Jones Albuquerque

Schistosomiasis transmission and environmental change: a spatio-temporal analysis in Porto de Galinhas, Pernambuco - Brazil

BackgroundIn Brazil, schistosomiasis mansoni infection is an endemic disease that mainly affects the country’s rural populations who carry out domestic and social activities in rivers and water accumulations that provide shelter for the snails of the disease. The process of rural migration to urban centers and the disorderly occupation of natural environments by these populations from endemic areas have favored expansion of schistosomiasis to locations that had been considered to be disease-free. Based on environmental changes that have occurred in consequent to an occupation and urbanization process in the locality of Porto de Galinhas, the present study sought to identify the relationship between those chances, measure by remote-sensing techniques, and establish a new endemic area for schistosomiasis on the coast of Pernambuco State - Brazil.MethodsTo gather prevalence data, two parasitological census surveys were conducted (2000 and 2010) using the Kato-Katz technique. Two malacological surveys were also conducted in the same years in order to define the density and infection rate of the intermediate host. Based on these data, spatial analyses were done, resulting in maps of the risk of disease transmission. To ascertain the environmental changes that have occurred at the locality, images from the QuickBird satellite were analyzed, thus resulting in land use maps.ResultsOver this 10-year period, the foci of schistosomiasis became more concentrated in the Salinas district. This area was considered to be at the greatest risk of schistosomiasis transmission and had the highest prevalence rates over this period. The study illustrated that this was the area most affected by the environmental changes resulting from the disorderly urbanization process, which gave rise to unsanitary environments that favored the establishment and maintenance of foci of schistosomiasis transmission, thereby consolidating the process of expansion and endemization of this parasitosis.

Applying PBL in Software Engineering Education

The Information Communication and Technology – ICT industry is facing a market of constant changes and challenges. These characteristics demand the ICT professionals to have a wide vision of the problem, rather than just knowledge on the technology. In this context, the objective of this article is to propose an innovative pedagogical methodology based on PBL (Problem Based Learning) to improve the learning effectiveness in software engineering, through the implementation of software factories, where students can work together to solve real problems. This methodology is running in a graduate course in Software Engineering managed by CESAR , a research institute with experience in the development of innovative software. Some important results about this course are presented and discussed in this paper.

Aspectos ecológicos e levantamento malacológico para identificação de áreas de risco para transmissão da esquistossomose mansoni no litoral norte de Pernambuco, Brasil

Realizou-se levantamento malacologico na praia de Carne de Vaca, municipio de Goiana, litoral norte de Pernambuco, entre novembro de 2006 e outubro de 2007, com o objetivo de conhecer a fauna malacologica dessa localidade e verificar as condicoes naturais, pouco ou bastante alteradas das areas de estudo atraves da aplicacao de um protocolo de avaliacao de diversidade de habitats. Foram coletados 5.912 moluscos, representados por sete especies e quatro familias, dos quais, 5.209 exemplares de Biomphalaria glabrata (Say, 1818), 113 de Drepanotrema lucidum (Pfeiffer, 1839), 55 de Drepanotrema cimex (Moricand, 1837), 13 de Drepanotrema anatinum (Pfeiffer, 1839), 222 de Melanoides tuberculatus (Muller, 1774), 263 de Pomacea sp. e 37 de Physa marmorata Guilding, 1828. Entre os exemplares de B. glabrata coletados, 44 mostraram-se positivos para Schistosoma mansoni Sambon, 1907 e 91 mostraram-se positivos para outras larvas de trematodeos. Um exemplar de Pomacea sp. mostrou-se positivo para larva de trematodeo. Os dados obtidos, georreferenciados espacialmente, serao utilizados para a determinacao das areas de risco para a transmissao da esquistossomose na praia de Carne de Vaca, alem de simulacoes computacionais para estudos de previsibilidade e comportamento do processo de expansao da esquistossomose no estado de Pernambuco.

Saúde na Copa: The World's First Application of Participatory Surveillance for a Mass Gathering at FIFA World Cup 2014, Brazil.

Background The 2005 International Health Regulations (IHRs) established parameters for event assessments and notifications that may constitute public health emergencies of international concern. These requirements and parameters opened up space for the use of nonofficial mechanisms (such as websites, blogs, and social networks) and technological improvements of communication that can streamline the detection, monitoring, and response to health problems, and thus reduce damage caused by these problems. Specifically, the revised IHR created space for participatory surveillance to function, in addition to the traditional surveillance mechanisms of detection, monitoring, and response. Participatory surveillance is based on crowdsourcing methods that collect information from society and then return the collective knowledge gained from that information back to society. The spread of digital social networks and wiki-style knowledge platforms has created a very favorable environment for this model of production and social control of information. Objective The aim of this study was to describe the use of a participatory surveillance app, Healthy Cup, for the early detection of acute disease outbreaks during the Fédération Internationale de Football Association (FIFA) World Cup 2014. Our focus was on three specific syndromes (respiratory, diarrheal, and rash) related to six diseases that were considered important in a mass gathering context (influenza, measles, rubella, cholera, acute diarrhea, and dengue fever). Methods From May 12 to July 13, 2014, users from anywhere in the world were able to download the Healthy Cup app and record their health condition, reporting whether they were good, very good, ill, or very ill. For users that reported being ill or very ill, a screen with a list of 10 symptoms was displayed. Participatory surveillance allows for the real-time identification of aggregates of symptoms that indicate possible cases of infectious diseases. Results From May 12 through July 13, 2014, there were 9434 downloads of the Healthy Cup app and 7155 (75.84%) registered users. Among the registered users, 4706 (4706/7155, 65.77%) were active users who posted a total of 47,879 times during the study period. The maximum number of users that signed up in one day occurred on May 30, 2014, the day that the app was officially launched by the Minister of Health during a press conference. During this event, the Minister of Health announced the special government program Health in the World Cup on national television media. On that date, 3633 logins were recorded, which accounted for more than half of all sign-ups across the entire duration of the study (50.78%, 3633/7155). Conclusions Participatory surveillance through community engagement is an innovative way to conduct epidemiological surveillance. Compared to traditional epidemiological surveillance, advantages include lower costs of data acquisition, timeliness of information collected and shared, platform scalability, and capacity for integration between the population being served and public health services.

The schisto track: a system for gathering and monitoring epidemiological surveys by connecting geographical information systems in real time

Background Using the Android platform as a notification instrument for diseases and disorders forms a new alternative for computerization of epidemiological studies. Objective The objective of our study was to construct a tool for gathering epidemiological data on schistosomiasis using the Android platform. Methods The developed application (app), named the Schisto Track, is a tool for data capture and analysis that was designed to meet the needs of a traditional epidemiological survey. An initial version of the app was finished and tested in both real situations and simulations for epidemiological surveys. Results The app proved to be a tool capable of automation of activities, with data organization and standardization, easy data recovery (to enable interfacing with other systems), and totally modular architecture. Conclusions The proposed Schisto Track is in line with worldwide trends toward use of smartphones with the Android platform for modeling epidemiological scenarios.

The Malaria System MicroApp: A New, Mobile Device-Based Tool for Malaria Diagnosis

Background Malaria is a public health problem that affects remote areas worldwide. Climate change has contributed to the problem by allowing for the survival of Anopheles in previously uninhabited areas. As such, several groups have made developing news systems for the automated diagnosis of malaria a priority. Objective The objective of this study was to develop a new, automated, mobile device-based diagnostic system for malaria. The system uses Giemsa-stained peripheral blood samples combined with light microscopy to identify the Plasmodium falciparum species in the ring stage of development. Methods The system uses image processing and artificial intelligence techniques as well as a known face detection algorithm to identify Plasmodium parasites. The algorithm is based on integral image and haar-like features concepts, and makes use of weak classifiers with adaptive boosting learning. The search scope of the learning algorithm is reduced in the preprocessing step by removing the background around blood cells. Results As a proof of concept experiment, the tool was used on 555 malaria-positive and 777 malaria-negative previously-made slides. The accuracy of the system was, on average, 91%, meaning that for every 100 parasite-infected samples, 91 were identified correctly. Conclusions Accessibility barriers of low-resource countries can be addressed with low-cost diagnostic tools. Our system, developed for mobile devices (mobile phones and tablets), addresses this by enabling access to health centers in remote communities, and importantly, not depending on extensive malaria expertise or expensive diagnostic detection equipment.

Using mobile technology to conduct epidemiological investigations

INTRODUCTION The aim of this study was to report the experience of an epidemiological field survey for which data were collected and analyzed using tablets. METHODS The devices used Epi Info 7 (Android version), which has been modeled a database with variables of the traditional form. RESULTS Twenty-one households were randomly selected in the study area; 75 residents were registered and completed household interviews with socioeconomic and environmental risk variables. CONCLUSIONS This new technology is a valuable tool for collecting and analyzing data from the field, with advantageous benefits to epidemiological surveys.

A proposal for automatic diagnosis of malaria: extended abstract

This paper presents a methodology for automatic diagnosis of malaria using computer vision techniques combined with artificial intelligence. We had obtained an accuracy rate of 74% in the detection system.

Forecasting Chaotic and Non-Linear Time Series with Artificial Intelligence and Statistical Measures

The most of the classical time series literature suppose that the series are stationary (or that the time series can be transformed in stationary series through some simple transformation, such as differentiation), and that the series phenomenon is a linear process. In this sense, all time series can be represented by linear models. However, time series encountered in practice way not always exhibit characteristics of a linear process, then there is not any reason that generalizes the linearity supposition for a real world time series. In fact, the high complexity of the real world phenomena induce to think, more naturally, about non-linear and chaotic structures presents in the data of time series than linear structures. Loosely speaking, a time series is a set of observations made sequentially in time. Examples of real world time series abound in such fields as economics, business, engineering, natural sciences (commonly in the meteorology, geophysics and biology), social sciences, etc (Lam, 1998). Phenomena like human breath rate, human electrocardiogram, earthquake, stock prizes are some examples of real world time series. A typical intrinsic feature of a time series is that the adjacent observations are dependent, where the nature of this dependence among time series observations is of considerable practical interest. The time series analysis and forecasting is concerned in mathematical and statistical (and more recently, computational) modelling for analysis of this dependence. Mathematical and statistical methods are successfully used for time series analysis and forecasting (Box et al., 1994; Gooijer and Kumar, 1992; Kantz, 2004), but sometimes these approaches are not trivial to apply in practical sense, considering that some times series (mainly real world time series, as the financial or economical series, climatic series, etc) have a chaotic and non-linear behavior and many types of components, such as trends, seasonality, impulses, steps, model exchange and other uncontrolled features. Alternatively, in the last two decades, the Artificial Neural Network (ANN) model have been widely used in order to solve the time series forecasting problem, presenting less mathematical complexity than the typical non-linear statistical methods. However, the ANN

Using Mathematical Modeling to Simulate Chagas Disease Spread by Congenital and Blood Transfusion Routes

Chagas disease is an important health problem in Latin America. Due to the mobility of Latin American population, the disease has spread to other countries. In this work, we used a mathematical model to gain insight into the disease dynamics in a scenario without vector presence as well as to assess the epidemiological effects provided by control strategies.