Rift Valley fever: an open-source transmission dynamics simulation model

Robert Sumaye, Famke Jansen, Dirk Berkvens, Bernard De Baets, Eveline Geubels, Etienne Thiry, Meryam Krit

    Research output: Contribution to journalA1: Web of Science-article

    Abstract

    Rift Valley fever (RVF) is one of the major viral zoonoses in Africa, affecting humans and several domestic animal species. The epidemics in eastern Africa occur in a 5-15 year cycle coinciding with abnormally high rainfall generally associated to the warm phase of the El Niño event. However, recently, evidence has been gathered of inter-epidemic transmission. An open-source, easily applicable, accessible and modifiable model was built to simulate the transmission dynamics of RVF. The model was calibrated using data collected in the Kilombero Valley in Tanzania with people and cattle as host species and Ædes mcintoshi, Æ. ægypti and two Culex species as vectors. Simulations were run over a period of 27 years using standard parameter values derived from two previous studies in this region. Our model predicts low-level transmission of RVF, which is in line with epidemiological studies in this area. Emphasis in our simulation was put on both the dynamics and composition of vector populations in three ecological zones, in order to elucidate the respective roles played by different vector species: the model output did indicate the necessity of Culex involvement and also indicated that vertical transmission in Ædes mcintoshi may be underestimated. This model, being built with open-source software and with an easy-to-use interface, can be adapted by researchers and control program managers to their specific needs by plugging in new parameters relevant to their situation and locality.

    Original languageEnglish
    Article numbere0209929
    JournalPLoS ONE
    Volume14
    Issue number1
    Number of pages27
    ISSN1932-6203
    DOIs
    Publication statusPublished - 2019

    Fingerprint Dive into the research topics of 'Rift Valley fever: an open-source transmission dynamics simulation model'. Together they form a unique fingerprint.

    Cite this