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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.

Arthropod-borne diseases currently constitute a source of major health concerns worldwide. They account for about 50% of global infectious diseases and cause nearly 700,000 deaths every year. Their rapid increase and spread constitute a huge challenge for public health, highlighting the need for early detection during epidemics, to curtail the virus spread, and to enhance outbreak management. Here, we compared a standard quantitative polymerase chain reaction (RT-qPCR) and a direct RT-qPCR assay for the detection of Zika (ZIKV), Chikungunya (CHIKV), and Rift Valley Fever (RVFV) viruses from experimentally infected-mosquitoes. The direct RT-qPCR could be completed within 1.5 h and required 1 µL of viral supernatant from homogenized mosquito body pools. Results showed that the direct RT-qPCR can detect 85.71%, 89%, and 100% of CHIKV, RVFV, and ZIKV samples by direct amplifications compared to the standard method. The use of 1:10 diluted supernatant is suggested for CHIKV and RVFV direct RT-qPCR. Despite a slight drop in sensitivity for direct PCR, our technique is more affordable, less time-consuming, and provides a better option for qualitative field diagnosis during outbreak management. It represents an alternative when extraction and purification steps are not possible because of insufficient sample volume or biosecurity issues. [ABSTRACT FROM AUTHOR]

Arthropod-borne diseases currently constitute a source of major health concerns worldwide. They account for about 50% of global infectious diseases and cause nearly 700,000 deaths every year. Their rapid increase and spread constitute a huge challenge for public health, highlighting the need for early detection during epidemics, to curtail the virus spread, and to enhance outbreak management. Here, we compared a standard quantitative polymerase chain reaction (RT-qPCR) and a direct RT-qPCR assay for the detection of Zika (ZIKV), Chikungunya (CHIKV), and Rift Valley Fever (RVFV) viruses from experimentally infected-mosquitoes. The direct RT-qPCR could be completed within 1.5 h and required 1 µL of viral supernatant from homogenized mosquito body pools. Results showed that the direct RT-qPCR can detect 85.71%, 89%, and 100% of CHIKV, RVFV, and ZIKV samples by direct amplifications compared to the standard method. The use of 1:10 diluted supernatant is suggested for CHIKV and RVFV direct RT-qPCR. Despite a slight drop in sensitivity for direct PCR, our technique is more affordable, less time-consuming, and provides a better option for qualitative field diagnosis during outbreak management. It represents an alternative when extraction and purification steps are not possible because of insufficient sample volume or biosecurity issues.