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Chaves LF, Meyers AC, Hodo CL, Sanders JP, Curtis-Robles R, Hamer GL, Hamer SA. Trypanosoma cruzi infection in dogs along the US-Mexico border: R 0 changes with vector species composition. Epidemics 2023; 45:100723. [PMID: 37935075 DOI: 10.1016/j.epidem.2023.100723] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/25/2022] [Revised: 07/05/2023] [Accepted: 10/26/2023] [Indexed: 11/09/2023] Open
Abstract
Infection with Trypanosoma cruzi, etiological agent of Chagas disease, is common in US government working dogs along the US-Mexico border. This 3145 km long border comprises four states: Texas (TX), New Mexico (NM), Arizona (AZ) and California (CA) with diverse ecosystems and several triatomine (a.k.a., kissing bug) species, primary vectors of T. cruzi in this region. The kissing bug (Heteroptera: Reduviidae) community ranging from CA to TX includes Triatoma protracta (Uhler), Triatoma recurva (Stål) and Triatoma rubida (Uhler) and becomes dominated by Triatoma gerstaeckeri Stål in TX. Here, we ask if T. cruzi infection dynamics in dogs varies along this border region, potentially reflecting changes in vector species and their vectorial capacity. Using reversible catalytic models of infection, where seropositivity can be lost, we estimated an R0 (Estimate ± S.E.) of 1.192 ± 0.084 for TX and NM. In contrast, seropositivity decayed to zero as dogs aged in AZ and CA. These results suggest that dogs are likely infected by T. cruzi during their training in western TX, with a force of infection large enough for keeping R0 above 1, i.e., the disease endemically established, in TX and NM. In AZ and CA, a lower force of infection, probably associated with different vector species communities and associated vectorial capacity and/or different lineages of T. cruzi, results in dogs decreasing their seropositivity with age.
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Affiliation(s)
- Luis Fernando Chaves
- Department of Environmental and Occupational Health, School of Public Health, Indiana University, Bloomington IN 47405, USA.
| | - Alyssa C Meyers
- Department of Veterinary Integrative Bioscienes, School of Veterinary Medicine and Biomedical Sciences, Texas A&M University, College Station, TX 77843, USA; Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI 48109, USA
| | - Carolyn L Hodo
- Department of Veterinary Integrative Bioscienes, School of Veterinary Medicine and Biomedical Sciences, Texas A&M University, College Station, TX 77843, USA; Department of Comparative Medicine, Keeling Center for Comparative Medicine and Research, The University of Texas MD Anderson Cancer Center, Bastrop, TX 78602, USA
| | - John P Sanders
- Office of Health Security, US Department of Homeland Security, Washington, DC 20528, USA
| | - Rachel Curtis-Robles
- Department of Veterinary Integrative Bioscienes, School of Veterinary Medicine and Biomedical Sciences, Texas A&M University, College Station, TX 77843, USA
| | - Gabriel L Hamer
- Department of Entomology, Texas A&M University, College Station, TX 77843, USA
| | - Sarah A Hamer
- Department of Veterinary Integrative Bioscienes, School of Veterinary Medicine and Biomedical Sciences, Texas A&M University, College Station, TX 77843, USA
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Fiatsonu E, Deka A, Ndeffo-Mbah ML. Effectiveness of Systemic Insecticide Dog Treatment for the Control of Chagas Disease in the Tropics. BIOLOGY 2023; 12:1235. [PMID: 37759635 PMCID: PMC10525078 DOI: 10.3390/biology12091235] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/01/2023] [Revised: 09/05/2023] [Accepted: 09/07/2023] [Indexed: 09/29/2023]
Abstract
Chagas disease, caused by Trypanosoma cruzi and transmitted by triatomines, can lead to severe cardiac issues and mortality in many mammals. Recent studies have shown that systemic insecticide treatment of dogs is highly effective in killing triatomines. Here, we assessed the impact of dog treatment on T. cruzi transmission. We developed a mathematical model of T. cruzi transmission among triatomines, dogs, humans, and rodents. We used the model to evaluate the impact of dog treatment regimens on T. cruzi transmission dynamics to determine their effectiveness in reducing T. cruzi infection among hosts. We show that a 3-month treatment regimen may reduce T. cruzi incidence among humans by 59-80% in a high transmission setting, and 26-82% in a low transmission setting. An annual treatment may reduce incidence among humans by 49-74% in a high transmission setting, and by 11-76% in a low transmission setting. However, dog treatment may substantially increase T. cruzi prevalence among dogs if dog consumption of dead triatomines increases. Our model indicates that dog treatment may reduce T. cruzi infections among humans, but it may increase infections in dogs. Therefore, a holistic approach targeting different hosts is necessary for Chagas elimination.
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Affiliation(s)
- Edem Fiatsonu
- Department of Veterinary Integrative Biosciences, College of Veterinary Medicine and Biomedical Sciences, Texas A&M University, College Station, TX 77845, USA; (A.D.); (M.L.N.-M.)
| | - Aniruddha Deka
- Department of Veterinary Integrative Biosciences, College of Veterinary Medicine and Biomedical Sciences, Texas A&M University, College Station, TX 77845, USA; (A.D.); (M.L.N.-M.)
| | - Martial L. Ndeffo-Mbah
- Department of Veterinary Integrative Biosciences, College of Veterinary Medicine and Biomedical Sciences, Texas A&M University, College Station, TX 77845, USA; (A.D.); (M.L.N.-M.)
- Department of Epidemiology and Biostatistics, School of Public Health, Texas A&M University, College Station, TX 77845, USA
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Lozada-Yavina R, Marchant C, Cancino-Faure B, Hernández-Rodríguez EW, Córdova-Lepe F. A description of the epidemiological dynamics of Chagas disease via mathematical modeling. Acta Trop 2023; 243:106930. [PMID: 37098356 DOI: 10.1016/j.actatropica.2023.106930] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/16/2022] [Revised: 04/15/2023] [Accepted: 04/19/2023] [Indexed: 04/27/2023]
Abstract
Chagas disease is caused by the protozoan Trypanosoma cruzi, which parasitizes many mammals, including humans. Its vectors are blood-feeding hematophagous triatomine insects of different species, which vary according to the geographical area. One of the 17 neglected diseases targeted by the World Health Organization, Chagas disease is endemic to the Americas, but has spread to other countries due to human migratory movements. In this study, we describe the epidemiological dynamics of Chagas disease in an endemic area, considering the main transmission mechanisms and the demographic effects of birth, mortality, and human migration in this phenomenon. We apply mathematical models as a methodological approach to simulate the interactions between reservoirs, vectors, and humans using a system of ordinary differential equations. The results show that the Chagas disease control measures currently in place cannot be relaxed without endangering the progress achieved to date.
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Affiliation(s)
- Rafael Lozada-Yavina
- Departamento de Matemática, Física y Estadística, Facultad de Ciencias Básicas, Universidad Católica del Maule, Talca, 3480112, Chile.
| | - Carolina Marchant
- Departamento de Matemática, Física y Estadística, Facultad de Ciencias Básicas, Universidad Católica del Maule, Talca, 3480112, Chile
| | - Beatriz Cancino-Faure
- Laboratorio de Microbiología y Parasitología, Departamento de Ciencias Preclínicas, Facultad de Medicina, Universidad Católica del Maule, Talca, 3480112, Chile
| | - Erix W Hernández-Rodríguez
- Laboratorio de Bioinformática y Química Computacional, Departamento de Medicina Traslacional, Facultad de Medicina, Universidad Católica del Maule, Talca, 3480112, Chile
| | - Fernando Córdova-Lepe
- Departamento de Matemática, Física y Estadística, Facultad de Ciencias Básicas, Universidad Católica del Maule, Talca, 3480112, Chile
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Fiatsonu E, Busselman RE, Ndeffo-Mbah ML. A Scoping Review of Mathematical Models Used to Investigate the Role of Dogs in Chagas Disease Transmission. Animals (Basel) 2023; 13:ani13040555. [PMID: 36830342 PMCID: PMC9951694 DOI: 10.3390/ani13040555] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/03/2023] [Revised: 01/24/2023] [Accepted: 02/02/2023] [Indexed: 02/08/2023] Open
Abstract
Chagas disease is a zoonotic vector-borne disease caused by the parasite Trypanosoma cruzi, which affects a variety of mammalian species across the Americas, including humans and dogs. Mathematical modeling has been widely used to investigate the transmission dynamics and control of vector-borne diseases. We performed a scoping review of mathematical models that investigated the role of dogs in T. cruzi transmission. We identified ten peer-reviewed papers that have explicitly modeled the role of dogs in Chagas transmission dynamics. We discuss the different methods employed in these studies, the different transmission metrics, disease transmission routes, and disease control strategies that have been considered and evaluated. In general, mathematical modeling studies have shown that dogs are not only at high risk of T. cruzi infection but are also major contributors to T. cruzi transmission to humans. Moreover, eliminating infected dogs from households or frequent use of insecticide was shown to be effective for curtailing T. cruzi transmission in both humans and dogs. However, when insecticide spraying is discontinued, T. cruzi infections in dogs were shown to return to their pre-spraying levels. We discuss the challenges and opportunities for future modeling studies to improve our understanding of Chagas disease transmission dynamics and control.
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Fiatsonu E, Busselman RE, Hamer GL, Hamer SA, Ndeffo-Mbah ML. Effectiveness of fluralaner treatment regimens for the control of canine Chagas disease: A mathematical modeling study. PLoS Negl Trop Dis 2023; 17:e0011084. [PMID: 36693084 PMCID: PMC9897538 DOI: 10.1371/journal.pntd.0011084] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/15/2022] [Revised: 02/03/2023] [Accepted: 01/09/2023] [Indexed: 01/25/2023] Open
Abstract
BACKGROUND Canine Chagas disease is caused by the protozoan parasite Trypanosoma cruzi and transmitted by insect triatomine vectors known as kissing bugs. The agent can cause cardiac damage and long-term heart disease and death in humans, dogs, and other mammals. In laboratory settings, treatment of dogs with systemic insecticides has been shown to be highly efficacious at killing triatomines that feed on treated dogs. METHOD We developed compartmental vector-host models of T. cruzi transmission between the triatomine and dog population accounting for the impact of seasonality and triatomine migration on disease transmission dynamics. We considered a single vector-host model without seasonality, and model with seasonality, and a spatially coupled model. We used the models to evaluate the effectiveness of the insecticide fluralaner with different durations of treatment regimens for reducing T. cruzi infection in different transmission settings. RESULTS In low and medium transmission settings, our model showed a marginal difference between the 3-month and 6-month regimens for reducing T. cruzi infection among dogs. The difference increases in the presence of seasonality and triatomine migration from a sylvatic transmission setting. In high transmission settings, the 3-month regimen was substantially more effective in reducing T. cruzi infections in dogs than the other regimens. Our model showed that increased migration rate reduces fluralaner effectiveness in all treatment regimens, but the relative reduction in effectiveness is minimal during the first years of treatment. However, if an additional 10% or more of triatomines killed by dog treatment were eaten by dogs, treatment could increase T. cruzi infections in the dog population at least during the first year of treatment. CONCLUSION Our analysis shows that treating all peridomestic dogs every three to six months for at least five years could be an effective measure to reduce T. cruzi infections in dogs and triatomines in peridomestic transmission settings. However, further studies at the local scale are needed to better understand the potential impact of routine use of fluralaner treatment on increasing dogs' consumption of dead triatomines.
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Affiliation(s)
- Edem Fiatsonu
- Department of Veterinary Integrative Biosciences, College of Veterinary Medicine and Biomedical Sciences, Texas A&M University, College Station, Texas, United States of America
| | - Rachel E. Busselman
- Department of Veterinary Integrative Biosciences, College of Veterinary Medicine and Biomedical Sciences, Texas A&M University, College Station, Texas, United States of America
| | - Gabriel L. Hamer
- Department of Entomology, College of Agriculture and Life Sciences, Texas A&M University, College Station, Texas, United States of America
| | - Sarah A. Hamer
- Department of Veterinary Integrative Biosciences, College of Veterinary Medicine and Biomedical Sciences, Texas A&M University, College Station, Texas, United States of America
| | - Martial L. Ndeffo-Mbah
- Department of Veterinary Integrative Biosciences, College of Veterinary Medicine and Biomedical Sciences, Texas A&M University, College Station, Texas, United States of America
- Department of Epidemiology and Biostatistics, School of Public Health, Texas A&M University, College Station, Texas, United States of America
- * E-mail:
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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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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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Han CY, Issa H, Rychtář J, Taylor D, Umana N. A voluntary use of insecticide treated nets can stop the vector transmission of Chagas disease. PLoS Negl Trop Dis 2020; 14:e0008833. [PMID: 33141850 PMCID: PMC7671556 DOI: 10.1371/journal.pntd.0008833] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/29/2020] [Revised: 11/17/2020] [Accepted: 09/24/2020] [Indexed: 11/19/2022] Open
Abstract
One of the stated goals of the London Declaration on Neglected Tropical Diseases is the interruption of domiciliary transmissions of Chagas disease in the region of the Americas. We used a game-theoretic approach to assess the voluntary use of insecticide treated nets (ITNs) in the prevention of the spread of infection through vector bites. Our results show that individuals behave rationally and weigh the risks of insect bites against the cost of the ITNs. The optimal voluntary use of ITNs results in predicted incidence rates that closely track the real incidence rates in Latin America. This means that ITNs are effective and could be used to control the spread of the disease by relying on individual decisions rather than centralized policies. Our model shows that to completely eradicate the vector transmission through the voluntary individual use of ITNs, the cost of ITNs should be as low as possible.
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Affiliation(s)
- Cheol Yong Han
- Department of Mechanical and Nuclear Engineering, Virginia Commonwealth University, Richmond, Virginia, USA
| | - Habeeb Issa
- Department of Biology, Virginia Commonwealth University, Richmond, Virginia, USA
| | - Jan Rychtář
- Department of Mathematics and Applied Mathematics, Virginia Commonwealth University, Richmond, Virginia, USA
| | - Dewey Taylor
- Department of Mathematics and Applied Mathematics, Virginia Commonwealth University, Richmond, Virginia, USA
| | - Nancy Umana
- Department of Biology, Virginia Commonwealth University, Richmond, Virginia, USA
- Department of Psychology, Virginia Commonwealth University, Richmond, Virginia, USA
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9
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Insights from quantitative and mathematical modelling on the proposed WHO 2030 goals for Chagas disease. Gates Open Res 2019; 3:1539. [PMID: 31781687 PMCID: PMC6856696 DOI: 10.12688/gatesopenres.13069.1] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 09/12/2019] [Indexed: 12/22/2022] Open
Abstract
Chagas disease (CD) persists as one of the neglected tropical diseases (NTDs) with a particularly large impact in the Americas. The World Health Organization (WHO) recently proposed goals for CD elimination as a public health problem to be reached by 2030 by means of achieving intradomiciliary transmission interruption (IDTI), blood transfusion and transplant transmission interruption, diagnostic and treatment scaling-up and prevention and control of congenital transmission. The NTD Modelling Consortium has developed mathematical models to study
Trypanosoma cruzi transmission dynamics and the potential impact of control measures. Modelling insights have shown that IDTI is feasible in areas with sustained vector control programmes and no presence of native triatomine vector populations. However, IDTI in areas with native vectors it is not feasible in a sustainable manner. Combining vector control with trypanocidal treatment can reduce the timeframes necessary to reach operational thresholds for IDTI (<2% seroprevalence in children aged <5 years), but the most informative age groups for serological monitoring are yet to be identified. Measuring progress towards the 2030 goals will require availability of vector surveillance and seroprevalence data at a fine scale, and a more active surveillance system, as well as a better understanding of the risks of vector re-colonization and disease resurgence after vector control cessation. Also, achieving scaling-up in terms of access to treatment to the expected levels (75%) will require a substantial increase in screening asymptomatic populations, which is anticipated to become very costly as CD prevalence decreases. Further modelling work includes refining and extending mathematical models (including transmission dynamics and statistical frameworks) to predict transmission at a sub-national scale, and developing quantitative tools to inform IDTI certification, post-certification and re-certification protocols. Potential perverse incentives associated with operational thresholds are discussed. These modelling insights aim to inform discussions on the goals and treatment guidelines for CD.
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10
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Pinsent A, Solomon AW, Bailey RL, Bid R, Cama A, Dean D, Goodhew B, Gwyn SE, Jack KR, Kandel RP, Kama M, Massae P, Macleod C, Mabey DCW, Migchelsen S, Müller A, Sandi F, Sokana O, Taoaba R, Tekeraoi R, Martin DL, White MT. The utility of serology for elimination surveillance of trachoma. Nat Commun 2018; 9:5444. [PMID: 30575720 PMCID: PMC6303365 DOI: 10.1038/s41467-018-07852-0] [Citation(s) in RCA: 36] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/25/2018] [Accepted: 11/27/2018] [Indexed: 11/24/2022] Open
Abstract
Robust surveillance methods are needed for trachoma control and recrudescence monitoring, but existing methods have limitations. Here, we analyse data from nine trachoma-endemic populations and provide operational thresholds for interpretation of serological data in low-transmission and post-elimination settings. Analyses with sero-catalytic and antibody acquisition models provide insights into transmission history within each population. To accurately estimate sero-conversion rates (SCR) for trachoma in populations with high-seroprevalence in adults, the model accounts for secondary exposure to Chlamydia trachomatis due to urogenital infection. We estimate the population half-life of sero-reversion for anti-Pgp3 antibodies to be 26 (95% credible interval (CrI): 21–34) years. We show SCRs below 0.015 (95% confidence interval (CI): 0.0–0.049) per year correspond to a prevalence of trachomatous inflammation—follicular below 5%, the current threshold for elimination of active trachoma as a public health problem. As global trachoma prevalence declines, we may need cross-sectional serological survey data to inform programmatic decisions. Robust surveillance methods are needed for trachoma control and recrudescence monitoring, but existing methods have limitations. Here, Pinsent et al. analyse data from nine trachoma-endemic populations and provide operational thresholds for interpretation of serological data in low transmission and post-elimination settings.
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Affiliation(s)
- Amy Pinsent
- Department of Public Health and Preventative Medicine, Monash University, Melbourne, VIC, 3004, Australia. .,Department of Infectious Disease Epidemiology, London School of Hygiene & Tropical Medicine, London, WC1E 7HT, UK.
| | - Anthony W Solomon
- Department of Control of Neglected Tropical Diseases, World Health Organization, 1211, Geneva 27, Switzerland.,Clinical Research Department, London School of Hygiene & Tropical Medicine, London, WC1E 7HT, UK
| | - Robin L Bailey
- Clinical Research Department, London School of Hygiene & Tropical Medicine, London, WC1E 7HT, UK
| | - Rhiannon Bid
- Clinical Research Department, London School of Hygiene & Tropical Medicine, London, WC1E 7HT, UK
| | - Anaseini Cama
- International Agency for the Prevention of Blindness, Western Pacific Region, Suva, Fiji.,The Fred Hollows Foundation, Level 2, 61 Dunning Ave, Rosebury, NSW, 2018, Australia
| | - Deborah Dean
- UCSF Benioff Children's Hospital Oakland Research Institute, 5700 Martin Luther King Jr Way, Oakland, CA, 94609, USA
| | - Brook Goodhew
- Division of Parasitic Diseases and Malaria, Centers for Disease Control and Prevention, 1600 Clifton Road, Atlanta, GA, 30333, USA
| | - Sarah E Gwyn
- Division of Parasitic Diseases and Malaria, Centers for Disease Control and Prevention, 1600 Clifton Road, Atlanta, GA, 30333, USA
| | - Kelvin R Jack
- Eyecare Department, Ministry of Health, Honiara, Solomon Islands
| | | | - Mike Kama
- Department of Communicable Diseases, Ministry of Health, Suva, Fiji
| | - Patrick Massae
- Department of Ophthalmology, Kilimanjaro Christian Medical Centre, Moshi, Tanzania
| | - Colin Macleod
- Clinical Research Department, London School of Hygiene & Tropical Medicine, London, WC1E 7HT, UK.,Sightsavers, 35 Perrymount Road, Haywards Heath, RH16 6NG, UK
| | - David C W Mabey
- Clinical Research Department, London School of Hygiene & Tropical Medicine, London, WC1E 7HT, UK
| | - Stephanie Migchelsen
- Clinical Research Department, London School of Hygiene & Tropical Medicine, London, WC1E 7HT, UK
| | - Andreas Müller
- Centre for Eye Research Australia, Level 7/32 Gisborne St, East Melbourne, VIC, 3002, Australia
| | - Frank Sandi
- Department of Ophthalmology, Kilimanjaro Christian Medical Centre, Moshi, Tanzania.,The University of Dodoma, Dodoma, Tanzania
| | - Oliver Sokana
- Eyecare Department, Ministry of Health, Honiara, Solomon Islands
| | - Raebwebwe Taoaba
- Eye Department, Ministry of Health and Medical Services, South Tarawa, Kiribati
| | - Rabebe Tekeraoi
- Eye Department, Ministry of Health and Medical Services, South Tarawa, Kiribati
| | - Diana L Martin
- Division of Parasitic Diseases and Malaria, Centers for Disease Control and Prevention, 1600 Clifton Road, Atlanta, GA, 30333, USA
| | - Michael T White
- Malaria: Parasites & Hosts, Department of Parasites and Insect Vectors, Institut Pasteur, 25-28 Rue du Dr Roux, 75015, Paris, France
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Hollingsworth TD, Medley GF. Learning from multi-model comparisons: Collaboration leads to insights, but limitations remain. Epidemics 2018; 18:1-3. [PMID: 28279450 DOI: 10.1016/j.epidem.2017.02.014] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/04/2023] Open
Affiliation(s)
- T D Hollingsworth
- Zeeman Institute, University of Warwick, Coventry CV4 7AL, United Kingdom
| | - G F Medley
- Department of Global Health and Development, London School of Hygiene and Tropical Medicine, London WC1E 7HT, United Kingdom
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12
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Hollingsworth TD. Counting Down the 2020 Goals for 9 Neglected Tropical Diseases: What Have We Learned From Quantitative Analysis and Transmission Modeling? Clin Infect Dis 2018; 66:S237-S244. [PMID: 29860293 PMCID: PMC5982793 DOI: 10.1093/cid/ciy284] [Citation(s) in RCA: 21] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/19/2022] Open
Abstract
The control of neglected tropical diseases (NTDs) has received huge investment in recent years, leading to large reductions in morbidity. In 2012, the World Health Organization set ambitious targets for eliminating many of these diseases as a public health problem by 2020, an aspiration that was supported by donations of treatments, intervention materials, and funding committed by a broad partnership of stakeholders in the London Declaration on NTDs. Alongside these efforts, there has been an increasing role for quantitative analysis and modeling to support the achievement of these goals through evaluation of the likely impact of interventions, the factors that could undermine these achievements, and the role of new diagnostics and treatments in reducing transmission. In this special issue, we aim to summarize those insights in an accessible way. This article acts as an introduction to the special issue, outlining key concepts in NTDs and insights from modeling as we approach 2020.
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Affiliation(s)
- T Déirdre Hollingsworth
- Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, Nuffideld Department of Medicine, University of Oxford, United Kingdom
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13
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Lee BY, Bartsch SM, Skrip L, Hertenstein DL, Avelis CM, Ndeffo-Mbah M, Tilchin C, Dumonteil EO, Galvani A. Are the London Declaration's 2020 goals sufficient to control Chagas disease?: Modeling scenarios for the Yucatan Peninsula. PLoS Negl Trop Dis 2018; 12:e0006337. [PMID: 29554086 PMCID: PMC5875875 DOI: 10.1371/journal.pntd.0006337] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/29/2017] [Revised: 03/29/2018] [Accepted: 02/22/2018] [Indexed: 01/03/2023] Open
Abstract
BACKGROUND The 2020 Sustainable Development goals call for 100% certified interruption or control of the three main forms of Chagas disease transmission in Latin America. However, how much will achieving these goals to varying degrees control Chagas disease; what is the potential impact of missing these goals and if they are achieved, what may be left? METHODS We developed a compartmental simulation model that represents the triatomine, human host, and non-human host populations and vector-borne, congenital, and transfusional T. cruzi transmission between them in the domestic and peridomestic settings to evaluate the impact of limiting transmission in a 2,000 person virtual village in Yucatan, Mexico. RESULTS Interruption of domestic vectorial transmission had the largest impact on T. cruzi transmission and prevalence in all populations. Most of the gains were achieved within the first few years. Controlling vectorial transmission resulted in a 46.1-83.0% relative reduction in the number of new acute Chagas cases for a 50-100% interruption in domestic vector-host contact. Only controlling congenital transmission led to a 2.4-8.1% (30-100% interruption) relative reduction in the total number of new acute cases and reducing only transfusional transmission led to a 0.1-0.3% (30-100% reduction). Stopping all three forms of transmission resulted in 0.5 total transmission events over five years (compared to 5.0 with no interruption); interrupting all forms by 30% resulted in 3.4 events over five years per 2,000 persons. CONCLUSIONS While reducing domestic vectorial, congenital, and transfusional transmission can successfully reduce transmission to humans (up to 82% in one year), achieving the 2020 goals would still result in 0.5 new acute cases per 2,000 over five years. Even if the goals are missed, major gains can be achieved within the first few years. Interrupting transmission should be combined with other efforts such as a vaccine or improved access to care, especially for the population of already infected individuals.
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Affiliation(s)
- Bruce Y. Lee
- Public Health Computational and Operations Research, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, United States of America
- Global Obesity Prevention Center, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, United States of America
- * E-mail:
| | - Sarah M. Bartsch
- Public Health Computational and Operations Research, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, United States of America
- Global Obesity Prevention Center, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, United States of America
| | - Laura Skrip
- Center for Infectious Disease Modeling and Analysis, Yale School of Public Health, New Haven, CT, United States of America
| | - Daniel L. Hertenstein
- Public Health Computational and Operations Research, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, United States of America
- Global Obesity Prevention Center, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, United States of America
| | - Cameron M. Avelis
- Public Health Computational and Operations Research, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, United States of America
- Global Obesity Prevention Center, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, United States of America
| | - Martial Ndeffo-Mbah
- Center for Infectious Disease Modeling and Analysis, Yale School of Public Health, New Haven, CT, United States of America
| | - Carla Tilchin
- Public Health Computational and Operations Research, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, United States of America
- Global Obesity Prevention Center, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, United States of America
| | - Eric O. Dumonteil
- Department of Tropical Medicine, School of Public Health and Tropical Medicine, Tulane University, New Orleans, LA, United States of America
| | - Alison Galvani
- Center for Infectious Disease Modeling and Analysis, Yale School of Public Health, New Haven, CT, United States of America
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