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Register a new userSpatio-temporal Dynamics of Foot-and-Mouth Disease Virus in South America
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Although foot-and-mouth disease virus (FMDV) incidence has decreased in South America over the last years, the pathogen still circulates in the region and the risk of re-emergence in previously FMDV-free areas is a veterinary public health concern. In this paper we merge environmental, epidemiological and genetic data to reconstruct spatiotemporal patterns and determinants of FMDV serotypes A and O dispersal in South America. Our dating analysis suggests that serotype A emerged in South America around 1930, while serotype O emerged around 1990. The rate of evolution for serotype A was significantly higher compared to serotype O. Phylogeographic inference identified two well-connected sub networks of viral flow, one including Venezuela, Colombia and Ecuador; another including Brazil, Uruguay and Argentina. The spread of serotype A was best described by geographic distances, while trade of live cattle was the predictor that best explained serotype O spread. Our findings show that the two serotypes have different underlying evolutionary and spatial dynamics and may pose different threats to control programmes. Key-words: Phylogeography, foot-and-mouth disease virus, South America, animal trade.
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We study the spatio-temporal patterns of the proportion of influenza B out of laboratory confirmations of both influenza A and B, with data from 139 countries and regions downloaded from the FluNet compiled by the World Health Organization, from January 2006 to October 2015, excluding 2009. We restricted our analysis to 34 countries that reported more than 2000 confirmations for each of types A and B over the study period. We find that Pearsons correlation is 0.669 between effective distance from Mexico and influenza B proportion among the countries from January 2006 to October 2015. In the United States, influenza B proportion in the pre-pandemic period (2003-2008) negatively correlated with that in the post-pandemic era (2010-2015) at the regional level. Our study limitations are the country-level variations in both surveillance methods and testing policies. Influenza B proportion displayed wide variations over the study period. Our findings suggest that even after excluding 2009s data, the influenza pandemic still has an evident impact on the relative burden of the two influenza types. Future studies could examine whether there are other additional factors. This study has potential implications in prioritizing public health control measures.
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In this chapter, an application of Mathematical Epidemiology to crop vector-borne diseases is presented to investigate the interactions between crops, vectors, and virus. The main illustrative example is the cassava mosaic disease (CMD). The CMD virus has two routes of infection: through vectors and also through infected crops. In the field, the main tool to control CMD spreading is roguing. The presented biological model is sufficiently generic and the same methodology can be adapted to other crops or crop vector-borne diseases. After an introduction where a brief history of crop diseases and useful information on Cassava and CMD is given, we develop and study a compartmental temporal model, taking into account the crop growth and the vector dynamics. A brief qualitative analysis of the model is provided,i.e., existence and uniqueness of a solution,existence of a disease-free equilibrium and existence of an endemic equilibrium. We also provide conditions for local (global) asymptotic stability and show that a Hopf Bifurcation may occur, for instance, when diseased plants are removed. Numerical simulations are provided to illustrate all possible behaviors. Finally, we discuss the theoretical and numerical outputs in terms of crop protection.
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