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Prada JM, Touloupou P, Kebede B, Giorgi E, Sime H, Smith M, Kontoroupis P, Brown P, Cano J, Farkas H, Irvine M, Reimer L, Caja Rivera R, de Vlas SJ, Michael E, Stolk WA, Pulan R, Spencer SEF, Hollingsworth TD, Seife F. Subnational Projections of Lymphatic Filariasis Elimination Targets in Ethiopia to Support National Level Policy. Clin Infect Dis 2024; 78:S117-S125. [PMID: 38662702 PMCID: PMC11045027 DOI: 10.1093/cid/ciae072] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/28/2024] Open
Abstract
BACKGROUND Lymphatic filariasis (LF) is a debilitating, poverty-promoting, neglected tropical disease (NTD) targeted for worldwide elimination as a public health problem (EPHP) by 2030. Evaluating progress towards this target for national programmes is challenging, due to differences in disease transmission and interventions at the subnational level. Mathematical models can help address these challenges by capturing spatial heterogeneities and evaluating progress towards LF elimination and how different interventions could be leveraged to achieve elimination by 2030. METHODS Here we used a novel approach to combine historical geo-spatial disease prevalence maps of LF in Ethiopia with 3 contemporary disease transmission models to project trends in infection under different intervention scenarios at subnational level. RESULTS Our findings show that local context, particularly the coverage of interventions, is an important determinant for the success of control and elimination programmes. Furthermore, although current strategies seem sufficient to achieve LF elimination by 2030, some areas may benefit from the implementation of alternative strategies, such as using enhanced coverage or increased frequency, to accelerate progress towards the 2030 targets. CONCLUSIONS The combination of geospatial disease prevalence maps of LF with transmission models and intervention histories enables the projection of trends in infection at the subnational level under different control scenarios in Ethiopia. This approach, which adapts transmission models to local settings, may be useful to inform the design of optimal interventions at the subnational level in other LF endemic regions.
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Affiliation(s)
- Joaquin M Prada
- Department of Comparative Biomedical Sciences, Faculty of Health and Medical Sciences, University of Surrey, Guildford, United Kingdom
| | | | - Biruck Kebede
- RTI International, 3040 E Cornwallis Rd, Research Triangle Park, North Carolina 27709, USA
| | | | - Heven Sime
- Malaria and Neglected Tropical Diseases Research Team, Bacterial, Parasitic and Zoonotic Disease Research Directorate, Ethiopian Public Health Institute, Addis Ababa, Ethiopia
| | - Morgan Smith
- Department of Biological Sciences, University of Notre Dame, Notre Dame, Indiana, USA
| | | | - Paul Brown
- Zeeman Institute for Systems Biology & Infectious Disease Epidemiology Research, University of Warwick, Coventry, United Kingdom
| | - Jorge Cano
- Expanded Special Project for Elimination of Neglected Tropical Diseases (ESPEN), WHO Regional Office for Africa, Brazzaville, Democratic Republic of the Congo
| | - Hajnal Farkas
- Zeeman Institute for Systems Biology & Infectious Disease Epidemiology Research, University of Warwick, Coventry, United Kingdom
| | - Mike Irvine
- Faculty of Science, BC Centre for Disease Control, Vancouver, Canada
| | - Lisa Reimer
- Department of Vector Biology, Liverpool School of Tropical Medicine, Liverpool, United Kingdom
| | - Rocio Caja Rivera
- College of Public Health, University of South Florida, Tampa, Florida, USA
| | - Sake J de Vlas
- Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands
| | - Edwin Michael
- College of Public Health, University of South Florida, Tampa, Florida, USA
| | - Wilma A Stolk
- Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands
| | - Rachel Pulan
- Faculty of Infectious and Tropical Diseases, London School of Hygiene & Tropical Medicine, London, United Kingdom
| | - Simon E F Spencer
- Zeeman Institute for Systems Biology & Infectious Disease Epidemiology Research, University of Warwick, Coventry, United Kingdom
| | - T Déirdre Hollingsworth
- Nuffield Department of Medicine, Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, University of Oxford, Oxford, United Kingdom
| | - Fikre Seife
- Disease Prevention and Control Directorate, Federal Ministry of Health, Addis Ababa, Ethiopia
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2
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Rock KS, Chapman LAC, Dobson AP, Adams ER, Hollingsworth TD. The Hidden Hand of Asymptomatic Infection Hinders Control of Neglected Tropical Diseases: A Modeling Analysis. Clin Infect Dis 2024; 78:S175-S182. [PMID: 38662705 PMCID: PMC11045017 DOI: 10.1093/cid/ciae096] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/28/2024] Open
Abstract
BACKGROUND Neglected tropical diseases are responsible for considerable morbidity and mortality in low-income populations. International efforts have reduced their global burden, but transmission is persistent and case-finding-based interventions rarely target asymptomatic individuals. METHODS We develop a generic mathematical modeling framework for analyzing the dynamics of visceral leishmaniasis in the Indian sub-continent (VL), gambiense sleeping sickness (gHAT), and Chagas disease and use it to assess the possible contribution of asymptomatics who later develop disease (pre-symptomatics) and those who do not (non-symptomatics) to the maintenance of infection. Plausible interventions, including active screening, vector control, and reduced time to detection, are simulated for the three diseases. RESULTS We found that the high asymptomatic contribution to transmission for Chagas and gHAT and the apparently high basic reproductive number of VL may undermine long-term control. However, the ability to treat some asymptomatics for Chagas and gHAT should make them more controllable, albeit over relatively long time periods due to the slow dynamics of these diseases. For VL, the toxicity of available therapeutics means the asymptomatic population cannot currently be treated, but combining treatment of symptomatics and vector control could yield a quick reduction in transmission. CONCLUSIONS Despite the uncertainty in natural history, it appears there is already a relatively good toolbox of interventions to eliminate gHAT, and it is likely that Chagas will need improvements to diagnostics and their use to better target pre-symptomatics. The situation for VL is less clear, and model predictions could be improved by additional empirical data. However, interventions may have to improve to successfully eliminate this disease.
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Affiliation(s)
- Kat S Rock
- Zeeman Institute for Systems Biology and Infectious Disease Epidemiology Research (SBIDER), University of Warwick, Coventry, United Kingdom
- Mathematics Institute, University of Warwick, Coventry, United Kingdom
| | - Lloyd A C Chapman
- Department of Mathematics and Statistics, Lancaster University, Lancaster, United Kingdom
- Centre for Mathematical Modelling of Infectious Diseases, London School of Hygiene and Tropical Medicine, London, United Kingdom
| | - Andrew P Dobson
- Department of Ecology and Evolutionary Biology, Princeton University, Princeton, New Jersey, USA
- Santa Fe Institute, Santa Fe, New Mexico, USA
| | - Emily R Adams
- Department of Clinical Sciences, Liverpool School of Tropical Medicine, Liverpool, United Kingdom
| | - T Déirdre Hollingsworth
- Nuffield Department of Medicine, Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, University of Oxford, Oxford, United Kingdom
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Crellen T, Haswell M, Sithithaworn P, Sayasone S, Odermatt P, Lamberton PHL, Spencer SEF, Déirdre Hollingsworth T. Diagnosis of helminths depends on worm fecundity and the distribution of parasites within hosts. Proc Biol Sci 2023; 290:20222204. [PMID: 36651047 PMCID: PMC9845982 DOI: 10.1098/rspb.2022.2204] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/03/2022] [Accepted: 12/16/2022] [Indexed: 01/19/2023] Open
Abstract
Helminth transmission and morbidity are dependent on the number of mature parasites within a host; however, observing adult worms is impossible for many natural infections. An outstanding challenge is therefore relating routine diagnostics, such as faecal egg counts, to the underlying worm burden. This relationship is complicated by density-dependent fecundity (egg output per worm reduces due to crowding at high burdens) and the skewed distribution of parasites (majority of helminths aggregated in a small fraction of hosts). We address these questions for the carcinogenic liver fluke Opisthorchis viverrini, which infects approximately 10 million people across Southeast Asia, by analysing five epidemiological surveys (n = 641) where adult flukes were recovered. Using a mechanistic model, we show that parasite fecundity varies between populations, with surveys from Thailand and Laos demonstrating distinct patterns of egg output and density-dependence. As the probability of observing faecal eggs increases with the number of mature parasites within a host, we quantify diagnostic sensitivity as a function of the worm burden and find that greater than 50% of cases are misdiagnosed as false negative in communities close to elimination. Finally, we demonstrate that the relationship between observed prevalence from routine diagnostics and true prevalence is nonlinear and strongly influenced by parasite aggregation.
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Affiliation(s)
- Thomas Crellen
- School of Biodiversity One Health and Veterinary Medicine, Graham Kerr Building, University of Glasgow, 82 Hillhead Street, Glasgow G12 8QQ, UK
- Wellcome Centre for Integrative Parasitology, Sir Graeme Davies Building, University of Glasgow, 120 University Place, Glasgow G12 8TA, UK
- Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, University of Oxford, Oxford OX3 7LF, UK
| | - Melissa Haswell
- Office of the Deputy Vice Chancellor, Indigenous Strategy and Services and School of Geosciences, John Woolley Building, University of Sydney, Sydney, New South Wales 2050, Australia
- School of Public Health and Social Work, Kelvin Grove Campus, Queensland University of Technology, Brisbane City, Queensland 4000, Australia
| | - Paiboon Sithithaworn
- Department of Parasitology, Khon Kaen University, 123 Thanon Mittraphap, Khon Kaen 40002, Thailand
| | - Somphou Sayasone
- Lao Tropical and Public Health Institute, Samsenthai Road, Sisattanak district, Vientiane, Lao PDR
| | - Peter Odermatt
- Department of Public Health and Epidemiology, Swiss Tropical and Public Health Institute, Kreuzstrasse 2, Allschwil 4123, Switzerland
- University of Basel, Petersplatz 1, Basel 4001, Switzerland
| | - Poppy H. L. Lamberton
- School of Biodiversity One Health and Veterinary Medicine, Graham Kerr Building, University of Glasgow, 82 Hillhead Street, Glasgow G12 8QQ, UK
- Wellcome Centre for Integrative Parasitology, Sir Graeme Davies Building, University of Glasgow, 120 University Place, Glasgow G12 8TA, 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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Dial NJ, Croft SL, Chapman LAC, Terris-Prestholt F, Medley GF. Challenges of using modelling evidence in the visceral leishmaniasis elimination programme in India. PLOS GLOBAL PUBLIC HEALTH 2022; 2:e0001049. [PMID: 36962829 PMCID: PMC10021829 DOI: 10.1371/journal.pgph.0001049] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 05/19/2022] [Accepted: 10/25/2022] [Indexed: 06/18/2023]
Abstract
As India comes closer to the elimination of visceral leishmaniasis (VL) as a public health problem, surveillance efforts and elimination targets must be continuously revised and strengthened. Mathematical modelling is a compelling research discipline for informing policy and programme design in its capacity to project incidence across space and time, the likelihood of achieving benchmarks, and the impact of different interventions. To gauge the extent to which modelling informs policy in India, this qualitative analysis explores how and whether policy makers understand, value, and reference recently produced VL modelling research. Sixteen semi-structured interviews were carried out with both users- and producers- of VL modelling research, guided by a knowledge utilisation framework grounded in knowledge translation theory. Participants reported that barriers to knowledge utilisation include 1) scepticism that models accurately reflect transmission dynamics, 2) failure of modellers to apply their analyses to specific programme operations, and 3) lack of accountability in the process of translating knowledge to policy. Political trust and support are needed to translate knowledge into programme activities, and employment of a communication intermediary may be a necessary approach to improve this process.
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Affiliation(s)
- Natalie J. Dial
- Department of Global Health and Development, Faculty of Public Health and Policy, London School of Hygiene and Tropical Medicine, London, United Kingdom
| | - Simon L. Croft
- Faculty of Infectious and Tropical Diseases, London School of Hygiene and Tropical Medicine, London, United Kingdom
| | - Lloyd A. C. Chapman
- Department of Global Health and Development, Faculty of Public Health and Policy, London School of Hygiene and Tropical Medicine, London, United Kingdom
| | - Fern Terris-Prestholt
- Department of Global Health and Development, Faculty of Public Health and Policy, London School of Hygiene and Tropical Medicine, London, United Kingdom
| | - Graham F. Medley
- Department of Global Health and Development, Faculty of Public Health and Policy, London School of Hygiene and Tropical Medicine, London, United Kingdom
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Oliveira Ascef B, de Oliveira GLA, Ribeiro Filha Coriolano C, De Oliveira Junior HA. Forecasting models for leprosy cases: a scoping review protocol. BMJ Open 2022; 12:e062828. [PMID: 35902193 PMCID: PMC9341210 DOI: 10.1136/bmjopen-2022-062828] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/14/2022] [Accepted: 07/20/2022] [Indexed: 11/16/2022] Open
Abstract
INTRODUCTION Leprosy is a neglected tropical disease caused by Mycobacterium leprae that mainly affects the skin, the peripheral nerves, the mucosa of the upper respiratory tract and the eyes. Mathematical models and statistical methodologies could play an important role in decision-making and help maintain the gains in elimination programmes. Various models for predicting leprosy cases have been reported in the literature, but they have different settings and distinct approaches to predicting the cases. This study describes the protocol for a scoping review to identify and synthesise information from studies using models to forecast leprosy cases. METHODS AND ANALYSIS A scoping review methodology will be applied following the Joanna Briggs Institute methodology for scoping reviews and will be reported according to Preferred Reporting Items for Systematic Reviews and Meta-analysis Extension for Scoping Reviews. We will perform a systematic search from when each database started until April 2022 and we will include the following electronic databases: MEDLINE via PubMed, Embase, Cochrane Library and Latin American and Caribbean Health Science Literature Database. Data will be extracted and recorded on a calibrated predefined data form and will be presented in a tabular form accompanied by a descriptive summary. The Prediction Model Study Risk of Bias Assessment Tool (PROBAST) will be used. ETHICS AND DISSEMINATION No ethical approval is required for this study. This scoping review will identify and map the methodological and other characteristics of modelling studies predicting leprosy cases. We hope that the review will contribute to scientific knowledge in this area and act as a basis for researchers designing and conducting leprosy models. This information can also be used to enhance national surveillance systems and to target specific policies. The protocol and consequent publications of this scoping review will be disseminated through peer-reviewed publications and policy briefs. SYSTEMATIC REVIEW REGISTRATION This scoping review was registered in the Open Science Framework (https://doi.org/10.17605/OSF.IO/W9375).
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Affiliation(s)
| | - Gustavo Laine Araújo de Oliveira
- The Disease Surveillance and Elimination Coordinating Committee, Department of Chronic Conditions and Sexually Transmitted Infections, Health Surveillance Secretariat, Ministry of Health, Brasília, Brazil
| | - Carmelita Ribeiro Filha Coriolano
- The Disease Surveillance and Elimination Coordinating Committee, Department of Chronic Conditions and Sexually Transmitted Infections, Health Surveillance Secretariat, Ministry of Health, Brasília, Brazil
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Janoušková E, Clark J, Kajero O, Alonso S, Lamberton PHL, Betson M, Prada JM. Public Health Policy Pillars for the Sustainable Elimination of Zoonotic Schistosomiasis. FRONTIERS IN TROPICAL DISEASES 2022. [DOI: 10.3389/fitd.2022.826501] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/13/2022] Open
Abstract
Schistosomiasis is a parasitic disease acquired through contact with contaminated freshwater. The definitive hosts are terrestrial mammals, including humans, with some Schistosoma species crossing the animal-human boundary through zoonotic transmission. An estimated 12 million people live at risk of zoonotic schistosomiasis caused by Schistosoma japonicum and Schistosoma mekongi, largely in the World Health Organization’s Western Pacific Region and in Indonesia. Mathematical models have played a vital role in our understanding of the biology, transmission, and impact of intervention strategies, however, these have mostly focused on non-zoonotic Schistosoma species. Whilst these non-zoonotic-based models capture some aspects of zoonotic schistosomiasis transmission dynamics, the commonly-used frameworks are yet to adequately capture the complex epi-ecology of multi-host zoonotic transmission. However, overcoming these knowledge gaps goes beyond transmission dynamics modelling. To improve model utility and enhance zoonotic schistosomiasis control programmes, we highlight three pillars that we believe are vital to sustainable interventions at the implementation (community) and policy-level, and discuss the pillars in the context of a One-Health approach, recognising the interconnection between humans, animals and their shared environment. These pillars are: (1) human and animal epi-ecological understanding; (2) economic considerations (such as treatment costs and animal losses); and (3) sociological understanding, including inter- and intra-human and animal interactions. These pillars must be built on a strong foundation of trust, support and commitment of stakeholders and involved institutions.
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7
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Clark J, Stolk WA, Basáñez MG, Coffeng LE, Cucunubá ZM, Dixon MA, Dyson L, Hampson K, Marks M, Medley GF, Pollington TM, Prada JM, Rock KS, Salje H, Toor J, Hollingsworth TD. How modelling can help steer the course set by the World Health Organization 2021-2030 roadmap on neglected tropical diseases. Gates Open Res 2022; 5:112. [PMID: 35169682 PMCID: PMC8816801 DOI: 10.12688/gatesopenres.13327.2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 01/28/2022] [Indexed: 01/12/2023] Open
Abstract
The World Health Organization recently launched its 2021-2030 roadmap, Ending the Neglect to Attain the Sustainable Development Goals , an updated call to arms to end the suffering caused by neglected tropical diseases. Modelling and quantitative analyses played a significant role in forming these latest goals. In this collection, we discuss the insights, the resulting recommendations and identified challenges of public health modelling for 13 of the target diseases: Chagas disease, dengue, gambiense human African trypanosomiasis (gHAT), lymphatic filariasis (LF), onchocerciasis, rabies, scabies, schistosomiasis, soil-transmitted helminthiases (STH), Taenia solium taeniasis/ cysticercosis, trachoma, visceral leishmaniasis (VL) and yaws. This piece reflects the three cross-cutting themes identified across the collection, regarding the contribution that modelling can make to timelines, programme design, drug development and clinical trials.
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Affiliation(s)
- Jessica Clark
- Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, University of Oxford, Old Road Campus, Headington, Oxford, OX3 7LF, UK
- Institute of Biodiversity, Animal Health & Comparative Medicine, College of Medical, Veterinary & Life Sciences, University of Glasgow, Glasgow, G12 8QQ, UK
| | - Wilma A. Stolk
- Department of Public Health, Erasmus MC, University Medical Center Rotterdam, Rotterdam, 3000 CA, The Netherlands
| | - María-Gloria Basáñez
- London Centre for Neglected Tropical Disease Research, Department of Infectious Disease Epidemiology, School of Public Health, Imperial College London, Norfolk Place, London, W2 1PG, UK
- MRC Centre for Global Infectious Disease Analysis, Department of Infectious Disease Epidemiology, School of Public Health, Imperial College London, Norfolk Place, London, W2 1PG, UK
| | - Luc E. Coffeng
- Department of Public Health, Erasmus MC, University Medical Center Rotterdam, Rotterdam, 3000 CA, The Netherlands
| | - Zulma M. Cucunubá
- London Centre for Neglected Tropical Disease Research, Department of Infectious Disease Epidemiology, School of Public Health, Imperial College London, Norfolk Place, London, W2 1PG, UK
- MRC Centre for Global Infectious Disease Analysis, Department of Infectious Disease Epidemiology, School of Public Health, Imperial College London, Norfolk Place, London, W2 1PG, UK
| | - Matthew A. Dixon
- MRC Centre for Global Infectious Disease Analysis, Department of Infectious Disease Epidemiology, School of Public Health, Imperial College London, Norfolk Place, London, W2 1PG, UK
- Schistosomiasis Control Initiative Foundation, London, SE11 5DP, UK
| | - Louise Dyson
- Mathematics Institute, University of Warwick, Coventry, CV4 7AL, UK
- School of Life Sciences, University of Warwick, Coventry, CV4 7AL, UK
| | - Katie Hampson
- Institute of Biodiversity, Animal Health & Comparative Medicine, College of Medical, Veterinary & Life Sciences, University of Glasgow, Glasgow, G12 8QQ, UK
| | - Michael Marks
- Department of Clinical Research, London School of Hygiene & Tropical Medicine, London, WC1E 7HT, UK
- Faculty of Infectious and Tropical Diseases, London School of Hygiene & Tropical Medicine, London, WC1E 7HT, UK
| | - Graham F. Medley
- Centre for Mathematical Modelling of Infectious Disease, London School of Hygiene & Tropical Medicine, 15-17 Tavistock Place, London, WC1H 9SH, UK
| | - Timothy M. Pollington
- Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, University of Oxford, Old Road Campus, Headington, Oxford, OX3 7LF, UK
- Mathematics Institute, University of Warwick, Coventry, CV4 7AL, UK
| | - Joaquin M. Prada
- School of Veterinary Medicine, Faculty of Health and Medical Sciences, University of Surrey, Guildford, GU2 7AL, UK
| | - Kat S. Rock
- Mathematics Institute, University of Warwick, Coventry, CV4 7AL, UK
| | - Henrik Salje
- Department of Genetics, University of Cambridge, Cambridge, CB2 3EH, UK
| | - Jaspreet Toor
- MRC Centre for Global Infectious Disease Analysis, Department of Infectious Disease Epidemiology, School of Public Health, Imperial College London, Norfolk Place, London, W2 1PG, UK
| | - T. Déirdre Hollingsworth
- Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, University of Oxford, Old Road Campus, Headington, Oxford, OX3 7LF, UK
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8
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Retkute R, Touloupou P, Basáñez MG, Hollingsworth TD, Spencer SEF. Integrating geostatistical maps and infectious disease transmission models using adaptive multiple importance sampling. Ann Appl Stat 2021. [DOI: 10.1214/21-aoas1486] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/19/2022]
Affiliation(s)
- Renata Retkute
- Epidemiology and Modelling Group, Department of Plant Sciences, University of Cambridge
| | | | - María-Gloria Basáñez
- London Centre for Neglected Tropical Disease Research and MRC Centre for Global Infectious Disease Analysis, Faculty of Medicine, School of Public Health, Imperial College London
| | - T. Déirdre Hollingsworth
- Big Data Institute, Li Ka Shing Centre for Health, Information and Discovery, University of Oxford
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9
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Clark J, Stolk WA, Basáñez MG, Coffeng LE, Cucunubá ZM, Dixon MA, Dyson L, Hampson K, Marks M, Medley GF, Pollington TM, Prada JM, Rock KS, Salje H, Toor J, Hollingsworth TD. How modelling can help steer the course set by the World Health Organization 2021-2030 roadmap on neglected tropical diseases. Gates Open Res 2021; 5:112. [PMID: 35169682 PMCID: PMC8816801 DOI: 10.12688/gatesopenres.13327.1] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 07/13/2021] [Indexed: 01/12/2023] Open
Abstract
The World Health Organization recently launched its 2021-2030 roadmap, Ending the Neglect to Attain the Sustainable Development Goals , an updated call to arms to end the suffering caused by neglected tropical diseases. Modelling and quantitative analyses played a significant role in forming these latest goals. In this collection, we discuss the insights, the resulting recommendations and identified challenges of public health modelling for 13 of the target diseases: Chagas disease, dengue, gambiense human African trypanosomiasis (gHAT), lymphatic filariasis (LF), onchocerciasis, rabies, scabies, schistosomiasis, soil-transmitted helminthiases (STH), Taenia solium taeniasis/ cysticercosis, trachoma, visceral leishmaniasis (VL) and yaws. This piece reflects the three cross-cutting themes identified across the collection, regarding the contribution that modelling can make to timelines, programme design, drug development and clinical trials.
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Affiliation(s)
- Jessica Clark
- Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, University of Oxford, Old Road Campus, Headington, Oxford, OX3 7LF, UK
- Institute of Biodiversity, Animal Health & Comparative Medicine, College of Medical, Veterinary & Life Sciences, University of Glasgow, Glasgow, G12 8QQ, UK
| | - Wilma A. Stolk
- Department of Public Health, Erasmus MC, University Medical Center Rotterdam, Rotterdam, 3000 CA, The Netherlands
| | - María-Gloria Basáñez
- London Centre for Neglected Tropical Disease Research, Department of Infectious Disease Epidemiology, School of Public Health, Imperial College London, Norfolk Place, London, W2 1PG, UK
- MRC Centre for Global Infectious Disease Analysis, Department of Infectious Disease Epidemiology, School of Public Health, Imperial College London, Norfolk Place, London, W2 1PG, UK
| | - Luc E. Coffeng
- Department of Public Health, Erasmus MC, University Medical Center Rotterdam, Rotterdam, 3000 CA, The Netherlands
| | - Zulma M. Cucunubá
- London Centre for Neglected Tropical Disease Research, Department of Infectious Disease Epidemiology, School of Public Health, Imperial College London, Norfolk Place, London, W2 1PG, UK
- MRC Centre for Global Infectious Disease Analysis, Department of Infectious Disease Epidemiology, School of Public Health, Imperial College London, Norfolk Place, London, W2 1PG, UK
| | - Matthew A. Dixon
- MRC Centre for Global Infectious Disease Analysis, Department of Infectious Disease Epidemiology, School of Public Health, Imperial College London, Norfolk Place, London, W2 1PG, UK
- Schistosomiasis Control Initiative Foundation, London, SE11 5DP, UK
| | - Louise Dyson
- Mathematics Institute, University of Warwick, Coventry, CV4 7AL, UK
- School of Life Sciences, University of Warwick, Coventry, CV4 7AL, UK
| | - Katie Hampson
- Institute of Biodiversity, Animal Health & Comparative Medicine, College of Medical, Veterinary & Life Sciences, University of Glasgow, Glasgow, G12 8QQ, UK
| | - Michael Marks
- Department of Clinical Research, London School of Hygiene & Tropical Medicine, London, WC1E 7HT, UK
- Faculty of Infectious and Tropical Diseases, London School of Hygiene & Tropical Medicine, London, WC1E 7HT, UK
| | - Graham F. Medley
- Centre for Mathematical Modelling of Infectious Disease, London School of Hygiene & Tropical Medicine, 15-17 Tavistock Place, London, WC1H 9SH, UK
| | - Timothy M. Pollington
- Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, University of Oxford, Old Road Campus, Headington, Oxford, OX3 7LF, UK
- Mathematics Institute, University of Warwick, Coventry, CV4 7AL, UK
| | - Joaquin M. Prada
- School of Veterinary Medicine, Faculty of Health and Medical Sciences, University of Surrey, Guildford, GU2 7AL, UK
| | - Kat S. Rock
- Mathematics Institute, University of Warwick, Coventry, CV4 7AL, UK
| | - Henrik Salje
- Department of Genetics, University of Cambridge, Cambridge, CB2 3EH, UK
| | - Jaspreet Toor
- MRC Centre for Global Infectious Disease Analysis, Department of Infectious Disease Epidemiology, School of Public Health, Imperial College London, Norfolk Place, London, W2 1PG, UK
| | - T. Déirdre Hollingsworth
- Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, University of Oxford, Old Road Campus, Headington, Oxford, OX3 7LF, UK
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10
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Minter A, Pellis L, Medley GF, Hollingsworth TD. What Can Modeling Tell Us About Sustainable End Points for Neglected Tropical Diseases? Clin Infect Dis 2021; 72:S129-S133. [PMID: 33905477 PMCID: PMC8201563 DOI: 10.1093/cid/ciab188] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/15/2023] Open
Abstract
As programs move closer toward the World Health Organization (WHO) goals of reduction in morbidity, elimination as a public health problem or elimination of transmission, countries will be faced with planning the next stages of surveillance and control in low prevalence settings. Mathematical models of neglected tropical diseases (NTDs) will need to go beyond predicting the effect of different treatment programs on these goals and on to predicting whether the gains can be sustained. One of the most important challenges will be identifying the policy goal and the right constraints on interventions and surveillance over the long term, as a single policy option will not achieve all aims—for example, minimizing morbidity and minimizing costs cannot both be achieved. As NTDs move toward 2030 and beyond, more nuanced intervention choices will be informed by quantitative analyses which are adapted to national context.
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Affiliation(s)
- Amanda Minter
- Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, University of Oxford, Oxford, United Kingdom
| | - Lorenzo Pellis
- Department of Mathematics, University of Manchester, Manchester, United Kingdom.,The Alan Turing Institute, London, United Kingdom
| | - Graham F Medley
- Centre for Mathematical Modelling of Infectious Diseases, London School of Hygiene and Tropical Medicine, London, United Kingdom
| | - T Déirdre Hollingsworth
- Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, University of Oxford, Oxford, United Kingdom
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11
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Bharadwaj M, Bengtson M, Golverdingen M, Waling L, Dekker C. Diagnosing point-of-care diagnostics for neglected tropical diseases. PLoS Negl Trop Dis 2021; 15:e0009405. [PMID: 34138846 PMCID: PMC8211285 DOI: 10.1371/journal.pntd.0009405] [Citation(s) in RCA: 18] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/17/2022] Open
Abstract
Inadequate and nonintegrated diagnostics are the Achilles' heel of global efforts to monitor, control, and eradicate neglected tropical diseases (NTDs). While treatment is often available, NTDs are endemic among marginalized populations, due to the unavailability or inadequacy of diagnostic tests that cause empirical misdiagnoses. The need of the hour is early diagnosis at the point-of-care (PoC) of NTD patients. Here, we review the status quo of PoC diagnostic tests and practices for all of the 24 NTDs identified in the World Health Organization's (WHO) 2021-2030 roadmap, based on their different diagnostic requirements. We discuss the capabilities and shortcomings of current diagnostic tests, identify diagnostic needs, and formulate prerequisites of relevant PoC tests. Next to technical requirements, we stress the importance of availability and awareness programs for establishing PoC tests that fit endemic resource-limited settings. Better understanding of NTD diagnostics will pave the path for setting realistic goals for healthcare in areas with minimal resources, thereby alleviating the global healthcare burden.
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Affiliation(s)
- Mitasha Bharadwaj
- Department of Bionanoscience, Kavli Institute of Nanoscience Delft, Delft University of Technology, Delft, The Netherlands
| | - Michel Bengtson
- Department of Bionanoscience, Kavli Institute of Nanoscience Delft, Delft University of Technology, Delft, The Netherlands
| | - Mirte Golverdingen
- Department of Bionanoscience, Kavli Institute of Nanoscience Delft, Delft University of Technology, Delft, The Netherlands
| | - Loulotte Waling
- Department of Bionanoscience, Kavli Institute of Nanoscience Delft, Delft University of Technology, Delft, The Netherlands
| | - Cees Dekker
- Department of Bionanoscience, Kavli Institute of Nanoscience Delft, Delft University of Technology, Delft, The Netherlands
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12
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Toor J, Hamley JID, Fronterre C, Castaño MS, Chapman LAC, Coffeng LE, Giardina F, Lietman TM, Michael E, Pinsent A, Le Rutte EA, Hollingsworth TD. Strengthening data collection for neglected tropical diseases: What data are needed for models to better inform tailored intervention programmes? PLoS Negl Trop Dis 2021; 15:e0009351. [PMID: 33983937 PMCID: PMC8118349 DOI: 10.1371/journal.pntd.0009351] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/19/2022] Open
Abstract
Locally tailored interventions for neglected tropical diseases (NTDs) are becoming increasingly important for ensuring that the World Health Organization (WHO) goals for control and elimination are reached. Mathematical models, such as those developed by the NTD Modelling Consortium, are able to offer recommendations on interventions but remain constrained by the data currently available. Data collection for NTDs needs to be strengthened as better data are required to indirectly inform transmission in an area. Addressing specific data needs will improve our modelling recommendations, enabling more accurate tailoring of interventions and assessment of their progress. In this collection, we discuss the data needs for several NTDs, specifically gambiense human African trypanosomiasis, lymphatic filariasis, onchocerciasis, schistosomiasis, soil-transmitted helminths (STH), trachoma, and visceral leishmaniasis. Similarities in the data needs for these NTDs highlight the potential for integration across these diseases and where possible, a wider spectrum of diseases.
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Affiliation(s)
- Jaspreet Toor
- Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, Oxford, United Kingdom
- * E-mail:
| | - 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
| | - Claudio Fronterre
- Centre for Health Informatics, Computing and Statistics, Lancaster University, Lancaster, United Kingdom
| | - María Soledad Castaño
- Department of Epidemiology and Public Health, Swiss Tropical and Public Health Institute, Basel, Switzerland
- University of Basel, Basel, Switzerland
| | - Lloyd A. C. Chapman
- Department of Global Health and Development, London School of Hygiene and Tropical Medicine, United Kingdom
- Department of Medicine, University of California, San Francisco, California, United States of America
| | - Luc E. Coffeng
- Department of Public Health, Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands
| | - Federica Giardina
- Department of Public Health, Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands
| | - 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
| | - Edwin Michael
- Department of Biological Sciences, University of Notre Dame, Notre Dame, Indiana, United States of America
| | - Amy Pinsent
- Department of Infectious Disease Epidemiology, London School of Hygiene & Tropical Medicine, London, United Kingdom
| | - Epke A. Le Rutte
- Department of Epidemiology and Public Health, Swiss Tropical and Public Health Institute, Basel, Switzerland
- University of Basel, Basel, Switzerland
- Department of Public Health, Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands
| | - T. Déirdre Hollingsworth
- Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, Oxford, United Kingdom
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13
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Skrip LA, Dermauw V, Dorny P, Ganaba R, Millogo A, Tarnagda Z, Carabin H. Data-driven analyses of behavioral strategies to eliminate cysticercosis in sub-Saharan Africa. PLoS Negl Trop Dis 2021; 15:e0009234. [PMID: 33755677 PMCID: PMC8018642 DOI: 10.1371/journal.pntd.0009234] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/29/2020] [Revised: 04/02/2021] [Accepted: 02/10/2021] [Indexed: 01/25/2023] Open
Abstract
Background The multi-host taeniosis/cysticercosis disease system is associated with significant neurological morbidity, as well as economic burden, globally. We investigated whether lower cost behavioral interventions are sufficient for local elimination of human cysticercosis in Boulkiemdé, Sanguié, and Nayala provinces of Burkina Faso. Methodology/Principal findings Province-specific data on human behaviors (i.e., latrine use and pork consumption) and serological prevalence of human and pig disease were used to inform a deterministic, compartmental model of the taeniosis/cysticercosis disease system. Parameters estimated via Bayesian melding provided posterior distributions for comparing transmission rates associated with human ingestion of Taenia solium cysticerci due to undercooking and human exposure to T. solium eggs in the environment. Reductions in transmission via these pathways were modeled to determine required effectiveness of a market-focused cooking behavior intervention and a community-led sanitation and hygiene program, independently and in combination, for eliminating human cysticercosis as a public health problem (<1 case per 1000 population). Transmission of cysticerci due to consumption of undercooked pork was found to vary significantly across transmission settings. In Sanguié, the rate of transmission due to undercooking was 6% higher than that in Boulkiemdé (95% CI: 1.03, 1.09; p-value < 0.001) and 35% lower than that in Nayala (95% CI: 0.64, 0.66; p-value < 0.001). We found that 67% and 62% reductions in undercooking of pork consumed in markets were associated with elimination of cysticercosis in Nayala and Sanguié, respectively. Elimination of active cysticercosis in Boulkiemdé required a 73% reduction. Less aggressive reductions of 25% to 30% in human exposure to Taenia solium eggs through sanitation and hygiene programs were associated with elimination in the provinces. Conclusions/Significance Despite heterogeneity in effectiveness due to local transmission dynamics and behaviors, education on the importance of proper cooking, in combination with community-led sanitation and hygiene efforts, has implications for reducing morbidity due to cysticercosis and neurocysticercosis. It is important to consider context-specific behaviors and transmission pathways when designing scalable and sustainable intervention strategies for neglected tropical diseases (NTDs). To reduce the morbidity and mortality associated with cysticercosis, suites of interventions have been recommended but are inconsistently implemented due to cost and feasibility-related constraints. This study investigated the potential of a cooking intervention to interrupt transmission via undercooked pork in marketplaces of Burkina Faso. The sensitivity of Taenia solium parasite to temperatures attainable via improved cooking strategies provides a low-cost, human-centered approach to prevent consumption of infected pork meals. By accounting for differential behavior and the relative role of this transmission route across three provinces, we show how the potential of cysticercosis elimination (as a public health problem) varies across behavior-focused interventions. Further investigation into intervention strategies against human and pig cysticercosis warrants data-driven analyses that account for local variation in transmission behaviors.
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Affiliation(s)
| | - Veronique Dermauw
- Department of Biomedical Sciences, Institute of Tropical Medicine, Antwerp, Belgium
| | - Pierre Dorny
- Department of Biomedical Sciences, Institute of Tropical Medicine, Antwerp, Belgium
| | | | - Athanase Millogo
- Department of Medicine, CHU Sourô Sanou, Bobo Dioulasso, Burkina Faso
| | - Zékiba Tarnagda
- Institut de Recherche en Sciences de la Santé (IRSS), Bobo Dioulasso, Burkina Faso
| | - Hélène Carabin
- Département de pathologie et microbiologie, Faculté de médecine vétérinaire, Université de Montréal, St-Hyacinthe, Québec, Canada
- Département de médecine sociale et préventive, École de Santé Publique, Université de Montréal, Montréal, Québec, Canada
- Centre de recherche en Santé Publique (CReSP), Montréal, Québec, Canada
- Groupe de recherche en épidémiologie des zoonoses et santé publique, St-Hyacinthe, Québec, Canada
- * E-mail:
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14
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Crellen T, Sithithaworn P, Pitaksakulrat O, Khuntikeo N, Medley GF, Hollingsworth TD. Towards Evidence-based Control of Opisthorchis viverrini. Trends Parasitol 2021; 37:370-380. [PMID: 33516657 DOI: 10.1016/j.pt.2020.12.007] [Citation(s) in RCA: 21] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/15/2020] [Revised: 12/18/2020] [Accepted: 12/25/2020] [Indexed: 01/21/2023]
Abstract
Transmission of the carcinogenic liver fluke Opisthorchis viverrini is ongoing across Southeast Asia. Endemic countries within the region are in different stages of achieving control. However, evidence on which interventions are the most effective for reducing parasite transmission, and the resulting liver cancer, is currently lacking. Quantitative modelling can be used to evaluate different control measures against O. viverrini and assist the design of clinical trials. In this article we evaluate the epidemiological parameters that underpin models of O. viverrini and the data necessary for their estimation, with the aim of developing evidence-based strategies for parasite control at a national or regional level.
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Affiliation(s)
- Thomas Crellen
- Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, Nuffield Department of Medicine, University of Oxford, Old Road Campus, Oxford, OX3 7LF, UK.
| | - Paiboon Sithithaworn
- Department of Parasitology, Khon Kaen University, Khon Kaen 40002, Thailand; Cholangiocarcinoma Research Institute, Khon Kaen University, Khon Kaen 40002, Thailand
| | - Opal Pitaksakulrat
- Department of Parasitology, Khon Kaen University, Khon Kaen 40002, Thailand
| | - Narong Khuntikeo
- Cholangiocarcinoma Research Institute, Khon Kaen University, Khon Kaen 40002, Thailand; Department of Surgery, Khon Kaen University, Khon Kaen 40002, Thailand
| | - Graham F Medley
- Faculty of Public Health and Policy, London School of Hygiene and Tropical Medicine, 15-17 Tavistock Place, London, WC1H 9SH, UK
| | - 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, OX3 7LF, UK
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15
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Statistical methods for linking geostatistical maps and transmission models: Application to lymphatic filariasis in East Africa. Spat Spatiotemporal Epidemiol 2020; 41:100391. [PMID: 35691660 PMCID: PMC9205338 DOI: 10.1016/j.sste.2020.100391] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/14/2020] [Revised: 11/06/2020] [Accepted: 11/06/2020] [Indexed: 11/30/2022]
Abstract
Novel methodology for combining geostatistical mapping and transmission modelling. Guide the planning of spatial control programmes by identifying affected areas. Current intervention strategy will not be sufficient to eliminate LF in most areas. Alternative strategies will be required to accelerate LF elimination in East Africa.
Infectious diseases remain one of the major causes of human mortality and suffering. Mathematical models have been established as an important tool for capturing the features that drive the spread of the disease, predicting the progression of an epidemic and hence guiding the development of strategies to control it. Another important area of epidemiological interest is the development of geostatistical methods for the analysis of data from spatially referenced prevalence surveys. Maps of prevalence are useful, not only for enabling a more precise disease risk stratification, but also for guiding the planning of more reliable spatial control programmes by identifying affected areas. Despite the methodological advances that have been made in each area independently, efforts to link transmission models and geostatistical maps have been limited. Motivated by this fact, we developed a Bayesian approach that combines fine-scale geostatistical maps of disease prevalence with transmission models to provide quantitative, spatially-explicit projections of the current and future impact of control programs against a disease. These estimates can then be used at a local level to identify the effectiveness of suggested intervention schemes and allow investigation of alternative strategies. The methodology has been applied to lymphatic filariasis in East Africa to provide estimates of the impact of different intervention strategies against the disease.
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16
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Toor J, Coffeng LE, Hamley JID, Fronterre C, Prada JM, Castaño MS, Davis EL, Godwin W, Vasconcelos A, Medley GF, Hollingsworth TD. When, Who, and How to Sample: Designing Practical Surveillance for 7 Neglected Tropical Diseases as We Approach Elimination. J Infect Dis 2020; 221:S499-S502. [PMID: 32529261 PMCID: PMC7289548 DOI: 10.1093/infdis/jiaa198] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/21/2022] Open
Abstract
As neglected tropical disease programs look to consolidate the successes of moving towards elimination, we need to understand the dynamics of transmission at low prevalence to inform surveillance strategies for detecting elimination and resurgence. In this special collection, modelling insights are used to highlight drivers of local elimination, evaluate strategies for detecting resurgence, and show the importance of rational spatial sampling schemes for several neglected tropical diseases (specifically schistosomiasis, soil-transmitted helminths, lymphatic filariasis, trachoma, onchocerciasis, visceral leishmaniasis, and gambiense sleeping sickness).
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Affiliation(s)
- Jaspreet Toor
- Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, University of Oxford, Oxford, United Kingdom
| | - Luc E Coffeng
- Department of Public Health, Erasmus Medical Center, University Medical Center Rotterdam, Rotterdam, The Netherlands
| | - 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, Imperial College London, London, United Kingdom
| | - Claudio Fronterre
- Centre for Health Informatics, Computing, and Statistics, Lancaster University, Lancaster, United Kingdom
| | - Joaquin M Prada
- School of Veterinary Medicine, Faculty of Health and Medical Sciences, University of Surrey, Guildford, United Kingdom
| | - M Soledad Castaño
- Department of Epidemiology and Public Health, Swiss Tropical and Public Health Institute, University of Basel, Basel, Switzerland
| | - Emma L Davis
- Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, University of Oxford, Oxford, United Kingdom
| | - William Godwin
- Francis I. Proctor Foundation, University of California San Francisco, San Francisco, California, USA
| | - Andreia Vasconcelos
- Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, University of Oxford, Oxford, United Kingdom
| | - Graham F Medley
- Centre for Mathematical Modelling of Infectious Disease, London School of Hygiene and Tropical Medicine, London, United Kingdom
| | - T Déirdre Hollingsworth
- Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, University of Oxford, Oxford, United Kingdom
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17
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Taylor EM. NTD Diagnostics for Disease Elimination: A Review. Diagnostics (Basel) 2020; 10:E375. [PMID: 32517108 PMCID: PMC7344624 DOI: 10.3390/diagnostics10060375] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/26/2020] [Revised: 05/07/2020] [Accepted: 06/02/2020] [Indexed: 11/16/2022] Open
Abstract
Neglected Tropical Diseases (NTDs) marked out for disease elimination provide a lens through which to explore the changing status of diagnosis in global health. This paper reports on the findings of a scoping review, which set out to explore the main debates around diagnosis for the elimination of NTDs, including the multiple roles diagnostic technologies are being ascribed and the ideal characteristics of tests. It also attempts to summarise the state of diagnosis for three NTDs with elimination goals. The review places special emphasis on point-of-care testing in acknowledgement of the remote and underserved areas where NTDs proliferate. Early NTD campaigns were largely focused on attack phase planning, whereby a similar set of interventions could be transplanted anywhere. Now, with elimination goals in sight, strategies must be tailored to local settings if they are to attain and sustain success. Diagnostic data helps with local adaptation and is increasingly used for programmatic decision-making. The review finds that elimination goals reframe whom diagnosis is for and the myriad roles diagnostics can play. The exigencies of elimination also serve to highlight deficiencies in the current diagnostic arsenal and development pipeline for many NTDs. Moving forward, a guiding framework is needed to drive research and stimulate investment in diagnosis to support NTD goals.
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Affiliation(s)
- Emma Michelle Taylor
- Department of Social Anthropology, University of Edinburgh, Edinburgh EH8 9LD, UK
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18
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Kura K, Collyer BS, Toor J, Truscott JE, Hollingsworth TD, Keeling MJ, Anderson RM. Policy implications of the potential use of a novel vaccine to prevent infection with Schistosoma mansoni with or without mass drug administration. Vaccine 2020; 38:4379-4386. [PMID: 32418795 PMCID: PMC7273196 DOI: 10.1016/j.vaccine.2020.04.078] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/25/2019] [Revised: 04/29/2020] [Accepted: 04/30/2020] [Indexed: 12/12/2022]
Abstract
Schistosomiasis is one of the most important neglected tropical diseases (NTDs) affecting millions of people in 79 different countries. The World Health Organization (WHO) has specified two control goals to be achieved by 2020 and 2025 - morbidity control and elimination as a public health problem (EPHP). Mass drug administration (MDA) is the main method for schistosomiasis control but it has sometimes proved difficult to both secure adequate supplies of the most efficacious drug praziquantel to treat the millions infected either annually or biannually, and to achieve high treatment coverage in targeted communities in regions of endemic infection. The development of alternative control methods remains a priority. In this paper, using stochastic individual-based models, we analyze whether the addition of a novel vaccine alone or in combination with drug treatment, is a more effective control strategy, in terms of achieving the WHO goals, as well as the time and costs to achieve these goals when compared to MDA alone. The key objective of our analyses is to help facilitate decision making for moving a promising candidate vaccine through the phase I, II and III trials in humans to a final product for use in resource poor settings. We find that in low to moderate transmission settings, both vaccination and MDA are highly likely to achieve the WHO goals within 15 years and are likely to be cost-effective. In high transmission settings, MDA alone is unable to achieve the goals, whereas vaccination is able to achieve both goals in combination with MDA. In these settings Vaccination is cost-effective, even for short duration vaccines, so long as vaccination costs up to US$7.60 per full course of vaccination. The public health value of the vaccine depends on the duration of vaccine protection, the baseline prevalence prior to vaccination and the WHO goal.
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Affiliation(s)
- 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, United Kingdom.
| | - Benjamin S Collyer
- Mathematics Institute, University of Warwick, United Kingdom; School of Life Sciences, University of Warwick, United Kingdom
| | - Jaspreet Toor
- 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, United Kingdom
| | - James E Truscott
- 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, United Kingdom; The DeWorm3 Project, The Natural History Museum of London, London, United Kingdom
| | - T Deirdre Hollingsworth
- Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, University of Oxford, Oxford OX3 7LF, United Kingdom
| | - Matt J Keeling
- Mathematics Institute, University of Warwick, United Kingdom; School of Life Sciences, University of Warwick, United Kingdom
| | - Roy M 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, United Kingdom; The DeWorm3 Project, The Natural History Museum of London, London, United Kingdom
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19
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Pereira CA, Sayé M, Reigada C, Silber AM, Labadie GR, Miranda MR, Valera-Vera E. Computational approaches for drug discovery against trypanosomatid-caused diseases. Parasitology 2020; 147:611-633. [PMID: 32046803 PMCID: PMC10317681 DOI: 10.1017/s0031182020000207] [Citation(s) in RCA: 16] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/20/2019] [Revised: 02/03/2020] [Accepted: 02/05/2020] [Indexed: 12/11/2022]
Abstract
During three decades, only about 20 new drugs have been developed for malaria, tuberculosis and all neglected tropical diseases (NTDs). This critical situation was reached because NTDs represent only 10% of health research investments; however, they comprise about 90% of the global disease burden. Computational simulations applied in virtual screening (VS) strategies are very efficient tools to identify pharmacologically active compounds or new indications for drugs already administered for other diseases. One of the advantages of this approach is the low time-consuming and low-budget first stage, which filters for testing experimentally a group of candidate compounds with high chances of binding to the target and present trypanocidal activity. In this work, we review the most common VS strategies that have been used for the identification of new drugs with special emphasis on those applied to trypanosomiasis and leishmaniasis. Computational simulations based on the selected protein targets or their ligands are explained, including the method selection criteria, examples of successful VS campaigns applied to NTDs, a list of validated molecular targets for drug development and repositioned drugs for trypanosomatid-caused diseases. Thereby, here we present the state-of-the-art of VS and drug repurposing to conclude pointing out the future perspectives in the field.
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Affiliation(s)
- Claudio A. Pereira
- Universidad de Buenos Aires, Facultad de Medicina, Instituto de Investigaciones Médicas A. Lanari, Buenos Aires, Argentina
- Consejo Nacional de Investigaciones Científicas y Técnicas, Universidad de Buenos Aires, Instituto de Investigaciones Médicas, Laboratorio de Parasitología Molecular, Buenos Aires, Argentina
| | - Melisa Sayé
- Universidad de Buenos Aires, Facultad de Medicina, Instituto de Investigaciones Médicas A. Lanari, Buenos Aires, Argentina
- Consejo Nacional de Investigaciones Científicas y Técnicas, Universidad de Buenos Aires, Instituto de Investigaciones Médicas, Laboratorio de Parasitología Molecular, Buenos Aires, Argentina
| | - Chantal Reigada
- Universidad de Buenos Aires, Facultad de Medicina, Instituto de Investigaciones Médicas A. Lanari, Buenos Aires, Argentina
- Consejo Nacional de Investigaciones Científicas y Técnicas, Universidad de Buenos Aires, Instituto de Investigaciones Médicas, Laboratorio de Parasitología Molecular, Buenos Aires, Argentina
| | - Ariel M. Silber
- Laboratory of Biochemistry of Tryps – LaBTryps, Department of Parasitology, Institute of Biomedical Sciences, University of São Paulo, São Paulo, Brazil
| | - Guillermo R. Labadie
- Instituto de Química Rosario (IQUIR-CONICET), Universidad Nacional de Rosario, Rosario, Argentina
- Departamento de Química Orgánica, Facultad de Ciencias Bioquímicas y Farmacéuticas, Universidad Nacional de Rosario, Rosario, Argentina
| | - Mariana R. Miranda
- Universidad de Buenos Aires, Facultad de Medicina, Instituto de Investigaciones Médicas A. Lanari, Buenos Aires, Argentina
- Consejo Nacional de Investigaciones Científicas y Técnicas, Universidad de Buenos Aires, Instituto de Investigaciones Médicas, Laboratorio de Parasitología Molecular, Buenos Aires, Argentina
| | - Edward Valera-Vera
- Universidad de Buenos Aires, Facultad de Medicina, Instituto de Investigaciones Médicas A. Lanari, Buenos Aires, Argentina
- Consejo Nacional de Investigaciones Científicas y Técnicas, Universidad de Buenos Aires, Instituto de Investigaciones Médicas, Laboratorio de Parasitología Molecular, Buenos Aires, Argentina
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20
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Huang XH, Qian MB, Zhu GH, Fang YY, Hao YT, Lai YS. Assessment of control strategies against Clonorchis sinensis infection based on a multi-group dynamic transmission model. PLoS Negl Trop Dis 2020; 14:e0008152. [PMID: 32218570 PMCID: PMC7156112 DOI: 10.1371/journal.pntd.0008152] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/07/2019] [Revised: 04/14/2020] [Accepted: 02/18/2020] [Indexed: 12/21/2022] Open
Abstract
Clonorchiasis is one of the most important food-borne trematodiases affecting millions of people. Strategies were recommended by different organizations and control programmes were implemented but mostly in short-time periods. It's important to assess the long-term benefits and sustainability of possible control strategies on morbidity control of the disease. We developed a multi-group transmission model to describe the dynamics of C. sinensis transmission among different groups of people with different raw-fish-consumption behaviors, based on which, a full model with interventions was proposed and three common control measures (i.e., preventive chemotherapy, information, education, and communication (IEC) and environmental modification) and their possible combinations were considered. Under a typical setting of C. sinensis transmission, we simulated interventions according to different strategies and with a series of values of intervention parameters. We found that combinations of measures were much beneficial than those singly applied; higher coverages of measures had better effects; and strategies targeted on whole population performed better than that on at-risk population with raw-fish-consumption behaviors. The strategy recommended by the government of Guangdong Province, China shows good and sustainable effects, under which, the infection control (with human prevalence <5%) could be achieved within 7.84 years (95% CI: 5.78-12.16 years) in our study setting (with original observed prevalence 33.67%). Several sustainable strategies were provided, which could lead to infection control within 10 years. This study makes the effort to quantitatively assess the long-term effects of possible control strategies against C. sinensis infection under a typical transmission setting, with application of a multi-group dynamic transmission model. The proposed model is easily facilitated with other transmission settings and the simulation outputs provide useful information to support the decision-making of control strategies on clonorchiasis.
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Affiliation(s)
- Xiao-Hong Huang
- Department of Medical Statistics, School of Public Health, Sun Yat-sen University, Guangzhou, Guangdong, People’s Republic of China
| | - Men-Bao Qian
- National Institute of Parasitic Diseases, Chinese Center for Disease Control and Prevention, Shanghai, People’s Republic of China
- WHO Collaborating Centre for Tropical Diseases, Key Laboratory of Parasite and Vector Biology, Ministry of Health, Shanghai, People’s Republic of China
| | - Guang-Hu Zhu
- Department of Mathematics and Computing Science, Guilin University of Electronic Technology, Guilin, Guangxi, People’s Republic of China
| | - Yue-Yi Fang
- Institute of Parasitic Diseases, Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, Guangdong, People’s Republic of China
| | - Yuan-Tao Hao
- Department of Medical Statistics, School of Public Health, Sun Yat-sen University, Guangzhou, Guangdong, People’s Republic of China
- Sun Yat-sen Global Health Institute, Sun Yat-sen University, Guangzhou, Guangdong, People’s Republic of China
| | - Ying-Si Lai
- Department of Medical Statistics, School of Public Health, Sun Yat-sen University, Guangzhou, Guangdong, People’s Republic of China
- Sun Yat-sen Global Health Institute, Sun Yat-sen University, Guangzhou, Guangdong, People’s Republic of China
- * E-mail:
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21
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Betson M, Alonte AJI, Ancog RC, Aquino AMO, Belizario VY, Bordado AMD, Clark J, Corales MCG, Dacuma MG, Divina BP, Dixon MA, Gourley SA, Jimenez JRD, Jones BP, Manalo SMP, Prada JM, van Vliet AHM, Whatley KCL, Paller VGV. Zoonotic transmission of intestinal helminths in southeast Asia: Implications for control and elimination. ADVANCES IN PARASITOLOGY 2020; 108:47-131. [PMID: 32291086 DOI: 10.1016/bs.apar.2020.01.036] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/12/2022]
Abstract
Intestinal helminths are extremely widespread and highly prevalent infections of humans, particularly in rural and poor urban areas of low and middle-income countries. These parasites have chronic and often insidious effects on human health and child development including abdominal problems, anaemia, stunting and wasting. Certain animals play a fundamental role in the transmission of many intestinal helminths to humans. However, the contribution of zoonotic transmission to the overall burden of human intestinal helminth infection and the relative importance of different animal reservoirs remains incomplete. Moreover, control programmes and transmission models for intestinal helminths often do not consider the role of zoonotic reservoirs of infection. Such reservoirs will become increasingly important as control is scaled up and there is a move towards interruption and even elimination of parasite transmission. With a focus on southeast Asia, and the Philippines in particular, this review summarises the major zoonotic intestinal helminths, risk factors for infection and highlights knowledge gaps related to their epidemiology and transmission. Various methodologies are discussed, including parasite genomics, mathematical modelling and socio-economic analysis, that could be employed to improve understanding of intestinal helminth spread, reservoir attribution and the burden associated with infection, as well as assess effectiveness of interventions. For sustainable control and ultimately elimination of intestinal helminths, there is a need to move beyond scheduled mass deworming and to consider animal and environmental reservoirs. A One Health approach to control of intestinal helminths is proposed, integrating interventions targeting humans, animals and the environment, including improved access to water, hygiene and sanitation. This will require coordination and collaboration across different sectors to achieve best health outcomes for all.
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Affiliation(s)
- Martha Betson
- University of Surrey, Guildford, Surrey, United Kingdom.
| | | | - Rico C Ancog
- University of the Philippines Los Baños, Laguna, Philippines
| | | | | | | | - Jessica Clark
- University of Surrey, Guildford, Surrey, United Kingdom
| | | | | | - Billy P Divina
- University of the Philippines Los Baños, Laguna, Philippines
| | | | | | | | - Ben P Jones
- University of Surrey, Guildford, Surrey, United Kingdom
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22
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The roadmap towards elimination of lymphatic filariasis by 2030: insights from quantitative and mathematical modelling. Gates Open Res 2019; 3:1538. [PMID: 31728440 PMCID: PMC6833911 DOI: 10.12688/gatesopenres.13065.1] [Citation(s) in RCA: 19] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 09/03/2019] [Indexed: 01/26/2023] Open
Abstract
The Global Programme to Eliminate Lymphatic Filariasis was launched in 2000 to eliminate lymphatic filariasis (LF) as a public health problem by 1) interrupting transmission through mass drug administration (MDA) and 2) offering basic care to those suffering from lymphoedema or hydrocele due to the infection. Although impressive progress has been made, the initial target year of 2020 will not be met everywhere. The World Health Organization recently proposed 2030 as the new target year for elimination of lymphatic filariasis (LF) as a public health problem. In this letter, LF modelers of the Neglected Tropical Diseases (NTDs) Modelling Consortium reflect on the proposed targets for 2030 from a quantitative perspective. While elimination as a public health problem seems technically and operationally feasible, it is uncertain whether this will eventually also lead to complete elimination of transmission. The risk of resurgence needs to be mitigated by strong surveillance after stopping interventions and sometimes perhaps additional interventions.
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23
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Chami GF, Bundy DAP. More medicines alone cannot ensure the treatment of neglected tropical diseases. THE LANCET. INFECTIOUS DISEASES 2019; 19:e330-e336. [PMID: 31160190 DOI: 10.1016/s1473-3099(19)30160-4] [Citation(s) in RCA: 25] [Impact Index Per Article: 4.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/31/2018] [Revised: 02/15/2019] [Accepted: 03/13/2019] [Indexed: 01/19/2023]
Abstract
Neglected tropical diseases afflict more than 1 billion of the world's poorest people. Pharmaceutical donations of preventive chemotherapy for neglected tropical diseases enable the largest en masse treatment campaigns globally with respect to the number of people targeted for treatment. However, the blanket distribution of medicines at no cost to individuals in need of treatment does not guarantee that those individuals are treated. In this Personal View, we aim to examine the next steps that need to be taken towards ensuring equitable treatment access, including health system integration and the role of endemic countries in ensuring medicines are delivered to patients. We argue that the expansion of medicine donation programmes and the development of new medicines are not the primary solutions to sustaining and expanding the growth of neglected tropical disease programmes. Treatment is often not verified by a medical professional, independent surveyor, or national programme officer. Additionally, access to medicines might not be equitable across at-risk populations, and treatment targets for disease control remain largely unmet within many endemic countries. To enable equitable access and efficient use of existing medicines, research is needed now on how best to integrate the treatment of neglected tropical diseases into local health systems. A comprehensive approach should be used, which combines mass drug administration with on-demand access to treatment. Increased commitment by endemic countries, when possible, around the ownership of treatment campaigns is essential to improve access to medicines for neglected tropical diseases.
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Affiliation(s)
- Goylette F Chami
- Department of Pathology, University of Cambridge, Cambridge, UK.
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