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      Colaborações científicas em Zika: identificação dos principais grupos e pesquisadores através da análise de redes sociais Translated title: Scientific collaboration in Zika: identification of the leading research groups and researchers via social network analysis Translated title: Colaboraciones científicas en Zika: identificación de los principales grupos e investigadores mediante el análisis de redes sociales

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          Abstract

          Resumo: Devido à associação entre Zika e microcefalia, o Brasil recebeu atenção neste cenário. A situação de emergência exigiu rapidez e esforço coletivo dos pesquisadores de todo o mundo, e a Ciência se apressou nas investigações e publicação dos resultados. A partir das interações formadas, criou-se e se disseminou conhecimento científico. Publicações ainda são a melhor forma de divulgar o conhecimento científico. Através delas é possível registrar os progressos realizados em um campo de estudos e observar como os cientistas colaboram entre si para conduzir avanços à medida que novos conhecimentos e tecnologias são engendrados. Um modo eficaz de mapear esses avanços é analisar as Redes Sociais (redes de relacionamentos e colaboração) dos cientistas, já que atualmente a colaboração constitui uma característica intrínseca da Ciência moderna. Desse modo, a coautoria em publicações se apresenta como um importante indicador de colaboração científica na compreensão dos progressos realizados em diversas áreas da Ciência. Este trabalho objetiva, por um método generalizável, mapear e analisar a Rede Social Científica formada no domínio de Zika, mostrando como os cientistas colaboraram entre si para conduzir os principais avanços de pesquisa, identificando os principais grupos de pesquisa em Zika, além dos pesquisadores mais influentes. Para isso, utilizaram-se técnicas de Análise de Redes Sociais nas redes de coautoria formadas entre os anos de 2015 e 2016. Os dados deste estudo sinalizam que a influência de um pesquisador em Zika é basicamente motivada por três fatores: (a) quantidade de publicações; (b) parcerias diversificadas; e (c) os vínculos estabelecidos com os pioneiros da área.

          Translated abstract

          Abstract: The association between Zika and microcephaly drew international attention to Brazil. The emergency situation demanded speed and collective effort by researchers worldwide, and Science was quick to investigate the disease and publish the results. Scientific knowledge was created and disseminated through collaboration in this process. Publications are still the best way of disseminating scientific knowledge. They allow to record progress in a field of studies and observe how scientists collaborate to produce advances as new knowledge and technologies are generated. An effective way to map such advances is to analyze scientists’ Social Networks (relationship and collaboration networks), since collaboration is currently an intrinsic characteristic of modern science. Co-authorship of publications is thus an important indicator of scientific collaboration for understanding progress in various areas of Science. The current study aimed to use a generalizable method for mapping and analyzing the Scientific Social Network formed in the domain of Zika, demonstrating how scientists collaborated to produce the main research results, identifying the leading research groups on Zika and the most influential researchers. Social Network Analysis was applied to the co-authorship networks formed from 2015 to 2016. The study showed that a Zika researcher’s influence is basically determined by three factors: (a) number of publications; (b) diversified partnerships; and (c) the links established with the research area’s pioneers.

          Translated abstract

          Resumen: Debido a la asociación entre el Zika y la microcefalia, Brasil, como país, llamó la atención sobre este campo de estudio. La situación de emergencia ocasionada exigió rapidez y un esfuerzo colectivo de los investigadores de todo el mundo, asimismo, la ciencia se apresuró en ofrecer investigaciones y la publicación de resultados sobre este tema. Debido a las interacciones surgidas, se creó y diseminó conocimiento científico. Las publicaciones hoy en día todavía son la mejor forma de divulgar conocimiento científico. Gracias a ellas, es posible registrar los progresos realizados en un campo de estudio y observar cómo los científicos colaboran entre sí para llevar a cabo avances, a medida que se generan nuevos conocimientos y tecnologías. Un modo eficaz de mapear estos avances es analizar las redes sociales (redes de relaciones y colaboración) de los científicos, ya que actualmente la colaboración constituye una característica intrínseca de la ciencia moderna. De este modo, la coautoría en publicaciones se presenta como un importante indicador de la colaboración científica en la comprensión de los progresos realizados en diversas áreas de la ciencia. El objetivo de este trabajo, como método generalizable, es mapear y analizar la Red Social Científica, formada en el campo de Zika, mostrando cómo los científicos colaboraron entre sí para llevar a cabo los principales avances en investigación, identificando los principales grupos de investigación sobre Zika, además de a los investigadores más influyentes. Para ello, se utilizaron técnicas de Análisis de Redes Sociales, en redes de coautoría formadas entre los años de 2015 y 2016. Los datos de este estudio señalan que la influencia de un investigador en Zika está básicamente motivada por tres factores: (a) cantidad de publicaciones; (b) colaboraciones diversificadas; y (c) vínculos establecidos con los pioneros del área.

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          Zika Virus Outside Africa

          In April 2007, an outbreak of illness characterized by rash, arthralgia, and conjunctivitis was reported on Yap Island in the Federated States of Micronesia. Serum samples from patients in the acute phase of illness contained RNA of Zika virus (ZIKV), a flavivirus in the same family as yellow fever, dengue, West Nile, and Japanese encephalitis viruses. These findings show that ZIKV has spread outside its usual geographic range ( 1 , 2 ). Sixty years earlier, on April 18, 1947, fever developed in a rhesus monkey that had been placed in a cage on a tree platform in the Zika Forest of Uganda ( 3 ). The monkey, Rhesus 766, was a sentinel animal in the Rockefeller Foundation’s program for research on jungle yellow fever. Two days later, Rhesus 766, still febrile, was brought to the Foundation’s laboratory at Entebbe and its serum was inoculated into mice. After 10 days all mice that were inoculated intracerebrally were sick, and a filterable transmissible agent, later named Zika virus, was isolated from the mouse brains. In early 1948, ZIKV was also isolated from Aedes africanus mosquitoes trapped in the same forest ( 4 ). Serologic studies indicated that humans could also be infected ( 5 ). Transmission of ZIKV by artificially fed Ae. aegypti mosquitoes to mice and a monkey in a laboratory was reported in 1956 ( 6 ). ZIKV was isolated from humans in Nigeria during studies conducted in 1968 and during 1971–1975; in 1 study, 40% of the persons tested had neutralizing antibody to ZIKV ( 7 – 9 ). Human isolates were obtained from febrile children 10 months, 2 years (2 cases), and 3 years of age, all without other clinical details described, and from a 10 year-old boy with fever, headache, and body pains ( 7 , 8 ). From 1951 through 1981, serologic evidence of human ZIKV infection was reported from other African countries such as Uganda, Tanzania, Egypt, Central African Republic, Sierra Leone ( 10 ), and Gabon, and in parts of Asia including India, Malaysia, the Philippines, Thailand, Vietnam, and Indonesia ( 10 – 14 ). In additional investigations, the virus was isolated from Ae. aegypti mosquitoes in Malaysia, a human in Senegal, and mosquitoes in Côte d’Ivoire ( 15 – 17 ). In 1981 Olson et al. reported 7 people with serologic evidence of ZIKV illness in Indonesia ( 11 ). A subsequent serologic study indicated that 9/71 (13%) human volunteers in Lombok, Indonesia, had neutralizing antibody to ZIKV ( 18 ). The outbreak on Yap Island in 2007 shows that ZIKV illness has been detected outside of Africa and Asia (Figure 1). Figure 1 Approximate known distribution of Zika virus, 1947–2007. Red circle represents Yap Island. Yellow indicates human serologic evidence; red indicates virus isolated from humans; green represents mosquito isolates. Dynamics of Transmission ZIKV has been isolated from Ae. africanus, Ae. apicoargenteus, Ae. luteocephalus, Ae. aegypti, Ae vitattus, and Ae. furcifer mosquitoes ( 9 , 15 , 17 , 19 ). Ae. hensilii was the predominant mosquito species present on Yap during the ZIKV disease outbreak in 2007, but investigators were unable to detect ZIKV in any mosquitoes on the island during the outbreak ( 2 ). Dick noted that Ae. africanus mosquitoes, which were abundant and infected with ZIKV in the Zika Forest, were not likely to enter monkey cages such as the one containing Rhesus 766 ( 5 ) raising the doubt that the monkey might have acquired ZIKV from some other mosquito species or through some other mechanism. During the studies of yellow fever in the Zika Forest, investigators had to begin tethering monkeys in trees because caged monkeys did not acquire yellow fever virus when the virus was present in mosquitoes ( 5 ). Thus, despite finding ZIKV in Ae. Africanus mosquitoes, Dick was not sure whether or not these mosquitoes were actually the vector for enzootic ZIKV transmission to monkeys. Boorman and Porterfield subsequently demonstrated transmission of ZIKV to mice and monkeys by Ae. aegypti in a laboratory ( 6 ). Virus content in the mosquitoes was high on the day of artificial feeding, dropped to undetectable levels through day 10 after feeding, had increased by day 15, and remained high from days 20 through 60 ( 6 ). Their study suggests that the extrinsic incubation period for ZIKV in mosquitoes is ≈10 days. The authors cautioned that their results did not conclusively demonstrate that Ae. aegypti mosquitoes could transmit ZIKV at lower levels of viremia than what might occur among host animals in natural settings. Nevertheless, their results, along with the viral isolations from wild mosquitoes and monkeys and the phylogenetic proximity of ZIKV to other mosquito-borne flaviviruses, make it reasonable to conclude that ZIKV is transmitted through mosquito bites. There is to date no solid evidence of nonprimate reservoirs of ZIKV, but 1 study did find antibody to ZIKV in rodents ( 20 ). Further laboratory, field, and epidemiologic studies would be useful to better define vector competence for ZIKV, to determine if there are any other arthropod vectors or reservoir hosts, and to evaluate the possibility of congenital infection or transmission through blood transfusion. Virology and Pathogenesis ZIKV is an RNA virus containing 10,794 nucleotides encoding 3,419 amino acids. It is closely related to Spondweni virus; the 2 viruses are the only members of their clade within the mosquito-borne cluster of flaviviruses (Figure 2) ( 1 , 21 , 22 ). The next nearest relatives include Ilheus, Rocio, and St. Louis encephalitis viruses; yellow fever virus is the prototype of the family, which also includes dengue, Japanese encephalitis, and West Nile viruses ( 1 , 21 ). Studies in the Zika Forest suggested that ZIKV infection blunted the viremia caused by yellow fever virus in monkeys but did not block transmission of yellow fever virus ( 19 , 23 ). Figure 2 Phylogenetic relationship of Zika virus to other flaviviruses based on nucleic acid sequence of nonstructural viral protein 5, with permission from Dr Robert Lanciotti ( 1 ). Enc, encephalitis; ME, meningoencephalitis. Information regarding pathogenesis of ZIKV is scarce but mosquito-borne flaviviruses are thought to replicate initially in dendritic cells near the site of inoculation then spread to lymph nodes and the bloodstream ( 24 ). Although flaviviral replication is thought to occur in cellular cytoplasm, 1 study suggested that ZIKV antigens could be found in infected cell nuclei ( 25 ). To date, infectious ZIKV has been detected in human blood as early as the day of illness onset; viral nucleic acid has been detected as late as 11 days after onset ( 1 , 26 ). The virus was isolated from the serum of a monkey 9 days after experimental inoculation ( 5 ). ZIKV is killed by potassium permanganate, ether, and temperatures >60°C, but it is not effectively neutralized with 10% ethanol ( 5 ). Clinical Manifestations The first well-documented report of human ZIKV disease was in 1964 when Simpson described his own occupationally acquired ZIKV illness at age 28 ( 27 ). It began with mild headache. The next day, a maculopapular rash covered his face, neck, trunk, and upper arms, and spread to his palms and soles. Transient fever, malaise, and back pain developed. By the evening of the second day of illness he was afebrile, the rash was fading, and he felt better. By day three, he felt well and had only the rash, which disappeared over the next 2 days. ZIKV was isolated from serum collected while he was febrile. In 1973, Filipe et al. reported laboratory-acquired ZIKV illness in a man with acute onset of fever, headache, and joint pain but no rash ( 26 ). ZIKV was isolated from serum collected on the first day of symptoms; the man’s illness resolved in ≈1 week. Of the 7 ZIKV case-patients in Indonesia described by Olson et al. all had fever, but they were detected by hospital-based surveillance for febrile illness ( 11 ). Other manifestations included anorexia, diarrhea, constipation, abdominal pain, and dizziness. One patient had conjunctivitis but none had rash. The outbreak on Yap Island was characterized by rash, conjunctivitis, and arthralgia ( 1 , 2 ). Other less frequent manifestations included myalgia, headache, retroorbital pain, edema, and vomiting ( 2 ). Diagnosis Diagnostic tests for ZIKV infection include PCR tests on acute-phase serum samples, which detect viral RNA, and other tests to detect specific antibody against ZIKV in serum. An ELISA has been developed at the Arboviral Diagnostic and Reference Laboratory of the Centers for Disease Control and Prevention (Ft. Collins, CO, USA) to detect immunoglobulin (Ig) M to ZIKV ( 1 ). In the samples from Yap Island, cross-reactive results in sera from convalescent-phase patients occurred more frequently among patients with evidence of previous flavivirus infections than among those with apparent primary ZIKV infections ( 1 , 2 ). Cross-reactivity was more frequently noted with dengue virus than with yellow fever, Japanese encephalitis, Murray Valley encephalitis, or West Nile viruses, but there were too few samples tested to derive robust estimates of the sensitivity and specificity of the ELISA. IgM was detectable as early as 3 days after onset of illness in some persons; 1 person with evidence of previous flavivirus infection had not developed IgM at day 5 but did have it by day 8 ( 1 ). Neutralizing antibody developed as early as 5 days after illness onset. The plaque reduction neutralization assay generally has improved specificity over immunoassays, but may still yield cross-reactive results in secondary flavivirus infections. PCR tests can be conducted on samples obtained less than 10 days after illness onset; 1 patient from Yap Island still had detectable viral RNA on day 11 ( 1 ). In general, diagnostic testing for flavivirus infections should include an acute-phase serum sample collected as early as possible after onset of illness and a second sample collected 2 to 3 weeks after the first. Public Health Implications Because the virus has spread outside Africa and Asia, ZIKV should be considered an emerging pathogen. Fortunately, ZIKV illness to date has been mild and self-limited, but before West Nile virus caused large outbreaks of neuroinvasive disease in Romania and in North America, it was also considered to be a relatively innocuous pathogen ( 28 ). The discovery of ZIKV on the physically isolated community of Yap Island is testimony to the potential for travel or commerce to spread the virus across large distances. A medical volunteer who was on Yap Island during the ZIKV disease outbreak became ill and was likely viremic with ZIKV after her return to the United States ( 2 ). The competence of mosquitoes in the Americas for ZIKV is not known and this question should be addressed. Spread of ZIKV across the Pacific could be difficult to detect because of the cross-reactivity of diagnostic flavivirus antibody assays. ZIKV disease could easily be confused with dengue and might contribute to illness during dengue outbreaks. Recognition of the spread of ZIKV and of the impact of ZIKV on human health will require collaboration between clinicians, public health officials, and high-quality reference laboratories. Given that the epidemiology of ZIKV transmission on Yap Island appeared to be similar to that of dengue, strategies for prevention and control of ZIKV disease should include promoting the use of insect repellent and interventions to reduce the abundance of potential mosquito vectors. Officials responsible for public health surveillance in the Pacific region and the United States should be alert to the potential spread of ZIKV and keep in mind the possible diagnostic confusion between ZIKV illness and dengue.
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            Rapid spread of emerging Zika virus in the Pacific area.

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              The structure of scientific collaboration networks.

              M E Newman (2001)
              The structure of scientific collaboration networks is investigated. Two scientists are considered connected if they have authored a paper together and explicit networks of such connections are constructed by using data drawn from a number of databases, including MEDLINE (biomedical research), the Los Alamos e-Print Archive (physics), and NCSTRL (computer science). I show that these collaboration networks form "small worlds," in which randomly chosen pairs of scientists are typically separated by only a short path of intermediate acquaintances. I further give results for mean and distribution of numbers of collaborators of authors, demonstrate the presence of clustering in the networks, and highlight a number of apparent differences in the patterns of collaboration between the fields studied.
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                Author and article information

                Contributors
                Role: ND
                Role: ND
                Role: ND
                Role: ND
                Journal
                csp
                Cadernos de Saúde Pública
                Cad. Saúde Pública
                Escola Nacional de Saúde Pública Sergio Arouca, Fundação Oswaldo Cruz (Rio de Janeiro, RJ, Brazil )
                0102-311X
                1678-4464
                2019
                : 35
                : 3
                : e00220217
                Affiliations
                [1] Rio de Janeiro Rio de Janeiro orgnameUniversidade Federal do Rio de Janeiro Brazil
                [3] Rio de Janeiro Rio de Janeiro orgnameUniversidade do Estado do Rio de Janeiro Brazil
                [2] Rio de Janeiro orgnameFundação Oswaldo Cruz Brazil
                Article
                S0102-311X2019000305006
                10.1590/0102-311x00220217
                7cd40df1-21b2-420d-a2a5-b9f9cc2580e5

                This work is licensed under a Creative Commons Attribution 4.0 International License.

                History
                : 26 December 2017
                : 17 August 2018
                Page count
                Figures: 0, Tables: 0, Equations: 0, References: 28, Pages: 0
                Product

                SciELO Brazil


                Zika Virus,Authorship and Co-authorship in Scientific Publications,Social Networking,Cooperative Behavior,Virus Zika,Autoría y Coautoría en la Publicación Científica,Red Social,Conducta Cooperativa,Zika Vírus,Autoria e Coautoria na Publicação Científica,Rede Social,Comportamento Cooperativo

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