"Portuguese Observatory of Taeniasis and Cysticercosis": A "One Health" example for epidemiological surveillance of one neglected disease in a European country

Cysticercosis results from the ingestion Taenia solium eggs directly by faecal-oral route or contaminated food or water. Human tapeworm carriers who have become infected after ingesting pork meat contaminated with cysticerci release these eggs. Cysticercosis occurs after tapeworm eggs are ingested by an intermediate host (pig or human) and then hatch, migrate, and lodge in the host's tissues, where they develop onto larval cysticerci. When they lodged in the central nervous system of humans, results in the disease condition called Neurocysticercosis (NCC), with a heterogeneous manifestations depending of the locations of cysts, number, size and their stage of evolution (1). Consequently the prognostic ranges from asymptomatic to situations leading to death in 2% to 9.8%. of cases (7) In swine’s there are few studies, but recent works have proved that animals, for the same reasons, also have neurological abnormalities, expressed by seizures, stereotypic walk in circles, chewing motions with foamy salivation included tonic muscle contractions followed by a sudden diminution in all muscle tone leading to collapse (2). Conventional domestic wastewater treatment processes may not be totally effective in inactivating parasites eggs from Taenia solium, allowing some contamination of soils and agricultural products (11). In Portugal there are some evidence of aggregation of human cysticercosis cases in specific regions, bases in ecological design studies (6). There are few information about human tapeworm carriers and social and economic factors associated with them. Success in knowledge and consequently in lowering transmission is limited by the complex network of biological and social factors that maintain the spread. Effective control of mostly zoonosis require One Health approach, after a real knowledge and transparency in the information provided by the institutions responsible for both animal and human health, allowing sustained interventions targeted at the transmission cycle's crucial nodes. In general, the model used to control, reflects a rural reality, where pigs are raised freely, poor sanitation conditions and incipient sanitary inspection. In cysticercosis, pigs are obligate intermediate hosts and so considered as first targets for control and used as sentinels to monitor environmental T. solium contamination (3). Usually environmental contamination with Taenia spp. eggs is a key issue in most of studies with landscape factors influencing presence of Taenia spp. antigens in both pigs and humans (5). Soil-related factors as well as socio-economic and behavioural factors are associated with the emergence of significant clustering human cysticercosis (4,5). However scarce studies has been produced in urban environmental and in developed countries with the finality to characterize the spatial pattern. There are still few data available regarding its prevalence and spatial distribution; Transmission patterns are likely to exhibit correlations as housing conditions, water supply, basic sanitation, schooling and birthplace of the individual or relatives, more than pigs rearing free, soil conditions (9). As a matter of fact, tapeworm carriers from endemic zones can auto-infect or transmit infection to other people or arrive already suffering NCC (as a result of travelling to or being a citizen from an endemic cysticercosis country) to a free cysticercosis country. Transmission is fecal-oral; this includes transmission through person-to-person contact, through autoinfection, or through contaminated food This has been happening in different continents as North America (5.4–18% been autochthonous), Europe and Australia (7). Recently, case reports of NCC have also emerged from Muslim countries. (10). Actually, different papers relate an epidemic situation in Spain and Portugal (7, 8). However the kind of study done does not authorize such conclusion. There are no evidence that infections were acquired in Portugal and there are not characterized the mode of transmission. Papers with these kind of information will be allow to have economic consequences resulted from artificial trade barriers with serious consequences for pig producers and pig meat trade. We need transparency in information’s that allow provide the basis to support the development and targeting of future effective control programmes (and prove we need that). So, to have a real picture of the disease, it is necessary integrate data from human, animal and environmental factors surrounding human and pig cases to characterize the pattern of the transmission. The design needs to be able to capture unexpected, and not common outcomes (routine data). We need to think “One Health” to get a genuine image of the situation.

Constraint-Informed Information Systems in Space Management Utilization

Declarative techniques such as Constraint Programming can be very effective in modeling and assisting management decisions. We present a method for managing university classrooms which extends the previous design of a Constraint-Informed Information System to generate the timetables while dealing with spatial resource optimization issues. We seek to maximize space utilization along two dimensions: classroom use and occupancy rates. While we want to maximize the room use rate, we still need to satisfy the soft constraints which model students’ and lecturers’ preferences. We present a constraint logic programming-based local search method which relies on an evaluation function that combines room utilization and timetable soft preferences. Based on this, we developed a tool which we applied to the improvement of classroom allocation in a University. Comparing the results to the current timetables obtained without optimizing space utilization, the initial versions of our tool manages to reach a 30% improvement in space utilization, while preserving the quality of the timetable, both for students and lecturers.

10th European Conference on Information Systems Management

The 10th European Conference on Information Systems Management is being held at The University of Evora, Portugal on the 8 /9 September 2016. The Conference Chair is Paulo Silva and the Programme Chairs are Prof. Rui Quaresma and Prof. António Guerreiro. ECISM provides an opportunity for individuals researching and working in the broad field of information systems management, including IT evaluation to come together to exchange ideas and discuss current research in the field. This has developed into a particularly important forum for the present era, where the modern challenges of managing information and evaluating the effectiveness of related technologies are constantly evolving in the world of Big Data and Cloud Computing. We hope that this year’s conference will provide you with plenty of opportunities to share your expertise with colleagues from around the world. The keynote speakers for the Conference are Carlos Zorrinho from the Portuguese Delegation and Isabel Ramos from University of Minho, Portugal. ECISM 2016 received an initial submission of 84 abstracts. After the double blind peer review process 25 aca demic papers, 7 PhD research papers, 3 Masters research paper and 5 work in progress papers have been ac cepted for publication in these Conference Proceedings. These papers represent research from around the world, including Belgium, Brazil, China, Czech Republic, Kazakhstan, Malaysia, New Zealand, Norway, Oman, Poland, Portugal, South Africa, Sweden, The Netherlands, UK and Vietnam.

Improving understandability in consumer health information search: Uevora @ 2016 fire chis

This paper presents our work at 2016 FIRE CHIS. Given a CHIS query and a document associated with that query, the task is to classify the sentences in the document as relevant to the query or not; and further classify the relevant sentences to be supporting, neutral or opposing to the claim made in the query. In this paper, we present two different approaches to do the classification. With the first approach, we implement two models to satisfy the task. We first implement an information retrieval model to retrieve the sentences that are relevant to the query; and then we use supervised learning method to train a classification model to classify the relevant sentences into support, oppose or neutral. With the second approach, we only use machine learning techniques to learn a model and classify the sentences into four classes (relevant & support, relevant & neutral, relevant & oppose, irrelevant & neutral). Our submission for CHIS uses the first approach.