Work Package 8 – Task 8.1 Report on: Vaccine hesitancy and uptake. From research and practices to implementation

This European Joint Action on Vaccination (JAV No801495) was funded by the European Union’s Health Programme (2014–2020

Sindbis virus outbreak and evidence for geographical expansion in Finland, 2021

Sindbis virus (SINV) caused a large outbreak in Finland in 2021 with 566 laboratory-confirmed human cases and a notable geographical expansion. Compared with the last large outbreak in 2002, incidence was higher in several hospital districts but lower in traditionally endemic locations in eastern parts of the country. A high incidence is also expected in 2022. Awareness of SINV should be raised in Finland to increase recognition of the disease and prevent transmission through the promotion of control measures.Peer reviewe

Modelling habitat suitability for occurrence of human tick-borne encephalitis (TBE) cases in Finland

The numbers of reported human tick-borne encephalitis (TBE) cases in Europe have increased in several endemic regions (including Finland) in recent decades, indicative of an increasing threat to public health. As such, it is important to identify the regions at risk and the most influential factors associated with TBE distributions, particularly in understudied regions. This study aimed to identify the risk areas of TBE transmission in two different datasets based on human TBE disease cases from 2007 to 2011 (n = 86) and 2012–2017 (n  = 244). We also examined which factors best explain the presence of human TBE cases. We used ensemble modelling to determine the relationship of TBE occurrence with environmental, ecological, and anthropogenic factors in Finland. Geospatial data including these variables were acquired from several open data sources and satellite and aerial imagery and, were processed in GIS software. Biomod2, an ensemble platform designed for species distribution modelling, was used to generate ensemble models in R. The proportion of built-up areas, field, forest, and snow-covered land in November, people working in the primary sector, human population density, mean precipitation in April and July, and densities of European hares, white-tailed deer, and raccoon dogs best estimated distribution of human TBE disease cases in the two datasets. Random forest and generalized boosted regression models performed with a very good to excellent predictive power (ROC = 0.89–0.96) in both time periods. Based on the predictive maps, high-risk areas for TBE transmission were located in the coastal regions in Southern and Western Finland (including the Åland Islands), several municipalities in Central and Eastern Finland, and coastal municipalities in Southern Lapland. To explore potential changes in TBE distributions in future climate, we used bioclimatic factors with current and future climate forecast data to reveal possible future hotspot areas. Based on the future forecasts, a slightly wider geographical extent of TBE risk was introduced in the Åland Islands and Southern, Western and Northern Finland, even though the risk itself was not increased. Our results are the first steps towards TBE-risk area mapping in current and future climate in Finland.</p

High habitat richness reduces the risk of tick-borne encephalitis in Europe: a multi-scale study

Background The natural transmission cycle of tick-borne encephalitis (TBE) virus is enhanced by complex interactions between ticks and key hosts strongly connected to habitat characteristics. The diversity of wildlife host species and their relative abundance is known to affect transmission of tick-borne diseases. Therefore, in the current context of global biodiversity loss, we explored the relationship between habitat richness and the pattern of human TBE cases in Europe to assess biodiversity's role in disease risk mitigation. Methods We assessed human TBE case distribution across 879 European regions using official epidemiological data reported to The European Surveillance System (TESSy) between 2017 and 2021 from 15 countries. We explored the relationship between TBE presence and the habitat richness index (HRI1) by means of binomial regression. We validated our findings at local scale using data collected between 2017 and 2021 in 227 municipalities located in Trento and Belluno provinces, two known TBE foci in northern Italy. Findings Our results showed a significant parabolic effect of HRI on the probability of presence of human TBE cases in the European regions included in our dataset, and a significant, negative effect of HRI on the local presence of TBE in northern Italy. At both spatial scales, TBE risk decreases in areas with higher values of HRI. Interpretation To our knowledge, no efforts have yet been made to explore the relationship between biodiversity and TBE risk, probably due to the scarcity of high-resolution, large-scale data about the abundance or density of critical host species. Hence, in this study we considered habitat richness as proxy for vertebrate host diversity. The results suggest that in highly diverse habitats TBE risk decreases. Hence, biodiversity loss could enhance TBE risk for both humans and wildlife. This association is relevant to support the hypothesis that the maintenance of highly diverse ecosystems mitigates disease ris

Mikrobilääkekulutus Suomessa 2013-2020

Mikrobilääkkeiden kulutuksen seuranta on tärkeä osa mikrobilääkeresistenssin torjuntaa. Tähän työpaperiin on koottu tietoa mikrobilääkkeiden ajallisesta ja alueellisesta kulutuksesta Suomessa. Vaikka kansallisesti mikrobilääkkeiden kulutus on vähenemässä, todetaan alueiden välillä huomattavia eroja. Tämän raportin tarkoitus on auttaa tunnistamaan ne lääkeaineryhmät, joihin olisi syytä kiinnittää huomiota niin kansallisesti kuin eri alueilla ja etsiä keinoja tarpeettoman mikrobilääkekäytön vähentämiseksi

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 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

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 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