{
  "abstract": "Introduction Research on modelling geographical accessibility to healthcare services has witnessed rapid methodological advancement and refinement. One of the contributing factors is the increasing availability of big data detailing the link between the population in need of care and the health facility such as infrastructure, travel modes and speeds, traffic congestion and the quality of road network. This has allowed more granular computation of geographic access metrics, particularly in low-and-middle income countries where data are scarce. However, there are no reviews providing a comprehensive overview of the availability and use of big data for assessing geographical accessibility to healthcare. This protocol aims to describe a methodological approach that will be used to review the existing literature on the application of big data (past or potential) in evaluating geographical accessibility to healthcare.Methods and analysis To characterise the big data that can be used to model geographical accessibility to healthcare, a scoping review will be undertaken and reported according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses extensions for Scoping Reviews guidelines. We will search seven scientific databases (PubMed, Scopus, Web of Science, EBSCOhost-CINAHL, Cochrane, Embase and MEDLINE via Ovid), grey literature, reference lists of identified publications and conference proceedings. Search engines will be used to identify relevant big data services not yet used in published academic literature. All literature published in English or French will be included, regardless of publication type, geographical location or year of publication provided it describes or mentions big data that may be useful for evaluating geographical accessibility to healthcare. Study selection and data extraction will be performed independently by two researchers with a third resolving any discrepancies. Analysis will be conducted to summarise big data providers, their characteristics and their usefulness in terms of types of spatial accessibility metrics that can be derived.Ethics and dissemination Formal ethical approval is not required, as primary data will not be collected in this review. Findings will be disseminated through peer-reviewed publication in a journal, conference presentation and condensed summaries for stakeholders through professional networks and social media summaries.Registration Open Science Framework (OSF): https://doi.org/10.17605/OSF.IO/S496F.",
  "authors": [
    {
      "affiliations": [
        "Department of Public Health, Institute of Tropical Medicine, Antwerp, Belgium"
      ],
      "name": "Ann Njogu"
    },
    {
      "affiliations": [
        "Department of Public Health, Institute of Tropical Medicine, Antwerp, Belgium"
      ],
      "name": "Lorenzo Libertini"
    },
    {
      "affiliations": [
        "Centre de recherche en reproduction humaine et en démographie (Cerrhud), Cotonou, Benin"
      ],
      "name": "Elias Martinien Avahoundjè"
    },
    {
      "affiliations": [
        "Department of Public Health, Institute of Tropical Medicine, Antwerp, Belgium",
        "Department of Public Health, Faculty of Health Sciences and Techniques, Gamal Abdel Nasser University of Conakry, Conakry, Guinea",
        "African Center of Excellence for the Prevention and Control of Communicable Diseases (CEA-PCMT), Gamal Abdel Nasser University of Conakry, Conakry, Guinea",
        "Centre National de Formation et de Recherche en Sante Rurale de Maferinyah, Forécariah, Guinea"
      ],
      "name": "Fassou Mathias Grovogui"
    },
    {
      "affiliations": [
        "GeoHealth Group, Institute of Global Health, Faculty of Medicine, University of Geneva, Geneva, Switzerland",
        "Institute for Environmental Sciences, University of Geneva, Geneva, Switzerland"
      ],
      "name": "Oumar Aly Ba"
    },
    {
      "affiliations": [
        "GeoHealth Group, Institute of Global Health, Faculty of Medicine, University of Geneva, Geneva, Switzerland",
        "Institute for Environmental Sciences, University of Geneva, Geneva, Switzerland"
      ],
      "name": "Nicolas Ray"
    },
    {
      "affiliations": [
        "Department of Public Health, Institute of Tropical Medicine, Antwerp, Belgium",
        "Faculty of Epidemiology and Population Health, London School of Hygiene and Tropical Medicine, London, UK"
      ],
      "name": "Lenka Beňová"
    },
    {
      "affiliations": [
        "Department of Public Health, Institute of Tropical Medicine, Antwerp, Belgium",
        "Population and Health Impact Surveillance Group, KEMRI-Wellcome Trust Research Programme Nairobi, Nairobi, Kenya"
      ],
      "name": "Peter M Macharia"
    }
  ],
  "title": "Big data in modelling geographical accessibility to healthcare: a scoping review protocol",
  "uid": "fa9fba75-8c51-516d-8d56-d599f9bc47e7"
}