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Background: Zika is of great medical relevance due to its rapid geographical spread in 2015 and 2016 in South America and its serious implications, for example, certain birth defects. Recent epidemics urgently require a better understanding of geographic patterns of the Zika virus transmission risk. This study aims to map the Zika virus transmission risk in South and Central America. We applied the maximum entropy approach, which is common for species distribution modelling, but is now also widely in use for estimating the geographical distribution of infectious diseases.
Methods: As predictor variables we used a set of variables considered to be potential drivers of both direct and indirect effects on the emergence of Zika. Specifically, we considered (a) the modelled habitat suitability for the two main vector species Aedes aegypti and Ae. albopictus as a proxy of vector species distributions; (b) temperature, as it has a great influence on virus transmission; (c) commonly called evidence consensus maps (ECM) of human Zika virus infections on a regional scale as a proxy for virus distribution; (d) ECM of human dengue virus infections and, (e) as possibly relevant socio-economic factors, population density and the gross domestic product.
Results: The highest values for the Zika transmission risk were modelled for the eastern coast of Brazil as well as in Central America, moderate values for the Amazon basin and low values for southern parts of South America. The following countries were modelled to be particularly affected: Brazil, Colombia, Cuba, Dominican Republic, El Salvador, Guatemala, Haiti, Honduras, Jamaica, Mexico, Puerto Rico and Venezuela. While modelled vector habitat suitability as predictor variable showed the highest contribution to the transmission risk model, temperature of the warmest quarter contributed only comparatively little. Areas with optimal temperature conditions for virus transmission overlapped only little with areas of suitable habitat conditions for the two main vector species. Instead, areas with the highest transmission risk were characterised as areas with temperatures below the optimum of the virus, but high habitat suitability modelled for the two main vector species.
Conclusion: Modelling approaches can help estimating the spatial and temporal dynamics of a disease. We focused on the key drivers relevant in the Zika transmission cycle (vector, pathogen, and hosts) and integrated each single component into the model. Despite the uncertainties generally associated with modelling, the approach applied in this study can be used as a tool and assist decision making and managing the spread of Zika.
The genus Ebolavirus comprises some of the deadliest viruses for primates and humans and associated disease outbreaks are increasing in Africa. Different evidence suggests that bats are putative reservoir hosts and play a major role in the transmission cycle of these filoviruses. Thus, detailed knowledge about their distribution might improve risk estimations of where future disease outbreaks might occur. A MaxEnt niche modelling approach based on climatic variables and land cover was used to investigate the potential distribution of 9 bat species associated to the Zaire ebolavirus. This viral species has led to major Ebola outbreaks in Africa and is known for causing high mortalities. Modelling results suggest suitable areas mainly in the areas near the coasts of West Africa with extensions into Central Africa, where almost all of the 9 species studied find suitable habitat conditions. Previous spillover events and outbreak sites of the virus are covered by the modelled distribution of 3 bat species that have been tested positive for the virus not only using serology tests but also PCR methods. Modelling the habitat suitability of the bats is an important step that can benefit public information campaigns and may ultimately help control future outbreaks of the disease.
The recent advances in molecular methods and data processing have facilitated research on anisakid nematodes. While most research efforts were made regarding the genus Anisakis, since this genus is held responsible for the majority of reported clinical signs, there is still a demand for data on the genus Pseudoterranova. Several case studies of severe invasive anisakidosis affecting various organs caused by species of the P. decipiens complex have been described. To better understand the way these parasites might infest their fish host, we examined whether parasite location within the fish host affects gene expression. A de novo assembly of the transcriptome of Pseudoterranova bulbosa, isolated from North Atlantic cod, was analysed for patterns of differential gene expression between samples taken from liver and viscera. We additionally searched for homologs to known nematode allergens, to give a first estimate of the potential allergenicity of P. bulbosa. There was a subtle difference in the gene expression of samples taken from liver and viscera. Seventy genes were differentially expressed, 32 genes were upregulated in parasites isolated from liver and 38 genes were upregulated in parasites from viscera. Homologs of five nematode allergens were identified among the genes expressed by P. bulbosa. Our transcriptome of P. bulbosa will be a valuable resource for further meta-analyses and resequencing projects.