ArticleEpidemiology and infection2013
Climatic, ecological and socioeconomic factors as predictors of Sindbis virus infections in Finland.
Article in Epidemiology and infection, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
7 citing papers in PubMed, 17 citations in OpenAlex.
- Sindbis virus outbreak and evidence for geographical expansion in Finland, 2021.Euro surveillance : bulletin Europeen sur les maladies transmissibles = European communicable disease bulletin · 2022Article
- Predicting Spatial Patterns of Sindbis Virus (SINV) Infection Risk in Finland Using Vector, Host and Environmental Data.International journal of environmental research and public health · 2021Article
- Sindbis Virus Strains of Divergent Origin Isolated from Humans and Mosquitoes During a Recent Outbreak in Finland.Vector borne and zoonotic diseases (Larchmont, N.Y.) · 2020Article
- Article
- Detection of Sindbis and Inkoo Virus RNA in Genetically Typed Mosquito Larvae Sampled in Northern Sweden.Vector borne and zoonotic diseases (Larchmont, N.Y.) · 2016Article
- Temporal Variation in Sindbis Virus Antibody Prevalence in Bird Hosts in an Endemic Area in Sweden.PloS one · 2016Article
- Imported dengue cases, weather variation and autochthonous dengue incidence in Cairns, Australia.PloS one · 2013Article
Corrections and comments
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Authors and funding
11 authors at 5 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Mosquito-borne Sindbis virus (SINV) causes rash-arthritis syndrome in Finland. Major outbreaks with approximately 7-year cycles have caused substantial burden of illness. Forest dwelling grouse are suspected to be amplifying hosts, with the infection transmitted to humans by mosquito bites. SINV infection surveillance data for 1984–2010 were used to create a negative binomial hurdle model, with seasonality, long-term cycles, climatic, ecological and socioeconomic variables. Climatic factors during early summer and amount of snow in April described the occurrence and incidence of SINV infections. Regulated water shore and hatch-year black grouse density described the occurrence, while population working in agriculture, agricultural land(negative) and income (negative) described the incidence of the disease. The prediction for 2009 was 85 cases (95% prediction interval 2-1187), while the actual occurrence was 106. We identified novel and known risk factors. The prevention of SINV infections in regulated water areas by infected mosquito populations should be targeted.
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