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Predicting Spatial Patterns of Sindbis Virus (SINV) Infection Risk in Finland Using Vector, Host and Environmental Data
Pogosta disease is a mosquito-borne infection, caused by Sindbis virus (SINV), which causes epidemics of febrile rash and arthritis in Northern Europe and South Africa. Resident grouse and migratory birds play a significant role as amplifying hosts and various mosquito species, including Aedes ciner...
Autores principales: | , , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8296873/ https://www.ncbi.nlm.nih.gov/pubmed/34281003 http://dx.doi.org/10.3390/ijerph18137064 |
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author | Uusitalo, Ruut Siljander, Mika Culverwell, C. Lorna Hendrickx, Guy Lindén, Andreas Dub, Timothée Aalto, Juha Sane, Jussi Marsboom, Cedric Suvanto, Maija T. Vajda, Andrea Gregow, Hilppa Korhonen, Essi M. Huhtamo, Eili Pellikka, Petri Vapalahti, Olli |
author_facet | Uusitalo, Ruut Siljander, Mika Culverwell, C. Lorna Hendrickx, Guy Lindén, Andreas Dub, Timothée Aalto, Juha Sane, Jussi Marsboom, Cedric Suvanto, Maija T. Vajda, Andrea Gregow, Hilppa Korhonen, Essi M. Huhtamo, Eili Pellikka, Petri Vapalahti, Olli |
author_sort | Uusitalo, Ruut |
collection | PubMed |
description | Pogosta disease is a mosquito-borne infection, caused by Sindbis virus (SINV), which causes epidemics of febrile rash and arthritis in Northern Europe and South Africa. Resident grouse and migratory birds play a significant role as amplifying hosts and various mosquito species, including Aedes cinereus, Culex pipiens, Cx. torrentium and Culiseta morsitans are documented vectors. As specific treatments are not available for SINV infections, and joint symptoms may persist, the public health burden is considerable in endemic areas. To predict the environmental suitability for SINV infections in Finland, we applied a suite of geospatial and statistical modeling techniques to disease occurrence data. Using an ensemble approach, we first produced environmental suitability maps for potential SINV vectors in Finland. These suitability maps were then combined with grouse densities and environmental data to identify the influential determinants for SINV infections and to predict the risk of Pogosta disease in Finnish municipalities. Our predictions suggest that both the environmental suitability for vectors and the high risk of Pogosta disease are focused in geographically restricted areas. This provides evidence that the presence of both SINV vector species and grouse densities can predict the occurrence of the disease. The results support material for public-health officials when determining area-specific recommendations and deliver information to health care personnel to raise awareness of the disease among physicians. |
format | Online Article Text |
id | pubmed-8296873 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-82968732021-07-23 Predicting Spatial Patterns of Sindbis Virus (SINV) Infection Risk in Finland Using Vector, Host and Environmental Data Uusitalo, Ruut Siljander, Mika Culverwell, C. Lorna Hendrickx, Guy Lindén, Andreas Dub, Timothée Aalto, Juha Sane, Jussi Marsboom, Cedric Suvanto, Maija T. Vajda, Andrea Gregow, Hilppa Korhonen, Essi M. Huhtamo, Eili Pellikka, Petri Vapalahti, Olli Int J Environ Res Public Health Article Pogosta disease is a mosquito-borne infection, caused by Sindbis virus (SINV), which causes epidemics of febrile rash and arthritis in Northern Europe and South Africa. Resident grouse and migratory birds play a significant role as amplifying hosts and various mosquito species, including Aedes cinereus, Culex pipiens, Cx. torrentium and Culiseta morsitans are documented vectors. As specific treatments are not available for SINV infections, and joint symptoms may persist, the public health burden is considerable in endemic areas. To predict the environmental suitability for SINV infections in Finland, we applied a suite of geospatial and statistical modeling techniques to disease occurrence data. Using an ensemble approach, we first produced environmental suitability maps for potential SINV vectors in Finland. These suitability maps were then combined with grouse densities and environmental data to identify the influential determinants for SINV infections and to predict the risk of Pogosta disease in Finnish municipalities. Our predictions suggest that both the environmental suitability for vectors and the high risk of Pogosta disease are focused in geographically restricted areas. This provides evidence that the presence of both SINV vector species and grouse densities can predict the occurrence of the disease. The results support material for public-health officials when determining area-specific recommendations and deliver information to health care personnel to raise awareness of the disease among physicians. MDPI 2021-07-01 /pmc/articles/PMC8296873/ /pubmed/34281003 http://dx.doi.org/10.3390/ijerph18137064 Text en © 2021 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Uusitalo, Ruut Siljander, Mika Culverwell, C. Lorna Hendrickx, Guy Lindén, Andreas Dub, Timothée Aalto, Juha Sane, Jussi Marsboom, Cedric Suvanto, Maija T. Vajda, Andrea Gregow, Hilppa Korhonen, Essi M. Huhtamo, Eili Pellikka, Petri Vapalahti, Olli Predicting Spatial Patterns of Sindbis Virus (SINV) Infection Risk in Finland Using Vector, Host and Environmental Data |
title | Predicting Spatial Patterns of Sindbis Virus (SINV) Infection Risk in Finland Using Vector, Host and Environmental Data |
title_full | Predicting Spatial Patterns of Sindbis Virus (SINV) Infection Risk in Finland Using Vector, Host and Environmental Data |
title_fullStr | Predicting Spatial Patterns of Sindbis Virus (SINV) Infection Risk in Finland Using Vector, Host and Environmental Data |
title_full_unstemmed | Predicting Spatial Patterns of Sindbis Virus (SINV) Infection Risk in Finland Using Vector, Host and Environmental Data |
title_short | Predicting Spatial Patterns of Sindbis Virus (SINV) Infection Risk in Finland Using Vector, Host and Environmental Data |
title_sort | predicting spatial patterns of sindbis virus (sinv) infection risk in finland using vector, host and environmental data |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8296873/ https://www.ncbi.nlm.nih.gov/pubmed/34281003 http://dx.doi.org/10.3390/ijerph18137064 |
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