Corrigendum to "Global correlates of emerging zoonoses: Anthropogenic, environmental, and biodiversity risk factors" [Int. J. Infect. Dis. 53 (Supplement) (December 2016) 21]

The authors regret that Dr Moreno di Marco's name was published with errors in the original abstract. The authors would like to apologise for any inconvenience caused

Evaluation and Verification of the Global Rapid Identification of Threats System for Infectious Diseases in Textual Data Sources

The Global Rapid Identification of Threats System (GRITS) is a biosurveillance application that enables infectious disease analysts to monitor nontraditional information sources (e.g., social media, online news outlets, ProMED-mail reports, and blogs) for infectious disease threats. GRITS analyzes these textual data sources by identifying, extracting, and succinctly visualizing epidemiologic information and suggests potentially associated infectious diseases. This manuscript evaluates and verifies the diagnoses that GRITS performs and discusses novel aspects of the software package. Via GRITS’ web interface, infectious disease analysts can examine dynamic visualizations of GRITS’ analyses and explore historical infectious disease emergence events. The GRITS API can be used to continuously analyze information feeds, and the API enables GRITS technology to be easily incorporated into other biosurveillance systems. GRITS is a flexible tool that can be modified to conduct sophisticated medical report triaging, expanded to include customized alert systems, and tailored to address other biosurveillance needs

Global correlates of emerging zoonoses: Anthropogenic, environmental, and biodiversity risk factors

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Mammal assemblage composition predicts global patterns in emerging infectious disease risk

As a source of emerging infectious diseases, wildlife assemblages (and related spatial patterns) must be quantitatively assessed to help identify high-risk locations. Previous assessments have largely focussed on the distributions of individual species; however, transmission dynamics are expected to depend on assemblage composition. Moreover, disease-diversity relationships have mainly been studied in the context of species loss, but assemblage composition and disease risk (e.g. infection prevalence in wildlife assemblages) can change without extinction. Based on the predicted distributions and abundances of 4466 mammal species, we estimated global patterns of disease risk through the calculation of the community-level basic reproductive ratio R0, an index of invasion potential, persistence, and maximum prevalence of a pathogen in a wildlife assemblage. For density-dependent diseases, we found that, in addition to tropical areas which are commonly viewed as infectious disease hotspots, northern temperate latitudes included high-risk areas. We also forecasted the effects of climate change and habitat loss from 2015 to 2035. Over this period, many local assemblages showed no net loss of species richness, but the assemblage composition (i.e. the mix of species and their abundances) changed considerably. Simultaneously, most areas experienced a decreased risk of density-dependent diseases but an increased risk of frequency-dependent diseases. We further explored the factors driving these changes in disease risk. Our results suggest that biodiversity and changes therein jointly influence disease risk. Understanding these changes and their drivers and ultimately identifying emerging infectious disease hotspots can help health officials prioritize resource distribution.Peer reviewe

Global hotspots and correlates of emerging zoonotic diseases.

Zoonoses originating from wildlife represent a significant threat to global health, security and economic growth, and combatting their emergence is a public health priority. However, our understanding of the mechanisms underlying their emergence remains rudimentary. Here we update a global database of emerging infectious disease (EID) events, create a novel measure of reporting effort, and fit boosted regression tree models to analyze the demographic, environmental and biological correlates of their occurrence. After accounting for reporting effort, we show that zoonotic EID risk is elevated in forested tropical regions experiencing land-use changes and where wildlife biodiversity (mammal species richness) is high. We present a new global hotspot map of spatial variation in our zoonotic EID risk index, and partial dependence plots illustrating relationships between events and predictors. Our results may help to improve surveillance and long-term EID monitoring programs, and design field experiments to test underlying mechanisms of zoonotic disease emergence

ecohealthalliance/hotspots2: Paper Resubmission

Modeling code as it stands at the resubmission of the "Global correlates of emerging zoonoses: anthropogenic, environmental, and biodiversity risk factors" paper

Holton Covered Bridge Over Otter Creek, Ripley County, Indiana

At one time Ripley County had 11 covered bridges, only 2 remain and both were constructed by Thomas A. Hardman. The Holton Bridge across Otter Creek was built in 1884; the Busching Bridge across Laughery Creek near Versailles State Park, was built in 1885.Ripley County Journe

Mantle: An Open Source Platform for One Health Biosurveillance and Research

Mantle is an open-source web platform designed for the storage, sharing, and visualization of One Health biosurveillance data and is designed to meet the needs of a wide variety of users. One Health scientists in the field or the lab will be able to upload datasets in multiple formats to Mantle's intelligent database, where they will be stored for easy download and analysis. Mantle users will be able to use fine-grained access controls to protect and share their uploaded datasets, and examine datasets in views appropriate to their content (e.g., tables, maps, and charts). Mantle's flexible storage layer will also display spatial datasets from different data sources alongside one another, and save and export combined datasets

Evaluation and Verification of the Global Rapid Identification of Threats System for Infectious Diseases in Textual Data Sources

The Global Rapid Identification of Threats System (GRITS) is a biosurveillance application that enables infectious disease analysts to monitor nontraditional information sources (e.g., social media, online news outlets, ProMED-mail reports, and blogs) for infectious disease threats. GRITS analyzes these textual data sources by identifying, extracting, and succinctly visualizing epidemiologic information and suggests potentially associated infectious diseases. This manuscript evaluates and verifies the diagnoses that GRITS performs and discusses novel aspects of the software package. Via GRITS' web interface, infectious disease analysts can examine dynamic visualizations of GRITS' analyses and explore historical infectious disease emergence events. The GRITS API can be used to continuously analyze information feeds, and the API enables GRITS technology to be easily incorporated into other biosurveillance systems. GRITS is a flexible tool that can be modified to conduct sophisticated medical report triaging, expanded to include customized alert systems, and tailored to address other biosurveillance needs