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Rocha TAH, Silva LL, Wen FH, Sachett J, Tupetz A, Staton CA, Monteiro WM, Vissoci JRN, Gerardo CJ. River dataset as a potential fluvial transportation network for healthcare access in the Amazon region. Sci Data 2023; 10:188. [PMID: 37024499 PMCID: PMC10078007 DOI: 10.1038/s41597-023-02085-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/24/2021] [Accepted: 03/20/2023] [Indexed: 04/08/2023] Open
Abstract
Remote areas, such as the Amazon Forest, face unique geographical challenges of transportation-based access to health services. As transportation to healthcare in most of the Amazon Forest is only possible by rivers routes, any travel time and travel distance estimation is limited by the lack of data sources containing rivers as potential transportation routes. Therefore, we developed an approach to convert the geographical representation of roads and rivers in the Amazon into a combined, interoperable, and reusable dataset. To build the dataset, we processed and combined data from three data sources: OpenStreetMap, HydroSHEDS, and GloRiC. The resulting dataset can consider distance metrics using the combination of streets and rivers as a transportation route network for the Amazon Forest. The created dataset followed the guidelines and attributes defined by OpenStreetMap to leverage its reusability and interoperability possibilities. This new data source can be used by policymakers, health authorities, and researchers to perform time-to-care analysis in the International Amazon region.
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Affiliation(s)
- Thiago Augusto Hernandes Rocha
- Department of Emergency Medicine, Duke University School of Medicine, Durham, NC, 27710, United States of America
- Duke Global Health Institute, Duke University, Durham, NC, 27710, United States of America
| | - Lincoln Luís Silva
- Department of Emergency Medicine, Duke University School of Medicine, Durham, NC, 27710, United States of America
- Post-Graduation Program in Biosciences and Physiopathology, State University of Maringá, Maringá, Paraná, 87020-900, Brazil
| | - Fan Hui Wen
- Butantan Institute, São Paulo, São Paulo, 05503-900, Brazil
| | | | - Anna Tupetz
- Department of Emergency Medicine, Duke University School of Medicine, Durham, NC, 27710, United States of America
| | - Catherine Ann Staton
- Department of Emergency Medicine, Duke University School of Medicine, Durham, NC, 27710, United States of America
- Duke Global Health Institute, Duke University, Durham, NC, 27710, United States of America
| | - Wuelton Marcelo Monteiro
- State University of Amazonas, Manaus, Amazonas, 69750-000, Brazil
- Tropical Medicine Foundation Dr. Heitor Vieira Dourado, Manaus, Amazonas, 69040-000, Brazil
| | - Joao Ricardo Nickenig Vissoci
- Department of Emergency Medicine, Duke University School of Medicine, Durham, NC, 27710, United States of America
- Duke Global Health Institute, Duke University, Durham, NC, 27710, United States of America
| | - Charles John Gerardo
- Department of Emergency Medicine, Duke University School of Medicine, Durham, NC, 27710, United States of America.
- Duke Global Health Institute, Duke University, Durham, NC, 27710, United States of America.
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Improving our estimates: assessing misclassification of abortion accessibility in the United States. Ann Epidemiol 2022; 76:98-107. [DOI: 10.1016/j.annepidem.2022.10.012] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/22/2022] [Revised: 09/30/2022] [Accepted: 10/19/2022] [Indexed: 11/11/2022]
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On the Representativeness of OpenStreetMap for the Evaluation of Country Tourism Competitiveness. ISPRS INTERNATIONAL JOURNAL OF GEO-INFORMATION 2021. [DOI: 10.3390/ijgi10050301] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
Since 2007, the World Economic Forum (WEF) has issued data on the factors and policies that contribute to the development of tourism and competitiveness across countries worldwide. While WEF compiles the yearly report out of data from governmental and private stakeholders, we seek to analyze the representativeness of the open and collaborative platform OpenStreetMap (OSM) to the international tourism scene. For this study, we selected eight parameters indicative of the tourism development of each country, such as the number of beds or cultural sites, and we extracted the OSM objects representative of these indicators. Then, we performed a statistical and regression analysis of the OSM data to compare and model the data emitted by WEF with data from OSM. Our aim is to analyze the tourist representativeness of the OSM data with respect to official reports to better understand when OSM data can be used to complement the official information and, in some cases, when official information is scarce or non-existent, to assess whether the OSM information can be a substitute. Results show that OSM data provide a fairly accurate picture of official tourism statistics for most variables. We also discuss the reasons why OSM data is not so representative for some variables in some specific countries. All in all, this work represents a step towards the exploitation of open and collaborative data for tourism.
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