The Geography of Disease Transmission

2011 ◽  
Author(s):  
A. Townsend Peterson ◽  
Jorge Soberón ◽  
Richard G. Pearson ◽  
Robert P. Anderson ◽  
Enrique Martínez-Meyer ◽  
...  
Keyword(s):  
Disease Transmission ◽  
Disease Ecology ◽  
Ecological Niche ◽  
Ecological Niche Modeling ◽  
Global Climate ◽  
Risk Identification ◽  
Niche Modeling ◽  
Transmission Risk ◽  
Populations At Risk ◽  
The Face

This chapter discusses various applications of ecological niche modeling in the study of the geography and ecology of disease transmission. Niche modeling approaches have many applications in the field of public health and epidemiology. Among the most common spatial epidemiological applications are mapping geographic patterns of disease transmission risk, identification of risk factors, and assessment of populations at risk of infection. The chapter describes a number of applications of ecological niche modeling in the realm of disease transmission, such as characterizing disease ecology, disease distributions and risk mapping, and potential distributions of pathogens or other individual component species in transmission systems, as well as forecasting disease transmission patterns in the face of ongoing global climate change. It also reviews practical considerations to keep in mind when exploring such applications and outlines some caveats, limitations, and challenges involved. Finally, it suggests future directions for research.

scholarly journals New localities and distribution models inform the conservation status of the endangered lizard Anolis guamuhaya (Squamata: Dactyloidae) in central Cuba

2020 ◽  
Vol 19 (1) ◽  
pp. 13-33
Author(s):  
Tomás M. Rodríguez-Cabrera ◽  
Javier Torres ◽  
Carlos A. Mancina ◽  
Ruben Marrero ◽  
Yasel U. Alfonso ◽  
...  
Keyword(s):  
Ecological Niche ◽  
Ecological Niche Modeling ◽  
New Records ◽  
Global Climate ◽  
Conservation Status ◽  
Niche Modeling ◽  
Distribution Models ◽  
Area Of Occupancy ◽  
New Localities ◽  
Iucn Criteria

New localities and distribution models inform the conservation status of the endangered lizard Anolis guamuhaya (Squamata: Dactyloidae) from central Cuba. Anolis guamuhaya is known from seven localities restricted to the Guamuhaya Massif in central Cuba and is always associated with mountane ecosystems above 300 m a.s.l. Previous evaluations of the conservation status of the species based on the estimated number of mature individuals have categorized the anole as Endangered. Eight new records of A. guamuhaya are provided here. These double the number of known localities, and two represent the first records of the species in lowland areas, apart from the Guamuhaya Massif. The new records extend the elevational range of the species from 15 m to above 1000 m. We used ecological niche modeling based on all of the locality records, along with what we considered the most appropriate IUCN criteria according to the available information (Criterion B) to reevaluate the conservation status of the species. These new records of A. guamuhaya increase its area of occupancy up to a total of 60 km2 , and its extent of occurrence up to 648 km2 . Despite this increase in geographic range, the species meets the IUCN criteria in the category of Endangered. We used ecological niche modeling to predict possible trends for the species under differing scenarios of global climate change, all of which portend a drastic reduction in area climatically suitable for A. guamuhaya.

scholarly journals Automatic variable selection in ecological niche modeling: A case study using Cassin’s Sparrow (Peucaea cassinii)

2021 ◽  
Author(s):  
John L. Schnase ◽  
Mark L. Carroll
Keyword(s):  
Monte Carlo ◽  
Variable Selection ◽  
Environmental Variables ◽  
Ecological Niche ◽  
Ecological Niche Modeling ◽  
Climate Model ◽  
Global Climate ◽  
Global Climate Model ◽  
Niche Modeling ◽  
Modeling Process

AbstractMERRA/Max provides a feature selection approach to dimensionality reduction that enables direct use of global climate model outputs in ecological niche modeling. The system accomplishes this reduction through a Monte Carlo optimization in which many independent MaxEnt runs, operating on a species occurrence file and a small set of randomly selected variables in a large collection of variables, converge on an estimate of the top contributing predictors in the larger collection. These top predictors can be viewed as potential candidates in the variable selection step of the ecological niche modeling process. MERRA/Max’s Monte Carlo algorithm operates on files stored in the underlying filesystem, making it scalable to large data sets. Its software components can run as parallel processes in a high-performance cloud computing environment to yield near real-time performance. In tests using Cassin’s Sparrow (Peucaea cassinii) as the target species, MERRA/Max selected a set of predictors from Worldclim’s Bioclim collection of 19 environmental variables that have been shown to be important determinants of the species’ bioclimatic niche. It also selected biologically and ecologically meaningful predictors from a more diverse set of 86 environmental variables derived from NASA’s Modern-Era Retrospective Analysis for Research and Applications Version 2 (MERRA-2) reanalysis, an output product of the Goddard Earth Observing System Version 5 (GEOS-5) modeling system. We believe these results point to a technological approach that could expand the use global climate model outputs in ecological niche modeling, streamline the modeling process, and, eventually, enable automated bioclimatic modeling as a practical, readily accessible, low-cost, commercial cloud service.

scholarly journals Potential Distribution of Chagas Disease Vectors (Hemiptera, Reduviidae, Triatominae) in Colombia, Based on Ecological Niche Modeling

2016 ◽  
Vol 2016 ◽  
pp. 1-10 ◽  
Author(s):  
Gabriel Parra-Henao ◽  
Laura C. Suárez-Escudero ◽  
Sebastián González-Caro
Keyword(s):  
Chagas Disease ◽  
Sierra Nevada ◽  
Geographic Distribution ◽  
Ecological Niche ◽  
Ecological Niche Modeling ◽  
Climatic Factors ◽  
Niche Modeling ◽  
Triatomine Species ◽  
Local Risk ◽  
And Control

Ecological niche modeling of Triatominae bugs allow us to establish the local risk of transmission of the parasiteTrypanosoma cruzi,which causes Chagas disease.This information could help to guide health authority recommendations on infection monitoring, prevention, and control. In this study, we estimated the geographic distribution of triatomine species in Colombia and identified the relationship between landscape structure and climatic factors influencing their occurrence. A total of 2451 records of 4 triatomine species (Panstrongylus geniculatus,Rhodnius pallescens,R. prolixus, andTriatoma maculata) were analyzed.The variables that provided more information to explain the ecologic niche of these vectors were related to precipitation, altitude, and temperature. We found that the species with the broadest potential geographic distribution wereP. geniculatus,R. pallescens, andR. prolixus. In general, the models predicted the highest occurrence probability of these vectors in the eastern slope of the Eastern Cordillera, the southern region of the Magdalena valley, and the Sierra Nevada of Santa Marta.

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