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Using Co-Occurrence Data to Predict Zoonoses & Emerging Patterns in Disease Ecology

Dr. Chris Stephens, Director of Data Science, C3 - Centro de Ciencias de la Complejidad Universidad Nacional Autonoma de Mexico; Full Professor, Instituto de Ciencias Nucleares Universidad Nacional Autonoma de Mexico

Dr. Gerardo Suzan, College of Veterinary Medicine, Universidad Nacional Autonoma de Mexico (UNAM)

Dr. Chris Stephens

Full Title: The “Why” from “Where” and “When”: Using Co-Occurrence Data to Predict Zoonoses

The use of co-occurrence data to identify ecological ‘interactions’, as well as its use in niche and species distribution modelling, has had a long and chequered history. In this talk, Dr. Chris Stephens will show why, suitably interpreted, co-occurrence data is enormously useful for predicting biotic interactions as well as incorporating biotic factors or, indeed, any factor that can be represented as a spatio-temporal distribution, into niche models, including, for example, socio-demographic or socio-economic data. Dr. Stephens will show how a Bayesian framework can be used to: 

i) predict interactions, using host-vector and predator-prey interactions as an example; 
ii) incorporate any factor that can be represented as a spatio-temporal distribution as a potential niche dimension, using a publicly available modelling platform - SPECIES ( for niche and community modelling to illustrate this point; 
iii) disentangle causal chains by showing how confounders can be identified and accounted for using as an example the causal chain: carnivore-herbivore-vegetation-climate.

Dr. Gerardo Suzan

Full Title: Multi-host, Multi-pathogen and Multi-vector approach to Identify Emerging Patterns in Disease Ecology: Examples from Neotropical and Nearctic Mexico

Anthropogenic activities such as increased deforestation, land use changes and urbanization have changed intra and interspecies interactions yielding novel species assemblages impacting ecosystem function and structure. To identify relevant interactions driving infectious diseases, a multihost-multivector-multipathogen approach is needed. 

Using metacommunity and landscape ecology, co-occurrence data, and network analysis, 
Dr. Gerardo Suzan will describe different disease systems in Neotropical and Nearctic regions in Mexico. Dr. Suzan will present studies performed at different spatial scales identifying community attributes and landscape metrics that relate to different infectious diseases (Bartonella, hantavirus, coronaviruses and flaviviruses) in bird, bat, rodent and viral species assemblages. Using these integrated methodologies, public health scientists may better evaluate the factors that predispose certain times and places for the origin and emergence of infectious diseases, and will provide important information for conservation biologists to identify emerging patterns that compromise diversity or ecosystem services.