Predicting Spatial Patterns of Sindbis Virus (SINV) Infection Risk in Finland Using Vector, Host and Environmental Data

Mosquito-borne viruses causing human disease in Fennoscandia—Past, current, and future perspectives

Five different mosquito-borne viruses (moboviruses) significant to human disease are known to be endemic to Fennoscandia (Sindbis virus, Inkoo virus, Tahyna virus, Chatanga virus, and Batai virus). However, the incidence of mosquito-borne virus infections in Fennoscandia is unknown, largely due to underdiagnosing and lack of surveillance efforts. The Fennoscandian moboviruses are difficult to prevent due to their method of transmission, and often difficult to diagnose due to a lack of clear case definition criteria. Thus, many cases are likely to be mis-diagnosed, or even not diagnosed at all. Significant long-term effects, often in the form of malaise, rashes, and arthralgia have been found for some of these infections. Research into mobovirus disease is ongoing, though mainly focused on a few pathogens, with many others neglected. With moboviruses found as far north as the 69th parallel, studying mosquito-borne disease occurring in the tropics is only a small part of the whole picture. This review is written with the objective of summarizing current medically relevant knowledge of moboviruses occurring in Fennoscandia, while highlighting what is yet unknown and possibly overlooked.

Vector Competence of Northern European Culex pipiens Biotype pipiens and Culex torrentium to West Nile Virus and Sindbis Virus

The West Nile Virus (WNV) and Sindbis virus (SINV) are avian-hosted mosquito-borne zoonotic viruses that co-circulate in some geographical areas and share vector species such as Culex pipiens and Culex torrentium. These are widespread in Europe, including northern parts and Finland, where SINV is endemic, but WNV is currently not. As WNV is spreading northwards in Europe, we wanted to assess the experimental vector competence of Finnish Culex pipiens and Culex torrentium mosquitoes to WNV and SINV in different temperature profiles. Both mosquito species were found susceptible to both viruses and got infected via infectious blood meal at a mean temperature of 18 °C. WNV-positive saliva was detected at a mean temperature of 24 °C, whereas SINV-positive saliva was detected already at a mean temperature of 18 °C. Cx. torrentium was found to be a more efficient vector for WNV and SINV over Cx. pipiens. Overall, the results were in line with the previous studies performed with more southern vector populations. The current climate does not seem optimal for WNV circulation in Finland, but temporary summertime transmission could occur in the future if all other essential factors are in place. More field data would be needed for monitoring and understanding the northward spreading of WNV in Europe.

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.

Ecological niche modeling predicting the potential distribution of African horse sickness virus from 2020 to 2060

African horse sickness is a vector-borne, non-contagious and highly infectious disease of equines caused by African horse sickness viruses (AHSv) that mainly affect horses. The occurrence of the disease causes huge economic impacts because of its high fatality rate, trade ban and disease control costs. In the planning of vectors and vector-borne diseases like AHS, the application of Ecological niche models (ENM) used an enormous contribution in precisely delineating the suitable habitats of the vector. We developed an ENM to delineate the global suitability of AHSv based on retrospective outbreak data records from 2005 to 2019. The model was developed in an R software program using the Biomod2 package with an Ensemble modeling technique. Predictive environmental variables like mean diurnal range, mean precipitation of driest month(mm), precipitation seasonality (cv), mean annual maximum temperature (^oc), mean annual minimum temperature (^oc), mean precipitation of warmest quarter(mm), mean precipitation of coldest quarter (mm), mean annual precipitation (mm), solar radiation (kj /day), elevation/altitude (m), wind speed (m/s) were used to develop the model. From these variables, solar radiation, mean maximum temperature, average annual precipitation, altitude and precipitation seasonality contributed 36.83%, 17.1%, 14.34%, 7.61%, and 6.4%, respectively. The model depicted the sub-Sahara African continent as the most suitable area for the virus. Mainly Senegal, Burkina Faso, Niger, Nigeria, Ethiopia, Sudan, Somalia, South Africa, Zimbabwe, Madagascar and Malawi are African countries identified as highly suitable countries for the virus. Besides, OIE-listed disease-free countries like India, Australia, Brazil, Paraguay and Bolivia have been found suitable for the virus. This model can be used as an epidemiological tool in planning control and surveillance of diseases nationally or internationally.