Global mapping of infectious disease
Open Access
- 19 March 2013
- journal article
- review article
- Published by The Royal Society in Philosophical Transactions B
- Vol. 368 (1614), 20120250
- https://doi.org/10.1098/rstb.2012.0250
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.Keywords
This publication has 87 references indexed in Scilit:
- Emerging fungal threats to animal, plant and ecosystem healthNature, 2012
- Bayesian geostatistics in health cartography: the perspective of malariaTrends in Parasitology, 2011
- The Applications of Model-Based Geostatistics in Helminth Epidemiology and ControlAdvances in Parasitology, 2011
- Ranking of elimination feasibility between malaria-endemic countriesThe Lancet, 2010
- A quantitative analysis of transmission efficiency versus intensity for malariaNature Communications, 2010
- BioCaster: detecting public health rumors with a Web-based text mining systemBioinformatics, 2008
- Global trends in emerging infectious diseasesNature, 2008
- Bayesian geostatistical prediction of the intensity of infection with Schistosoma mansoni in East AfricaParasitology, 2006
- Determining Global Population Distribution: Methods, Applications and DataAdvances In Parasitology, Vol 64, 2006
- Global Environmental Data for Mapping Infectious Disease DistributionAdvances In Parasitology, Vol 64, 2006