Suchergebnisse

ObjectiveDue to human-caused climate change, extreme temperature-related morbidity/mortality are increasing global public health concerns. To better understand the burdens of heat exposure, researchers must merge accurate/granular environmental data with clinical data. We developed a privacy-preserving method that links high-spatial-resolution continuous, gridded, meteorological data to geocoded healthcare encounters.
ApproachIn an R environment, we developed code that links geocoded healthcare encounters to publicly-available Daymet data via the corresponding Daymet raster cell number and healthcare encounter date. Daymet provides daily 1km x 1km surface meteorological data over North America since 1980. User specifications include the bounding box latitude/longitude of Daymet data download, which Daymet environmental variables are linked, and the day-lag of Daymet data matching to healthcare encounter date.
ResultsLinking 500,000 healthcare encounters over a 7-day lag with 7 years of Daymet data comprising minimum/maximum temperature over a bounding box encompassing Cook County, Illinois (5,670 1km raster cells) took 11.92 minutes with 4 CPUs and 8GB RAM. Thirteen years of Daymet data took 23.85 minutes. Linking 7.5 million encounters with 7 years of data took 28.49 minutes.
ConclusionsOur newly-developed method for linking Daymet data to geocoded healthcare encounters preserves patient privacy, and processes the data efficiently over a minimal timespan.
ImplicationsDaymet data linked to healthcare encounters allows for accurate assessment of the association between environmental variable exposure and any clinical outcome over North America. Packaging the code allows for public distribution within the Decentralized Geomarker Assessment for Multi-Site Studies (DeGAUSS) universe of geoanalytic tools.

In South Africa, canid rabies virus (RABV) infection is maintained in domestic and wildlife species. The identification of rabies in African civets raised the question of whether this wildlife carnivore is a potential reservoir host of RABVs of direct and ancestral dog origin (dog-maintained and dog-derived origins) with an independent cycle of transmission. Genetic analyses of African civet nucleoprotein sequences for 23 African civet RABVs and historically published sequences demonstrated that RABVs from African civets have two origins related to dog and mongoose rabies enzootics. The data support observations of the interaction of civets with domestic dogs and wildlife mongooses, mostly in Northern South Africa and North-East Zimbabwe. Within each host species clade, African civet RABVs group exclusively together, implying intra-species virus transfer occurs readily. The canid RABV clade appears to support virus transfer more readily between hosts than mongoose RABVs. Furthermore, these data probably indicate short transmission chains with conspecifics that may be related to transient rabies maintenance in African civets. Hence, it is important to continue monitoring the emergence of lyssaviruses in this host. Observations from this study are supported by ongoing and independent similar cases, in which bat-eared foxes and black-backed jackal species maintain independent rabies cycles of what were once dog-maintained RABVs. ; Table S1: PCR primers used in the study, Table S2: RABV sequences used for phylogenetic analysis with African civet sequences (Figure 2). ; Defra, Scottish Government and Welsh Government under project SE0431, and the EU Framework Horizon 2020 Innovation Grant, European Virus Archive (EVAg, grant no. 653316). DLH was funded by the Academy of Medical Sciences and the Wellcome Trust, grant number 86200571. ; http://www.mdpi.com/journal/viruses ; am2021 ; Veterinary Tropical Diseases

Abstract. In steep wildfire-burned terrains, intense rainfall can produce large runoff that can trigger highly destructive debris flows. However, the ability
to accurately characterize and forecast debris flow susceptibility in burned terrains using physics-based tools remains limited. Here, we augment
the Weather Research and Forecasting Hydrological modeling system (WRF-Hydro) to simulate both overland and channelized flows and assess postfire
debris flow susceptibility over a regional domain. We perform hindcast simulations using high-resolution weather-radar-derived precipitation and
reanalysis data to drive non-burned baseline and burn scar sensitivity experiments. Our simulations focus on January 2021 when an atmospheric river
triggered numerous debris flows within a wildfire burn scar in Big Sur – one of which destroyed California's famous Highway 1. Compared to the
baseline, our burn scar simulation yields dramatic increases in total and peak discharge and shorter lags between rainfall onset and peak
discharge, consistent with streamflow observations at nearby US Geological Survey (USGS) streamflow gage sites. For the 404 catchments located in
the simulated burn scar area, median catchment-area-normalized peak discharge increases by ∼ 450 % compared to the baseline. Catchments
with anomalously high catchment-area-normalized peak discharge correspond well with post-event field-based and remotely sensed debris flow
observations. We suggest that our regional postfire debris flow susceptibility analysis demonstrates WRF-Hydro as a compelling new physics-based
tool whose utility could be further extended via coupling to sediment erosion and transport models and/or ensemble-based operational weather
forecasts. Given the high-fidelity performance of our augmented version of WRF-Hydro, as well as its potential usage in probabilistic hazard
forecasts, we argue for its continued development and application in postfire hydrologic and natural hazard assessments.

© Wildlife Disease Association 2019. Many infectious diseases originating from, or carried by, wildlife affect wildlife conservation and biodiversity, livestock health, or human health. We provide an update on changes in the epidemiology of 25 selected infectious, wildlife-related diseases in Europe (from 2010–16) that had an impact, or may have a future impact, on the health of wildlife, livestock, and humans. These pathogens were selected based on their: 1) identification in recent Europe-wide projects as important surveillance targets, 2) inclusion in European Union legislation as pathogens requiring obligatory surveillance, 3) presence in recent literature on wildlife-related diseases in Europe since 2010, 4) inclusion in key pathogen lists released by the Office International des Epizooties, 5) identification in conference presentations and informal discussions on a group email list by a European network of wildlife disease scientists from the European Wildlife Disease Association, or 6) identification as pathogens with changes in their epidemiology during 2010–16. The wildlife pathogens or diseases included in this review are: avian influenza virus, seal influenza virus, lagoviruses, rabies virus, bat lyssaviruses, filoviruses, canine distemper virus, morbilliviruses in aquatic mammals, bluetongue virus, West Nile virus, hantaviruses, Schmallenberg virus, Crimean-Congo hemorrhagic fever virus, African swine fever virus, amphibian ranavirus, hepatitis E virus, bovine tuberculosis (Mycobacterium bovis), tularemia (Francisella tularensis), brucellosis (Brucella spp.), salmonellosis (Salmonella spp.), Coxiella burnetii, chytridiomycosis, Echinococcus multilocularis, Leishmania infantum, and chronic wasting disease. Further work is needed to identify all of the key drivers of disease change and emergence, as they appear to be influencing the incidence and spread of these pathogens in Europe. We present a summary of these recent changes during 2010–16 to discuss possible commonalities and drivers of disease ...

Despite decades of climate science research, existing climate actions have had limited impacts on mitigating climate change. Efforts to reduce emissions, for example, have yet to spur sufficient action to reduce the most severe effects of climate change. We draw from our experiences as Ojibwe knowledge holders and community members, scientists, and scholars to demonstrate how the lack of recognition of traditional knowledges (TK) within climate science constrains effective climate action and exacerbates climate injustice. Often unrecognized in science and policy arenas, TK generates insights into how justice-driven climate action, rooted in relational interdependencies between humans and older-than-human relatives, can provide new avenues for effectively addressing climate change. We conclude by arguing for a shift toward meaningful and respectful inclusion of plural knowledge systems in climate governance.