The global scientific research response to the public ...Jul 16, 2019 · 11 4 Casa Oswaldo Cruz,...

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The global scientific research response to the 1

public health emergency of Zika virus infection 2

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Juliane Fonseca de Oliveira1, Julia Moreira Pescarini1, Moreno de Souza Rodrigues1,2, Bethania 4 de Araujo Almeida1, Claudio Maierovitch Pessanha Henriques3, Fabio Castro Gouveia4, Elaine 5 Teixeira Rabello5, Gustavo Correa Matta6, Mauricio L. Barreto1,7, Ricardo Barros Sampaio1,3* 6

7 1 Centro de Integração de Dados e Conhecimentos para Saúde, Fiocruz, Salvador, Bahia, Brazil 8 2 Laboratório de Análise e Visualização de dados, Fiocruz, Rondônia, Brazil 9 3 Gerência Regional de Brasília, Fiocruz, Brasília, Brazil 10 4 Casa Oswaldo Cruz, Fiocruz, Rio de Janeiro, Brazil 11 5 Universidade do Estado do Rio de Janeiro, Rio de Janeiro, Brazil 12 6 Escola Nacional de Saúde Pública, Fiocruz, Rio de Janeiro, Brazil 13 7 Instituto de Saúde Coletiva, Universidade Federal da Bahia, Salvador, Bahia, Brazil 14

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*Corresponding author: 16

Ricardo Barros Sampaio e-mail: [email protected] 17

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All authors have contributed equaly to this work 19

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Keywords: 21

Zika Virus Infection; Network Analysis; Scientometrics; Text Analysis 22

23

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https://doi.org/10.1101/19001313

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Abstract 24

Background 25

Science studies have been a field of research for different knowledge areas and they have 26

been successfully used to analyse the construction of scientific knowledge, practice and 27

dissemination. In this study, we aimed to verify how the Zika epidemic has moulded scientific 28

production worldwide analysing international collaboration and the knowledge landscape 29

through time, research topics and country involvement. 30

Methodology 31

We searched the Web of Science (WoS) for studies published up to 31st December 2018 32

on Zika using the search terms “zika”, “zkv” or “zikv”. We analysed the scientific production 33

regarding which countries have published the most, on which topics, as well as country level 34

collaboration. We performed a scientometric analysis of research on Zika focusing on 35

knowledge mapping and the scientific research path over time and space. 36

Findings 37

We found two well defined research areas divided into three subtopics accounting for six 38

clusters. With regard to country analysis, the USA followed by Brazil were the leading countries 39

in publications on Zika. China entered as a new player focusing on specific research areas. When 40

we took into consideration the epidemics and reported cases, Brazil and France were the leading 41

research countries on related topics. As for international collaboration, the USA followed by 42

England and France stand out as the main hubs. The research areas most published included 43

public health related topics from 2015 until the very beginning of 2016, followed by an increase 44



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in topics related to the clinical aspects of the disease in 2016 and the beginnings of laboratorial 45

research in 2017/2018. 46

Conclusions 47

Mapping the response to Zika, a public health emergency, demonstrated a clear pattern of 48

the participation of countries in the scientific advances. The pattern of knowledge production 49

found in this study represented the different perspectives and interests of countries based firstly 50

on their level of exposure to the epidemic and secondly on their financial positions with regard to 51

science. 52

Introduction 53

Zika virus infection (ZVI) was first reported in humans in 1954, but only in 2007 did the 54

first outbreak occur in Micronesia [1, 2], and several small outbreaks in Micronesia and the 55

Pacific Islands have been reported since then. However, it was only in 2013 that ZVI started 56

revealing its epidemic potential [3]. In 2015, the virus was linked with associated neurological 57

disorders, including Guillain-Barré syndrome, microcephaly and yet unknown neurological 58

disorders in newborns [4, 5]. It was and remains an event of scientific uncertainties. 59

In February 2016, mostly driven by the Brazilian Zika-associated microcephaly cases, 60

WHO declared a public health emergency of international concern (PHEIC). Different research 61

groups all over the world, as part of separate and collaborative research networks, made a 62

concerted effort to understand the various factors required to cope with the epidemic, including 63

the Zika virus infection, transmission and control, as well as the social impact of severe forms of 64

the disease in the most affected societies [3]. During the outbreak, especially after WHO PHEIC, 65



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international funding and fast-tracking procedures for publishing scientific outcomes stimulated 66

scientific research and publication. The increasing number of publications on Zika after 2015 has 67

been attributed mainly to its association with microcephaly [6], but by 2016, only a few core 68

journals had published on Zika [7]. 69

Since the emergency declaration, science studies' applied to the Zika epidemics 70

publications has come mostly from focusing on scientific networks and their collaboration and 71

co-publication. Some researchers have adopted bibliometric and/or scientometric perspectives, 72

analysing papers and documents to discuss different aspects of scientific production in terms of 73

co-authorship, cooperative networks and innovative potentials on the Zika topic (see [7-10]). 74

Furthermore, the discussion about the influence and centrality of certain groups, 75

researchers and even countries have enriched the debate raised by scientometrics applied to Zika. 76

A first mapping of the scientific networks and their most influential researchers in Zika as a 77

theme was done in 2018 [11]. Using techniques of Social Network Analysis, the authors mapped 78

the co-authorship networks on Zika papers published in 2015 and 2016. The study revealed that, 79

besides the number of publications, two other factors might be connected to explain the 80

prominence of a given researcher in these scientific networks: the diversity of partnerships and 81

the established connections with the pioneers in the field. 82

Another interesting perspective is to address the role of specific regions on the matter. 83

Zika-related publications and patents, investigated from a scientometric perspective, highlighted 84

the strategic role played by the Latin America and Caribbean research network in terms of 85

addressing the science and technology (S&T) challenges related to the outbreak [12]. According 86

to this study, Brazil itself stands out in reporting and researching the clinical manifestations of 87



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the ZVI and also in studies about vector control, the latter related to the filing of patents in 88

particular. 89

State of the art considered, these studies are central to the systematisation of current 90

knowledge in terms of which research areas have been most developed so far. This scenario 91

allows, for instance, policy managers to contribute by allocating and prioritising research to the 92

current prevention and epidemiological combat of the Zika virus. It is also essential to identify 93

interaction and collaboration among countries to help further the development of shared 94

governance in Zika and other research-related fields and increase scientific production and 95

knowledge in the area. Regarding neglected populations and diseases, these studies can support 96

further analysis on equity and sustainability, and science production between low and middle-97

income countries and developed countries, during and after health emergencies. 98

In this study, we aimed to verify how the Zika epidemic has moulded scientific 99

production worldwide analysing international collaboration and the knowledge landscape 100

through time, research topics and country involvement. Therefore, this study explores how the 101

epidemic of Zika has translated into research all over the world and over time, identifying what 102

the main thematic areas of scientific development on Zika are. We also explore how the S&T 103

apparatus of each country responded to the Zika emergency, from the first studies until 2018 and 104

according to knowledge areas. 105



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Materials and methods 106

Data collection, treatment and cleaning 107

Our dataset was obtained by searching terms related to Zika virus infection (“zika” OR 108

“zkv” OR “zikv”) by Topic in Web of Science (WoS). We selected all the articles published 109

from 1945 to the end of December 2018. The search was performed on January 21st, 2019. From 110

the retrieved articles, we extracted the title and abstract to develop a knowledge map and used 111

the metadata variables regarding date published, authors and co-authors’ affiliation countries as 112

well as the ISI subject categories from WoS assigned to them [13]. 113

The selected contents were downloaded as a text file containing all the results of our 114

query. The file was cleaned by (i) converting all words to lowercase, (ii) removing special 115

characters (e.g., “.”, “:” and “/”), and (iii) standardizing similar terms (e.g., “ae aegypti”, “aedes 116

aegypti”). Data cleaning was conducted in Python. The Python code used is available at GitHub 117

[14]. 118

Data Analysis 119

We conducted two main analyses on the Zika publications retrieved. First, a descriptive 120

analysis to understand how countries collaborate towards Zika knowledge; and second, a textual 121

analysis of research on Zika using knowledge mapping over time and space (i.e., countries). 122

Descriptive analysis 123

The descriptive analysis was performed both directly by filtering information from Web 124

of Science homepage and by using VOSviewer software [15] to perform country collaboration 125

network analysis. To summarize data information for each research article, we extracted from 126



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each author his institutional affiliation country. Articles produced by different institutions of the 127

same country were considered a national collaboration, and articles produced by authors 128

affiliated to institutions from more than one country were considered international 129

collaborations. After that, we constructed a co-authorship network at the country level using data 130

exported from VOSviewer and reconstructed and filtered using Gephi software for visualization 131

[16]. 132

In order to measure collaboration in Zika publications, we deduced an international 133

collaboration index (ICI), which is the ratio of the number of countries that a given country 134

collaborated with, over the total number of countries (minus the country itself) which produced 135

results toward Zika knowledge. The closer the index is to one, the more collaborative the country 136

is, and the closer it is to zero, the less internationally collaborative the country is. 137

To address the issue of international collaboration over time as a proportion of published 138

articles, an international collaboration factor (ICF) was calculated as the number of articles with 139

author(s) affiliation from more than one country over the number of articles with author(s) 140

affiliation to just one country. As with the ICI, the more colaborative a country is, the closer it is 141

to one, the less collaborative, the closer it is to zero. 142

Textual analysis 143

We carried out a textual analysis to discover textual data relationships among extracted 144

words. The method reveals thematic trends and identifies publication subjects surrounding 145

specific topics or fields [17]. To do this, we analysed the titles and abstracts of the articles in our 146

sample. More specifically, we analysed words (also called terms or forms), extracted from the 147

titles and abstracts, grouped by text segments comprised of 40 terms each, and applied 148



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Correspondence Factorial Analysis (CFA) to correlate them. The baseline assessment of research 149

areas into clusters relied on the clustering algorithm of IRAMuTeQ v7.2 (Interface for 150

Multidimensional Analysis of Texts and Questionnaires). The correlation process is obtained by 151

testing if the frequency of a given word is statistically associated with another using Pearson 152

Chi-square at a significance level of 5%. Based on the similarity, words are aggregated into 153

clusters of main areas of knowledge. Content analysis was also performed using IRAMuTeQ. 154

The defined number of clusters in IRAMuTeQ required empirical knowledge in the field 155

as well as several tests on how many clusters made a fair and accurate separation of knowledge 156

areas. Therefore, to validate our baseline clusters, we compared the number and content of each 157

cluster obtained using IRAMuTeQ with those obtained using VOSviewer. Moreover, we used 158

the categories defined by WoS for each article, based on the journal in which it was published to 159

further evaluate if the clusterisation process and defined sub-areas of research were aligned. 160

Finally, we showed the results to a panel of specialists on Zika and public health. 161

After we had established statistically significant knowledge area clusters, we evaluated 162

which knowledge areas emerged over time, and stratified them into four groups by publication 163

year: <=2015, 2016, 2017 or 2018; second, we evaluated the participation in each cluster/field of 164

the top 10 countries with regard to the number of publications. 165

Results 166

Descriptive analysis on the countries collaborations 167

The collected data yielded a total of 3,454 articles produced by 18,453 authors, associated 168

with institutions from 150 countries. These articles were published with and without 169



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international collaboration. Fig 1 shows a dispersion matrix using the number of publications and 170

ICI by country. 171

Fig 1. Number of publications by International Collaboration Index for each of the top ten 172

countries. The graph is a dispersion matrix, the y axis is the number of publications on a 173

logarithmic scale base 2 starting at 100 publications and the ICI is on the x axis starting at 0.3. 174

The size of the circles is related to the number of publications and the intensity of the color from 175

dark red to light pink is related to the ICI as shown on the right side scale. 176

According to Fig 1 The most internationally collaborative countries were the USA (ICI = 177

0.67), followed by France (ICI = 0.57), England (ICI = 0.55), Germany (ICI = 0.47) and Brazil 178

(ICI = 0.45). The remaining most productive countries, Italy, India, Australia, China and Canada, 179

presented international collaboration indexes of 0.41, 0.40, 0.35, 0.32 and 0.31, respectively. 180

When we take into consideration the ICI with the number of publications we can see that the 181

USA has the highest ICI and number of publications placing it in the top right corner of the 182

graph. In contrast, China, the third country with the highest number of publications, is the ninth 183

in ICI in the bottom left corner of the graph. Brazil seems to occupy an intermediate position 184

regarding the number of collaborating countries and the number of publications, with the second 185

largest number of publications on Zika, and the fourth in ICI. France and England seems to be 186

well positioned in terms of the number of collaborating countries. The remaining five countries 187

have fewer than 200 publications and show a similar ratio between the logarithmic number of 188

publications and the number of countries with which they have collaborated. 189

Table 1 summarizes the overall information about international collaborations for the ten 190

most productive countries. The countries that published the most on Zika during the study period 191

were the USA and Brazil followed by China, France and England. 192



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Table 1. National and International publications about Zika Virus Infection for the top 10 193

most productive countries. The table depicts the total number of publications. The column 194

“Articles Total” represents the total number of articles published by a country and the percentage 195

of these productions over the total number of articles about Zika found in WoS until 2018. 196

Among these values, we see the number of articles produced by the country itself and the 197

proportion produced with international collaboration. 198

Countries

Articles Total Articles with single country author(s)

Articles with international collaboration

N % N % N %

USA 1,676 48.52 958 57.16 718 42.84

Brazil 631 18.27 299 47.38 332 52.62

China 272 7.87 125 46.0 147 54.0

France 257 7.44 68 26.46 189 73.54

England 230 6.66 35 15.22 195 84.78

Germany 181 5.24 46 25.41 135 74.58

Italy 172 4.98 42 24.42 130 75.58

India 148 4.28 54 36.49 94 63.51

Australia 144 4.17 65 45.14 79 54.86

Canada 139 4.02 44 31.65 95 68.35

The column with the total number of articles and the percentage in Table 1 accounts for 199

more than the total number of articles on Zika due to the collaboration amongst these countries. 200

With regard to the articles written by authors from one country alone and with collaboration we 201

can see that the only country with fewer than half of its articles being the result of collaboration 202

is the USA, in contrast with England, which has published almost double that of the USA, with 203

84.78%. The other three European countries, France, Germany and Italy, also shows higher 204

percentages compared to other non European countries. 205

In order to see how international collaboration among the top 10 publishing countries 206

occurred over time, in Fig 2 we plotted the yearly evolution of their international collaboration 207



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factor - ICF (the number of articles produced with international collaborations over the total 208

production) until 2018 combining papers before 2015 all together. We can see a clear pattern in 209

the USA, Brazil, China and Australia, where the countries have a balanced level of production 210

with and without international collaboration. As a contrast, we can see that England, Germany 211

and France published articles in international collaborations at a higher frequency. Nonetheless, 212

the yearly ICF of the ten most productive countries together with the ICF for Zika publication 213

and WoS overall publication are considered in Fig 2. 214

Fig 2. The production evolution of the top 10 countries plus the overall Zika Production 215

and WoS production. The closer the dots are to 0.5 (highlighted by the black line), the articles 216

produced with collaborations are proportional to the articles produced without collaborations. 217

The value corresponding to the year 2015 represents the sum of all work produced by the 218

selected country up until 2015. Points on the zero line correspond to publications that had no 219

international collaboration. The size of the dots for Global WoS articles are divided by 1,000 in 220

order to fit the scale. 221

Using co-authorship networks between countries, we see that the majority (61.89%) of 222

the articles were produced within one country, 24.17% were collaborations between two 223

countries, 8.88% between three countries and 2.51% between four countries. The remaining 224

2.55% were collaborations between five or more countries. Interestingly, we also found that 225

international collaborations were present on average in 64.47% of articles produced by the top 10 226

countries. The reason for this apparent discrepancy has to do with the fact that an international 227

paper will be considered a collaboration for every country represented in that paper but only 228

once when comparing articles with and without international collaboration. 229

Analysing country-level collaboration, as shown in Table 1 England has the highest 230

number of publications that resulted from international collaboration (84.78%), followed by Italy 231



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(75.58%) and Germany (74.58%). Another collaboration analysis which supports the results for 232

Table 1 and Fig 2 is presented in Fig 3 with an international collaboration network graph. This 233

figure presents all the collaborations amongst the top ten countries. 234

Fig 3: Collaborations among the 10 most productive countries. Each node corresponds to a 235

country and the size of the node is related to the number of international collaborations they have 236

within that group. The thickness of the lines represents the number of collaborations between any 237

two countries and an aproximation of those numbers are presented by the box on the top right. 238

The color scheme emphasizes link differences between countries since the color of a line is a mix 239

of the color of the nodes it connects. The node distribution on the figure has been chosen only to 240

facilitate visualization. The two countries with the fewest number of publications are positioned 241

at the center of the graph and the most productive to the least from top to bottom and left to right. 242

The USA is in the first position in terms of absolute numbers of publications. In contrast, 243

it occupies the 10th position (42.84%) in terms of the percentage of articles produced with 244

international collaboration. Despite being in 10th position, the number of articles that the USA 245

published with international collaboration corresponds to more than three times the total number 246

of articles published by England, the country with the highest international collaboration ratio. 247

Out of the 958 articles published by the USA with international collaboration, over 15% were 248

with Brazil and nearly 10% with China. This strength of collaboration is shown in Fig 3 by the 249

thickness of the line between the nodes. 250

Out of the 299 Brazilian studies published as results of international collaboration, over 251

60% were with the USA, followed by nearly 20% with England and 10% with both France and 252

Germany. For the 147 Chinese studies published with international collaboration, over 75% were 253

with the USA and a few articles with other countries. (Fig 3). 254



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Main research areas of knowledge 255

A total of 24,685 words were analyzed inside 21,055 text segments, of which 17,525 256

were considered active words (i.e., verbs, nouns and adjectives). Using IRAMuTeQ, six clusters 257

were identified and named according to the most frequent words. Cluster 1 represented the 258

“Clinical Aspects” of the disease (13.8% of the words); Cluster 2 the “Diagnosis” (10.6%); 259

Cluster 3 included the “Epidemiology” of the disease (20.1%); Cluster 4 the “Entomology” 260

(14.5%); Cluster 5 “Cellular Biology” (19.9%); and Cluster 6 "Molecular Biology" (21%) (Fig 261

4). 262

Fig 4. Dendrogram of the clusters obtained with IRAMuTeQ. The dendrogram is divided 263

into 6 clusters formed by branch divisions. The first branch divides Group A, and Group B. 264

Group A is further divided into two subgroups called Group A1 and Group A2. The size of each 265

bar corresponds to the number of words in that cluster directly related to the percentage value in 266

the bottom right corner of each bar. The associated name for each cluster appears on its bar, and 267

the colour scheme has been chosen to facilitate visualization. In front of each bar, there is a 268

square word cloud of words with the highest chi-square value to aid the understanding and the 269

representation of each cluster. 270

Using the WoS subject categories, 165 of 252 possible categories were present in the 271

studied articles, and each article is classified in one or more category. To compare WoS 272

categories with the clusters defined using Iramuteq, we used the following approach. First, we 273

selected the ten most frequent categories presented in our studied articles. Second, we analysed if 274

the most significant categories for each one of the 6 clusters independently appeared with a high 275

frequency or not. By doing this, we were able to better classify the clusters by the words which 276

appeared in them. 277

The ten most frequent categories were: Infectious Diseases; Public Environmental 278

Occupational Health; Tropical Medicine; Virology; Multidisciplinary Sciences; Microbiology; 279



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Parasitology; Immunology; Biochemistry Molecular Biology; and Medicine General Internal. 280

Other six categories, among the 10% most frequent, which were not included in the top ten list 281

but were significant to categorize the clusters were: Entomology; Cell Biology; Health Policy 282

and Services; Clinical Neurology; Pediatrics; and Diagnosis. Based on these sixteen categories, 283

we found the following results for Group A: Public Environmental Occupational Health category 284

was well defined in the “Epidemiology” cluster (cluster 3). The clusters "Diagnosis" and 285

"Entomology" (clusters 2 and 4) shared some of the same categories such as Infectious Diseases 286

and Tropical Medicine, with a difference for the Parasitology category which appeared in cluster 287

4 but not in 2. Furthermore, Diagnosis category was in cluster 2 and Entomology category in 288

cluster 4; each cluster was named after these categories. Cluster 1 “Clinical Aspects” had none of 289

the top 10 high-frequency categories of WoS in it. However, it included less frequent categories 290

such as Clinical Neurology and Pediatrics. 291

In Group B, with clusters "Cellular Biology" and "Molecular Biology" (cluster 5 and 6), 292

there were similarities in Virology and Microbiology as main categories. The main difference 293

was that in cluster 6, the most common category was Immunology, and in cluster 2 Virology 294

with Multidisciplinary Sciences were some of the areas. The category Cell Biology was included 295

in cluster 5 which was named after it. Similarly, the category Biochemistry Molecular Biology 296

was very evident in cluster 6. 297

After the validation of the clusters by the categories and their representations, we asked a 298

total of 12 specialists to evaluate the clustering results and the nomenclature. All responses were 299

positive in considering the clusters a well-defined set of research sub-areas within the field of 300

Zika taking into consideration the words available and the categories. Spatial distribution of the 301



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words coloured according to the cluster was presented to the specialists with the inferred 302

nomenclature and positive responses were received. 303

Fig 5. Knowledge map. Words extracted from titles and abstracts of articles on WoS related to 304

Zika Virus infection from January of 1945 through December 2018. The names in the solid line 305

boxes represent the cluster names and the dotted line boxes represent the most frequent periods 306

for the articles represented by the clusters. The size of each word represents their chi-square 307

value; the distance between them represents how statistically related they are based on the results 308

of the correspondence factorial analysis. 309

Year and Country distribution by cluster 310

Another scientometric analysis, after the construction of the knowledge map and the 311

validation of the clusters, concerns the global research path of science over time, based on the 312

year of publication of the articles. Because a large number of papers were published from 2016 313

onward we decided to group all publications before and including 2015 together. These 314

accounted for 3.2%. The publications of our sample yielded four groups (<=2015, 2016, 2017 315

and 2018). We carried out this investigation in the same way as we did with the subject 316

categories, by evaluating how statistically relevant a specific time group were in one or more of 317

the six clusters. 318

We incorporated the findings into Fig 5 with the boxes and using tilde (~) in front of the 319

year to emphasise the fact that the results are an approximation. This means that a particular 320

cluster might have publications or words in all year groups, although its prevalence is in a 321

particular quadrant position or year. 322

Similar to the subject categories, the year of publication analysis presented a well-defined 323

pattern. Publications before and up to 2015 were most prevalent in the bottom right part of the 324

figure with entomology research and related words in years before 2015 and regarding public 325



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health in 2015 and 2016. Publications in 2015 showed a higher than expected presence, by 326

analysing the chi-square, for clusters 3 "Epidemiology" and cluster 2 "Diagnosis". For 327

"Diagnosis", the production surged between 2015 and 2016 the period at the start of the 328

epidemics. The top right quadrant has publications from 2015 to 2016 mostly, where the clusters 329

"Diagnosis" and "Clinical Aspects" are present. In broad terms, epidemiology is defined as the 330

study of the distribution and determinants of health-related states or events in specified 331

populations in order to characterise and determine associations between exposures and outcomes 332

[18]. Taking into account that 2015 through 2016 was the most critical period due to knowledge 333

gaps related to the infection, the three remaining areas in Group A - clinical aspects, diagnosis 334

and entomology - are key factors to be studied in order to better understand epidemiology. 335

Furthermore, entomology is related to the need for a public health quick response during an 336

emergency. 337

In the left part of Fig 5, the clusters from Group B can be seen for both years 2017 on top 338

and 2018 on the bottom. Each year is well established in those quadrants and aligned with the 339

areas of research and clusters "Cellular Biology" and "Molecular Biology" respectively. Taking 340

into consideration the areas with lower than expected values for chi-square for these years, 341

cluster 4 "Entomology" is lower in 2017 and cluster 1 "Clinical Aspects" is lower for 2018, 342

which shows a significant shift in research topics from previous areas to new areas. 343

Finally, we performed a country analysis for the clusters with the top ten countries 344

regarding the number of publications. Fig 6 shows the Chi (not squared) results in order to 345

capture the negative values (lower than expected) for the countries participating in a cluster. The 346

higher or lower than expected results could be interpreted as the amount of research above or 347

below average, represented on the text analysis, carried out by each country. If a country’s 348



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research distribution to a particular cluster is close to zero, the percentage of articles expected for 349

that cluster follows the overall trend. If the number of articles is above or below the percentage 350

expected for that cluster, a bar will appear considering how far from the expected value they are. 351

If a country shows a particular concentration in a cluster, it should show a lower than 352

expected in one or more clusters. From Fig 6, we can infer the presence of a country as well as 353

its contribution to research on the topic or area. 354

Fig 6. Chi values for the top 10 countries for each cluster. The results are calculated taking 355

the observed value (number of text segments) within a cluster minus the expected value for that 356

cluster and country divided by the square root of the expected value. This is the Chi value (not 357

squared) to show negative (or less than expected) values. For each cluster (1 through 6) we have 358

all ten countries and their respective chi value. 359

Starting with the most productive, the USA has a high presence with statistical relevance 360

in cluster 6 focusing on "Cellular Biology". Although the USA has a presence in all the 6 361

clusters, due to its high number of publications and collaborations, the most significant presence, 362

statistically speaking, is in cluster 6 and its least significant presence in cluster 1 "Clinical 363

Aspects" and 4 "Entomology". Brazil, the country with the second highest scientific production 364

is most significant in cluster 1 regarding "Clinical Aspects" of the disease, while it is almost 365

absent in "Cellular Biology" (cluster 5). China is present in two clusters mainly, "Cellular 366

Biology" (cluster 5) and "Molecular Biology" (cluster 6) along with the USA. Clusters 1 through 367

4 are of very little statistical relevance for China. France is present in clusters 1, 2 and 4 playing 368

a role as an important research centre for public health but focusing on the disease as well since 369

French Polynesia had been one of the first places to show endemic signs of the virus. About 370

England, while a non endemic country, its important presence in cluster 3 “Epidemiology” 371

might be related to the fact that it is home to one of the largest centre for tropical and neglected 372



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diseases in the northern hemisphere, the London School of Hygiene & Tropcial Medicine. 373

Australia, Canada and Italy show a very high presence in cluster 4 "Entomology". For Germany, 374

India, and China, cellular biology (cluster 5) appears as the main area of research. 375

Discussion 376

In this study, one of the first analyses on Zika publication that has taken into 377

consideration international collaborations, we have attempted to understand the scientific 378

research path towards Zika science production. The unexpected appearance of the virus in an 379

epidemic form and with devastating effects on pregnancy was followed by the rapid growth of 380

scientific research on ZVI with a great inflow of research capital and institutional interests. It 381

makes research into Zika scientific production at the international context a compelling case in 382

international health and biomedical research perspectives, given its unique characteristics. 383

In general, collaborations in science occur through the need for complementary resources 384

among different actors, institutions and countries, such as knowledge and skills, financial 385

resources and access to the field and key actors in order to conduct relevant research. Co-386

authorship studies indicate that more connected actors tend to attract a higher number of 387

connections over time [19], an aspect that amplifies learning capacities and the absorption of 388

knowledge. This study shows how ZVI related-science has evolved since 2015, as a result of the 389

interest of an international research community focused on solving new and challenging research 390

questions, related to a recognized worldwide health problem. 391

The appearance of ZVI in its epidemic form in the Americas in 2015, particularly in 392

Brazil, initially triggered epidemiological field studies. In 2016, when the outbreak was declared 393

an international public health emergency, the science related to ZVI was intensified in endemic 394



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and non-endemic countries. The evolution of the study field over a short period evolved from 395

epidemiology and entomology to cover clinical and diagnostic aspects of the virus. 396

Subsequently, laboratory-based studies took over, with an emphasis on molecular and cellular 397

biology. This process has mobilized scientific efforts and resources from different countries, 398

institutions and research teams from different scientific areas. In a very short time, complex 399

interactions among these teams from different scientific areas have taken place. An analysis of 400

articles published on this subject in this period provides important insights into our 401

understanding of the path of the scientific response to ZVI. 402

The strong collaboration between the USA and countries from different continents (e.g., 403

Brazil, Canada, Germany and Australia), showed that the USA is the main contributor in terms 404

of collaboration and suggests its key research capacity in the field. Among the possible reasons 405

why the USA is found to be such a prominent publication country as well as a central player in 406

terms of international collaboration in Zika, might be the fact that it is the top R&D funder for 407

neglected diseases [20]. Furthermore, this country has considerable knowledge accumulation in 408

tropical diseases, including the Department of Defence, which has been one of the main 409

supporters of scientific research in this area [21,22]. 410

By using the International Collaboration Index (ICI) and the International Collaboration 411

Factor (ICF), we were able to examine the influence of the countries by taking into consideration 412

the number of countries they have contributed with and their ratio of international collaboration 413

over time. The most collaborative countries in relative terms are in Europe. The high levels of 414

the international collaboration of England may be explained by the significant recent investment 415

made available by the British government and philanthropic funding agencies for the research 416

community aiming to respond to the challenges posed by ZVI [23]. The same can be said for the 417



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European Union, which counts on four large research consortia (ZikaPlan, ZikAction, 418

ZikAlliance and ZikaVax) coordinated by European organizations in association with research 419

institutions from different regions across the world [24]. 420

Also, the potential threat of a Zika epidemic could partially explain the increased country 421

collaboration over time. When the first case of Zika virus infection was confirmed in the 422

Northeast region of Brazil, in May 2015, an epidemiological alert by the Pan American Health 423

Organization (PAHO)/World Health Organization (WHO) was released. The alert recommended 424

Member States to establish and maintain a capacity for ZVI detection, clinical management and 425

an effective public communication strategy [25]. In November 2015, Brazil declared ZVI a 426

national public health emergency and three months later, the World Health Organization 427

declared it a PHEIC [26]. We suggest that a causal effect between the alert/emergency and the 428

increased number of collaborations took place during this period considering the knowledge gaps 429

in understanding ZVI. 430

Brazil is a country with a vast scientific literature on dengue virus transmission, among 431

other arboviruses. However, the results indicate that it had carried out almost no research on Zika 432

virus before the start of the epidemic. Most of the entomological studies had taken place in 433

countries such as Italy, India and Australia. The scarce research resources for research and the 434

virtual inexistence of Zika virus in the Western Hemisphere until 2014 could justify this finding. 435

One of the first steps for health surveillance is to take the kind of disease into 436

consideration. In this sense, research into the clinical aspects of Zika helps in the characterization 437

of the disease. At the end of 2015, Zika infection and especially microcephaly appeared as a new 438

problem to be tackled. Questions regarding the clinical aspects and the epidemiology were the 439

main focus at this moment. Physicians might argue: "What is the Diagnosis?", "What are the 440



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physical pathological mechanisms of the virus/disease?", "What is the case definition?", putting 441

the focus on physiopathology. 442

These questions boosted basic science, since research on the clinical aspects and 443

epidemiology depends basically on people and methods, while applied science builds upon 444

cellular and molecular biology, depending on expensive equipment and other technologies and 445

qualifications. This scenario gives an academic advantage to countries with a higher 446

technological density. We saw Cluster 1 "Clinical Aspects" in 2016 being superseded by Clusters 447

5 and 6 ("Cellular Biology" and "Molecular Biology") in the following years. It also gives clues 448

to understanding the dominant participation of countries such as the USA and China in the 449

clusters related to cellular and molecular biology. 450

Nevertheless, these results have some limitations as our source of information was the 451

Web of Science, which could have excluded articles not indexed in this database. All in all, this 452

study, with its strengths and limitations, shows that science has values, interests and practical 453

applications. The fulfilling of the research objectives are thus strategic in the sense that it could 454

aid the dissemination of research, appropriation and the use of the knowledge produced within 455

the framework of scientific research to support strategies for the control and prevention of the 456

ZVI. 457

However, in the Global Health arena, it is known that inequities in science and 458

technology among high and low and middle-income countries area default in the historical 459

trajectory. Since the Zika outbreak, Brazil has played an important and essential role in 460

developing research and publishing about ZVI and its repercussions. However, regarding ZVI 461

scientific production, we can ask how sustainable the Brazilian prominence in time is. Until 462

when will Brazil be an almost mandatory partner to develop research and publishing on this 463



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matter? How to improve more equitable and sustainable scientific production in the so-called 464

"Global South"? Challenging questions yet to be considered in further studies. 465

Conclusions 466

In this study, we have demonstrated that the scientific global research path in response to 467

the public health emergency of ZVI can be traced with data from indexed articles. It shows the 468

value of the study of scientific networks to help to understand science production in response to a 469

PHEIC. As soon as the public health emergency of ZVI started, our findings showed a first phase 470

of the scientific inquiry focused on entomological and epidemiological studies. It was followed 471

by a second phase with a dominance of studies on the diagnosis and clinical aspects of the ZVI, 472

and by a third and fourth phase focused on molecular and cellular biology. We also found that 473

Brazil has played an important role not only in the rapid response to the epidemic but also in the 474

capacity to produce research and to evoke international collaboration within a short period with 475

high-income countries such as the USA and England. 476

477



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Acknowledements 478

We would like to thank all the specialists that evaluate the clusters established in our study. 479

480

This work is supported by the Center of Data and Knowledge Integration for Health (CIDACS) 481

through the Zika Platform - a long-term surveillance platform for the Zika virus and 482

microcephaly, Unified Health System (SUS) - Brazilian Ministry of Health. 483

484

This work was partially supported by the European Union’s Horizon 2020 Research and 485

Innovation Programme under ZIKAlliance Grant Agreement no. 734548, and by the Oswaldo 486

Cruz Foundation/ Vice-Presidency of Research and Biological Collections-Fiocruz/ VPPCB and 487

the Newton Fund/ British Council. 488

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