TY - JOUR
T1 - Publishing data to support the fight against human vector-borne diseases
AU - Edmunds, Scott C
AU - Fouque, Florence
AU - Copas, Kyle A
AU - Hirsch, Tim
AU - Shimabukuro, Paloma Helena Fernandes
AU - Andrade-Filho, José Dilermando
AU - Marceló, Catalina
AU - Morales, Carlos Andrés
AU - Lesmes, María Camila
AU - Fuya, Patricia
AU - Méndez, Sergio
AU - Cadena, Horacio
AU - Ávila-Díaz, Álvaro
AU - Santamaría, Erika
AU - Južnič-Zonta, Živko
AU - Eritja, Roger
AU - Palmer, John R B
AU - Bartumeus, Frederic
AU - Dos Santos-Conceição, Maurício
AU - Chahad-Ehlers, Samira
AU - Silva-Inácio, Cássio Lázaro
AU - Lozovei, Ana Leuch
AU - de Andrade, Andrey José
AU - Paull, Sara
AU - Ángel Miranda, Miguel
AU - Barceló, Carlos
AU - Schaffner, Francis
AU - Della-Torre, Alessandra
AU - Brosens, Dimitri
AU - Dekoninck, Wouter
AU - Hendrickx, Guy
AU - Van Bortel, Wim
AU - Deblauwe, Isra
AU - Smitz, Nathalie
AU - Versteirt, Veerle
AU - Godoy, Rodrigo Espindola
AU - Brilhante, Andreia Fernandes
AU - Ceccarelli, Soledad
AU - Balsalobre, Agustín
AU - Vicente, María Eugenia
AU - Curtis-Robles, Rachel
AU - Hamer, Sarah A
AU - Landa, José Manuel Ayala
AU - Rabinovich, Jorge E
AU - Marti, Gerardo A
AU - Schigel, Dmitry
N1 - FTX; (CC BY 4.0)
PY - 2022
Y1 - 2022
N2 - Vector-borne diseases are responsible for more than 17% of human cases of infectious diseases. In most situations, effective control of debilitating and deadly vector-bone diseases (VBDs), such as malaria, dengue, chikungunya, yellow fever, Zika and Chagas requires up-to-date, robust and comprehensive information on the presence, diversity, ecology, bionomics and geographic spread of the organisms that carry and transmit the infectious agents. Huge gaps exist in the information related to these vectors, creating an essential need for campaigns to mobilise and share data. The publication of data papers is an effective tool for overcoming this challenge. These peer-reviewed articles provide scholarly credit for researchers whose vital work of assembling and publishing well-described, properly-formatted datasets often fails to receive appropriate recognition. To address this, GigaScience's sister journal GigaByte partnered with the Global Biodiversity Information Facility (GBIF) to publish a series of data papers, with support from the Special Programme for Research and Training in Tropical Diseases (TDR), hosted by the World Health Organisation (WHO). Here we outline the initial results of this targeted approach to sharing data and describe its importance for controlling VBDs and improving public health.
AB - Vector-borne diseases are responsible for more than 17% of human cases of infectious diseases. In most situations, effective control of debilitating and deadly vector-bone diseases (VBDs), such as malaria, dengue, chikungunya, yellow fever, Zika and Chagas requires up-to-date, robust and comprehensive information on the presence, diversity, ecology, bionomics and geographic spread of the organisms that carry and transmit the infectious agents. Huge gaps exist in the information related to these vectors, creating an essential need for campaigns to mobilise and share data. The publication of data papers is an effective tool for overcoming this challenge. These peer-reviewed articles provide scholarly credit for researchers whose vital work of assembling and publishing well-described, properly-formatted datasets often fails to receive appropriate recognition. To address this, GigaScience's sister journal GigaByte partnered with the Global Biodiversity Information Facility (GBIF) to publish a series of data papers, with support from the Special Programme for Research and Training in Tropical Diseases (TDR), hosted by the World Health Organisation (WHO). Here we outline the initial results of this targeted approach to sharing data and describe its importance for controlling VBDs and improving public health.
KW - Animals
KW - Humans
KW - Disease Vectors
KW - Communicable Diseases
KW - Zika Virus Infection
KW - Zika Virus
KW - Publishing
U2 - 10.1093/gigascience/giac114
DO - 10.1093/gigascience/giac114
M3 - A1: Web of Science-article
C2 - 36329618
SN - 2047-217X
VL - 11
JO - GigaScience
JF - GigaScience
M1 - giac114
ER -