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...
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creator | 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 |
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. |
doi_str_mv | 10.3390/ijerph18137064 |
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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</creator><creatorcontrib>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</creatorcontrib><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.</description><identifier>ISSN: 1660-4601</identifier><identifier>ISSN: 1661-7827</identifier><identifier>EISSN: 1660-4601</identifier><identifier>DOI: 10.3390/ijerph18137064</identifier><identifier>PMID: 34281003</identifier><language>eng</language><publisher>Basel: MDPI AG</publisher><subject>Arthritis ; Birds ; Climate change ; Determinants ; Epidemics ; Fever ; Health risks ; Infections ; Infectious diseases ; Laboratories ; Mathematical models ; Migratory birds ; Mosquitoes ; Municipalities ; Pathogens ; Physicians ; Public health ; Risk ; Signs and symptoms ; Spatial analysis ; Statistical analysis ; Statistical models ; Surveillance ; Vectors ; Vectors (Biology) ; Viruses</subject><ispartof>International journal of environmental research and public health, 2021-07, Vol.18 (13), p.7064</ispartof><rights>2021 by the authors. 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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. 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Lorna</au><au>Hendrickx, Guy</au><au>Lindén, Andreas</au><au>Dub, Timothée</au><au>Aalto, Juha</au><au>Sane, Jussi</au><au>Marsboom, Cedric</au><au>Suvanto, Maija T.</au><au>Vajda, Andrea</au><au>Gregow, Hilppa</au><au>Korhonen, Essi M.</au><au>Huhtamo, Eili</au><au>Pellikka, Petri</au><au>Vapalahti, Olli</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Predicting Spatial Patterns of Sindbis Virus (SINV) Infection Risk in Finland Using Vector, Host and Environmental Data</atitle><jtitle>International journal of environmental research and public health</jtitle><date>2021-07-01</date><risdate>2021</risdate><volume>18</volume><issue>13</issue><spage>7064</spage><pages>7064-</pages><issn>1660-4601</issn><issn>1661-7827</issn><eissn>1660-4601</eissn><abstract>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.</abstract><cop>Basel</cop><pub>MDPI AG</pub><pmid>34281003</pmid><doi>10.3390/ijerph18137064</doi><orcidid>https://orcid.org/0000-0003-4170-8809</orcidid><orcidid>https://orcid.org/0000-0001-6819-4911</orcidid><orcidid>https://orcid.org/0000-0003-4730-7715</orcidid><orcidid>https://orcid.org/0000-0002-5996-9268</orcidid><orcidid>https://orcid.org/0000-0003-2270-6824</orcidid><orcidid>https://orcid.org/0000-0001-9640-6547</orcidid><orcidid>https://orcid.org/0000-0001-6254-049X</orcidid><oa>free_for_read</oa></addata></record> |
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subjects | Arthritis Birds Climate change Determinants Epidemics Fever Health risks Infections Infectious diseases Laboratories Mathematical models Migratory birds Mosquitoes Municipalities Pathogens Physicians Public health Risk Signs and symptoms Spatial analysis Statistical analysis Statistical models Surveillance Vectors Vectors (Biology) Viruses |
title | Predicting Spatial Patterns of Sindbis Virus (SINV) Infection Risk in Finland Using Vector, Host and Environmental Data |
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