14 research outputs found

    Modeling the Influence of Environment and Intervention on Cholera in Haiti

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    We propose a simple model with two infective classes in order to model the cholera epidemic in Haiti. We include the impact of environmental events (rainfall, temperature and tidal range) on the epidemic in the Artibonite and Ouest regions by introducing terms in the transmission rate that vary with environmental conditions. We fit the model on weekly data from the beginning of the epidemic until December 2013, including the vaccination programs that were recently undertaken in the Ouest and Artibonite regions. We then modified these projections excluding vaccination to assess the programs' effectiveness. Using real-time daily rainfall, we found lag times between precipitation events and new cases that range from 3.4 to 8.4 weeks in Artibonite and 5.1 to 7.4 in Ouest. In addition, it appears that, in the Ouest region, tidal influences play a significant role in the dynamics of the disease. Intervention efforts of all types have reduced case numbers in both regions; however, persistent outbreaks continue. In Ouest, where the population at risk seems particularly besieged and the overall population is larger, vaccination efforts seem to be taking hold more slowly than in Artibonite, where a smaller core population was vaccinated. The models including the vaccination programs predicted that a year and six months later, the mean number of cases in Artibonite would be reduced by about two thousand cases, and in Ouest by twenty four hundred cases below that predicted by the models without vaccination. We also found that vaccination is best when done in the early spring, and as early as possible in the epidemic. Comparing vaccination between the first spring and the second, there is a drop of about 40% in the case reduction due to the vaccine and about 10% per year after that

    Kepler Data Validation I: Architecture, Diagnostic Tests, and Data Products for Vetting Transiting Planet Candidates

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    The Kepler Mission was designed to identify and characterize transiting planets in the Kepler Field of View and to determine their occurrence rates. Emphasis was placed on identification of Earth-size planets orbiting in the Habitable Zone of their host stars. Science data were acquired for a period of four years. Long-cadence data with 29.4 min sampling were obtained for approx. 200,000 individual stellar targets in at least one observing quarter in the primary Kepler Mission. Light curves for target stars are extracted in the Kepler Science Data Processing Pipeline, and are searched for transiting planet signatures. A Threshold Crossing Event is generated in the transit search for targets where the transit detection threshold is exceeded and transit consistency checks are satisfied. These targets are subjected to further scrutiny in the Data Validation (DV) component of the Pipeline. Transiting planet candidates are characterized in DV, and light curves are searched for additional planets after transit signatures are modeled and removed. A suite of diagnostic tests is performed on all candidates to aid in discrimination between genuine transiting planets and instrumental or astrophysical false positives. Data products are generated per target and planet candidate to document and display transiting planet model fit and diagnostic test results. These products are exported to the Exoplanet Archive at the NASA Exoplanet Science Institute, and are available to the community. We describe the DV architecture and diagnostic tests, and provide a brief overview of the data products. Transiting planet modeling and the search for multiple planets on individual targets are described in a companion paper. The final revision of the Kepler Pipeline code base is available to the general public through GitHub. The Kepler Pipeline has also been modified to support the Transiting Exoplanet Survey Satellite (TESS) Mission which is expected to commence in 2018

    A Two-Sex, Age-Structured Population Model in Discrete-Time

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    This work examines how the life history parameters effect the stable age distribution of the different classes and compares these results with the standard single sex model. The conditions necessary for a population projected forward in time to reach a stable age distribution is analyzed. The conditions for existence are dependent on the nature of the mating function, i.e. the rate at which the two sexes find each other and mate. In addition, the assumptions under which these mating functions are constructed have important implications for the dynamics of the population and ultimate age distribution, stable or not. An analysis of when including both sexes becomes essential to the understanding of reproductive strategies, examination of whether a population fulfils the necessary assumptions about mating to make certain statements about population growth, growth rates and relative fitness, and outlining an accessible approach to modeling the joint life histories will be of practical value. Toward this end, a framework for discrete-time two-sex models with age structure is developed. In addition a marriage (mating) function based on an analogy with foraging theory and preferences based on the predispositions of one age group for another is proposed. Some of the properties of these models and their solutions are also investigated

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