12 research outputs found

    Network analysis of spreading of dengue, Zika and chikungunya in the state of Bahia based on notified, confirmed and discarded cases

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    Despite successful results of using complex networks to model and characterize the spread of dengue cases, works to date have mainly used data from primarily reported cases, without further consideration whether they were later confirmed or not. On the other hand, a study of the interdependence of confirmed and discarded cases of arboviruses have emphasized that the co-circulation of three arboviruses—dengue, Zika and chikungunya—may have led to false diagnoses due to several similarities in the early symptoms of the three diseases on acute phase. This implies that case notifications of one disease could be confirmed cases of others, and that discarded cases must be taken into account to avoid misinterpretations of the phenomenon. In this work we investigated the consequences of including information from discarded and confirmed cases in the analysis of arbovirus networks. This is done by firstly evaluating the possible changes in the networks after removing the discarded cases from the database of each arbovirus, and secondly by verifying the cross-relationship of the indices of the networks of confirmed and discarded cases of arboviruses. As will be detailed later on, our results reveal changes in the network indices when compared to when only confirmed cases are considered. The magnitudes of the changes are directly proportional to the amount of discarded cases. The results also reveal a strong correlation between the average degree of the networks of discarded cases of dengue and confirmed cases of Zika, but only a moderate correlation between that for networks of discarded cases of dengue and confirmed cases of chikungunya. This finding is compatible with the fact that dengue and Zika diseases are caused by closely related flaviviruses, what is not the case of the chikungunya caused by a togavirus

    Complex network analysis of arboviruses in the same geographic domain: Differences and similarities.

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    Arbovirus can cause diseases with a broad spectrum from mild to severe and long-lasting symptoms, affecting humans worldwide and therefore considered a public health problem with global and diverse socio-economic impacts. Understanding how they spread within and across different regions is necessary to devise strategies to control and prevent new outbreaks. Complex network approaches have widespread use to get important insights on several phenomena, as the spread of these viruses within a given region. This work uses the motif-synchronization methodology to build time varying complex networks based on data of registered infections caused by Zika, chikungunya, and dengue virus from 2014 to 2020, in 417 cities of the state of Bahia, Brazil. The resulting network sets capture new information on the spread of the diseases that are related to the time delay in the synchronization of the time series among different municipalities. Thus the work adds new and important network-based insights to previous results based on dengue dataset in the period 2001-2016. The most frequent synchronization delay time between time series in different cities, which control the insertion of edges in the networks, ranges 7 to 14 days, a period that is compatible with the time of the individual-mosquito-individual transmission cycle of these diseases. As the used data covers the initial periods of the first Zika and chikungunya outbreaks, our analyses reveal an increasing monotonic dependence between distance among cities and the time delay for synchronization between the corresponding time series. The same behavior was not observed for dengue, first reported in the region back in 1986, either in the previously 2001-2016 based results or in the current work. These results show that, as the number of outbreaks accumulates, different strategies must be adopted to combat the dissemination of arbovirus infections

    Classification algorithm for congenital Zika Syndrome: characterizations, diagnosis and validation.

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    Zika virus was responsible for the microcephaly epidemic in Brazil which began in October 2015 and brought great challenges to the scientific community and health professionals in terms of diagnosis and classification. Due to the difficulties in correctly identifying Zika cases, it is necessary to develop an automatic procedure to classify the probability of a CZS case from the clinical data. This work presents a machine learning algorithm capable of achieving this from structured and unstructured available data. The proposed algorithm reached 83% accuracy with textual information in medical records and image reports and 76% accuracy in classifying data without textual information. Therefore, the proposed algorithm has the potential to classify CZS cases in order to clarify the real effects of this epidemic, as well as to contribute to health surveillance in monitoring possible future epidemics

    Composition of fatty acids in the maternal and umbilical cord plasma of adolescent and adult mothers: relationship with anthropometric parameters of newborn

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    <p>Abstract</p> <p>Background</p> <p>Considering the importance of long chain polyunsaturated fatty acids to fetal development and the lack of studies that have compared the status of fatty acids between adolescents and adults mothers, the purpose of this study was to evaluate the composition of fatty acids in maternal and umbilical cord plasma from adolescent and adults mothers.</p> <p>Methods</p> <p>Forty pregnant adolescents and forty pregnant adults were selected to assess the distribution profile of fatty acids in the maternal and umbilical cord plasma. Quantification of fatty acids in the total lipids of the sample groups was performed through the use of gas-liquid chromatography.</p> <p>Results</p> <p>The maternal and umbilical cord plasma of the adolescents showed a greater concentration of AA than did that of the adults (P < 0.05). However, a greater percentage of EPA was found in the umbilical cord plasma of the adults (P < 0.05). DHA in the plasma of the adolescent mothers correlated positively to birth weight and head circumference.</p> <p>Conclusions</p> <p>This suggests that in situations of greater nutritional risk, as in adolescent pregnancy, n-3PUFA concentrations have a greater influence on the proper development of newborns. Moreover, variations in fatty acid concentrations in the maternal and cord plasma of adolescents and adults may indicate that pregnancy affects the LC-PUFA status of adults and adolescents in distinct ways.</p
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