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Analyzing the Spread of Chikungunya in the Caribbean 2013-2015

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This work examines one dimension of the effect that complex human transport systems have on the spread of Chikungunya Virus (CHIKV) in the Caribbean from 2013 to 2015. CHIKV is transmitted by mosquitos and its novel spread through the Caribbean

This work examines one dimension of the effect that complex human transport systems have on the spread of Chikungunya Virus (CHIKV) in the Caribbean from 2013 to 2015. CHIKV is transmitted by mosquitos and its novel spread through the Caribbean islands provided a chance to examine disease transmission through complex human transportation systems. Previous work by Cauchemez et al. had shown a simple distance-based model successfully predict CHIKV spread in the Caribbean using Markov chain Monte Carlo (MCMC) statistical methods. A MCMC simulation is used to evaluate different transportation methods (air travel, cruise ships, and local maritime traffic) for the primary transmission patterns through linear regression. Other metrics including population density to account for island size variation and dengue fever incidence rates as a proxy for vector control and health spending were included. Air travel and cruise travel were gathered from monthly passenger arrivals by island. Local maritime traffic is approximated with a gravity model proxy incorporating GDP-per-capita and distance and historic dengue rates were used for determine existing vector control measures for the islands. The Caribbean represents the largest cruise passenger market in the world, cruise ship arrivals were expected to show the strongest signal; however, the gravity model representing local traffic was the best predictor of infection routes. The early infected islands (<30 days) showed a heavy trend towards an alternate primary transmission but our consensus model able to predict the time until initial infection reporting with 94.5% accuracy for islands 30 days post initial reporting. This result can assist public health entities in enacting measures to mitigate future epidemics and provide a modelling basis for determining transmission modes in future CHIKV outbreaks.

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2015-12

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Genetic diversity across the pseudoautosomal boundary varies across human populations

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Unlike the autosomes, recombination on the sex chromosomes is limited to the pseudoautosomal regions (PARs) at each end of the chromosome. PAR1 spans approximately 2.7 Mb from the tip of the proximal arm of each sex chromosome, and a pseudoautosomal

Unlike the autosomes, recombination on the sex chromosomes is limited to the pseudoautosomal regions (PARs) at each end of the chromosome. PAR1 spans approximately 2.7 Mb from the tip of the proximal arm of each sex chromosome, and a pseudoautosomal boundary between the PAR1 and non-PAR region is thought to have evolved from a Y-specific inversion that suppressed recombination across the boundary. In addition to the two PARs, there is also a human-specific X-transposed region (XTR) that was duplicated from the X to the Y chromosome. Genetic diversity is expected to be higher in recombining than nonrecombining regions, particularly because recombination reduces the effects of linked selection, allowing neutral variation to accumulate. We previously showed that diversity decreases linearly across the previously defined pseudoautosomal boundary (rather than drop suddenly at the boundary), suggesting that the pseudoautosomal boundary may not be as strict as previously thought. In this study, we analyzed data from 1271 genetic females to explore the extent to which the pseudoautosomal boundary varies among human populations (broadly, African, European, South Asian, East Asian, and the Americas). We found that, in all populations, genetic diversity was significantly higher in the PAR1 and XTR than in the non-PAR regions, and that diversity decreased linearly from the PAR1 to finally reach a non-PAR value well past the pseudoautosomal boundary in all populations. However, we also found that the location at which diversity changes from reflecting the higher PAR1 diversity to the lower nonPAR diversity varied by as much as 500 kb among populations. The lack of genetic evidence for a strict pseudoautosomal boundary and the variability in patterns of diversity across the pseudoautosomal boundary are consistent with two potential explanations: (1) the boundary itself may vary across populations, or (2) that population-specific demographic histories have shaped diversity across the pseudoautosomal boundary.

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2016-12