e-infrastructure Roadmap for Open Science in Agriculture

A bibliometric study

The e-ROSA project seeks to build a shared vision of a future sustainable e-infrastructure for research and education in agriculture in order to promote Open Science in this field and as such contribute to addressing related societal challenges. In order to achieve this goal, e-ROSA’s first objective is to bring together the relevant scientific communities and stakeholders and engage them in the process of coelaboration of an ambitious, practical roadmap that provides the basis for the design and implementation of such an e-infrastructure in the years to come.

This website highlights the results of a bibliometric analysis conducted at a global scale in order to identify key scientists and associated research performing organisations (e.g. public research institutes, universities, Research & Development departments of private companies) that work in the field of agricultural data sources and services. If you have any comment or feedback on the bibliometric study, please use the online form.

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Simulation Modelling of Population Dynamics of Mosquito Vectors for Rift Valley Fever Virus in a Disease Epidemic Setting


Background: Rift Valley Fever (RVF) is weather dependent arboviral infection of livestock and humans. Population dynamics of mosquito vectors is associated with disease epidemics. In our study, we use daily temperature and rainfall as model inputs to simulate dynamics of mosquito vectors population in relation to disease epidemics. Methods/Findings: Time-varying distributed delays (TVDD) and multi-way functional response equations were implemented to simulate mosquito vectors and hosts developmental stages and to establish interactions between stages and phases of mosquito vectors in relation to vertebrate hosts for infection introduction in compartmental phases. An open-source modelling platforms, Universal Simulator and Qt integrated development environment were used to develop models in C++ programming language. Developed models include source codes for mosquito fecundity, host fecundity, water level, mosquito infection, host infection, interactions, and egg time. Extensible Markup Language (XML) files were used as recipes to integrate source codes in Qt creator with Universal Simulator plug-in. We observed that Floodwater Aedines and Culicine population continued to fluctuate with temperature and water level over simulation period while controlled by availability of host for blood feeding. Infection in the system was introduced by floodwater Aedines. Culicines pick infection from infected host once to amplify disease epidemic. Simulated mosquito population show sudden unusual increase between December 1997 and January 1998 a similar period when RVF outbreak occurred in Ngorongoro district. Conclusion/Significance: Findings presented here provide new opportunities for weather-driven RVF epidemic simulation modelling. This is an ideal approach for understanding disease transmission dynamics towards epidemics prediction, prevention and control. This approach can be used as an alternative source for generation of calibrated RVF epidemics data in different settings.

  • TZ
  • DK
  • Aarhus_Univ (DK)
Data keywords
  • XML
Agriculture keywords
  • livestock
Data topic
  • modeling
Document type

Inappropriate format for Document type, expected simple value but got array, please use list format

Institutions 10 co-publis
  • Aarhus_Univ (DK)
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e-ROSA - e-infrastructure Roadmap for Open Science in Agriculture has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 730988.
Disclaimer: The sole responsibility of the material published in this website lies with the authors. The European Union is not responsible for any use that may be made of the information contained therein.