Beatriz Martinez Lopez, PhD; MPVM

Associate Professor

  • Source: Scopus
  • Calculated based on no. of publications stored in Pure and citations from Scopus
20072020

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Personal profile

Research interests

My research focus on the development and implementation of novel epidemiological methods to gain knowledge about the evolution, spread and impact of infectious diseases and to support health policies.

I have been primarily working on epidemiological modeling and risk assessment for the evaluation of the potential introduction and/or spread of diseases affecting domestic and/or wild animal populations. I am also interesting in the use of quantitative methods related with spatial epidemiology, network analysis and graph theory and the use of Big Data analytics and Bayesian modeling to identify individuals, areas and time periods at higher risk of becoming infected and to detect the most important factors contributing to such risk. Currently I am working in the integration of these and other methods (i.e. Big Data analytics, data mining, time-series analysis) in operational, user-friendly, web-based, platforms with the aim to provide a near real-time monitoring and early warning systems for better prevent and control transboundary, emerging and re-emerging infectious diseases at a local and global scale.

Some of the diseases I am currently working with are African swine fever, classical swine fever, foot-and-mouth disease, African horse sickness, bluetongue, avian influenza, West Nile, Rift Valley Fever, bovine tuberculosis and Shrimp and Salmon diseases.

Research interests

My research focus on the development and implementation of novel epidemiological methods to gain knowledge about the evolution, spread and impact of infectious diseases and to support health policies.

I have been primarily working on epidemiological modeling and risk assessment for the evaluation of the potential introduction and/or spread of diseases affecting domestic and/or wild animal populations. I am also interesting in the use of quantitative methods related with spatial epidemiology, network analysis and graph theory and the use of Big Data analytics and Bayesian modeling to identify individuals, areas and time periods at higher risk of becoming infected and to detect the most important factors contributing to such risk. Currently I am working in the integration of these and other methods (i.e. Big Data analytics, data mining, time-series analysis) in operational, user-friendly, web-based, platforms with the aim to provide a near real-time monitoring and early warning systems for better prevent and control transboundary, emerging and re-emerging infectious diseases at a local and global scale.

Some of the diseases I am currently working with are African swine fever, classical swine fever, foot-and-mouth disease, African horse sickness, bluetongue, avian influenza, West Nile, Rift Valley Fever, bovine tuberculosis and Shrimp and Salmon diseases.

Keywords

  • SF Animal culture
  • Epidemiology
  • Risk assessment
  • Modeling
  • Spatial epidemiology
  • Network analysis
  • Infectious diseases
  • Bayesian methods
  • Spatial analysis
  • statistical models
  • swine diseases
  • livestock health
  • Big Data
  • surveillance research
  • preventive veterinary medicine
  • international programs
  • early warning systems

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