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Cutaneous leishmaniasis (CL) is a neglected tropical disease transmitted by species of Phlebotominae sand flies. CL is responsible for more than 1000 reported cases per year in Ecuador. Vector collection studies in Ecuador suggest that there is a strong association between the ecological diversity of an ecosystem, the presence of potential alternative or reservoir hosts and the abundance of sand fly species. Data collected from a coastal community in Ecuador showed that Leishmania parasites may be circulating in diverse hosts, including mammalian and potentially avian species, and these hosts may serve as potential hosts for the parasite. There has been limited reporting of CL cases in Ecuador because the disease is non-fatal and its surveillance system is passive. Hence, the actual incidence of CL is unknown. In this study, an epidemic model was developed and analysed to understand the complexity of CL transmission dynamics with potential non-human hosts in the coastal ecosystem and to estimate critical epidemiological quantities for Ecuador. The model is fitted to the 2010 CL outbreak in the town of Valle Hermoso in the Santo Domingo de los Tsachilas province of Ecuador and parameters such as CL transmission rates in different types of hosts (primary and alternative), and levels of case reporting in the town are estimated. The results suggest that the current surveillance in this region fails to capture 38% (with 95% CI (29%, 47%)) of the actual number of cases under the assumption that alternative hosts are dead-end hosts and that the mean CL reproduction number in the town is 3.9. This means that on the average 3.9 new human CL cases were generated by a single infectious human in the town during the initial period of the 2010 outbreak. Moreover, major outbreaks of CL in Ecuador in coastal settings are unavoidable until reporting through the surveillance system is improved and alternative hosts are managed properly. The estimated infection transmission probabilities from alternative hosts to sand flies, and sand flies to alternative hosts are 27% and 32%, respectively. The analysis highlights that vector control and alternative host management are two effective programmes for Ecuador but need to be implemented concurrently to avoid future major outbreaks.

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Leishmaniasis is a neglected tropical disease caused by the Leishmania parasite and transmitted by the Phlebotominae subfamily of sandflies, which infects humans and other mammals. Clinical manifestations of the disease include cutaneous leishmaniasis (CL), mucocutaneous leishmaniasis (MCL) and visceral leishmaniasis (VL) with a majority (more than three-quarters) of worldwide cases being CL. There are a number of risk factors for CL, such as the presence of multiple reservoirs, the movement of individuals, inequality, and social determinants of health. However, studies related to the role of these factors in the dynamics of CL have been limited. In this work, we (i) develop and analyze a vector-borne epidemic model to study the dynamics of CL in two ecologically distinct CL-affected regions-Madrid, Spain and Tolima, Colombia; (ii) derived three different methods for the estimation of model parameters by reducing the dimension of the systems; (iii) estimated reproduction numbers for the 2010 outbreak in Madrid and the 2016 outbreak in Tolima; and (iv) compared the transmission potential of the two economically-different regions and provided different epidemiological metrics that can be derived (and used for evaluating an outbreak), once R0 is known and additional data are available. On average, Spain has reported only a few hundred CL cases annually, but in the course of the outbreak during 2009⁻2012, a much higher number of cases than expected were reported and that too in the single city of Madrid. Cases in humans were accompanied by sharp increase in infections among domestic dogs, the natural reservoir of CL. On the other hand, CL has reemerged in Colombia primarily during the last decade, because of the frequent movement of military personnel to domestic regions from forested areas, where they have increased exposure to vectors. In 2016, Tolima saw an unexpectedly high number of cases leading to two successive outbreaks. On comparing, we estimated reproduction number of the Madrid outbreak to be 3.1 (with range of 2.8⁻3.9), which was much higher than reproduction number estimates of the Tolima first outbreak 1.2 (with range of 1.1⁻1.3), and the estimate for the second outbreak in Tolima of 1.019 (with range of 1.018⁻1.021). This suggests that the epidemic outbreak in Madrid was much more severe than the Tolima outbreak, even though Madrid was economically better-off compared to Tolima. It indicates a potential relationship between urban development and increasing health disparities.

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RESUMEN Este trabajo presenta una experiencia educativa, parte de las actividades del proyecto Caribbean Computing Center for Excellence, desarrollada en la Universidad del Turabo del Sistema Universitario Ana G. Méndez en Puerto Rico, otras universidades puertorriqueñas y en la Universidad de las Islas Vírgenes. El proyecto contempla dos componentes: uno orientado a estudiantes de pregrado y otro a estudiantes preuniversitarios, que se complementan con la mentoría ofrecida por los estudiantes universitarios a los estudiantes preuniversitarios para desarrollar sus proyectos de investigación, mediante una metodología guiada por el aprendizaje basado en proyectos y el aprendizaje activo. Queremos argumentar que estas son estrategias apropiadas para incentivar y orientar a estudiantes a estudiar pregrados y posgrados en diferentes áreas de la computación y la ingeniería, pero principalmente queremos mostrar su utilidad para iniciar a los estudiantes en la investigación científica en estas áreas.

ABSTRACT This work presents an educational experience, which is part of the activities of the project Caribbean Computing Center for Excellence, developed at the University of Turabo in Puerto Rico, from the Ana G. Mendez University System, other Puerto Rican universities and the University of the Virgin Islands. The project includes two components, one aimed at undergraduates and other to precollege students, both are complementary through the mentoring done by undergraduate students to precollege students to develop their research projects using a methodology focused on project based learning and active learning. We want to discuss that these are appropriate strategies to encourage and guide students to pursue undergraduate and graduate programs in different areas of computing and engineering, but mainly we want to show their usefulness to initiate the students in scientific research in these areas.

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OBJECTIVE: To stratify and understand the potential transmission processes of Zika virus in Colombia, in order to effectively address the efforts on surveillance and disease control. METHODS: We compare R0 of Zika for municipalities based on data from the regional surveillance system of Antioquia, Colombia. The basic reproduction number (R0 ) and its 95% confidence intervals were estimated from an SIR model with implicit vector dynamics, in terms of recovered individuals in each time unit, using an approximate solution. These parameters were estimated fitting the solution of the model to the daily cumulative frequency of each Zika case according to symptoms onset date relative to the index case reported to the local surveillance system. RESULTS: R0 was estimated for 20 municipalities with a median of 30 000 inhabitants, all located less than 2200 m above sea level. The reported cases ranged from 17 to 347 between these municipalities within 4 months (January to April of 2016). The results suggest that 15 municipalities had a high transmission potential (R0  > 1), whereas in five municipality transmissions were potentially not sustaining (R0  < 1), although the upper bound of the confidence interval of the R0 for 3 of these 5 was greater than one, indicating the possibility of an outbreak later on. CONCLUSION: The study identified high-risk municipalities (R0  > 1) and provide a technique to optimise surveillance and control of Zika. Health authorities should promote the collection, analysis, modelling and sharing of anonymous data onto individual cases to estimate R0 .

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