| Literature DB >> 24340113 |
Kaye Phillips1, Jillian Clare Kohler, Peter Pennefather, Halla Thorsteinsdottir, Joseph Wong.
Abstract
BACKGROUND: This study designed and applied accessible yet systematic methods to generate baseline information about the patterns and structure of Canada's neglected tropical disease (NTD) research network; a network that, until recently, was formed and functioned on the periphery of strategic Canadian research funding.Entities:
Mesh:
Year: 2013 PMID: 24340113 PMCID: PMC3854962 DOI: 10.1371/journal.pntd.0002568
Source DB: PubMed Journal: PLoS Negl Trop Dis ISSN: 1935-2727
Publication screening results.
| # of publications from initial search | 2,063 |
| # of duplicates removed: | 205 |
| # of non-NTDs removed: | 391 |
| # of non-scholarly publications removed: | 311 |
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Canada's NTD network-level measures and results.
| Measure | Description | Results |
| Size | The total number of nodes (actors) that define the unit of network analysis. | 62 |
| Clique | The set of nodes (actors) within a network all directly connected to one another. Represents a dense pocket of interconnectivity. | > = 3 members: 46> = 2 members: 42 |
| Density | The number of connections (links) within the network as a fraction of the total number of possible connections (links). | Mean: 0.422 SD: 3.88 |
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| n(n-1) | ||
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| For undirected (symmetric) networks, the numerator is multiplied by 2 –, which is the case for this study. | ||
| Centrality Degree (CD) | The number of links a country sends and receives. | Mean: 25.74 SD: 73.97 Range: 1, 541 |
| The centralization of a network, the degree to which the network's ties are focused on one node (actor) or a set of nodes (actors), is indicated by the standard deviation of the centrality scores for the network. | ||
| A small standard deviation indicates little variation in the centrality scores and a decentralized structure. | ||
| A large standard deviation indicates a lot of variation in the centrality scores and a centralized structure (Valente, p. 140). |
Figure 1Canada's NTD research.
Trends in publication growth 1950–2010 (n = 1,079).
Canada's NTD publications: Top 12 countries by share of first authors and co-authors (1950–2010).
| Country | First Author Count | Co-Author Count | Total Author Share | OECD Status (Y/N) |
| Canada | 879 | 2,009 | 69.6% | Y |
| United States | 50 | 305 | 8.5% | Y |
| United Kingdom | 21 | 93 | 2.7% | Y |
| France | 16 | 83 | 2.3% | Y |
| Brazil | 12 | 54 | 1.5% | N |
| Iran | 13 | 53 | 1.5% | N |
| Germany | 11 | 43 | 1.3% | Y |
| Peru | 4 | 26 | 0.7% | N |
| Switzerland | 5 | 23 | 0.6% | Y |
| Uganda | 0 | 28 | 0.6% | N |
| Vietnam | 1 | 26 | 0.6% | N |
| Japan | 5 | 21 | 0.6% | Y |
| Sweden | 6 | 18 | 0.5% | Y |
| Remaining countries (n = 54) | 47 | 293 | 8.2% | - |
| Total | 1,070 | 3,075 | 1 |
9 publications did not include the country of the first author.
Figure 2Canada's NTD research.
International share of co-authors and first authors by continent 1950–2010 (n = 1,257).
Canada's NTD publication activity and co-authorship rate (1950–2010).
| NTD Disease Type | # of Publication | # of publications with one or more other countries | Country co-authorship rate |
| Leishmania | 423 | 156 | 36.8% |
| African Sleeping Sickness | 186 | 57 | 30.6% |
| Leprosy | 148 | 31 | 20.9% |
| Chagas Disease | 68 | 39 | 57.3% |
| Roundworm | 51 | 12 | 23.5% |
| Blinding Trachoma | 44 | 20 | 45.4% |
| River Blindness | 44 | 21 | 47.7% |
| Elephantiasis | 33 | 16 | 48.4% |
| Neglected Tropical Diseases | 24 | 9 | 37.5% |
| Hookworm | 18 | 6 | 33.3% |
| Whipworm | 11 | 5 | 45.4% |
| Buruli Ulcer | 10 | 3 | 30.0% |
| Snail Fever | 10 | 1 | 10.0% |
| Guinea Worm | 9 | 3 | 33.3% |
| Grand Total | 1079 | 379 | 35.1% |
Includes all authors (first and co-authors). Only calculates one country instance per publication.
Figure 3Canada's NTD co-authorship network (>2 country connections) (n = 42).
Within this network map the circles (“nodes”) represent each country within Canada's NTD research co-authorship network, and the colors of the nodes represent OECD or non-OECD nations. OECD country nodes are blue and non-OECD nation country nodes are black. Canada is distinguished as a red node. The lines (“ties”) connecting one node to the next represent lines of relation between countries. The ties in this map are not valued or weighted and represent a reciprocal or undirected relation; one country either has a relation/tie with another country or not. The sizes of the nodes are scaled to represent the GDP of each country.
Figure 4Canada's NTD research network k-core bar graph (n = 62).
The country network map and the k-core bar graph show that within Canada's NTD research co-authorship network, there are dense connections among the subset of the twelve countries in the 7k-core. Therefore, there is an indication that Canada's NTD research country-level co-authorship network is a core-periphery structure. This means that there is a distinct core group of twelve countries that are all connected to at least seven other countries within the core. In contrast, there exist a number of countries on the ‘periphery’ of the network that have few connections with other countries within the network.
Canada's NTD co-authorship network by countries in the 7k-core (n = 12).
| Country | First Auth Count | First Auth Rank | All Auth Count | All Auth Rank | All NTD Pub | All NTD Pub Rank | SJR NTD Avg | SJR Rank |
| Canada | 879 | 1 | 2888 | 1 | 1079 | 1 | 0.815 | 1 |
| United States | 50 | 2 | 355 | 2 | 141 | 2 | 0.108 | 2 |
| United Kingdom | 21 | 3 | 114 | 3 | 59 | 3 | 0.04 | 3 |
| France | 16 | 4 | 99 | 4 | 40 | 4 | 0.031 | 4 |
| Germany | 11 | 7 | 54 | 7 | 23 | 5 | 0.014 | 6.5 |
| Switzerland | 5 | 10 | 28 | 9.5 | 16 | 7.5 | 0.01 | 11.5 |
| Uganda | 0 | 49.5 | 28 | 9.5 | 16 | 7.5 | 0.009 | 13.5 |
| Kenya | 4 | 13.5 | 23 | 15 | 9 | 16 | 0.006 | 17 |
| Belgium | 1 | 29.5 | 16 | 19.5 | 10 | 11.5 | 0.006 | 17 |
| Cameroon | 0 | 49.5 | 9 | 27.5 | 6 | 24 | 0.004 | 23.5 |
| Nigeria | 3 | 17 | 12 | 23.5 | 5 | 26 | 0.003 | 29 |
| Ghana | 0 | 49.5 | 8 | 29 | 5 | 26 | 0.003 | 29 |
Canada's NTD co-authorship network by countries in the 2k-core and 1k-core.
| Country | First Auth Count | First Auth Rank | All Auth Count | All Auth Rank | All NTD Pub | All NTD Pub Rank | SJR NTD Avg | SJR Rank |
| 2k-core (n = 4) | ||||||||
| Costa Rica | 0 | 49.5 | 3 | 42.5 | 1 | 54 | 0.001 | 47.5 |
| Gambia | 1 | 29.5 | 2 | 50 | 2 | 41 | 0.001 | 47.5 |
| Cuba | 0 | 49.5 | 1 | 58.5 | 1 | 54 | 0.001 | 47.5 |
| Syrian Arab Republic | 0 | 49.5 | 1 | 58.5 | 1 | 54 | 0 | 58.5 |
| 1k-core (n = 16) | ||||||||
| Burkina Faso | 0 | 49.5 | 1 | 58.5 | 1 | 54 | 0.004 | 23.5 |
| Italy | 0 | 49.5 | 5 | 36 | 3 | 33.5 | 0.003 | 29 |
| Austria | 2 | 20.5 | 12 | 23.5 | 3 | 33.5 | 0.002 | 36.5 |
| Greece | 1 | 29.5 | 5 | 36 | 2 | 41 | 0.002 | 36.5 |
| Pakistan | 1 | 29.5 | 4 | 38.5 | 1 | 54 | 0.002 | 36.5 |
| Panama | 0 | 49.5 | 3 | 42.5 | 2 | 41 | 0.002 | 36.5 |
| Mexico | 1 | 29.5 | 9 | 27.5 | 2 | 41 | 0.001 | 47.5 |
| Nepal | 0 | 49.5 | 2 | 50 | 1 | 54 | 0.001 | 47.5 |
| Chile | 0 | 49.5 | 2 | 50 | 1 | 54 | 0.001 | 47.5 |
| Cambodia | 0 | 49.5 | 1 | 58.5 | 1 | 54 | 0.001 | 47.5 |
| Egypt | 0 | 49.5 | 1 | 58.5 | 1 | 54 | 0.001 | 47.5 |
| Finland | 1 | 29.5 | 4 | 38.5 | 1 | 54 | 0 | 58.5 |
| Malaysia | 1 | 29.5 | 3 | 42.5 | 1 | 54 | 0 | 58.5 |
| Zambia | 0 | 49.5 | 2 | 50 | 1 | 54 | 0 | 58.5 |
| Uruguay | 0 | 49.5 | 1 | 58.5 | 1 | 54 | 0 | 58.5 |
| Haiti | 0 | 49.5 | 1 | 58.5 | 1 | 54 | 0 | 58.5 |
Figure 5Canada's NTD research.
Top 15 institutions by authorship and publication activity.