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The Region of Central Macedonia (RCM) in Northern Greece recorded the highest number of human West Nile virus (WNV) infections in Greece, despite considerable local mosquito control actions. We examined spatial patterns and associations of mosquito levels, infected mosquito levels, and WNV human cases (WNVhc) across the municipalities of this region over the period 2010–2023 and linked it with climatic characteristics. We combined novel entomological and available epidemiological and climate data for the RCM, aggregated at the municipality level and used Local and Global Moran's I index to assess spatial associations of mosquito levels, infected mosquito levels, and WNVhc. We identified areas with strong interdependencies between adjacent municipalities in the Western part of the region. Furthermore, we employed a Generalized Linear Mixed Model to first, identify the factors driving the observed levels of mosquitoes, infected mosquitoes and WNVhc and second, estimate the influence of climatic features on the observed levels. This modeling approach indicates a strong dependence of the mosquito levels on the temperatures in winter and spring and the total precipitation in early spring, while virus circulation relies on the temperatures of late spring and summer. Our findings highlight the significant influence of climatic factors on mosquito populations (∼60 % explained variance) and the incidence of WNV human cases (∼40 % explained variance), while the unexplained ∼40 % of the variance suggests that targeted interventions and enhanced surveillance in identified hot-spots can enhance public health response.

Abstract We extend a previously developed epidemiological model for West Nile virus (WNV) infection in humans in Greece, employing laboratory-confirmed WNV cases and mosquito-specific characteristics of transmission, such as host selection and temperature-dependent transmission of the virus. Host selection was defined by bird host selection and human host selection, the latter accounting only for the fraction of humans that develop symptoms after the virus is acquired. To model the role of temperature on virus transmission, we considered five temperature intervals (≤ 19.25 °C; > 19.25 and 26.75 °C). The capacity of the new model to fit human cases and the week of first case occurrence was compared with the original model and showed improved performance. The model was also used to infer further quantities of interest, such as the force of infection for different temperatures as well as mosquito and bird abundances. Our results indicate that the inclusion of mosquito-specific characteristics in epidemiological models of mosquito-borne diseases leads to improved modelling capacity.

West Nile Virus (WNV) is transmitted among amplifying hosts and transferred through the bites of mosquitoes; humans and other mammals may become infected. The overwintering of infected mosquitoes is important for next season’s circulation of the virus. In this study, we combined the available climatic and entomological data at the municipality level to identify the impact of the wintertime climatic anomalies on the survival ability of diapausing mosquitoes in Central Macedonia, a region with great epidemiological interest in Greece. The analysis indicated a strong dependence of the mosquito abundances with spring temperature and winter precipitation, depending on the land use type and the geomorphology of the municipalities.

In this study, initial elements of a modelling framework aimed to become a spatial forecasting model for the transmission risk of West Nile virus (WNV) are presented. The model describes the dynamics of a WNV epidemic in population health states of mosquitoes, birds and humans and was applied to the case of Greece for the period 2010–2019. Calibration was performed with the available epidemiological data from the Hellenic Centre for Disease Control and Prevention and the environmental data from the European Union's earth observation program, Copernicus. Numerical results of the model for each municipality were evaluated against observations. Specifically, the occurrence of WNV, the number of infected humans and the week of incidence predicted from the model were compared to the corresponding numbers from observations. The results suggest that dynamic downscaling of a climate-dependent epidemiological model is feasible down-to roughly 80km2. This below nomenclature of territorial units for statistics (NUTS) 3 level represents the municipalities being the lowest level of administrative units, able to cope with WNV and take actions. The average detection probability in hindcast mode was 72%, improving strongly as the number of infected humans increased. Using the developed model, we were also able to show the fundamental importance of the May temperatures in shaping the WNV dynamics. The modeling framework couples epidemiological and environmental dynamical variables with surveillance data producing risk maps downscaled at a local level. The approach can be expanded to provide targeted early warning probabilistic forecasts that can be used to inform public health policy decision making.

The study explored the possibilities to improve students’ argumentation ability concerning factors that affect dissolving, through the implementation of two versions of a teaching scheme, with and without particle theory. The participants (age range 10–11, n = 27) belonged to two fifth-grade classes of a primary school in Northern Greece. Data were collected through an open-ended written test and a semi-structured interview targeting four of the components of an argument: Claims, data, warrants, and rebuttals, for five factors affecting the dissolving of a solid substance in water: Temperature, stirring, amount of the substance, grain size, and nature of the substance itself. Results showed an improvement concerning the structure of students’ arguments, whereas improvements in content quality appeared mainly in some cases where particle theory was implemented. Study limitations and implications for science education are discussed.