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4
National Institute of Parasitic Diseases, Chinese Center for Disease Control and Prevention, Chinese Center for Tropical Diseases Research, WHO Collaborating Centre for Tropical Diseases, National Center for International Research on Tropical Diseases, Ministry of Science and Technology, Key Laboratory of Parasite and Vector Biology, Ministry of Health, Shanghai, 200025, China
4
National Institute of Parasitic Diseases, Chinese Center for Disease Control and Prevention, Chinese Center for Tropical Diseases Research, WHO Collaborating Centre for Tropical Diseases, National Center for International Research on Tropical Diseases, Ministry of Science and Technology, Key Laboratory of Parasite and Vector Biology, Ministry of Health, Shanghai, 200025, China
4
National Institute of Parasitic Diseases, Chinese Center for Disease Control and Prevention, Chinese Center for Tropical Diseases Research, WHO Collaborating Centre for Tropical Diseases, National Center for International Research on Tropical Diseases, Ministry of Science and Technology, Key Laboratory of Parasite and Vector Biology, Ministry of Health, Shanghai, 200025, China
1
Centro de Estudios Parasitológicos y de Vectores (CEPAVE-CCT-La Plata-CONICET-UNLP), B1900 La Plata, Buenos Aires, Argentina
2
Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET), C1425FQB Buenos Aires, Argentina
3
CIC, Comisión de Investigaciones Científicas de la Provincia de Buenos Aires, B1900 La Plata, Buenos Aires, Argentina
4
National Institute of Parasitic Diseases, Chinese Center for Disease Control and Prevention, Chinese Center for Tropical Diseases Research, WHO Collaborating Centre for Tropical Diseases, National Center for International Research on Tropical Diseases, Ministry of Science and Technology, Key Laboratory of Parasite and Vector Biology, Ministry of Health, Shanghai, 200025, China
This is an Open Access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.
Chagas disease is caused by Trypanosoma cruzi, which is transmitted to mammals, including humans, mainly by insects of the subfamily Triatominae (Hemiptera: Reduviidae). Also known as “kissing bugs”, the subfamily includes 159 species in 18 genera and five tribes. Although most species are in the Americas, here we present the first compilation of non-American triatomine occurrences. The data (396 records) corresponds to 16 species of the genera Linschosteus and Triatoma from Africa, Asia, and Oceania collected between 1926 and 2022, and include verified records with geographic coordinates, collection dates, and ecological information. The key novelties of our dataset regard (i) temporal and geographical updates of non-American species, (ii) records of T. rubrofasciata hundreds of kilometers inland, and (iii) geographical records of the last two described Triatoma species (T. atrata and T. picta). Our resource supports global surveillance, ecological modeling, and risk assessment by providing evidence of potential vectors for Chagas disease control outside the Americas.
Data description
Context
Chagas disease, caused by the protozoan Trypanosoma cruzi (Chagas, 1909) (NCBI:txid5693) (Kinetoplastida, Trypanosomatidae), is transmitted mainly through the feces of triatomine (Hemiptera: Reduviidae: Triatominae) insect vectors, but may also be transmitted from mother to child, by blood transfusions or infected organ transplants, and by oral transmission through contaminated food and/or beverages. These multiple routes of transmission make Chagas disease an important public health problem, primarily in the Americas [1]. However, the migratory movements of people infected with the parasite from the Americas to other continents have contributed to the global spread of Trypanosoma cruzi [2], raising the need to strengthen entomological surveillance in regions previously considered non-endemic [3].
Currently, the subfamily Triatominae consists of 156 extant and three fossil species, grouped into five tribes and 18 genera [4, 5]. Since the publication on American triatomine species by Carcavallo et al. [6], a new, complete, and integrated database on American triatomine occurrences has been made available [7]. However, since Ryckman and Archbold [8], there has been no integration and updating of information on the distribution of triatomine species outside the Americas. In this context, the main goal of this work is to describe the features of a dataset of non-American triatomine occurrences (henceforth referred to as the “Non-American dataset”), highlighting the most important updates and inclusions. Our Non-American dataset complements the current American triatomine information (henceforth referred to as the “American datasets”), comprising two datasets with more than 35,000 records and made available via the Global Biodiversity Information Facility (GBIF) platform [9, 10] (Figure 1).
Global distribution of people with Chagas disease and triatomine vectors. Green polygons indicate countries with people infected by Trypanosoma cruzi according to the last official estimates, 2018 [11]. Orange dots represent records of American triatomine species [9, 10] and red dots represent non-American triatomine species [12, 13].
This work is the result of an exhaustive review of public information combined with substantial interinstitutional collaborations. This geodatabase may contribute not only to improving knowledge of the biodiversity of the triatomine species outside the Americas, but also to designing improved strategies for health promotion and vector control, with the ability to assess the status and to show the probable impact of Chagas disease management at a global scale.
Non-American triatomine species occurrence dataset
In 1951, Lent assigned the Indo-Pacific species to only two genera, Triatoma Laporte, 1832, and Linshcosteus Distant, 1904 [14]. This study integrated data of 16 species from both genera of triatomine (Table 1), increasing to a total of 396 occurrence records. In this dataset, records from the last two described species of Triatoma (T. atrata Zhao & Cai sp. nov., 2023, and T. picta Zhao & Cai sp. nov., 2023 [5]) have been included. These incorporations, together with the 126 species included in the American dataset [9] and the 17 species included in the Argentinean dataset [10], make a total of 158 triatomine species (T. rubrofasciata is included in both the new Non-American dataset and the Argentinean dataset due to its global geographic distribution). Except for the particular case of the species T. rosai (Alevi, de Oliveira, Caris Garcia, Cesaretto Cristal, Grzyb Delgado, de Freitas Bittinelli, Visinho dos Reis, Ravazi, Bortolozo de Oliveira, Galvão, Vilela de Azeredo-Oliveira and Fernandez Madeira, 2020), which was described in 2020 after the last update of the Argentinean dataset (and therefore not included), occurrence records of all the American triatomine species described up to date [4, 5] are included among the three datasets (American dataset, Argentinean dataset, and Non-American dataset).
Table 1.
Current taxa classification of the Non-American triatomine species (T. rubrofasciata is also present in America) according to the last taxonomic classification of Alevi et al. [4] and Zhao et al. [5].
The triatomine species included in the Non-American dataset are distributed in 34 countries (or overseas territories) of Africa (n = 14, including Réunion (France) and Azores (Portugal)), Asia (n = 15), and Oceania (n = 5, including Hawaii (United States)) being Indonesia, China, India and Vietnam the countries with the highest amount of species (Table 2). The six species belonging to the genus Linshcosteus (L. carnifex Distant, 1904, L. chota Lent & Wygodzinsky, 1979, L. confumus Ghauri, 1976, L. costalis Ghauri, 1976, L. kali Lent & Wygodzinsky, 1979, and L. karupus Galvao, Patterson, Rocha & Jurberg, 2002) have records (n = 26) only in India (Table 2).
Table 2.
Triatomine species present in each country or overseas territory.
Continent
Countries
Species
Africa
Angola Central African Republic Comoros Democratic Republic of the Congo France (Réunion) Madagascar Mali Mauritius Portugal (Azores) Seychelles Sierra Leone South Africa Sudan Tanzania
Triatoma rubrofasciata T. rubrofasciata T. rubrofasciata T. rubrofasciata T. rubrofasciata T. rubrofasciata T. rubrofasciata T. rubrofasciata T. rubrofasciata T. rubrofasciata T. rubrofasciata T. rubrofasciata T. rubrofasciata T. rubrofasciata
Asia
Brunei Cambodia China
Hong Kong India
Indonesia
Japan Malysia
Myanmar Philippines
Saudi Arabia Singapore Sri Lanka
Thailand
Vietnam
T. migrans T. rubrofasciata T. atrata T. picta T. rubrofasciata T. sinica T. rubrofasciata Linshcosteus carnifex L. chota L. confumus L. costalis L. kali L. karupus T. bouvieri T. migrans T. rubrofasciata T. leopoldi T. migrans T. pugasi T. rubrofasciata T. rubrofasciata T. cavernicola T. migrans T. rubrofasciata T. rubrofasciata T. bouvieri T. migrans T. rubrofasciata T. rubrofasciata T. rubrofasciata T. amicitiae T. rubrofasciata T. migrans T. rubrofasciata T. bouvieri T. migrans T. picta T. rubrofasciata
Oceania
Australia Papua New Guinea Republic of Kiribati Tonga United States (Hawaii)
T. leopoldi T. leopoldi T. rubrofasciata T. rubrofasciata T. rubrofasciata
Triatoma rubrofasciata is the only tropicopolitan species of the subfamily Triatominae (Figure 2). It was most frequently found in port cities, although the dataset described here has records in some countries (such as India, China, Vietnam) where this species has been found 100–500 hundreds kilometers inland.
Global geographic distribution of Triatoma rubrofasciata. Georeferenced occurrences from Africa, Asia, and Oceania belong to the Non-American dataset described here [12] and from GBIF-mediated data [13]. The records from America belong to the Argentinean dataset [10].
The temporal range covered in the dataset is from 1926 to 2022 (Figure 3). Date information was available for 73% of the records (n = 289), and 80% of these records (n = 239) belong to T. rubrofasciata. This species was the first triatomine species to be described in 1773 [15], and the oldest record included in this dataset is from 1963. However, 95.3% of the data of this species have been collected in the last 10 years (Figure 4).
Frequency distribution of the number of records per year of T. rubrofasciata.
Methods
Information source types and compilation of triatomine species data
To build the dataset, data for each triatomine species were obtained through a detailed and exhaustive review of information. Non-specific temporal range limits were set to obtain the greatest possible amount of new data from as many countries as possible.
Regarding the published information, several public bibliographic online repositories were used (BioOne, Google Scholar, PLoS, PubMed, Scielo, ScienceDirect, and Wiley). They were reviewed using terms such as “Chagas disease” or “Triatominae” plus “Africa”, “Asia”, and “Oceania” without language restriction.
A large amount of data from China, spanning 2016–2018, was provided by colleagues (co-authors of this work). The geographic information is part of a public paper [16], but the dataset is unpublished.
Data georeferencing process
To rigorously associate each record with a specific location in the geographical space, data must have information expressed in geographic coordinates (latitude and longitude). If no geographic coordinates were available, the site name was used together with information on administrative divisions to attain an accurate location using Google Earth [17]. Where only the geographic coordinates and the site name (locality) were available, the corresponding administrative divisions were completed using GeoLoc [18]. In the case of records with information only at the state/province level, the geographic coordinates were not added.
The datum (coordinate system and set of reference points used to locate places on Earth) used for all geographic records was the World Geodetic System 1984. The final dataset was built after data quality control.
Description of the dataset fields
We compiled all relevant and available information associated with each triatomine species. We attached the data to each dataset field, including characteristics of the specimens collected and of the sampled sites. To better describe the fields (based on Darwin Core terms [19]) used to systematize the information, they were grouped into the following six categories: (1) identifiers (including fields used to identify each record, e.g., occurrence ID, institution code, language of the resource, associated references); (2) systematic (including fields used for systematic information, e.g., scientific name, scientific name authorship, taxon rank, and taxon remarks); (3) geographical (including fields with information such as administrative divisions, coordinates, georreference sources); (4) temporal (including fields related to the event date, such as year, month and day); (5) sampling (including fields related to the sampling process, such as name(s) of specimen collector(s), sampled habitat, sampling protocol and effort); and (6) individual (fields related to the total number, sex, and life stage of individuals sampled).
The following subsections provide details about some of the above-mentioned fields requiring specific clarification.
Systematic fields
When appropriate, the “taxonRemarks” field included notes and/or references about synonyms or formal transferals of the species described in the corresponding record.
Temporal fields
When a group of specimens’ information corresponded to a certain period but with specific available dates, the data were split into different records. If it was not possible to split the data, each record included the original time interval information (in years, months, or days) in the “eventDate” field (e.g., 2016/2018).
Sampling fields
The “habitat” field refers to the type of habitat where the triatomines were collected, and classified into three categories: domicile, peridomicile, and sylvatic. When specific habitat information was aggregated, the habitat was expressed as a combination of two or three those categories (e.g., domicile–peridomicile, domicile–sylvatic, peridomicile–sylvatic, or domicile–peridomicile–sylvatic).
For the “SamplingProtocols” field, the available information was classified into two major categories: (i) active search, when the searching involved specialized staff; and (ii) passive collection, when different types of traps (e.g., light traps) were used and/or data originated from participative science projects (e.g., iNaturalist).
Data validation and quality control
The dataset was subjected to exhaustive quality control. First, each datum was extracted by one person and checked by two others to ensure accuracy and to verify no duplication of records. Subsequently, data were checked to avoid errors (e.g., typing, georeferencing, incorrect locations, synonyms, errors in spelling of administrative divisions) that might have arisen during compilation or data entry. To correct and remove typographical errors and spelling mistakes in the names of administrative divisions, we used OpenRefine software (RRID:SCR_021305) [20], which helps to detect these types of errors in large datasets.
All geographic coordinates were checked using open GIS (QGIS, RRID:SCR_018507 [21]) and Google Earth software [17] to detect georeferenced errors and incorrect locations, ensuring that each point corresponded to a location on the continent and in the correct country. Any outlier coordinates that were geographically distant from the known distribution of a given species were studied to ensure correctness. To detect taxonomic synonym errors, we used the most recent triatomine reviews of currently valid species [4, 5]. If any species name was suspected to be outdated, we consulted the current bibliography or requested the expert opinion of colleagues.
Finally, we improved the quality of our final dataset using the GBIF data validator [22] to identify and address potential issues prior to the dataset publication through the Integrated Publishing Toolkit [23].
Reuse potential
As the information contained within the dataset has been collected using different procedures, this compilation may contain some inherent biases, which should be addressed when the data are used. Most of the data (60%) were obtained from papers published in scientific journals, together with those provided by colleagues (40%). Although data spans 34 countries/overseas territories, China has a volume of data higher than that of other countries; this was due to the significant contribution from colleagues from this country, also co-authors of this work (Qin Liu, Zhou Xiao-Nong, and Di Wu).
Three important notes about the data are: (1) for most species, their presence could be confirmed in countries/states where records had only been available from the 1960s and 1970s; (2) in relation to the above, the GBIF-mediated records (i.e., iNaturalist) used as a complement to show the global distribution of T. rubrofasciata (Figure 2) demonstrate the significant contribution for scientific research and policy by current data coming from participatory science projects; (3) making public and available the geographical records from the last two described species of Triatoma (T. atrata Zhao & Cai sp. nov., 2023 and T. picta Zhao & Cai, 2023 [5]).
For habitat sampling, we recognize a potential bias in favor of the domiciliary and peridomiciliary habitats because these are the habitats of greater epidemiological importance. Additionally, the paucity of sylvatic habitat data also results from the difficulty of sampling procedures in the large variety of sylvatic habitats used by triatomines from locations outside those areas where reports are commonly made. Here, we remark on the utility of applications based on citizen-science projects in promoting an increase in reports of sylvatic species. Finally, it is worth noting that about 27% of the records lack available date information, and around 7% of them lack geographic coordinates; thus, we recommend that any analysis based on this dataset should use methods that take such biases into account.
Finally, we would like to remark one reference of a T. rubrofasciata record that we considered as having doubtful geographic information (Region of Murcia, Spain) [24], and it was possibly the result of passive transport. Although the record was not included in the dataset, the available evidence indicates this is a plausible mode of transportation for these insects with merchandise. Additionally, it shows that these bugs have high resistance to starvation, and that the highest prevalence of Chagas disease in Europe is in Spain. Hence, we considered that the establishment of a new population of this vector would create a new epidemiological scenario, so we have to be alert.
Despite the information biases described above, the dataset described in this paper, and the complementary American datasets, constitute a valuable compilation of geographic data on American and non-American triatomines, which is as complete, updated, and integrated as possible. Thus, all datasets mentioned herein better represent the number of species and countries, and have more accurate geographic coordinates. Since these datasets are hosted in an open and public repository, we hope that they will contribute to fulfilling national and international goals, such as promoting the exchange of biological information, increasing and improving the accessibility of such information, providing biological data produced and compiled in several countries, and enhancing knowledge of both the biodiversity and epidemiological data related to Chagas disease.
Acknowledgements
The authors are grateful to the people who provided unpublished data, and to the authors who confirmed details related to their published work and who are cited in the published datasets linked to this data paper. SC and GAM had full access to all the data in the study and take responsibility for the integrity of the data and the accuracy of the data analysis. We thank the Argentine GBIF Node for the valuable technical support provided during the data management, standardization, and publication process.
Funding Statement
This research was funded by grants “Fortalecimiento y promoción de proyectos de ciencia ciudadana” 2022, No 40 (Head Researcher PhD GAM) from Fondo para la Investigación Científica y Tecnológica (FONCYT), Argentina.
Data availability
The dataset “Non-American triatomine occurrence data (Reduviidae:Triatominae)” has been published by Centro de Estudios Parasitológicos y de Vectores (CEPAVE) [25] and is available in the GBIF repository under a CC0 public domain waiver [12]. Additional data is available in GigaDB [26].
Editors’ note
This paper is part of a series of Data Release articles working with GBIF and supported by TDR, the Special Programme for Research and Training in Tropical Diseases hosted at the World Health Organization, in order to publish datasets on vectors of human diseases [27].
Declarations
Ethical approval
Not applicable.
Consent for publication
Not applicable.
Competing interests
The authors declare that they have no competing interests.
Authors’ contributions
SC, MEV, AB, and RV drafted the data collection protocol. SC, GM, and MEV requested unpublished data from researchers. MEV and SC quality controlled the data; QL, X-NZ, and DW quality controlled the data from China. SC wrote the first draft and all authors contributed to the manuscript. All authors read and approved the final version of the manuscript.
Funding
This research was funded by grants “Fortalecimiento y promoción de proyectos de ciencia ciudadana” 2022, No 40 (Head Researcher PhD GAM) from Fondo para la Investigación Científica y Tecnológica (FONCYT), Argentina.
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Triatominos por fuera de las Américas: conjunto de datos integral para la vigilancia global de los vectores de la enfermedad de Chagas
4
National Institute of Parasitic Diseases, Chinese Center for Disease Control and Prevention, Chinese Center for Tropical Diseases Research, WHO Collaborating Centre for Tropical Diseases, National Center for International Research on Tropical Diseases, Ministry of Science and Technology, Key Laboratory of Parasite and Vector Biology, Ministry of Health, Shanghai, 200025, China
4
National Institute of Parasitic Diseases, Chinese Center for Disease Control and Prevention, Chinese Center for Tropical Diseases Research, WHO Collaborating Centre for Tropical Diseases, National Center for International Research on Tropical Diseases, Ministry of Science and Technology, Key Laboratory of Parasite and Vector Biology, Ministry of Health, Shanghai, 200025, China
4
National Institute of Parasitic Diseases, Chinese Center for Disease Control and Prevention, Chinese Center for Tropical Diseases Research, WHO Collaborating Centre for Tropical Diseases, National Center for International Research on Tropical Diseases, Ministry of Science and Technology, Key Laboratory of Parasite and Vector Biology, Ministry of Health, Shanghai, 200025, China
1
Centro de Estudios Parasitológicos y de Vectores (CEPAVE-CCT-La Plata-CONICET-UNLP), B1900 La Plata, Buenos Aires, Argentina
2
Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET), C1425FQB Buenos Aires, Argentina
3
CIC, Comisión de Investigaciones Científicas de la Provincia de Buenos Aires, B1900 La Plata, Buenos Aires, Argentina
4
National Institute of Parasitic Diseases, Chinese Center for Disease Control and Prevention, Chinese Center for Tropical Diseases Research, WHO Collaborating Centre for Tropical Diseases, National Center for International Research on Tropical Diseases, Ministry of Science and Technology, Key Laboratory of Parasite and Vector Biology, Ministry of Health, Shanghai, 200025, China
*
Autor correspondiente. E-mail: soledad.ceccarelli@gmail.com
Roles
Soledad Ceccarelli: Conceptualization, Formal analysis, Writing - original draft
Maria Eugenia Vicente: Data curation, Methodology, Writing - review editing
Qin Liu: Data curation, Writing - review editing
Xiao-Nong Zhou: Data curation, Writing - review editing
Di Wu: Data curation, Writing - review editing
Agustin Balsalobre: Formal analysis, Data curation, Writing - review editing
Emiliano A Bruno: Writing - review editing
S Emilia Barboza: Writing - review editing
Romina Valente: Data curation, Writing - review editing
Gerardo A Marti: Conceptualization, Methodology, Writing - review editing
Received 2025 Jun 6; Accepted 2025 Aug 19; Collection date 2025.
This is an Open Access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.
La enfermedad de Chagas es causada por el Trypanosoma cruzi, que se transmite a mamíferos, incluyendo humanos, principalmente por insectos de la subfamilia Triatominae (Hemiptera: Reduviidae). Esta subfamilia incluye 159 especies en 18 géneros y cinco tribus. Aunque la mayoría de las especies se encuentran en el continente americano, aquí presentamos la primera compilación de ocurrencias de triatominos no americanos. Los datos (396 registros) corresponden a 16 especies de los géneros Linschosteus y Triatoma de África, Asia y Oceanía recolectadas entre 1926 y 2022, e incluyen registros verificados con coordenadas geográficas, fechas de recolección e información ecológica. Las principales novedades de nuestro conjunto de datos se refieren a: (i) actualizaciones temporales y geográficas de especies no americanas, (ii) registros de T. rubrofasciata cientos de kilómetros tierra adentro, y (iii) registros geográficos de las dos últimas especies de Triatoma descritas (T. atrata y T. picta). Nuestro recurso apoya la vigilancia global, el modelado ecológico y la evaluación de riesgos al proporcionar evidencia de vectores potenciales para el control de la enfermedad de Chagas fuera de las Américas.
Descripción de los datos
Contexto
La enfermedad de Chagas, causada por el protozoo Trypanosoma cruzi (Chagas, 1909) (NCBI:txid5693) (Kinetoplastida, Trypanosomatidae), se transmite principalmente a través de las heces de insectos vectores llamados triatominos (Hemiptera: Reduviidae: Triatominae), aunque también puede transmitirse de una persona gestante a su descendencia, por transfusiones de sangre o trasplantes de órganos infectados, y por transmisión oral mediante la ingesta de alimentos y/o bebidas contaminados. Estas múltiples rutas de transmisión hacen que la enfermedad de Chagas sea un problema importante de salud pública, principalmente en las Américas [1]. Sin embargo, los movimientos migratorios de personas infectadas con el parásito desde las América a otros continentes han contribuido a la expansión global del Trypanosoma cruzi [2], lo que resalta la necesidad de fortalecer la vigilancia entomológica en regiones previamente consideradas no endémicas [3].
Actualmente, la subfamilia Triatominae está formada por 156 especies actuales y tres fósiles, agrupadas en cinco tribus y 18 géneros [4, 5]. Luego de la última publicación integral sobre especies americanas de triatominos de Carcavallo y col. [6], se publica una base de datos actualizada e integrada sobre presencias de triatominos americanos [7]. Sin embargo, desde Ryckman y Archbold [8], no se ha realizado una integración ni actualización de la información sobre la distribución de especies de triatominos fuera de las Américas. En este contexto, el objetivo principal de este trabajo es describir las características de un conjunto de datos de presencias de triatominos no americanos (de ahora en adelante, el “conjunto de datos no americano”), destacando las actualizaciones e inclusiones más importantes. Este conjunto complementa la información actual sobre triatominos americanos (denominado “conjuntos de datos americanos”), que comprende dos bases con más de 35,000 registros y están disponibles en la plataforma Global Biodiversity Information Facility (GBIF) [9, 10] (Figura 1).
Distribución global de personas con Chagas y de especies de triatominos. Los polígonos verdes indican países con personas infectadas por el Trypanosoma cruzi según las últimas estimaciones oficiales, 2018 [11]. Los puntos naranjas representan registros de especies americanas de triatominos [9, 10] y los puntos rojos, representan registros de especies no americanas [12, 13].
Este trabajo es el resultado de una revisión exhaustiva de información pública combinada con una colaboración interinstitucional sustancial. Este conjunto de datos puede contribuir, no solo a mejorar el conocimiento sobre la biodiversidad de las especies de triatominos fuera de las Américas, sino también en el diseño de estrategias mejoradas para la promoción de la salud y el control de vectores, para evaluar el estado actual y mostrar el impacto probable de la enfermedad de Chagas a escala global.
Conjunto de datos de presencias de triatominos no americanos
En 1951, Lent asignó las especies del Indo-Pacífico solo a dos géneros, Triatoma Laporte, 1832 y Linshcosteus Distant, 1904 [14]. El presente estudio integra datos de 16 especies de ambos géneros de triatominos (Tabla 1), llegando a un total de 396 registros de presencias. En este conjunto de datos se han incluido registros de las dos últimas especies descritas de Triatoma (T. atrata Zhao & Cai sp. nov. 2023 y T. picta Zhao & Cai sp. nov., 2023 [5]). Estas incorporaciones, junto con las 126 especies incluidas en el conjunto de datos americano [9] y las 17 especies del conjunto de datos argentino [10], hacen un total de 158 especies de triatominos (T. rubrofasciata está incluida tanto en el nuevo conjunto de datos no americano como en el conjunto argentino debido a su distribución geográfica global). Exceptuando el caso particular de la especie T. rosai (Alevi, de Oliveira, Caris Garcia, Cesaretto Cristal, Grzyb Delgado, de Freitas Bittinelli, Visinho dos Reis, Ravazi, Bortolozo de Oliveira, Galvão, Vilela de Azeredo-Oliveira & Fernandez Madeira, 2020), que fue descrita en 2020 luego de la última actualización del conjunto de datos argentino (y por lo tanto no incluida), los registros de presencia de todas las especies americanas de triatominos descritas hasta la fecha [4, 5] están incluidos entre los tres conjuntos de datos (conjunto americano, argentino y no americano).
Tabla 1.
Clasificaciń taxonómica actual de las especies de triatominos no americanos (T. rubrofasciata también está presente en América) según la última clasificación taxonómica de Alevi et al. [4] y Zhao et al. [5].
Los géneros de triatominos incluidos en el conjunto de datos no americano están distribuidos en 34 países (o territorios de ultramar) de África (n = 14, incluyendo Reunión (Francia) y Azores (Portugal)), Asia (n = 15) y Oceanía (n = 5, incluyendo Hawái (Estados Unidos)), siendo Indonesia, China, India y Vietnam los países con la mayor cantidad de especies presentes (Tabla 2). Las seis especies del género Linshcosteus (L. carnifex Distant, 1904; L. chota Lent & Wygodzinsky, 1979; L. confumus Ghauri, 1976; L. costalis Ghauri, 1976; L. kali Lent & Wygodzinsky, 1979; y L. karupus Galvao, Patterson, Rocha & Jurberg, 2002) tienen registros (n = 26) solo en India (Tabla 2).
Tabla 2.
Especies de triatominos presentes en cada país o territorio de ultramar.
Continent
Countries
Species
África
Angola Comoros Francia (Reunión) Madagascar Mali Mauricio República Centroafricana República Democrática del Congo Seychelles Sierra Leona Sudáfrica Sudán Tanzania Portugal (Azores)
Triatoma rubrofasciata T. rubrofasciata T. rubrofasciata T. rubrofasciata T. rubrofasciata T. rubrofasciata T. rubrofasciata T. rubrofasciata T. rubrofasciata T. rubrofasciata T. rubrofasciata T. rubrofasciata T. rubrofasciata T. rubrofasciata
Asia
Arabia Saudita Brunei Camboya China
Filipinas
Hong Kong India
Indonesia
Japón Malasia
Myanmar Singapur Sri Lanka
Tailandia
Vietnam
T. rubrofasciata T. migrans T. rubrofasciata T. atrata T. picta T. rubrofasciata T. sinica T. bouvieri T. migrans T. rubrofasciata T. rubrofasciata Linshcosteus carnifex L. chota L. confumus L. costalis L. kali L. karupus T. bouvieri T. migrans T. rubrofasciata T. leopoldi T. migrans T. pugasi T. rubrofasciata T. rubrofasciata T. cavernicola T. migrans T. rubrofasciata T. rubrofasciata T. rubrofasciata T. amicitiae T. rubrofasciata T. migrans T. rubrofasciata T. bouvieri T. migrans T. picta T. rubrofasciata
Oceanía
Australia Estados Unidos (Hawai) Papúa Nueva Guinea República de kiribati Tonga
T. leopoldi T. rubrofasciata T. leopoldi T. rubrofasciata T. rubrofasciata
Triatoma rubrofasciata es la única especie tropicopolita de la subfamilia Triatominae (Figura 2). Se encontró con mayor frecuencia en ciudades portuarias, aunque el conjunto de datos aquí descrito presenta registros en algunos países (como India, China, Vietnam) donde esta especie ha sido encontrada entre 100 y 500 kilómetros tierra adentro.
Distribución geográfica global de Triatoma rubrofasciata. Los registros georreferenciados de África, Asia y Oceanía pertenecen al conjunto de datos no americano aquí descrito [12] y a datos mediados por GBIF [13]. Los registros de América pertenecen al conjunto de datos argentino [10].
El rango temporal cubierto en el conjunto de datos va desde 1926 hasta 2022 (Figura 3). La información de fechas está disponible para el 73% de los registros (n = 289), y el 80% de estos registros (n = 239) corresponden a T. rubrofasciata. Esta especie fue la primera en ser descrita en el año 1773 [15], y el registro más antiguo incluido en este conjunto de datos corresponde al año 1963. Sin embargo, el 95,3% de los datos de esta especie se han recopilado en los últimos 10 años (Figura 4).
Distribución de frecuencia del número de registros por año de la especie T. rubrofasciata.
Métodos
Tipos de fuentes de información y recopilación de datos sobre especies de triatominos
Para construir el conjunto de datos, se obtuvo la información para cada especie de triatomino mediante una revisión detallada y exhaustiva. No se establecieron límites temporales específicos para así poder obtener la mayor cantidad posible de nuevos datos provenientes de tantos países como fuera posible.
En cuanto a la información publicada, se utilizaron varios repositorios bibliográficos en línea (como BioOne, Google Scholar, PLoS, PubMed, Scielo, ScienceDirect, Wiley) y se revisaron los mismos usando términos como “enfermedad de Chagas”, “Triatominae” junto con “África”, “Asia” y “Oceanía”, sin restricción idiomática.
Hubo una gran cantidad de datos correspondientes a China entre 2016 y 2018 proporcionados por colegas (coautores de este trabajo). La información geográfica forma parte de un artículo público [16], pero el conjunto de datos no estaba disponible.
Proceso de georreferenciación de datos
Para asociar rigurosamente cada registro a una ubicación específica en el espacio geográfico, los datos deben contener información expresada en coordenadas geográficas (latitud y longitud). Si no estaban disponibles dichas coordenadas geográficas, se utilizó el nombre del sitio junto con información sobre divisiones administrativas para obtener una ubicación precisa mediante Google Earth [17]. Cuando solo estaban disponibles las coordenadas geográficas y el nombre del sitio (localidad), se completaron las divisiones administrativas correspondientes usando GeoLoc [18]. En el caso de los registros que solo tenían información a nivel de estado/provincia, no se añadieron las coordenadas geográficas. El datum (sistema de coordenadas y conjunto de puntos de referencia utilizados para localizar lugares en la Tierra) empleado para todos los registros geográficos fue el WGS84 (World Geodetic System 1984). El conjunto de datos final se construyó tras realizar un control de calidad de los datos.
Descripción de los campos del conjunto de datos
Se recopiló toda la información relevante y disponible relacionada con cada especie de triatomino y se vincularon los datos a cada campo del conjunto de datos, incluyendo las características de los especímenes recolectados y de los sitios muestreados. Para describir mejor los campos (basados en los términos de Darwin Core [19]) utilizados para sistematizar la información, estos se agruparon en las siguientes seis categorías: (1) identificadores (incluyendo campos utilizados para identificar cada registro, por ejemplo, ID de presencia, código de la institución, idioma del recurso, referencias asociadas, etc.); (2) sistemático (incluyendo campos utilizados para la información sistemática, como nombre científico, autoría del nombre científico, rango taxonómico y observaciones sobre el taxón); (3) geográfico (incluyendo campos con información como divisiones administrativas, coordenadas geográficas, fuentes de georreferenciación, etc.); (4) temporal (incluyendo campos relacionados con la fecha del evento, como año, mes y día); (5) muestreo (incluyendo campos relacionados con el proceso de muestreo, como nombres del(os) colector(es), hábitat muestreado, protocolo y esfuerzo de muestreo, etc.); y (6) de individuos (campos relacionados con el número total, sexo y etapa de vida de los individuos muestreados). Las siguientes subsecciones proporcionan detalles sobre algunos de los campos mencionados que requieren aclaraciones específicas.
Campos sistemáticos
Cuando fue apropiado, en el campo “taxonRemarks” se incluyeron notas y/o referencias sobre sinónimos o transferencias formales de la especie descrita en el registro correspondiente.
Campos temporales
Cuando la información de un grupo de especímenes correspondía a un período de tiempo determinado pero con fechas específicas disponibles, los datos se dividieron en diferentes registros. Si no fue posible dividir los datos, cada registro incluía la información original del intervalo temporal (en años, meses o días) en el campo “eventDate” (por ejemplo, 2016/2018).
Campos de muestreo
El campo “hábitat” refiere al tipo de hábitat donde se recolectaron los triatominos, y se clasificó en tres categorías: domicilio, peridomicilio y silvestre. Cuando la información específica del hábitat estaba agrupada, el hábitat se expresa como una combinación de dos o tres de estas categorías (por ejemplo, domicilio–peridomicilio, domicilio–silvestre, peridomicilio–silvestre o domicilio–peridomicilio–silvestre). Para el campo “SamplingProtocols”, la información disponible se clasificó en dos categorías principales: (i) búsqueda activa, cuando la búsqueda involucraba personal especializado; y (ii) recolección pasiva, cuando se utilizaban diferentes tipos de trampas (por ejemplo, trampas de luz) y/o los datos provenían de proyectos de ciencia participativa (por ejemplo, iNaturalist).
Validación de datos y control de calidad
El conjunto de datos fue sometido a un exhaustivo control de calidad. Primero, cada dato fue extraído por una persona y revisado por otras dos para garantizar su precisión y verificar que no hubiera registros duplicados. Posteriormente, los datos fueron revisados para evitar errores (por ejemplo, errores tipográficos, georreferenciación incorrecta, ubicaciones erróneas, sinónimos, errores en la ortografía de divisiones administrativas) que pudieran haber surgido durante la compilación o entrada de datos. Para corregir y eliminar errores tipográficos y errores ortográficos en los nombres de las divisiones administrativas, utilizamos el software OpenRefine (RRID:SCR_021305) [20], el cual ayuda a detectar estos tipos de errores en grandes conjuntos de datos. Todas las coordenadas geográficas fueron verificadas usando un software SIG libre (QGIS, RRID:SCR_018507 [21]) y Google Earth [17] con el fin de detectar errores de georreferenciación, como así también ubicaciones incorrectas, asegurando que cada punto correspondiera a una ubicación en el continente y país correcto. Cualquier coordenada atípica que estuviera geográficamente lejos de la distribución conocida de una especie dada fue estudiada en mayor profundidad para garantizar su precisión. Para detectar errores de sinónimos taxonómicos, utilizamos las revisiones más recientes sobre triatominos de especies actualmente válidas [4, 5]. Si algún nombre de especie parecía estar desactualizado, consultamos bibliografía actual o solicitamos la opinión de colegas.
Finalmente, mejoramos la calidad de nuestro conjunto de datos final utilizando el validador de datos de GBIF [22] con el fin de identificar y abordar posibles problemas antes de la publicación del conjunto de datos a través del Toolkit de Publicación Integrada (IPT, [23]).
Potencial de reutilización
Dado que la información contenida en el conjunto de datos ha sido recopilada mediante diferentes procedimientos, esta compilación puede contener sesgos inherentes, los cuales deben ser considerados al utilizar los datos. La mayor parte de los datos (60%) proviene de artículos publicados en revistas científicas, junto con aquellos proporcionados por colegas (40%). Aunque los datos abarcan 34 países/territorios de ultramar, China tiene un volumen de datos mayor que los demás debido a que el número de registros está influenciado por la gran contribución de colegas de ese país, coautores de este trabajo (Qin Liu, Zhou Xiao-Nong y Di Wu). Al mismo tiempo, cabe mencionar tres notas importantes sobre los datos: (1) para la mayoría de las especies, su presencia pudo ser confirmada en países/estados donde los registros solo estaban disponibles en las décadas de 1960 y 1970; (2) en relación con lo anterior, los registros mediados por GBIF (es decir, iNaturalist), utilizados como complemento para mostrar la distribución global de T. rubrofasciata (Figura 2), demuestran la gran contribución que tienen los datos actuales provenientes de proyectos de ciencia participativa para la investigación científica y las políticas públicas; y (3) hacer públicos y disponibles los registros geográficos de las dos especies descritas más recientemente del género Triatoma (T. atrata Zhao & Cai sp. nov., 2023 y T. picta Zhao & Cai sp. nov., 2023 [5]).
Respecto al muestreo de los diferentes hábitats, reconocemos un posible sesgo a favor de los hábitats domiciliarios y peridomiciliarios, ya que estos son los hábitats de mayor importancia epidemiológica. Además, la escasez de datos sobre hábitats silvestres también resulta de la dificultad de los procedimientos de muestreo en la gran variedad de hábitats silvestres utilizados por los triatominos en lugares fuera de aquellas áreas donde comúnmente se reportan. Aquí es donde destacamos la utilidad en el uso de aplicaciones enmarcadas en proyectos de ciencia participativa para promover el aumento en los reportes de especies silvestres. Finalmente, cabe señalar que aproximadamente el 27% de los registros carecen de información temporal, y alrededor del 7% no tienen coordenadas geográficas; por lo tanto, recomendamos que cualquier análisis basado en este conjunto de datos utilice métodos que tengan en cuenta estos sesgos.
Por último, nos gustaría mencionar una referencia de un registro de T. rubrofasciata que consideramos que aunque posee información geográfica dudosa (Región de Murcia, España) [24], posiblemente como resultado de transporte pasivo, se debe considerar. Aunque el registro no se incluyó en el conjunto de datos, la evidencia disponible indica que éste es un modo plausible de transporte para estos insectos con mercancías. Adicionalmente, se demuestra la alta resistencia a la inanición que poseen estos insectos y el hecho de que la prevalencia más alta de enfermedad de Chagas en Europa ocurre en España. Por ello, consideramos que el establecimiento de una nueva población de este vector podría crear un nuevo escenario epidemiológico y debemos estar alertas.
A pesar de los sesgos de información descritos anteriormente, el conjunto de datos descrito en este artículo, junto con los conjuntos de datos complementarios de América, constituyen una valiosa recopilación de datos geográficos sobre triatominos americanos y no americanos, que es la más completa, actualizada e integrada hasta el momento. Por lo tanto, todos los conjuntos de datos mencionados aquí representan de la mejor manera el número de especies y países, y cuentan con coordenadas geográficas precisas. Dado que estos conjuntos de datos están alojados en un repositorio abierto y público, esperamos que contribuyan a cumplir con metas nacionales e internacionales, como promover el intercambio de información biológica, aumentar y mejorar la accesibilidad a dicha información, proporcionar datos biológicos producidos y compilados en varios países, y ampliar el conocimiento tanto sobre la biodiversidad como sobre los datos epidemiológicos relacionados con la enfermedad de Chagas.
Agradecimientos
Los autores y autoras del presente trabajo agradecen a quienes proporcionaron datos inéditos y a quienes confirmaron detalles relacionados con su trabajo publicado y aparecen citados en los correspondientes conjuntos de datos vinculados a este documento. SC y GAM tuvieron pleno acceso a todos los datos del estudio y se responsabilizan de su integridad y precisión en el análisis. Agradecemos al Nodo argentino de GBIF por el valioso apoyo técnico brindado durante el proceso de gestión, estandarización y publicación de los datos.
Funding Statement
Esta investigación fue financiada por el subsidio “Fortalecimiento y promoción de proyectos de ciencia ciudadana” 2022, No 40 (Investigador principal GAM) del Fondo para la Investigación Científica y Tecnológica (FONCYT), Argentina.
Disponibilidad de datos
El conjunto de datos “Non-American triatomine occurrence data (Reduviidae:Triatominae)” ha sido publicado por el Centro de Estudios Parasitológicos y de Vectores (CEPAVE) [25] y está disponible en el repositorio GBIF bajo una licencia CC0 [12]. Datos adicionales están disponibles en GigaDB [26].
Nota del editor
Este documento forma parte de una serie de artículos de publicación de datos en colaboración con GBIF y con el apoyo de TDR, el Programa Especial de Investigación y Capacitación sobre Enfermedades Tropicales de la Organización Mundial de la Salud, con el fin de publicar conjuntos de datos sobre vectores de enfermedades humanas [27].
Declaraciones
Aprobación ética
No aplica.
Consentimiento para publicar
No aplica.
Conflicto de intereses
Los autores declaran que no tienen conflictos de interés.
Contribuciones de los autores
SC, MEV, AB y RV elaboraron el protocolo para la recolección de datos. SC, GM y MEV solicitaron datos no publicados a investigadores. MEV y SC realizaron el control de calidad general del conjunto de datos; QL, X-NZ y DW controlaron la calidad de los datos provenientes de China. SC redactó el primer borrador y todos los autores y autoras contribuyeron en el manuscrito. Todos los autores y autoras leyeron y aprobaron la versión final del manuscrito.
Financiamiento
Esta investigación fue financiada por el subsidio “Fortalecimiento y promoción de proyectos de ciencia ciudadana” 2022, No 40 (Investigador principal GAM) del Fondo para la Investigación Científica y Tecnológica (FONCYT), Argentina.
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Reviewer name and names of any other individual's who aided in reviewer
none
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Yes
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Yes
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none
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Yes
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Are the data and metadata consistent with relevant minimum information or reporting standards? See GigaDB checklists for examples <a href="http://gigadb.org/site/guide" target="_blank">http://gigadb.org/site/guide</a>
No
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below in the review
Is the data acquisition clear, complete and methodologically sound?
Yes
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Is there sufficient detail in the methods and data-processing steps to allow reproduction?
Yes
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Is there sufficient data validation and statistical analyses of data quality?
Yes
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Is the validation suitable for this type of data?
Yes
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Is there sufficient information for others to reuse this dataset or integrate it with other data?
Yes
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Any Additional Overall Comments to the Author
I would like to express my gratitude for the opportunity to review this manuscript. It is a solid, well-written, and highly relevant study for the field of global health, particularly concerning entomological surveillance of Chagas disease in non-endemic regions. The authors’ effort to systematize occurrence data of triatomines outside the Americas bringing together nearly a century’s worth of records into a curated and accessible database represents a significant contribution to the scientific community and public health programs. In the data description, I suggest updating the number of currently recognized genera, which now stands at 19. Please refer to: Paiva VF, de Oliveira J, Belintani T, Galvão C, Gil-Santana HR, da Rosa JA. Hospesneotomae n. gen. of the Triatomini tribe presents a turnaround in the taxonomy of the Triatoma protracta species complex. Sci Rep. 2025 Mar 9;15(1):8143. doi: 10.1038/s41598-025-91399-w. Another relevant point is to consider the occurrence of Triatoma rubrofasciata in Europe: Collantes F, Campos-Serrano JF, Ruiz-Arrondo I. Accidental importation of the vector of Chagas disease, Triatoma rubrofasciata (De Geer, 1773) (Hemiptera, Reduviidae, Triatominae), in Europe. J Vector Ecol. 2023 Jun;48(1):63-65. doi: 10.52707/1081-1710-48.1.63. I would, however, like to suggest a few specific adjustments aimed at improving the clarity and precision of the information presented. Firstly, I noticed a minor inconsistency in the data: the manuscript states that 299 records contain a collection date (“eventDate”), but upon accessing the dataset published on GBIF, I found only 289 records with this field completed. Similarly, it is stated that approximately 33% of records lack a date, whereas the actual figure appears to be closer to 27% (107 records without a date out of 396 total). I recommend reviewing and adjusting these figures to ensure consistency between the manuscript and the dataset. Another important point concerns the dataset’s license. The manuscript refers to a CC0 license, whereas the license registered on GBIF is CC BY-NC 4.0. I suggest correcting this information to accurately reflect the data’s access and reuse policy. I also noted that 46 records include dates that do not follow the ISO 8601 format, which may affect the dataset’s interoperability. I recommend reviewing and standardizing these entries using the YYYY-MM-DD format, in accordance with GBIF guidelines. With respect to the content of the manuscript, I commend the integration of data from citizen science sources (such as iNaturalist), which innovatively broadens the scope and contemporaneity of the dataset. This approach could be further enriched by a brief discussion on the strengths and limitations of such data for entomological surveillance purposes. Finally, I acknowledge and appreciate the transparent discussion of potential biases within the dataset, especially regarding the predominance of records in domestic and peridomestic habitats. It might be valuable to emphasize a bit more the potential impact of this limitation on future ecological analyses and to suggest possible strategies to encourage records from sylvatic environments. In summary, this is an excellent piece of work that, with a few minor adjustments, will certainly have even greater impact and utility. I recommend the acceptance of the manuscript pending minor revisions.
Reviewer name and names of any other individual's who aided in reviewer
Bastien MOLCRETTE
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Yes
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Yes
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“Date information was available for 75% of the records (n= 299)”: I only count 289 occurrences with event date in the GBIF dataset; needs to be clarified. Related: “Finally, it is worth noting that about 33% of the records lack available date information”: 107 occurrences missing data info over 396 occurrences = 27% (not 33%)
Are the data and metadata consistent with relevant minimum information or reporting standards? See GigaDB checklists for examples <a href="http://gigadb.org/site/guide" target="_blank">http://gigadb.org/site/guide</a>
Yes
Additional Comments
1 - GBIF Non-American dataset catalog number 86 (Azores occurrence) is indicated as continent = Asia, when it is Africa in the manuscript (Africa makes more sense than Asia) 2 - 46 Recorded date are not formatted correctly, need to follow ISO 8601 (see https://discourse.gbif.org/t/please-share-your-dates-correctly/3824)
Is the data acquisition clear, complete and methodologically sound?
Yes
Additional Comments
Is there sufficient detail in the methods and data-processing steps to allow reproduction?
Yes
Additional Comments
Is there sufficient data validation and statistical analyses of data quality?
Yes
Additional Comments
Is the validation suitable for this type of data?
Yes
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Is there sufficient information for others to reuse this dataset or integrate it with other data?
Reviewer name and names of any other individual's who aided in reviewer
Johan Manuel Calderón
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Yes
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Yes
Please add additional comments on language quality to clarify if needed
Are all data available and do they match the descriptions in the paper?
Yes
Additional Comments
Are the data and metadata consistent with relevant minimum information or reporting standards? See GigaDB checklists for examples <a href="http://gigadb.org/site/guide" target="_blank">http://gigadb.org/site/guide</a>
Yes
Additional Comments
Is the data acquisition clear, complete and methodologically sound?
Yes
Additional Comments
Is there sufficient detail in the methods and data-processing steps to allow reproduction?
Yes
Additional Comments
Is there sufficient data validation and statistical analyses of data quality?
Yes
Additional Comments
Is the validation suitable for this type of data?
Yes
Additional Comments
Is there sufficient information for others to reuse this dataset or integrate it with other data?
Yes
Additional Comments
Thios dataset is an important contribution to the datasets available for researchers, and they would allow to increase and diversity to amount of information given to ecological models, increasing their prediction power.
Triatomines or kissing bugs are vectors of Chagas disease, caused by the protozoan Trypanosoma cruzi. Chagas disease is predominantly a public health problem in the Americas, however, the increasing risks and migratory movements of people infected with the parasite spreading it to other continents has increased the need to strengthen entomological surveillance in regions previously considered non-endemic. As part of the GBIF and TDR supported vectors of human disease series in GigaByte we have here a dataset of non-American triatomine occurrences. This work being the result of an exhaustive review of public information combined with substantial interinstitutional collaborations (particularly China). In total 396 records were reported between 1926 and 2022, corresponding to 16 species of the genera Linschosteus and Triatoma from Africa, Asia, and Oceania, and include verified records with geographic coordinates, collection dates, and ecological information. Data was validated and peer reviewed, and records that look suspect were fixed or omitted. The dataset described in this paper should constitute a valuable compilation geographic data non-American triatomines, which is as complete, updated, and integrated as possible.
Editor’s Assessment
Triatomines or kissing bugs are vectors of Chagas disease, caused by the protozoan Trypanosoma cruzi. Chagas disease is predominantly a public health problem in the Americas, however, the increasing risks and migratory movements of people infected with the parasite spreading it to other continents has increased the need to strengthen entomological surveillance in regions previously considered non-endemic. As part of the GBIF and TDR supported vectors of human disease series in GigaByte we have here a dataset of non-American triatomine occurrences. This work being the result of an exhaustive review of public information combined with substantial interinstitutional collaborations (particularly China). In total 396 records were reported between 1926 and 2022, corresponding to 16 species of the genera Linschosteus and Triatoma from Africa, Asia, and Oceania, and include verified records with geographic coordinates, collection dates, and ecological information. Data was validated and peer reviewed, and records that look suspect were fixed or omitted. The dataset described in this paper should constitute a valuable compilation geographic data non-American triatomines, which is as complete, updated, and integrated as possible.
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Data Availability Statement
The dataset “Non-American triatomine occurrence data (Reduviidae:Triatominae)” has been published by Centro de Estudios Parasitológicos y de Vectores (CEPAVE) [25] and is available in the GBIF repository under a CC0 public domain waiver [12]. Additional data is available in GigaDB [26].
El conjunto de datos “Non-American triatomine occurrence data (Reduviidae:Triatominae)” ha sido publicado por el Centro de Estudios Parasitológicos y de Vectores (CEPAVE) [25] y está disponible en el repositorio GBIF bajo una licencia CC0 [12]. Datos adicionales están disponibles en GigaDB [26].
