Global mapping of infectious disease

Author:

Hay Simon I.12,Battle Katherine E.1,Pigott David M.1,Smith David L.23,Moyes Catherine L.1,Bhatt Samir1,Brownstein John S.4,Collier Nigel5,Myers Monica F.1,George Dylan B.2,Gething Peter W.1

Affiliation:

1. Spatial Ecology and Epidemiology Group, Department of Zoology, University of Oxford, Oxford, UK

2. Fogarty International Center, National Institutes of Health, Bethesda, MD, USA

3. Department of Epidemiology and Malaria Research Institute, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA

4. Department of Pediatrics, Harvard Medical School and Children's Hospital Informatics Program, Boston Children's Hospital, Boston, MA, USA

5. National Institute of Informatics, Research Organization of Information and Systems, Tokyo, Japan

Abstract

The primary aim of this review was to evaluate the state of knowledge of the geographical distribution of all infectious diseases of clinical significance to humans. A systematic review was conducted to enumerate cartographic progress, with respect to the data available for mapping and the methods currently applied. The results helped define the minimum information requirements for mapping infectious disease occurrence, and a quantitative framework for assessing the mapping opportunities for all infectious diseases. This revealed that of 355 infectious diseases identified, 174 (49%) have a strong rationale for mapping and of these only 7 (4%) had been comprehensively mapped. A variety of ambitions, such as the quantification of the global burden of infectious disease, international biosurveillance, assessing the likelihood of infectious disease outbreaks and exploring the propensity for infectious disease evolution and emergence, are limited by these omissions. An overview of the factors hindering progress in disease cartography is provided. It is argued that rapid improvement in the landscape of infectious diseases mapping can be made by embracing non-conventional data sources, automation of geo-positioning and mapping procedures enabled by machine learning and information technology, respectively, in addition to harnessing labour of the volunteer ‘cognitive surplus’ through crowdsourcing.

Publisher

The Royal Society

Subject

General Agricultural and Biological Sciences,General Biochemistry, Genetics and Molecular Biology

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