Of all the animal kingdom, arthropods are by far the most numerous phylum and are the cause of the most deadly infectious or parasitic diseases in the world (WHO, 1998). Arthropods belong to different orders but are for the most part hematophagous, characterized by the taking of blood meals through the bite of homeothermic animals including humans. Among these arthropods, mosquitoes are the most formidable, both because of their abundance (Rodhain and Perez, 1985), and because of the diseases they carry. Vector-borne diseases transmitted by mosquitoes have recently been on the rise (Morens et al., 2004) and now represent 28% of emerging diseases (Jones, et al., 2008), which constitute a heavy burden on public health and the global economy (Morens et al., 2004; Jones et al., 2008; Suaya et al., 2009). The incidence of these diseases has increased almost fourfold over the past 50 years and their occurrence has increased significantly since the 1980s (Jones et al., 2008). Some of these diseases primarily affect the poorest populations, who live in remote rural areas of tropical Africa. These diseases are thus sustained by poverty and affect almost exclusively poor populations in developing countries. The people who suffer from them, because they do not have significant political power, are not a public health priority. As a result, many of these diseases are neglected because there are few or no control interventions available for case management, leading the WHO to label them as Neglected Tropical Diseases (NTDs). The WHO has established a list of 17 priority neglected tropical diseases.
In recent years, these diseases have received much attention on the international political scene, thanks to the numerous advocacy efforts and, above all, the recognized links between the control and elimination of these diseases and the achievement of the Millennium Development Goals (MDGs), and the prospects for controlling these diseases are quite promising.
The approach to control of these diseases currently advocated by WHO and various stakeholders is an integrated, population-based approach to the control of several NTDs, as opposed to the traditional vertical, disease-based approach. It is therefore important to elaborate the spatial distribution of the vectors of these diseases
Description of the project
Title: Occurrences of neglected tropical disease vectors identified during medical consultations at Mènontin Hospital
Description of the study area: the Atlantic-Littoral-Mono-Couffo-Collines-Alibori and Ouémé departments of Benin
Dataset link: https://doi.org/10.15468/7kymun
Description of the methodology:
The dataset is based on the registration of consultations at the Menontin zone hospital. Information from the consultation is collected such as the disease from which the patient suffers, the date of consultation and the place of origin. From the disease, the incriminated vectors are searched in collaboration with the chief doctors and by referring to the google search engine. Based on the scientific names obtained from the Global Biodiversity Information (GBIF) website (www.gbif.org/tools/name-parser) and the resolver global names tool (resolver.globalnames.org), taxonomic information such as (Kingdom, Phylum, Class, Order, Family, Genus, SpecificEpithet) were generated. Based on the place of origin of the patients, the geographical coordinates (longitude, latitude) were obtained using tools such as geolocate (http://www.geo-locate.org/web/) and earthexplorer (https://earthexplorer.usgs.gov/). Then the data were entered in an Excel spreadsheet considering the name of the fields according to the Darwin Core format. Then these data were processed, cleaned and published on the Gbif website.
Geographic coverage :
Description: The dataset contains information on the presence of vectors of neglected tropical diseases in seven departments of Benin, namely: Atlantic, Coastal, Mono, Couffo, Collines, Alibori and Ouémé.
Coordinates: 1.01 west 3.694 east Latitude 11.979 north and 6.357 south Longitude
Taxonomic coverage: the dataset includes occurrences of vectors of neglected tropical diseases. A total of 8 species belonging to 8 families of 6 orders were recorded
Temporal scope
- October 1, 2017 - September 9, 2020
Licence d’utilisation: Licence creative commons Attribution
Study project: "Biodiversity Information for Development (BID)
Data use to inform decisions on biodiversity conservation and public health in Benin
This project is designed to provide data solutions to support expressed decisions making of three government institutions. Through workshops, the desired decisions the end-users are willing to make will be examined so as to clearly identify the appropriated needs of information and related key research questions to be answered. Data needs will then be adequately identified and, data mobilization in free access databases like GBIF, data gap analysis on available data, and complementary data mobilization in data holdings will be planned. Data mobilization, data and checklist publications on GBIF site will then be achieved. Under the supervision of trainers and project advisor, students in the master program, through their master research topics will achieve, in response to the key research questions, adequate data analysis and address the required needs of information to support decisions making of government institutions. Following the evaluation process by end-users, a plan will be set in place through partnership agreements between parties so as to enable the establishment of workflows and refinement of data mobilization and data solutions to fit more conveniently in decisions making during and beyond the project. Data solutions will be used in national biodiversity policy and international biodiversity platforms. Indicators towards the achievements of SDG and CBD targets as well as information on biodiversity assessments will be provided to end-users.
Study area
The data digitized and published in the framework of this project are gathered throughout the whole country with respect to the data needs to inform decisions in the three partner institutions
Description
The design is detailed according to the objectives of the project The initial planning phase will be achieved in the framework of workshops during which the consortium members and their collaborators, students, and supervisors of theses of the master program will be invited. The end-users from DGEFC, CENAGREF, and Hôpital Menontin will present their needs of information and the decisions they wish to support. The needs of information will be reformulated into key questions to be answered with respect to the decisions to be supported so as to identify the possible information resources to be taken into account. They can be databases like GBIF, Vertnet, species links etc. Any other relevant sources of information (data holders, data users, resource persons etc.) will also be considered. This will result in a plan of data mobilization, data publication, and data uses to support decisions. This plan will be consolidated through partnership agreements between parties. During data mobilization phase, taking into account the key questions to be answered, research topics will be identified and attributed to the students of the master program and other data users. Data will then be downloaded from GBIF, Vertenet, species links etc. and data gap analysis will be performed so as to find out the gaps of occurrences to be filled either from complementary field surveys, data holders, and literature reviews etc. Data collected to fill data gaps will be formatted, georeferenced, cleaned up, and published on GBIF site. The evaluation process will be carried out in two phases: i) during the information development phase, under the umbrella of their supervisors and the advisor of the program, students will process data to provide relevant answers to the key questions in order to guide the intended decision making of the partners; ii) in an evaluation phase, the results obtained (answers to the key questions) will be scrutinized with respect to their adequacy to support the intended decisions of end-users and, whenever necessary, data mobilization and data analysis refinements will be reconsidered to provide more relevant answers to the key questions to support decisions.