, Georgia, USA
| | - Pamela J Hooper
- International Trachoma Initiative, The Task Force for Global Health, Decatur, Georgia, USA
| | - Anna Borlase
- Nuffield Department of Medicine, Medical Sciences Division, University of Oxford, Oxford, UK
| | - T Deirdre Hollingsworth
- Nuffield Department of Medicine, Medical Sciences Division, University of Oxford, Oxford, UK
| | - Catherine E Oldenburg
- Francis I Proctor Foundation, University of California San Francisco, San Francisco, CA, USA.,Department of Epidemiology and Biostatistics, University of California San Francisco, San Francisco, CA, USA.,Department of Ophthalmology, University of California San Francisco, San Francisco, CA, USA
| | - Travis C Porco
- Francis I Proctor Foundation, University of California San Francisco, San Francisco, CA, USA.,Department of Epidemiology and Biostatistics, University of California San Francisco, San Francisco, CA, USA.,Department of Ophthalmology, University of California San Francisco, San Francisco, CA, USA
| | - Benjamin F Arnold
- Francis I Proctor Foundation, University of California San Francisco, San Francisco, CA, USA.,Department of Ophthalmology, University of California San Francisco, San Francisco, CA, USA
| | - Thomas M Lietman
- Francis I Proctor Foundation, University of California San Francisco, San Francisco, CA, USA.,Department of Epidemiology and Biostatistics, University of California San Francisco, San Francisco, CA, USA.,Department of Ophthalmology, University of California San Francisco, San Francisco, CA, USA.,Institute for Global Health Sciences, University of California San Francisco, San Francisco, CA, USA
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9
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Catalano S, Léger E, Fall CB, Borlase A, Diop SD, Berger D, Webster BL, Faye B, Diouf ND, Rollinson D, Sène M, Bâ K, Webster JP. Multihost Transmission of Schistosoma mansoni in Senegal, 2015-2018. Emerg Infect Dis 2021; 26:1234-1242. [PMID: 32441625 PMCID: PMC7258455 DOI: 10.3201/eid2606.200107] [Citation(s) in RCA: 23] [Impact Index Per Article: 7.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/21/2023] Open
Abstract
In West Africa, Schistosoma spp. are capable of infecting multiple definitive hosts, a lifecycle feature that may complicate schistosomiasis control. We characterized the evolutionary relationships among multiple Schistosoma mansoni isolates collected from snails (intermediate hosts), humans (definitive hosts), and rodents (definitive hosts) in Senegal. On a local scale, diagnosis of S. mansoni infection ranged 3.8%-44.8% in school-aged children, 1.7%-52.6% in Mastomys huberti mice, and 1.8%-7.1% in Biomphalaria pfeifferi snails. Our phylogenetic framework confirmed the presence of multiple S. mansoni lineages that could infect both humans and rodents; divergence times of these lineages varied (0.13-0.02 million years ago). We propose that extensive movement of persons across West Africa might have contributed to the establishment of these various multihost S. mansoni clades. High S. mansoni prevalence in rodents at transmission sites frequented by humans further highlights the implications that alternative hosts could have on future public health interventions.
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10
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Lucas TCD, Davis EL, Ayabina D, Borlase A, Crellen T, Pi L, Medley GF, Yardley L, Klepac P, Gog J, Déirdre Hollingsworth T. Engagement and adherence trade-offs for SARS-CoV-2 contact tracing. Philos Trans R Soc Lond B Biol Sci 2021; 376:20200270. [PMID: 34053257 PMCID: PMC8165588 DOI: 10.1098/rstb.2020.0270] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/23/2022] Open
Abstract
Contact tracing is an important tool for allowing countries to ease lockdown policies introduced to combat SARS-CoV-2. For contact tracing to be effective, those with symptoms must self-report themselves while their contacts must self-isolate when asked. However, policies such as legal enforcement of self-isolation can create trade-offs by dissuading individuals from self-reporting. We use an existing branching process model to examine which aspects of contact tracing adherence should be prioritized. We consider an inverse relationship between self-isolation adherence and self-reporting engagement, assuming that increasingly strict self-isolation policies will result in fewer individuals self-reporting to the programme. We find that policies which increase the average duration of self-isolation, or that increase the probability that people self-isolate at all, at the expense of reduced self-reporting rate, will not decrease the risk of a large outbreak and may increase the risk, depending on the strength of the trade-off. These results suggest that policies to increase self-isolation adherence should be implemented carefully. Policies that increase self-isolation adherence at the cost of self-reporting rates should be avoided. This article is part of the theme issue ‘Modelling that shaped the early COVID-19 pandemic response in the UK’.
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Affiliation(s)
- Tim C D Lucas
- Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, University of Oxford, Oxford, UK
| | - Emma L Davis
- Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, University of Oxford, Oxford, UK
| | - Diepreye Ayabina
- Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, University of Oxford, Oxford, UK
| | - Anna Borlase
- Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, University of Oxford, Oxford, UK
| | - Thomas Crellen
- Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, University of Oxford, Oxford, UK
| | - Li Pi
- Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, University of Oxford, Oxford, UK
| | - Graham F Medley
- MathSys CDT, University of Warwick, Coventry, UK.,Centre for Mathematical Modelling of Infectious Disease and Department of Global Health and Development, London School of Hygiene and Tropical Medicine, London, UK
| | - Lucy Yardley
- School of Psychology, University of Southampton, Southampton, UK.,School of Psychological Science, University of Bristol, Bristol, UK
| | - Petra Klepac
- Department of Infectious Disease Epidemiology, London School of Hygiene and Tropical Medicine, London, UK.,Department for Applied Mathematics and Theoretical Physics, University of Cambridge, Cambridge, UK
| | - Julia Gog
- Department for Applied Mathematics and Theoretical Physics, University of Cambridge, Cambridge, UK
| | - T Déirdre Hollingsworth
- Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, University of Oxford, Oxford, UK
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11
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Blumberg S, Borlase A, Prada JM, Solomon AW, Emerson P, Hooper PJ, Deiner MS, Amoah B, Hollingsworth TD, Porco TC, Lietman TM. Implications of the COVID-19 pandemic in eliminating trachoma as a public health problem. Trans R Soc Trop Med Hyg 2021; 115:222-228. [PMID: 33449114 PMCID: PMC7928550 DOI: 10.1093/trstmh/traa170] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/29/2020] [Revised: 11/07/2020] [Accepted: 01/09/2021] [Indexed: 11/13/2022] Open
Abstract
Background Progress towards elimination of trachoma as a public health problem has been substantial, but the coronavirus disease 2019 (COVID-19) pandemic has disrupted community-based control efforts. Methods We use a susceptible-infected model to estimate the impact of delayed distribution of azithromycin treatment on the prevalence of active trachoma. Results We identify three distinct scenarios for geographic districts depending on whether the basic reproduction number and the treatment-associated reproduction number are above or below a value of 1. We find that when the basic reproduction number is <1, no significant delays in disease control will be caused. However, when the basic reproduction number is >1, significant delays can occur. In most districts, 1 y of COVID-related delay can be mitigated by a single extra round of mass drug administration. However, supercritical districts require a new paradigm of infection control because the current strategies will not eliminate disease. Conclusions If the pandemic can motivate judicious, community-specific implementation of control strategies, global elimination of trachoma as a public health problem could be accelerated.
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Affiliation(s)
- Seth Blumberg
- Francis I Proctor Foundation, University of California, San Francisco, San Francisco, CA, USA
| | | | - Joaquin M Prada
- Faculty of Health and Medical Sciences, University of Surrey, Guildford, UK
| | - Anthony W Solomon
- Department of Control of Neglected Tropical Diseases, World Health Organization, Geneva, Switzerland
| | - Paul Emerson
- International Trachoma Initiative, Task Force for Global Health, Decatur, GA, USA
| | - Pamela J Hooper
- International Trachoma Initiative, Task Force for Global Health, Decatur, GA, USA
| | - Michael S Deiner
- Francis I Proctor Foundation, University of California, San Francisco, San Francisco, CA, USA
| | - Benjamin Amoah
- Lancaster Medical School, Lancaster University, Bailrigg, Lancaster, UK
| | | | - Travis C Porco
- Francis I Proctor Foundation, University of California, San Francisco, San Francisco, CA, USA.,Department of Epidemiology and Biostatistics, University of California, San Francisco, San Francisco, CA, USA
| | - Thomas M Lietman
- Francis I Proctor Foundation, University of California, San Francisco, San Francisco, CA, USA.,Department of Epidemiology and Biostatistics, University of California, San Francisco, San Francisco, CA, USA.,Institute for Global Health Sciences, University of California, San Francisco, San Francisco, CA, USA.,Department of Ophthalmology, University of California, San Francisco, San Francisco, CA, USA
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12
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Borlase A, Blumberg S, Callahan EK, Deiner MS, Nash SD, Porco TC, Solomon AW, Lietman TM, Prada JM, Hollingsworth TD. Modelling trachoma post-2020: opportunities for mitigating the impact of COVID-19 and accelerating progress towards elimination. Trans R Soc Trop Med Hyg 2021; 115:213-221. [PMID: 33596317 PMCID: PMC7928577 DOI: 10.1093/trstmh/traa171] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/08/2020] [Revised: 11/10/2020] [Accepted: 02/12/2021] [Indexed: 02/06/2023] Open
Abstract
BACKGROUND The COVID-19 pandemic has disrupted planned annual antibiotic mass drug administration (MDA) activities that have formed the cornerstone of the largely successful global efforts to eliminate trachoma as a public health problem. METHODS Using a mathematical model we investigate the impact of interruption to MDA in trachoma-endemic settings. We evaluate potential measures to mitigate this impact and consider alternative strategies for accelerating progress in those areas where the trachoma elimination targets may not be achievable otherwise. RESULTS We demonstrate that for districts that were hyperendemic at baseline, or where the trachoma elimination thresholds have not already been achieved after three rounds of MDA, the interruption to planned MDA could lead to a delay to reaching elimination targets greater than the duration of interruption. We also show that an additional round of MDA in the year following MDA resumption could effectively mitigate this delay. For districts where the probability of elimination under annual MDA was already very low, we demonstrate that more intensive MDA schedules are needed to achieve agreed targets. CONCLUSION Through appropriate use of additional MDA, the impact of COVID-19 in terms of delay to reaching trachoma elimination targets can be effectively mitigated. Additionally, more frequent MDA may accelerate progress towards 2030 goals.
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Affiliation(s)
- Anna Borlase
- Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, University of Oxford, Oxford, UK
| | | | - E Kelly Callahan
- Trachoma Control Program, The Carter Center, Atlanta, Georgia, USA
| | | | - Scott D Nash
- Trachoma Control Program, The Carter Center, Atlanta, Georgia, USA
| | | | - Anthony W Solomon
- Department of Control of Neglected Tropical Diseases, World Health Organisation, Geneva, Switzerland
| | | | - Joaquin M Prada
- Faculty of Health and Medical Sciences, University of Surrey, UK
| | - T Dèirdre Hollingsworth
- Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, University of Oxford, Oxford, UK
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13
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Blumberg S, Borlase A, Prada JM, Solomon AW, Emerson P, Hooper PJ, Deiner MS, Amoah B, Hollingsworth D, Porco TC, Lietman TM. Implications of the COVID-19 pandemic on eliminating trachoma as a public health problem. medRxiv 2020. [PMID: 33140063 PMCID: PMC7605574 DOI: 10.1101/2020.10.26.20219691] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 12/26/2022]
Abstract
Background: Progress towards elimination of trachoma as a public health problem has been substantial, but the COVID-19 pandemic has disrupted community-based control efforts. Methods: We use a susceptible-infected model to estimate the impact of delayed distribution of azithromycin treatment on the prevalence of active trachoma. Results: We identify three distinct scenarios for geographic districts depending on whether the basic reproduction number and the treatment-associated reproduction number are above or below a value of one. We find that when the basic reproduction number is below one, no significant delays in disease control will be caused. However, when the basic reproduction number is above one, significant delays can occur. In most districts a year of COVID-related delay can be mitigated by a single extra round of mass drug administration. However, supercritical districts require a new paradigm of infection control because the current strategies will not eliminate disease. Conclusion: If the pandemic can motivate judicious, community-specific implementation of control strategies, global elimination of trachoma as a public health problem could be accelerated.
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Affiliation(s)
| | | | - Joaquin M Prada
- Faculty of Health and Medical Sciences, University of Surrey, UK
| | - Anthony W Solomon
- Department of Control of Neglected Tropical Diseases, World Health Organization, Geneva, Switzerland
| | - Paul Emerson
- International Trachoma Initiative, The Task Force for Global Health, USA
| | - Pamela J Hooper
- International Trachoma Initiative, The Task Force for Global Health, USA
| | | | - Benjamin Amoah
- Lancaster Medical School, Lancaster University, Bailrigg, Lancaster, UK
| | | | - Travis C Porco
- Francis I Proctor Foundation, UCSF, USA.,Department of Epidemiology and Biostatistics, UCSF, USA
| | - Thomas M Lietman
- Francis I Proctor Foundation, UCSF, USA.,Department of Epidemiology and Biostatistics, UCSF, USA.,Institute for Global Health Sciences, UCSF, USA.,Department of Ophthalmology, UCSF, USA
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14
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Toor J, Adams ER, Aliee M, Amoah B, Anderson RM, Ayabina D, Bailey R, Basáñez MG, Blok DJ, Blumberg S, Borlase A, Rivera RC, Castaño MS, Chitnis N, Coffeng LE, Crump RE, Das A, Davis CN, Davis EL, Deiner MS, Diggle PJ, Fronterre C, Giardina F, Giorgi E, Graham M, Hamley JID, Huang CI, Kura K, Lietman TM, Lucas TCD, Malizia V, Medley GF, Meeyai A, Michael E, Porco TC, Prada JM, Rock KS, Le Rutte EA, Smith ME, Spencer SEF, Stolk WA, Touloupou P, Vasconcelos A, Vegvari C, de Vlas SJ, Walker M, Hollingsworth TD. Predicted Impact of COVID-19 on Neglected Tropical Disease Programs and the Opportunity for Innovation. Clin Infect Dis 2020; 72:1463-1466. [PMID: 32984870 PMCID: PMC7543306 DOI: 10.1093/cid/ciaa933] [Citation(s) in RCA: 49] [Impact Index Per Article: 12.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/14/2020] [Accepted: 07/10/2020] [Indexed: 11/12/2022] Open
Abstract
Due to the COVID-19 pandemic, many key neglected tropical disease (NTD) activities have been postponed. This hindrance comes at a time when the NTDs are progressing towards their ambitious goals for 2030. Mathematical modelling on several NTDs, namely gambiense sleeping sickness, lymphatic filariasis, onchocerciasis, schistosomiasis, soil-transmitted helminthiases (STH), trachoma, and visceral leishmaniasis, shows that the impact of this disruption will vary across the diseases. Programs face a risk of resurgence, which will be fastest in high-transmission areas. Furthermore, of the mass drug administration diseases, schistosomiasis, STH, and trachoma are likely to encounter faster resurgence. The case-finding diseases (gambiense sleeping sickness and visceral leishmaniasis) are likely to have fewer cases being detected but may face an increasing underlying rate of new infections. However, once programs are able to resume, there are ways to mitigate the impact and accelerate progress towards the 2030 goals.
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Affiliation(s)
- Jaspreet Toor
- Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, Oxford, United Kingdom
| | - Emily R Adams
- Department of Tropical Disease Biology, Liverpool School of Tropical Medicine, Liverpool, United Kingdom
| | - Maryam Aliee
- Mathematics Institute, University of Warwick, Coventry, United Kingdom,Zeeman Institute for Systems Biology and Infectious Disease Epidemiology Research, University of Warwick, Coventry, United Kingdom
| | - Benjamin Amoah
- Centre for Health Informatics, Computing and Statistics, Lancaster University, Lancaster, United Kingdom
| | - Roy M Anderson
- London Centre for Neglected Tropical Disease Research, Department of Infectious Disease Epidemiology, Imperial College London, London, United Kingdom,Medical Research Council Centre for Global Infectious Disease Analysis, Department of Infectious Disease Epidemiology, School of Public Health, Imperial College London, London, United Kingdom,The DeWorm3 Project, Natural History Museum, London, United Kingdom
| | - Diepreye Ayabina
- Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, Oxford, United Kingdom
| | - Robin Bailey
- Faculty of Infectious and Tropical Diseases, London School of Hygiene and Tropical Medicine, London, United Kingdom
| | - Maria-Gloria Basáñez
- London Centre for Neglected Tropical Disease Research, Department of Infectious Disease Epidemiology, Imperial College London, London, United Kingdom,Medical Research Council Centre for Global Infectious Disease Analysis, Department of Infectious Disease Epidemiology, School of Public Health, Imperial College London, London, United Kingdom
| | - David J Blok
- Department of Public Health, Erasmus University Medical Center Rotterdam, Rotterdam, The Netherlands
| | - Seth Blumberg
- Francis I Proctor Foundation, University of California, San Francisco, California, United States of America
| | - Anna Borlase
- Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, Oxford, United Kingdom
| | - Rocio Caja Rivera
- Department of Biological Sciences, University of Notre Dame, Notre Dame, Indiana, United States of America
| | - María Soledad Castaño
- Department of Epidemiology and Public Health, Swiss Tropical and Public Health Institute, Basel, Switzerland,University of Basel, Basel, Switzerland
| | - Nakul Chitnis
- Department of Epidemiology and Public Health, Swiss Tropical and Public Health Institute, Basel, Switzerland,University of Basel, Basel, Switzerland
| | - Luc E Coffeng
- Department of Public Health, Erasmus University Medical Center Rotterdam, Rotterdam, The Netherlands
| | - Ronald E Crump
- Mathematics Institute, University of Warwick, Coventry, United Kingdom,Zeeman Institute for Systems Biology and Infectious Disease Epidemiology Research, University of Warwick, Coventry, United Kingdom,The School of Life Sciences, University of Warwick, Coventry, United Kingdom
| | - Aatreyee Das
- Department of Epidemiology and Public Health, Swiss Tropical and Public Health Institute, Basel, Switzerland,University of Basel, Basel, Switzerland
| | - Christopher N Davis
- Mathematics Institute, University of Warwick, Coventry, United Kingdom,Zeeman Institute for Systems Biology and Infectious Disease Epidemiology Research, University of Warwick, Coventry, United Kingdom
| | - Emma L Davis
- Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, Oxford, United Kingdom
| | - Michael S Deiner
- Francis I Proctor Foundation, University of California, San Francisco, California, United States of America,Department of Ophthalmology, University of California, San Francisco, California, United States of America
| | - Peter J Diggle
- Centre for Health Informatics, Computing and Statistics, Lancaster University, Lancaster, United Kingdom
| | - Claudio Fronterre
- Centre for Health Informatics, Computing and Statistics, Lancaster University, Lancaster, United Kingdom
| | - Federica Giardina
- Department of Public Health, Erasmus University Medical Center Rotterdam, Rotterdam, The Netherlands
| | - Emanuele Giorgi
- Centre for Health Informatics, Computing and Statistics, Lancaster University, Lancaster, United Kingdom
| | - Matthew Graham
- Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, Oxford, United Kingdom,Centre for Mathematical Modelling of Infectious Disease, London School of Hygiene and Tropical Medicine, London, United Kingdom
| | - Jonathan I D Hamley
- London Centre for Neglected Tropical Disease Research, Department of Infectious Disease Epidemiology, Imperial College London, London, United Kingdom,Medical Research Council Centre for Global Infectious Disease Analysis, Department of Infectious Disease Epidemiology, School of Public Health, Imperial College London, London, United Kingdom
| | - Ching-I Huang
- Mathematics Institute, University of Warwick, Coventry, United Kingdom,Zeeman Institute for Systems Biology and Infectious Disease Epidemiology Research, University of Warwick, Coventry, United Kingdom
| | - Klodeta Kura
- London Centre for Neglected Tropical Disease Research, Department of Infectious Disease Epidemiology, Imperial College London, London, United Kingdom,Medical Research Council Centre for Global Infectious Disease Analysis, Department of Infectious Disease Epidemiology, School of Public Health, Imperial College London, London, United Kingdom
| | - Thomas M Lietman
- Francis I Proctor Foundation, University of California, San Francisco, California, United States of America,Department of Ophthalmology, University of California, San Francisco, California, United States of America,Department of Epidemiology & Biostatistics, University of California, San Francisco, California, United States of America
| | - Tim C D Lucas
- Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, Oxford, United Kingdom
| | - Veronica Malizia
- Department of Public Health, Erasmus University Medical Center Rotterdam, Rotterdam, The Netherlands
| | - Graham F Medley
- Centre for Mathematical Modelling of Infectious Disease, London School of Hygiene and Tropical Medicine, London, United Kingdom
| | - Aronrag Meeyai
- Centre for Mathematical Modelling of Infectious Disease, London School of Hygiene and Tropical Medicine, London, United Kingdom
| | - Edwin Michael
- Department of Biological Sciences, University of Notre Dame, Notre Dame, Indiana, United States of America
| | - Travis C Porco
- Francis I Proctor Foundation, University of California, San Francisco, California, United States of America,Department of Ophthalmology, University of California, San Francisco, California, United States of America,Department of Epidemiology & Biostatistics, University of California, San Francisco, California, United States of America
| | - Joaquin M Prada
- School of Veterinary Medicine, Faculty of Health and Medical Sciences, University of Surrey, Guildford, United Kingdom
| | - Kat S Rock
- Mathematics Institute, University of Warwick, Coventry, United Kingdom,Zeeman Institute for Systems Biology and Infectious Disease Epidemiology Research, University of Warwick, Coventry, United Kingdom
| | - Epke A Le Rutte
- Department of Public Health, Erasmus University Medical Center Rotterdam, Rotterdam, The Netherlands,Department of Epidemiology and Public Health, Swiss Tropical and Public Health Institute, Basel, Switzerland,University of Basel, Basel, Switzerland
| | - Morgan E Smith
- Department of Biological Sciences, University of Notre Dame, Notre Dame, Indiana, United States of America
| | - Simon E F Spencer
- Zeeman Institute for Systems Biology and Infectious Disease Epidemiology Research, University of Warwick, Coventry, United Kingdom,Department of Statistics, University of Warwick, Coventry, United Kingdom
| | - Wilma A Stolk
- Department of Public Health, Erasmus University Medical Center Rotterdam, Rotterdam, The Netherlands
| | | | - Andreia Vasconcelos
- Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, Oxford, United Kingdom
| | - Carolin Vegvari
- London Centre for Neglected Tropical Disease Research, Department of Infectious Disease Epidemiology, Imperial College London, London, United Kingdom,Medical Research Council Centre for Global Infectious Disease Analysis, Department of Infectious Disease Epidemiology, School of Public Health, Imperial College London, London, United Kingdom
| | - Sake J de Vlas
- Department of Public Health, Erasmus University Medical Center Rotterdam, Rotterdam, The Netherlands
| | - Martin Walker
- London Centre for Neglected Tropical Disease Research, Department of Infectious Disease Epidemiology, Imperial College London, London, United Kingdom,London Centre for Neglected Tropical Disease Research, Department of Pathobiology and Population Sciences, Royal Veterinary College, University of London, Hatfield, Hertfordshire, United Kingdom
| | - T Déirdre Hollingsworth
- Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, Oxford, United Kingdom,Correspondence: T. D. Hollingsworth, Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, Old Road Campus, Oxford OX3 7LF, UK ()
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15
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Léger E, Borlase A, Fall CB, Diouf ND, Diop SD, Yasenev L, Catalano S, Thiam CT, Ndiaye A, Emery A, Morrell A, Rabone M, Ndao M, Faye B, Rollinson D, Rudge JW, Sène M, Webster JP. Prevalence and distribution of schistosomiasis in human, livestock, and snail populations in northern Senegal: a One Health epidemiological study of a multi-host system. Lancet Planet Health 2020; 4:e330-e342. [PMID: 32800151 PMCID: PMC7443702 DOI: 10.1016/s2542-5196(20)30129-7] [Citation(s) in RCA: 52] [Impact Index Per Article: 13.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/19/2019] [Revised: 05/18/2020] [Accepted: 05/19/2020] [Indexed: 05/30/2023]
Abstract
BACKGROUND Schistosomiasis is a neglected tropical disease of global medical and veterinary importance. As efforts to eliminate schistosomiasis as a public health problem and interrupt transmission gather momentum, the potential zoonotic risk posed by livestock Schistosoma species via viable hybridisation in sub-Saharan Africa have been largely overlooked. We aimed to investigate the prevalence, distribution, and multi-host, multiparasite transmission cycle of Haematobium group schistosomiasis in Senegal, West Africa. METHODS In this epidemiological study, we carried out systematic surveys in definitive hosts (humans, cattle, sheep, and goats) and snail intermediate hosts, in 2016-18, in two areas of Northern Senegal: Richard Toll and Lac de Guiers, where transmission is perennial; and Barkedji and Linguère, where transmission is seasonal. The occurrence and distribution of Schistosoma species and hybrids were assessed by molecular analyses of parasitological specimens obtained from the different hosts. Children in the study villages aged 5-17 years and enrolled in school were selected from school registers. Adults (aged 18-78 years) were self-selecting volunteers. Livestock from the study villages in both areas were also randomly sampled, as were post-mortem samples from local abattoirs. Additionally, five malacological surveys of snail intermediate hosts were carried out at each site in open water sources used by the communities and their animals. FINDINGS In May to August, 2016, we surveyed 375 children and 20 adults from Richard Toll and Lac de Guiers, and 201 children and 107 adults from Barkedji and Linguère; in October, 2017, to January, 2018, we surveyed 386 children and 88 adults from Richard Toll and Lac de Guiers, and 323 children and 85 adults from Barkedji and Linguère. In Richard Toll and Lac de Guiers the prevalence of urogenital schistosomiasis in children was estimated to be 87% (95% CI 80-95) in 2016 and 88% (82-95) in 2017-18. An estimated 63% (in 2016) and 72% (in 2017-18) of infected children were shedding Schistosoma haematobium-Schistosoma bovis hybrids. In adults in Richard Toll and Lac de Guiers, the prevalence of urogenital schistosomiasis was estimated to be 79% (52-97) in 2016 and 41% (30-54) in 2017-18, with 88% of infected samples containing S haematobium-S bovis hybrids. In Barkedji and Linguère the prevalence of urogenital schistosomiasis in children was estimated to be 30% (23-38) in 2016 and 42% (35-49) in 2017-18, with the proportion of infected children found to be shedding S haematobium-S bovis hybrid miracidia much lower than in Richard Toll and Lac de Guiers (11% in 2016 and 9% in 2017-18). In adults in Barkedji and Linguère, the prevalence of urogenital schistosomiasis was estimated to be 26% (17-36) in 2016 and 47% (34-60) in 2017-18, with 10% of infected samples containing S haematobium-S bovis hybrids. The prevalence of S bovis in the sympatric cattle population of Richard Toll and the Lac de Guiers was 92% (80-99), with S bovis also found in sheep (estimated prevalence 14% [5-31]) and goats (15% [5-33]). In Barkedji and Linguère the main schistosome species in livestock was Schistosoma curassoni, with an estimated prevalence of 73% (48-93) in sheep, 84% (61-98) in goats and 8% (2-24) in cattle. S haematobium-S bovis hybrids were not found in livestock. In Richard Toll and Lac de Guiers 35% of infected Bulinus spp snail intermediate hosts were found to be shedding S haematobium-S bovis hybrids (68% shedding S haematobium; 17% shedding S bovis); however, no snails were found to be shedding S haematobium hybrids in Barkedji and Linguère (29% shedding S haematobium; 71% shedding S curassoni). INTERPRETATION Our findings suggest that hybrids originate in humans via zoonotic spillover from livestock populations, where schistosomiasis is co-endemic. Introgressive hybridisation, evolving host ranges, and wider ecosystem contexts could affect the transmission dynamics of schistosomiasis and other pathogens, demonstrating the need to consider control measures within a One Health framework. FUNDING Zoonoses and Emerging Livestock Systems programme (UK Biotechnology and Biological Sciences Research Council, UK Department for International Development, UK Economic and Social Research Council, UK Medical Research Council, UK Natural Environment Research Council, and UK Defence Science and Technology Laboratory).
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Affiliation(s)
- Elsa Léger
- Centre for Emerging, Endemic and Exotic Diseases, Department of Pathobiology and Population Sciences, Royal Veterinary College, University of London, Hertfordshire, UK; London Centre for Neglected Tropical Disease Research, School of Public Health, Imperial College London, London, UK.
| | - Anna Borlase
- Centre for Emerging, Endemic and Exotic Diseases, Department of Pathobiology and Population Sciences, Royal Veterinary College, University of London, Hertfordshire, UK; London Centre for Neglected Tropical Disease Research, School of Public Health, Imperial College London, London, UK; NTD Modelling Consortium, Big Data Institute, University of Oxford, Oxford, UK
| | - Cheikh B Fall
- Faculté de Médecine, Pharmacie et Odontologie, Université Cheikh Anta Diop, Dakar, Senegal
| | - Nicolas D Diouf
- Institut Supérieur de Formation Agricole et Rurale, Université de Thiès, Bambey, Senegal; Unité de Formation et de Recherche des Sciences Agronomiques, d'Aquaculture et de Technologies Alimentaires, Université Gaston Berger, Saint-Louis, Senegal
| | - Samba D Diop
- Institut Supérieur de Formation Agricole et Rurale, Université de Thiès, Bambey, Senegal
| | - Lucy Yasenev
- Centre for Emerging, Endemic and Exotic Diseases, Department of Pathobiology and Population Sciences, Royal Veterinary College, University of London, Hertfordshire, UK
| | - Stefano Catalano
- Centre for Emerging, Endemic and Exotic Diseases, Department of Pathobiology and Population Sciences, Royal Veterinary College, University of London, Hertfordshire, UK; London Centre for Neglected Tropical Disease Research, School of Public Health, Imperial College London, London, UK
| | - Cheikh T Thiam
- Unité de Formation et de Recherche des Sciences Agronomiques, d'Aquaculture et de Technologies Alimentaires, Université Gaston Berger, Saint-Louis, Senegal
| | - Alassane Ndiaye
- Unité de Formation et de Recherche des Sciences Agronomiques, d'Aquaculture et de Technologies Alimentaires, Université Gaston Berger, Saint-Louis, Senegal
| | - Aidan Emery
- London Centre for Neglected Tropical Disease Research, School of Public Health, Imperial College London, London, UK; Parasites and Vectors Division, Life Sciences Department, Natural History Museum, London, UK
| | - Alice Morrell
- Centre for Emerging, Endemic and Exotic Diseases, Department of Pathobiology and Population Sciences, Royal Veterinary College, University of London, Hertfordshire, UK
| | - Muriel Rabone
- London Centre for Neglected Tropical Disease Research, School of Public Health, Imperial College London, London, UK; Parasites and Vectors Division, Life Sciences Department, Natural History Museum, London, UK
| | - Momar Ndao
- National Reference Centre for Parasitology, Research Institute of the McGill University Health Centre, Montreal, QC, Canada
| | - Babacar Faye
- Faculté de Médecine, Pharmacie et Odontologie, Université Cheikh Anta Diop, Dakar, Senegal
| | - David Rollinson
- London Centre for Neglected Tropical Disease Research, School of Public Health, Imperial College London, London, UK; Parasites and Vectors Division, Life Sciences Department, Natural History Museum, London, UK
| | - James W Rudge
- London Centre for Neglected Tropical Disease Research, School of Public Health, Imperial College London, London, UK; Communicable Diseases Policy Research Group, London School of Hygiene & Tropical Medicine, London, UK; Faculty of Public Health, Mahidol University, Bangkok, Thailand
| | - Mariama Sène
- Unité de Formation et de Recherche des Sciences Agronomiques, d'Aquaculture et de Technologies Alimentaires, Université Gaston Berger, Saint-Louis, Senegal
| | - Joanne P Webster
- Centre for Emerging, Endemic and Exotic Diseases, Department of Pathobiology and Population Sciences, Royal Veterinary College, University of London, Hertfordshire, UK; London Centre for Neglected Tropical Disease Research, School of Public Health, Imperial College London, London, UK
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16
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Catalano S, Symeou A, Marsh KJ, Borlase A, Léger E, Fall CB, Sène M, Diouf ND, Ianniello D, Cringoli G, Rinaldi L, Bâ K, Webster JP. Mini-FLOTAC as an alternative, non-invasive diagnostic tool for Schistosoma mansoni and other trematode infections in wildlife reservoirs. Parasit Vectors 2019; 12:439. [PMID: 31522684 PMCID: PMC6745783 DOI: 10.1186/s13071-019-3613-6] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/18/2019] [Accepted: 07/08/2019] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND Schistosomiasis and food-borne trematodiases are not only of major public health concern, but can also have profound implications for livestock production and wildlife conservation. The zoonotic, multi-host nature of many digenean trematodes is a significant challenge for disease control programmes in endemic areas. However, our understanding of the epidemiological role that animal reservoirs, particularly wild hosts, may play in the transmission of zoonotic trematodiases suffers a dearth of information, with few, if any, standardised, reliable diagnostic tests available. We combined qualitative and quantitative data derived from post-mortem examinations, coprological analyses using the Mini-FLOTAC technique, and molecular tools to assess parasite community composition and the validity of non-invasive methods to detect trematode infections in 89 wild Hubert's multimammate mice (Mastomys huberti) from northern Senegal. RESULTS Parasites isolated at post-mortem examination were identified as Plagiorchis sp., Anchitrema sp., Echinostoma caproni, Schistosoma mansoni, and a hybrid between Schistosoma haematobium and Schistosoma bovis. The reports of E. caproni and Anchitrema sp. represent the first molecularly confirmed identifications for these trematodes in definitive hosts of sub-Saharan Africa. Comparison of prevalence estimates derived from parasitological analysis at post-mortem examination and Mini-FLOTAC analysis showed non-significant differences indicating comparable results between the two techniques (P = 1.00 for S. mansoni; P = 0.85 for E. caproni; P = 0.83 for Plagiorchis sp.). A Bayesian model, applied to estimate the sensitivities of the two tests for the diagnosis of Schistosoma infections, indicated similar median posterior probabilities of 83.1% for Mini-FLOTAC technique and 82.9% for post-mortem examination (95% Bayesian credible intervals of 64.0-94.6% and 63.7-94.7%, respectively). CONCLUSIONS Our results showed that the Mini-FLOTAC could be applied as an alternative diagnostic technique for the detection of the zoonotic S. mansoni and other trematodes in rodent reservoirs. The implementation of non-invasive diagnostics in wildlife would offer numerous advantages over lethal sampling methodologies, with potential impact on control strategies of zoonotic helminthiases in endemic areas of sub-Saharan Africa and on fostering a framework of animal use reduction in scientific practice.
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Affiliation(s)
- Stefano Catalano
- Centre for Emerging, Endemic and Exotic Diseases, Department of Pathobiology and Population Sciences, The Royal Veterinary College, University of London, Hatfield, AL97TA UK
- London Centre for Neglected Tropical Disease Research, School of Public Health, Faculty of Medicine, Imperial College London, London, W21PG UK
| | - Amelia Symeou
- Centre for Emerging, Endemic and Exotic Diseases, Department of Pathobiology and Population Sciences, The Royal Veterinary College, University of London, Hatfield, AL97TA UK
| | - Kirsty J. Marsh
- Centre for Emerging, Endemic and Exotic Diseases, Department of Pathobiology and Population Sciences, The Royal Veterinary College, University of London, Hatfield, AL97TA UK
| | - Anna Borlase
- Centre for Emerging, Endemic and Exotic Diseases, Department of Pathobiology and Population Sciences, The Royal Veterinary College, University of London, Hatfield, AL97TA UK
- London Centre for Neglected Tropical Disease Research, School of Public Health, Faculty of Medicine, Imperial College London, London, W21PG UK
| | - Elsa Léger
- Centre for Emerging, Endemic and Exotic Diseases, Department of Pathobiology and Population Sciences, The Royal Veterinary College, University of London, Hatfield, AL97TA UK
- London Centre for Neglected Tropical Disease Research, School of Public Health, Faculty of Medicine, Imperial College London, London, W21PG UK
| | - Cheikh B. Fall
- Faculté de Médecine, de Pharmacie et d’Odonto-Stomatologie, Université Cheikh Anta Diop, BP 5005, Dakar, Senegal
| | - Mariama Sène
- Unité de Formation et de Recherche des Sciences Agronomiques, de l’Aquaculture et des Technologies Alimentaires, Université Gaston Berger, BP 234, Saint-Louis, Senegal
| | - Nicolas D. Diouf
- Unité de Formation et de Recherche des Sciences Agronomiques, de l’Aquaculture et des Technologies Alimentaires, Université Gaston Berger, BP 234, Saint-Louis, Senegal
| | - Davide Ianniello
- Department of Veterinary Medicine and Animal Production, University of Naples Federico II, 80137 Naples, Italy
| | - Giuseppe Cringoli
- Department of Veterinary Medicine and Animal Production, University of Naples Federico II, 80137 Naples, Italy
| | - Laura Rinaldi
- Department of Veterinary Medicine and Animal Production, University of Naples Federico II, 80137 Naples, Italy
| | - Khalilou Bâ
- Centre de Biologie et de Gestion des Populations, Institut de Recherche pour le Développement, BP 1386, Dakar, Senegal
| | - Joanne P. Webster
- Centre for Emerging, Endemic and Exotic Diseases, Department of Pathobiology and Population Sciences, The Royal Veterinary College, University of London, Hatfield, AL97TA UK
- London Centre for Neglected Tropical Disease Research, School of Public Health, Faculty of Medicine, Imperial College London, London, W21PG UK
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17
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Catalano S, Sène M, Diouf ND, Fall CB, Borlase A, Léger E, Bâ K, Webster JP. Rodents as Natural Hosts of Zoonotic Schistosoma Species and Hybrids: An Epidemiological and Evolutionary Perspective From West Africa. J Infect Dis 2019; 218:429-433. [PMID: 29365139 DOI: 10.1093/infdis/jiy029] [Citation(s) in RCA: 58] [Impact Index Per Article: 11.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/05/2017] [Accepted: 01/17/2018] [Indexed: 11/13/2022] Open
Abstract
The complex multi-host disease dynamics of schistosomiasis and Schistosoma spp., including the emergence of zoonotic parasite hybrids, remain largely unexplored in West Africa. We elucidated the role of wild small mammals as reservoir for zoonotic Schistosoma species and hybrids in endemic areas of Senegal. We identified Schistosoma mansoni, Schistosoma bovis, and a Schistosoma haematobium/S. bovis hybrid, with local prevalence in wild rodents ranging from 1.9% to 28.6%. Our findings indicate that rodents may be an important local reservoir for zoonotic schistosomiasis in endemic areas of West Africa, amplifying transmission to humans and acting as natural definitive hosts of schistosome hybrids.
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Affiliation(s)
- Stefano Catalano
- Centre for Emerging, Endemic and Exotic Diseases, Department of Pathobiology and Population Sciences, The Royal Veterinary College, University of London, Hatfield, United Kingdom
| | - Mariama Sène
- Unité de Formation et de Recherche des Sciences Agronomiques, d'Aquaculture et de Technologies Alimentaires, Université Gaston Berger, Saint-Louis, Senegal
| | - Nicolas D Diouf
- Unité de Formation et de Recherche des Sciences Agronomiques, d'Aquaculture et de Technologies Alimentaires, Université Gaston Berger, Saint-Louis, Senegal.,Institut Supérieur de Formation Agricole et Rurale, Université de Thiès, Bambey, Senegal
| | - Cheikh B Fall
- Faculté de Médecine, de Pharmacie et d'Odontologie, Université Cheikh Anta Diop, Dakar, Senegal
| | - Anna Borlase
- Centre for Emerging, Endemic and Exotic Diseases, Department of Pathobiology and Population Sciences, The Royal Veterinary College, University of London, Hatfield, United Kingdom
| | - Elsa Léger
- Centre for Emerging, Endemic and Exotic Diseases, Department of Pathobiology and Population Sciences, The Royal Veterinary College, University of London, Hatfield, United Kingdom
| | - Khalilou Bâ
- Centre de Biologie et de Gestion des Populations, Institut de Recherche pour le Développement, Campus ISRA-IRD Bel Air, Dakar, Senegal
| | - Joanne P Webster
- Centre for Emerging, Endemic and Exotic Diseases, Department of Pathobiology and Population Sciences, The Royal Veterinary College, University of London, Hatfield, United Kingdom
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18
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Borlase A, Webster JP, Rudge JW. Opportunities and challenges for modelling epidemiological and evolutionary dynamics in a multihost, multiparasite system: Zoonotic hybrid schistosomiasis in West Africa. Evol Appl 2018; 11:501-515. [PMID: 29636802 PMCID: PMC5891036 DOI: 10.1111/eva.12529] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/08/2017] [Accepted: 08/01/2017] [Indexed: 01/01/2023] Open
Abstract
Multihost multiparasite systems are evolutionarily and ecologically dynamic, which presents substantial trans-disciplinary challenges for elucidating their epidemiology and designing appropriate control. Evidence for hybridizations and introgressions between parasite species is gathering, in part in line with improvements in molecular diagnostics and genome sequencing. One major system where this is becoming apparent is within the Genus Schistosoma, where schistosomiasis represents a disease of considerable medical and veterinary importance, the greatest burden of which occurs in sub-Saharan Africa. Interspecific hybridizations and introgressions bring an increased level of complexity over and above that already inherent within multihost, multiparasite systems, also representing an additional source of genetic variation that can drive evolution. This has the potential for profound implications for the control of parasitic diseases, including, but not exclusive to, widening host range, increased transmission potential and altered responses to drug therapy. Here, we present the challenging case example of haematobium group Schistosoma spp. hybrids in West Africa, a system involving multiple interacting parasites and multiple definitive hosts, in a region where zoonotic reservoirs of schistosomiasis were not previously considered to be of importance. We consider how existing mathematical model frameworks for schistosome transmission could be expanded and adapted to zoonotic hybrid systems, exploring how such model frameworks can utilize molecular and epidemiological data, as well as the complexities and challenges this presents. We also highlight the opportunities and value such mathematical models could bring to this and a range of similar multihost, multi and cross-hybridizing parasites systems in our changing world.
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Affiliation(s)
- Anna Borlase
- Department of Pathobiology and Population SciencesCentre for Emerging, Endemic and Exotic DiseasesRoyal Veterinary CollegeUniversity of LondonLondonUK
- Department of Infectious Disease EpidemiologyLondon Centre for Neglected Tropical Disease ResearchSchool of Public HealthImperial College LondonLondonUK
| | - Joanne P. Webster
- Department of Pathobiology and Population SciencesCentre for Emerging, Endemic and Exotic DiseasesRoyal Veterinary CollegeUniversity of LondonLondonUK
- Department of Infectious Disease EpidemiologyLondon Centre for Neglected Tropical Disease ResearchSchool of Public HealthImperial College LondonLondonUK
| | - James W. Rudge
- Department of Infectious Disease EpidemiologyLondon Centre for Neglected Tropical Disease ResearchSchool of Public HealthImperial College LondonLondonUK
- Communicable Diseases Policy Research GroupLondon School of Hygiene and Tropical MedicineLondonUK
- Faculty of Public HealthMahidol UniversityBangkokThailand
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19
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Webster JP, Borlase A, Rudge JW. Who acquires infection from whom and how? Disentangling multi-host and multi-mode transmission dynamics in the 'elimination' era. Philos Trans R Soc Lond B Biol Sci 2017; 372:20160091. [PMID: 28289259 PMCID: PMC5352818 DOI: 10.1098/rstb.2016.0091] [Citation(s) in RCA: 58] [Impact Index Per Article: 8.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 08/25/2016] [Indexed: 12/21/2022] Open
Abstract
Multi-host infectious agents challenge our abilities to understand, predict and manage disease dynamics. Within this, many infectious agents are also able to use, simultaneously or sequentially, multiple modes of transmission. Furthermore, the relative importance of different host species and modes can itself be dynamic, with potential for switches and shifts in host range and/or transmission mode in response to changing selective pressures, such as those imposed by disease control interventions. The epidemiology of such multi-host, multi-mode infectious agents thereby can involve a multi-faceted community of definitive and intermediate/secondary hosts or vectors, often together with infectious stages in the environment, all of which may represent potential targets, as well as specific challenges, particularly where disease elimination is proposed. Here, we explore, focusing on examples from both human and animal pathogen systems, why and how we should aim to disentangle and quantify the relative importance of multi-host multi-mode infectious agent transmission dynamics under contrasting conditions, and ultimately, how this can be used to help achieve efficient and effective disease control.This article is part of the themed issue 'Opening the black box: re-examining the ecology and evolution of parasite transmission'.
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Affiliation(s)
- Joanne P Webster
- Department of Pathology and Pathogen Biology, Centre for Emerging, Endemic and Exotic Diseases, Royal Veterinary College, University of London, Hatfield AL9 7TA, UK
| | - Anna Borlase
- Department of Pathology and Pathogen Biology, Centre for Emerging, Endemic and Exotic Diseases, Royal Veterinary College, University of London, Hatfield AL9 7TA, UK
| | - James W Rudge
- Communicable Diseases Policy Research Group, London School of Hygiene and Tropical Medicine, Keppel Street, London WC1E 7HT, UK
- Faculty of Public Health, Mahidol University, 420/1 Rajavithi Road, Bangkok 10400, Thailand
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