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de Wit MM, Dimas Martins A, Delecroix C, Heesterbeek H, ten Bosch QA. Mechanistic models for West Nile virus transmission: a systematic review of features, aims and parametrization. Proc Biol Sci 2024; 291:20232432. [PMID: 38471554 PMCID: PMC10932716 DOI: 10.1098/rspb.2023.2432] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/30/2023] [Accepted: 02/14/2024] [Indexed: 03/14/2024] Open
Abstract
Mathematical models within the Ross-Macdonald framework increasingly play a role in our understanding of vector-borne disease dynamics and as tools for assessing scenarios to respond to emerging threats. These threats are typically characterized by a high degree of heterogeneity, introducing a range of possible complexities in models and challenges to maintain the link with empirical evidence. We systematically identified and analysed a total of 77 published papers presenting compartmental West Nile virus (WNV) models that use parameter values derived from empirical studies. Using a set of 15 criteria, we measured the dissimilarity compared with the Ross-Macdonald framework. We also retrieved the purpose and type of models and traced the empirical sources of their parameters. Our review highlights the increasing refinements in WNV models. Models for prediction included the highest number of refinements. We found uneven distributions of refinements and of evidence for parameter values. We identified several challenges in parametrizing such increasingly complex models. For parameters common to most models, we also synthesize the empirical evidence for their values and ranges. The study highlights the potential to improve the quality of WNV models and their applicability for policy by establishing closer collaboration between mathematical modelling and empirical work.
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Affiliation(s)
- Mariken M. de Wit
- Quantitative Veterinary Epidemiology, Wageningen University and Research, Wageningen, The Netherlands
| | - Afonso Dimas Martins
- Department of Population Health Sciences, Faculty of Veterinary Medicine, University of Utrecht, Utrecht, The Netherlands
| | - Clara Delecroix
- Quantitative Veterinary Epidemiology, Wageningen University and Research, Wageningen, The Netherlands
- Department of Environmental Sciences, Wageningen University and Research, Wageningen, The Netherlands
| | - Hans Heesterbeek
- Department of Population Health Sciences, Faculty of Veterinary Medicine, University of Utrecht, Utrecht, The Netherlands
| | - Quirine A. ten Bosch
- Quantitative Veterinary Epidemiology, Wageningen University and Research, Wageningen, The Netherlands
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Gubbins S. Quantifying the relationship between within-host dynamics and transmission for viral diseases of livestock. J R Soc Interface 2024; 21:20230445. [PMID: 38379412 PMCID: PMC10879856 DOI: 10.1098/rsif.2023.0445] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/02/2023] [Accepted: 01/18/2024] [Indexed: 02/22/2024] Open
Abstract
Understanding the population dynamics of an infectious disease requires linking within-host dynamics and between-host transmission in a quantitative manner, but this is seldom done in practice. Here a simple phenomenological model for viral dynamics within a host is linked to between-host transmission by assuming that the probability of transmission is related to log viral titre. Data from transmission experiments for two viral diseases of livestock, foot-and-mouth disease virus in cattle and swine influenza virus in pigs, are used to parametrize the model and, importantly, test the underlying assumptions. The model allows the relationship between within-host parameters and transmission to be determined explicitly through their influence on the reproduction number and generation time. Furthermore, these critical within-host parameters (time and level of peak titre, viral growth and clearance rates) can be computed from more complex within-host models, raising the possibility of assessing the impact of within-host processes on between-host transmission in a more detailed quantitative manner.
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Affiliation(s)
- Simon Gubbins
- The Pirbright Institute, Ash Road, Pirbright, Surrey GU24 0NF, UK
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Heitzman-Breen N, Liyanage YR, Duggal N, Tuncer N, Ciupe SM. The effect of model structure and data availability on Usutu virus dynamics at three biological scales. R Soc Open Sci 2024; 11:231146. [PMID: 38328567 PMCID: PMC10846940 DOI: 10.1098/rsos.231146] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Figures] [Subscribe] [Scholar Register] [Received: 08/04/2023] [Accepted: 01/11/2024] [Indexed: 02/09/2024]
Abstract
Understanding the epidemiology of emerging pathogens, such as Usutu virus (USUV) infections, requires systems investigation at each scale involved in the host-virus transmission cycle, from individual bird infections, to bird-to-vector transmissions, and to USUV incidence in bird and vector populations. For new pathogens field data are sparse, and predictions can be aided by the use of laboratory-type inoculation and transmission experiments combined with dynamical mathematical modelling. In this study, we investigated the dynamics of two strains of USUV by constructing mathematical models for the within-host scale, bird-to-vector transmission scale and vector-borne epidemiological scale. We used individual within-host infectious virus data and per cent mosquito infection data to predict USUV incidence in birds and mosquitoes. We addressed the dependence of predictions on model structure, data uncertainty and experimental design. We found that uncertainty in predictions at one scale change predicted results at another scale. We proposed in silico experiments that showed that sampling every 12 hours ensures practical identifiability of the within-host scale model. At the same time, we showed that practical identifiability of the transmission scale functions can only be improved under unrealistically high sampling regimes. Instead, we proposed optimal experimental designs and suggested the types of experiments that can ensure identifiability at the transmission scale and, hence, induce robustness in predictions at the epidemiological scale.
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Affiliation(s)
- Nora Heitzman-Breen
- Department of Mathematics, Virginia Polytechnic Institute and State University, Blacksburg, VA, USA
| | - Yuganthi R. Liyanage
- Department of Mathematical Sciences, Florida Atlantic University, Boca Raton, FL, USA
| | - Nisha Duggal
- Department of Biomedical Sciences and Pathobiology, VA-MD College of Veterinary Medicine, Virginia Tech, Blacksburg, VA, USA
| | - Necibe Tuncer
- Department of Mathematical Sciences, Florida Atlantic University, Boca Raton, FL, USA
| | - Stanca M. Ciupe
- Department of Mathematics, Virginia Polytechnic Institute and State University, Blacksburg, VA, USA
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Bron GM, Wichgers Schreur PJ, de Jong MCM, van Keulen L, Vloet RPM, Koenraadt CJM, Kortekaas J, ten Bosch QA. Quantifying Rift Valley fever virus transmission efficiency in a lamb-mosquito-lamb model. Front Cell Infect Microbiol 2023; 13:1206089. [PMID: 38170150 PMCID: PMC10759236 DOI: 10.3389/fcimb.2023.1206089] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/14/2023] [Accepted: 10/30/2023] [Indexed: 01/05/2024] Open
Abstract
Rift Valley fever virus (RVFV) is a (re)emerging mosquito-borne pathogen impacting human and animal health. How RVFV spreads through a population depends on population-level and individual-level interactions between vector, host and pathogen. Here, we estimated the probability for RVFV to transmit to naive animals by experimentally exposing lambs to a bite of an infectious mosquito, and assessed if and how RVFV infection subsequently developed in the exposed animal. Aedes aegypti mosquitoes, previously infected via feeding on a viremic lamb, were used to expose naive lambs to the virus. Aedes aegypti colony mosquitoes were used as they are easy to maintain and readily feed in captivity. Other mosquito spp. could be examined with similar methodology. Lambs were exposed to either 1-3 (low exposure) or 7-9 (high exposure) infectious mosquitoes. All lambs in the high exposure group became viremic and showed characteristic signs of Rift Valley fever within 2-4 days post exposure. In contrast, 3 out of 12 lambs in the low exposure group developed viremia and disease, with similar peak-levels of viremia as the high exposure group but with some heterogeneity in the onset of viremia. These results suggest that the likelihood for successful infection of a ruminant host is affected by the number of infectious mosquitoes biting, but also highlights that a single bite of an infectious mosquito can result in disease. The per bite mosquito-to-host transmission efficiency was estimated at 28% (95% confidence interval: 15 - 47%). We subsequently combined this transmission efficiency with estimates for life traits of Aedes aegypti or related mosquitoes into a Ross-McDonald mathematical model to illustrate scenarios under which major RVFV outbreaks could occur in naïve populations (i.e., R0 >1). The model revealed that relatively high vector-to-host ratios as well as mosquitoes feeding preferably on competent hosts are required for R0 to exceed 1. Altogether, this study highlights the importance of experiments that mimic natural exposure to RVFV. The experiments facilitate a better understanding of the natural progression of disease and a direct way to obtain epidemiological parameters for mathematical models.
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Affiliation(s)
- Gebbiena M. Bron
- Quantitative Veterinary Epidemiology, Wageningen University and Research, Wageningen, Netherlands
| | | | - Mart C. M. de Jong
- Quantitative Veterinary Epidemiology, Wageningen University and Research, Wageningen, Netherlands
| | - Lucien van Keulen
- Wageningen Bioveterinary Research, Wageningen University and Research, Lelystad, Netherlands
| | - Rianka P. M. Vloet
- Wageningen Bioveterinary Research, Wageningen University and Research, Lelystad, Netherlands
| | | | - Jeroen Kortekaas
- Wageningen Bioveterinary Research, Wageningen University and Research, Lelystad, Netherlands
| | - Quirine A. ten Bosch
- Quantitative Veterinary Epidemiology, Wageningen University and Research, Wageningen, Netherlands
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Colella JP, Cobos ME, Salinas I, Cook JA. Advancing the central role of non-model biorepositories in predictive modeling of emerging pathogens. PLoS Pathog 2023; 19:e1011410. [PMID: 37319170 DOI: 10.1371/journal.ppat.1011410] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/17/2023] Open
Affiliation(s)
- Jocelyn P Colella
- University of Kansas Biodiversity Institute and Department of Ecology & Evolutionary Biology, Lawrence, Kansas, United States of America
| | - Marlon E Cobos
- University of Kansas Biodiversity Institute and Department of Ecology & Evolutionary Biology, Lawrence, Kansas, United States of America
| | - Irene Salinas
- University of New Mexico, Department of Biology, Albuquerque, New Mexico, United States of America
- Center for Evolutionary and Theoretical Immunology, University of New Mexico, Albuquerque, New Mexico, United States of America
| | - Joseph A Cook
- University of New Mexico, Department of Biology, Albuquerque, New Mexico, United States of America
- Museum of Southwestern Biology, University of New Mexico, Albuquerque, New Mexico, United States of America
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Cecilia H, Drouin A, Métras R, Balenghien T, Durand B, Chevalier V, Ezanno P. Mechanistic models of Rift Valley fever virus transmission: A systematic review. PLoS Negl Trop Dis 2022; 16:e0010339. [PMID: 36399500 DOI: 10.1371/journal.pntd.0010339] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/18/2022] [Revised: 12/02/2022] [Accepted: 10/31/2022] [Indexed: 11/19/2022] Open
Abstract
Rift Valley fever (RVF) is a zoonotic arbovirosis which has been reported across Africa including the northernmost edge, South West Indian Ocean islands, and the Arabian Peninsula. The virus is responsible for high abortion rates and mortality in young ruminants, with economic impacts in affected countries. To date, RVF epidemiological mechanisms are not fully understood, due to the multiplicity of implicated vertebrate hosts, vectors, and ecosystems. In this context, mathematical models are useful tools to develop our understanding of complex systems, and mechanistic models are particularly suited to data-scarce settings. Here, we performed a systematic review of mechanistic models studying RVF, to explore their diversity and their contribution to the understanding of this disease epidemiology. Researching Pubmed and Scopus databases (October 2021), we eventually selected 48 papers, presenting overall 49 different models with numerical application to RVF. We categorized models as theoretical, applied, or grey, depending on whether they represented a specific geographical context or not, and whether they relied on an extensive use of data. We discussed their contributions to the understanding of RVF epidemiology, and highlighted that theoretical and applied models are used differently yet meet common objectives. Through the examination of model features, we identified research questions left unexplored across scales, such as the role of animal mobility, as well as the relative contributions of host and vector species to transmission. Importantly, we noted a substantial lack of justification when choosing a functional form for the force of infection. Overall, we showed a great diversity in RVF models, leading to important progress in our comprehension of epidemiological mechanisms. To go further, data gaps must be filled, and modelers need to improve their code accessibility.
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Gerken KN, Ndenga BA, Owuor KO, Winter CA, Seetah K, LaBeaud AD. Leveraging livestock movements to urban slaughterhouses for wide-spread Rift Valley fever virus surveillance in Western Kenya. One Health 2022; 15:100457. [PMID: 36532672 PMCID: PMC9754961 DOI: 10.1016/j.onehlt.2022.100457] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/12/2022] [Revised: 11/11/2022] [Accepted: 11/12/2022] [Indexed: 11/16/2022] Open
Abstract
Rift Valley fever virus (RVFV) is an economically devastating, zoonotic arbovirus endemic across Africa with potential to cause severe disease in livestock and humans. Viral spread is primarily driven by movement of domestic ruminants and there is a high potential for transboundary spread. Despite influx of livestock to urban areas in response to the high demand for meat and animal products, RVFV has not been detected in any urban center. The objectives of this study were to determine the feasibility of assessing risk of RVFV introduction to urban Kisumu, Kenya, by testing slaughtered livestock for RVFV exposure and mapping livestock origins. Blood was collected from cattle, sheep, and goats directly after slaughter and tested for anti-RVFV IgG antibodies. Slaughterhouse businessmen responded to a questionnaire on their individual animals' origin, marketplace, and transport means. Thereafter, we mapped livestock flow from origin to slaughterhouse using participatory methods in focus group discussions with stakeholders. Qualitative data on route choice and deviations were spatially integrated into the map. A total of 304 blood samples were collected from slaughtered livestock in October and November 2021. Most (99%) of animals were purchased from 28 different markets across eight counties in Western Kenya. The overall RVFV seroprevalence was 9% (19% cattle, 3% in sheep, and 7% in goats). Migori County bordering Tanzania had the highest county-level seroprevalence (34%) and 80% of all seropositive cattle were purchased at the Suba Kuria market in Migori County. Road quality and animal health influenced stakeholders' decisions for choice of transport means. Overall, this proof-of-concept study offers a sampling framework for RVFV that can be locally implemented and rapidly deployed in response to regional risk. This system can be used in conjunction with participatory maps to improve active livestock surveillance and monitoring of RVFV in Western Kenya, and these methods could be extrapolated to other urban centers or livestock diseases.
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Affiliation(s)
- Keli Nicole Gerken
- Department of Pediatrics, Division of Infectious Disease, Stanford University School of Medicine, Stanford, CA, USA,Corresponding author at: LaBeaud Research Lab, Stanford University School of Medicine, Biomedical Innovation BMI Building, 2 Floor, Room 2400, 1291 Welch Road, Stanford, CA -, USA.
| | | | - Kevin Omondi Owuor
- Centre for Global Health Research, Kenya Medical Research Institute, Kisumu, Kenya
| | | | - Krish Seetah
- Department of Anthropology, Stanford University, USA
| | - Angelle Desiree LaBeaud
- Department of Pediatrics, Division of Infectious Disease, Stanford University School of Medicine, Stanford, CA, USA
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