Spatial epidemiology of hemorrhagic disease in Illinois wild white-tailed deer.

Epizootic hemorrhagic disease (EHD) and bluetongue (BT) are vector-borne viral diseases that affect wild and domestic ruminants. Clinical signs of EHD and BT are similar; thus, the syndrome is referred to as hemorrhagic disease (HD). Syndromic surveillance and virus detection in North America reveal a northern expansion of HD. High mortalities at northern latitudes suggest recent incursions of HD viruses into northern geographic areas. We evaluated the occurrence of HD in wild Illinois white-tailed deer from 1982 to 2019. Our retrospective space-time analysis identified high-rate clusters of HD cases from 2006 to 2019. The pattern of northward expansion indicates changes in virus-host-vector interactions. Serological evidence from harvested deer revealed prior infection with BTV. However, BTV was not detected from virus isolation in dead deer sampled during outbreaks. Our findings suggest the value of capturing the precise geographic location of outbreaks, the importance of virus isolation to confirm the cause of an outbreak, and the importance of expanding HD surveillance to hunter-harvested wild white-tailed deer. Similarly, it assists in predicting future outbreaks, allowing for targeted disease and vector surveillance, helping wildlife agencies communicate with the public the cause of mortality events and viral hemorrhagic disease outcomes at local and regional scales.

Where do uncertainties reside within environmental risk assessments? Testing UnISERA, a guide for uncertainty assessment.

A means for identifying and prioritising the treatment of uncertainty (UnISERA) in environmental risk assessments (ERAs) is tested, using three risk domains where ERA is an established requirement and one in which ERA practice is emerging. UnISERA's development draws on 19 expert elicitations across genetically modified higher plants, particulate matter, and agricultural pesticide release and is stress tested here for engineered nanomaterials (ENM). We are concerned with the severity of uncertainty; its nature; and its location across four accepted stages of ERAs. Using an established uncertainty scale, the risk characterisation stage of ERA harbours the highest severity level of uncertainty, associated with estimating, aggregating and evaluating expressions of risk. Combined epistemic and aleatory uncertainty is the dominant nature of uncertainty. The dominant location of uncertainty is associated with data in problem formulation, exposure assessment and effects assessment. Testing UnISERA produced agreements of 55%, 90%, and 80% for the severity level, nature and location dimensions of uncertainty between the combined case studies and the ENM stress test. UnISERA enables environmental risk analysts to prioritise risk assessment phases, groups of tasks, or individual ERA tasks and it can direct them towards established methods for uncertainty treatment.

Where do uncertainties reside within environmental risk assessments? Expert opinion on uncertainty distributions for pesticide risks to surface water organisms.

A reliable characterisation of uncertainties can aid uncertainty identification during environmental risk assessments (ERAs). However, typologies can be implemented inconsistently, causing uncertainties to go unidentified. We present an approach based on nine structured elicitations, in which subject-matter experts, for pesticide risks to surface water organisms, validate and assess three dimensions of uncertainty: its level (the severity of uncertainty, ranging from determinism to ignorance); nature (whether the uncertainty is epistemic or aleatory); and location (the data source or area in which the uncertainty arises). Risk characterisation contains the highest median levels of uncertainty, associated with estimating, aggregating and evaluating the magnitude of risks. Regarding the locations in which uncertainty is manifest, data uncertainty is dominant in problem formulation, exposure assessment and effects assessment. The comprehensive description of uncertainty described will enable risk analysts to prioritise the required phases, groups of tasks, or individual tasks within a risk analysis according to the highest levels of uncertainty, the potential for uncertainty to be reduced or quantified, or the types of location-based uncertainty, thus aiding uncertainty prioritisation during environmental risk assessments. In turn, it is expected to inform investment in uncertainty reduction or targeted risk management action.