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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] [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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Cheng Y, Tjaden NB, Jaeschke A, Thomas SM, Beierkuhnlein C. Deriving risk maps from epidemiological models of vector borne diseases: State-of-the-art and suggestions for best practice. Epidemics 2020; 33:100411. [PMID: 33130413 DOI: 10.1016/j.epidem.2020.100411] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/18/2020] [Revised: 09/03/2020] [Accepted: 10/01/2020] [Indexed: 11/19/2022] Open
Abstract
Epidemiological models (EMs) are widely used to predict the temporal outbreak risk of vector-borne diseases (VBDs). EMs typically use the basic reproduction number (R0), a threshold quantity, to indicate risk. To provide an overall view of the risk, these model outputs can be transformed into spatial risk maps, using various aggregation methods (e.g. average R0 over time, cumulative number of days with R0 > 1). However, there is no standardized methodology available for this. Depending on the specific aggregation methods used, the yielded spatial risk maps may have considerably different interpretations. Additionally, the method used to visualize the aggregated data also affects the perceived spatial patterns. In this review, we compare commonly used aggregation and visualization methods and discuss the respective interpretation of risk maps. Research publications using epidemiological modelling methods were drawn from Web of Science. Only publications containing maps of R0 transformed from EMs were considered for the analysis. An example EM was applied to illustrate how aggregation and visualization methods affect the final presentations of risk maps. Risk maps can be generated to show duration, intensity and spatio-temporal dynamics of potential outbreak risk of VBDs. We show that 1) different temporal aggregation methods lead to different interpretations; 2) similar spatial patterns do not necessarily bear the same meaning; 3) visualization methods considerably affect how results are perceived, and thus should be applied with caution. We recommend mapping both intensity and duration of the VBD outbreak risk, using small time-steps to show spatio-temporal dynamics when possible.
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Affiliation(s)
- Yanchao Cheng
- Department of Biogeography, University of Bayreuth, Universitätsstr. 30, 95447, Bayreuth, Germany.
| | - Nils Benjamin Tjaden
- Department of Biogeography, University of Bayreuth, Universitätsstr. 30, 95447, Bayreuth, Germany
| | - Anja Jaeschke
- Department of Biogeography, University of Bayreuth, Universitätsstr. 30, 95447, Bayreuth, Germany
| | - Stephanie Margarete Thomas
- Department of Biogeography, University of Bayreuth, Universitätsstr. 30, 95447, Bayreuth, Germany; BayCEER, Bayreuth Center for Ecology and Environmental Research, Bayreuth, Germany
| | - Carl Beierkuhnlein
- Department of Biogeography, University of Bayreuth, Universitätsstr. 30, 95447, Bayreuth, Germany; BayCEER, Bayreuth Center for Ecology and Environmental Research, Bayreuth, Germany
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Aguilar-Vega C, Bosch J, Fernández-Carrión E, Lucientes J, Sánchez-Vizcaíno JM. Identifying Spanish Areas at More Risk of Monthly BTV Transmission with a Basic Reproduction Number Approach. Viruses 2020; 12:E1158. [PMID: 33066209 PMCID: PMC7602074 DOI: 10.3390/v12101158] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/10/2020] [Revised: 10/08/2020] [Accepted: 10/12/2020] [Indexed: 01/24/2023] Open
Abstract
Bluetongue virus (BTV) causes a disease that is endemic in Spain and its two major biological vector species, C. imicola and the Obsoletus complex species, differ greatly in their ecology and distribution. Understanding the seasonality of BTV transmission in risk areas is key to improving surveillance and control programs, as well as to better understand the pathogen transmission networks between wildlife and livestock. Here, monthly risk transmission maps were generated using risk categories based on well-known BTV R0 equations and predicted abundances of the two most relevant vectors in Spain. Previously, Culicoides spp. predicted abundances in mainland Spain and the Balearic Islands were obtained using remote sensing data and random forest machine learning algorithm. Risk transmission maps were externally assessed with the estimated date of infection of BTV-1 and BTV-4 historical outbreaks. Our results highlight the differences in risk transmission during April-October, June-August being the period with higher R0 values. Likewise, a natural barrier has been identified between northern and central-southern areas at risk that may hamper BTV spread between them. Our results can be relevant to implement risk-based interventions for the prevention, control and surveillance of BTV and other diseases shared between livestock and wildlife host populations.
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Affiliation(s)
- Cecilia Aguilar-Vega
- VISAVET Health Surveillance Centre, Animal Health Department, Faculty of Veterinary Medicine, Complutense University of Madrid, 28040 Madrid, Spain; (J.B.); (E.F.-C.); (J.M.S.-V.)
| | - Jaime Bosch
- VISAVET Health Surveillance Centre, Animal Health Department, Faculty of Veterinary Medicine, Complutense University of Madrid, 28040 Madrid, Spain; (J.B.); (E.F.-C.); (J.M.S.-V.)
| | - Eduardo Fernández-Carrión
- VISAVET Health Surveillance Centre, Animal Health Department, Faculty of Veterinary Medicine, Complutense University of Madrid, 28040 Madrid, Spain; (J.B.); (E.F.-C.); (J.M.S.-V.)
| | - Javier Lucientes
- Department of Animal Pathology (Animal Health), AgriFood Institute of Aragón IA2, Faculty of Veterinary Medicine, University of Zaragoza, 50013 Zaragoza, Spain;
| | - José Manuel Sánchez-Vizcaíno
- VISAVET Health Surveillance Centre, Animal Health Department, Faculty of Veterinary Medicine, Complutense University of Madrid, 28040 Madrid, Spain; (J.B.); (E.F.-C.); (J.M.S.-V.)
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Kain MP, Bolker BM. Predicting West Nile virus transmission in North American bird communities using phylogenetic mixed effects models and eBird citizen science data. Parasit Vectors 2019; 12:395. [PMID: 31395085 PMCID: PMC6686473 DOI: 10.1186/s13071-019-3656-8] [Citation(s) in RCA: 17] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/28/2018] [Accepted: 08/03/2019] [Indexed: 12/29/2022] Open
Abstract
BACKGROUND West Nile virus (WNV) is a mosquito-transmitted disease of birds that has caused bird population declines and can spill over into human populations. Previous research has identified bird species that infect a large fraction of the total pool of infected mosquitoes and correlate with human infection risk; however, these analyses cover small spatial regions and cannot be used to predict transmission in bird communities in which these species are rare or absent. Here we present a mechanistic model for WNV transmission that predicts WNV spread (R0) in any bird community in North America by scaling up from the physiological responses of individual birds to transmission at the level of the community. We predict unmeasured bird species' responses to infection using phylogenetic imputation, based on these species' phylogenetic relationships with bird species with measured responses. RESULTS We focused our analysis on Texas, USA, because it is among the states with the highest total incidence of WNV in humans and is well sampled by birders in the eBird database. Spatio-temporal patterns: WNV transmission is primarily driven by temperature variation across time and space, and secondarily by bird community composition. In Texas, we predicted WNV R0 to be highest in the spring and fall when temperatures maximize the product of mosquito transmission and survival probabilities. In the most favorable months for WNV transmission (April, May, September and October), we predicted R0 to be highest in the "Piney Woods" and "Oak Woods & Prairies" ecoregions of Texas, and lowest in the "High Plains" and "South Texas Brush County" ecoregions. Dilution effect: More abundant bird species are more competent hosts for WNV, and predicted WNV R0 decreases with increasing species richness. Keystone species: We predicted that northern cardinals (Cardinalis cardinalis) are the most important hosts for amplifying WNV and that mourning doves (Zenaida macroura) are the most important sinks of infection across Texas. CONCLUSIONS Despite some data limitations, we demonstrate the power of phylogenetic imputation in predicting disease transmission in heterogeneous host communities. Our mechanistic modeling framework shows promise both for assisting future analyses on transmission and spillover in heterogeneous multispecies pathogen systems and for improving model transparency by clarifying assumptions, choices and shortcomings in complex ecological analyses.
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Affiliation(s)
- Morgan P. Kain
- Department of Biology, McMaster University, 1280 Main Street West, Hamilton, ON L8S 4K1 Canada
| | - Benjamin M. Bolker
- Department of Biology, McMaster University, 1280 Main Street West, Hamilton, ON L8S 4K1 Canada
- Department of Mathematics and Statistics, McMaster University, 1280 Main Street West, Hamilton, ON L8S 4K1 Canada
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Culex torrentium: A Potent Vector for the Transmission of West Nile Virus in Central Europe. Viruses 2019; 11:v11060492. [PMID: 31146418 PMCID: PMC6630772 DOI: 10.3390/v11060492] [Citation(s) in RCA: 22] [Impact Index Per Article: 4.4] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/25/2019] [Revised: 05/23/2019] [Accepted: 05/24/2019] [Indexed: 12/17/2022] Open
Abstract
The continuous circulation of West Nile virus (WNV) in Central, South and East Europe and its recent detection in several dead birds and two horses in Germany highlights the need for information on WNV vector competence of mosquitoes from Central Europe. Therefore, three common Culex species (Culex pipiens biotype pipiens, Culex pipiens biotype molestus and Culex torrentium) from Germany were orally infected with WNV and kept at 18 °C, 21 °C, 24 °C or 27 °C for 14 or 21 days post infection (dpi). Thereafter viable WNV was present in the saliva in all tested taxa, but only at incubation temperatures of 24 °C or 27 °C and predominantly at the extended incubation period of 21 dpi. Highest transmission efficiency rates of 17 % (24 °C) and 24% (27 °C) were found for Cx. torrentium. Culex p. pipiens and Cx. p. molestus showed low transmission efficiencies with a maximum of only 3%. Consequently, temperatures above 21 °C support transmission of WNV, which matches the predominant distribution of human WNV cases around the Mediterranean Sea and in South-East Europe. Culex torrentium has been identified as a potent vector for WNV in Central and Northern Europe, which highlights the need for surveillance of mosquito-borne viruses north of the Alps.
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More S, Bøtner A, Butterworth A, Calistri P, Depner K, Edwards S, Garin‐Bastuji B, Good M, Gortázar Schmidt C, Michel V, Miranda MA, Nielsen SS, Raj M, Sihvonen L, Spoolder H, Stegeman JA, Thulke H, Velarde A, Willeberg P, Winckler C, Baldinelli F, Broglia A, Dhollander S, Beltrán‐Beck B, Kohnle L, Morgado J, Bicout D. Assessment of listing and categorisation of animal diseases within the framework of the Animal Health Law (Regulation (EU) No 2016/429): West Nile fever. EFSA J 2017; 15:e04955. [PMID: 32625621 PMCID: PMC7009844 DOI: 10.2903/j.efsa.2017.4955] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/11/2022] Open
Abstract
West Nile fever (WNF) has been assessed according to the criteria of the Animal Health Law (AHL), in particular criteria of Article 7 on disease profile and impacts, Article 5 on the eligibility of WNF to be listed, Article 9 for the categorisation of WNF according to disease prevention and control rules as in Annex IV and Article 8 on the list of animal species related to WNF. The assessment has been performed following a methodology composed of information collection and compilation, expert judgement on each criterion at individual and, if no consensus was reached before, also at collective level. The output is composed of the categorical answer, and for the questions where no consensus was reached, the different supporting views are reported. Details on the methodology used for this assessment are explained in a separate opinion. According to the assessment performed, WNF can be considered eligible to be listed for Union intervention as laid down in Article 5(3) of the AHL. The disease would comply with the criteria as in Sections 2 and 5 of Annex IV of the AHL, for the application of the disease prevention and control rules referred to in points (b) and (e) of Article 9(1). The animal species to be listed for WNF according to Article 8(3) criteria are several orders of birds and mammals as susceptible species and several families of birds as reservoir. Different mosquito species can serve as vectors.
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Faverjon C, Andersson MG, Decors A, Tapprest J, Tritz P, Sandoz A, Kutasi O, Sala C, Leblond A. Evaluation of a Multivariate Syndromic Surveillance System for West Nile Virus. Vector Borne Zoonotic Dis 2016; 16:382-90. [PMID: 27159212 DOI: 10.1089/vbz.2015.1883] [Citation(s) in RCA: 14] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2022] Open
Abstract
BACKGROUND Various methods are currently used for the early detection of West Nile virus (WNV) but their outputs are not quantitative and/or do not take into account all available information. Our study aimed to test a multivariate syndromic surveillance system to evaluate if the sensitivity and the specificity of detection of WNV could be improved. METHODS Weekly time series data on nervous syndromes in horses and mortality in both horses and wild birds were used. Baselines were fitted to the three time series and used to simulate 100 years of surveillance data. WNV outbreaks were simulated and inserted into the baselines based on historical data and expert opinion. Univariate and multivariate syndromic surveillance systems were tested to gauge how well they detected the outbreaks; detection was based on an empirical Bayesian approach. The systems' performances were compared using measures of sensitivity, specificity, and area under receiver operating characteristic curve (AUC). RESULTS When data sources were considered separately (i.e., univariate systems), the best detection performance was obtained using the data set of nervous symptoms in horses compared to those of bird and horse mortality (AUCs equal to 0.80, 0.75, and 0.50, respectively). A multivariate outbreak detection system that used nervous symptoms in horses and bird mortality generated the best performance (AUC = 0.87). CONCLUSIONS The proposed approach is suitable for performing multivariate syndromic surveillance of WNV outbreaks. This is particularly relevant, given that a multivariate surveillance system performed better than a univariate approach. Such a surveillance system could be especially useful in serving as an alert for the possibility of human viral infections. This approach can be also used for other diseases for which multiple sources of evidence are available.
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Affiliation(s)
- Céline Faverjon
- 1 INRA UR0346 Animal Epidemiology , VetagroSup, Marcy l'Etoile, France
| | - M Gunnar Andersson
- 2 Department of Chemistry, Environment and Feed Hygiene, The National Veterinary Institute , Uppsala, Sweden
| | - Anouk Decors
- 3 Office National de la Chasse et de la Faune Sauvage, Direction des Études et de la Recherche , Auffargis, France
| | - Jackie Tapprest
- 4 ANSES Dozulé Laboratory for Equine Diseases , Dozulé, France
| | - Pierre Tritz
- 5 Clinique Vétérinaire, Collège Syndrome Nerveux du RESPE et Commission Maladies Infectieuses de l'AVEF , Faulquemont, Caen, France
| | - Alain Sandoz
- 6 Centre de Recherche Pour la Conservation des Zones Humides Méditerranéennes , Fondation Tour du Valat, Arles, France .,7 UFR Sciences, Aix-Marseille University , Marseille, France
| | - Orsolya Kutasi
- 8 Hungarian Academy of Sciences-Szent Istvan University (MTA-SZIE) Large Animal Clinical Research Group , Ullo, Dóra major, Hungary
| | - Carole Sala
- 9 ANSES-Lyon , Epidemiology Unit, Lyon, France
| | - Agnès Leblond
- 10 INRA UR0346 Animal Epidemiology et Département Hippique , VetAgroSup, Marcy L'Etoile, France .,11 Réseau d'Epidémio-Surveillance en Pathologie Equine (RESPE) , Caen, France
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