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Infectious Disease Atlas

It is perhaps surprising that we have an extremely poor knowledge of the global distribution of the vast majority of infectious diseases. A review conducted by our group of all infectious diseases of clinical significance has revealed it would be of public health benefit to map about half of these conditions; yet, astonishingly, only 2% (seven of 355) have been mapped comprehensively. This geographical ignorance frustrates a variety of clinical, epidemiological, and public health aspirations.

In short, we want to fundamentally improve the landscape of infectious disease mapping by automating many of the labour intensive aspects of the cartographic process. The platform we have designed and hope to implement to achieve this is called ABRAID (Atlas of Baseline Risk Assessment for Infectious Disease).

Current projects

ABRAID
Atlas of Baseline Risk Assessment for Infectious Disease

January 2014 - December 2016

The Atlas of Baseline Risk Assessment for Infectious Disease (ABRAID) is the acronym for an automated mapping platform. The essence of the project is to create a system that automatically generates spatially comprehensive, iteratively improving, evidence-based maps of disease risk at the global scale. They will be continuously updated in response to new occurrence data collection. A grant to build a prototype for this work has been awarded and the concept is outlined in more detail in Hay et al. (2013).

The Atlas of Baseline Risk Assessment for Infectious Disease (ABRAID) is the acronym for an automated mapping platform. The essence of the project is to create a system that automatically generates spatially comprehensive, iteratively improving, evidence-based maps of disease risk at the global scale. They will be continuously updated in response to new occurrence data collection. A grant to build a prototype for this work has been awarded and the concept is outlined in more detail in Hay et al. (2013).

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The Atlas of Baseline Risk Assessment for Infectious Disease (ABRAID) is the acronym for an automated mapping platform. The essence of the project is to create a system that automatically generates spatially comprehensive, iteratively improving,...

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Predicting the geographic spread of Ebola virus disease in West Africa

November 2014 - November 2015

The geographic spread of Ebola virus disease (EVD) during the ongoing outbreak in West Africa has been driven by human movement within and between countries. Using data on human mobility in these countries to make quantitative predictions of disease spread will enable more rational deployment of resources as efforts are scaled to contain the epidemic.

High-resolution maps of EVD importation risk in West Africa will be developed and disseminated to WHO and authorized partners. These maps along with relevant summary information (such as the health centres most likely to see new cases) will be continuously updated as data become available and automatically disseminated via an online geographic information system alongside other spatial information to guide control of the ongoing outbreak. These tools will also be useful to maintain vigilance as the epidemic comes under control.

This project is funded by Enhancing Learning and Research for Humanitarian Assistance (ELRHA) as part of the Research for Health in Humanitarian Crisis (R2HC) programme.

 

Nick Golding and Moritz Kraemer are working on this project.

 

 -           The Research for Health in Humanitarian Crises (R2HC) programme aims to improve health outcomes by strengthening the evidence base for public health interventions in humanitarian crises. Visit www.elrha.org/work/r2hc for more information.

-          The £8 million R2HC programme is funded equally by the Wellcome Trust and DFID, with Enhancing Learning and Research for Humanitarian Assistance (ELRHA) overseeing the programme’s execution and management.

 

 -          In response to the Ebola outbreak in West Africa, the R2HC launched an emergency Ebola Health Research Call in August 2014, aiming to fund research which will help to strengthen interventions to tackle this and future outbreaks.

 

The geographic spread of Ebola virus disease (EVD) during the ongoing outbreak in West Africa has been driven by human movement within and between countries. Using data on human mobility in these countries to make quantitative predictions of disease spread will enable more rational deployment of resources as efforts are scaled to contain the epidemic.

High-resolution maps of EVD importation risk in West Africa will be developed and disseminated to WHO and authorized partners. These maps along with relevant summary information (such as the health centres most likely to see new cases) will be continuously updated as data become available and automatically disseminated via an online geographic information system alongside other spatial information to guide control of the ongoing outbreak. These tools will also be useful to maintain vigilance as the epidemic comes under control.

This project is funded by Enhancing Learning and Research for Humanitarian Assistance (ELRHA) as part of the Research for Health in Humanitarian Crisis (R2HC) programme.

 

Nick Golding and Moritz Kraemer are working on this project.

 

 -           The Research for Health in Humanitarian Crises (R2HC) programme aims to improve health outcomes by strengthening the evidence base for public health interventions in humanitarian crises. Visit www.elrha.org/work/r2hc for more information.

-          The £8 million R2HC programme is funded equally by the Wellcome Trust and DFID, with Enhancing Learning and Research for Humanitarian Assistance (ELRHA) overseeing the programme’s execution and management.

 

 -          In response to the Ebola outbreak in West Africa, the R2HC launched an emergency Ebola Health Research Call in August 2014, aiming to fund research which will help to strengthen interventions to tackle this and future outbreaks.

 

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The geographic spread of Ebola virus disease (EVD) during the ongoing outbreak in West Africa has been driven by human movement within and between countries. Using data on human mobility in these countries to make quantitative predictions of disease...

Read more

Wellcome Trust Intermediate Fellowship
Risk map of meliodiosis

September 2013 - October 2015

Melioidosis is a threat to human health throughout South and East Asia, Northern Australia, the Indian subcontinent and areas of Africa and South America. The overall case fatality rate of melioidosis in northeast Thailand is 40%. The geographic distribution of this infection is predicated on the presence of the causative organism, Burkholderia pseudomallei, in the environment. Nonetheless, there is a striking lack of accurate information on the worldwide clinical burden of melioidosis, particularly in tropical developing countries. Direk Limmathurotsakul will use mathematical models to predict areas at risk of acquiring melioidosis worldwide, including areas where melioidosis might be endemic but under diagnosed or undiagnosed.

Melioidosis is a threat to human health throughout South and East Asia, Northern Australia, the Indian subcontinent and areas of Africa and South America. The overall case fatality rate of melioidosis in northeast Thailand is 40%. The geographic distribution of this infection is predicated on the presence of the causative organism, Burkholderia pseudomallei, in the environment. Nonetheless, there is a striking lack of accurate information on the worldwide clinical burden of melioidosis, particularly in tropical developing countries. Direk Limmathurotsakul will use mathematical models to predict areas at risk of acquiring melioidosis worldwide, including areas where melioidosis might be endemic but under diagnosed or undiagnosed.

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Melioidosis is a threat to human health throughout South and East Asia, Northern Australia, the Indian subcontinent and areas of Africa and South America. The overall case fatality rate of melioidosis in northeast Thailand is 40%. The geographic...

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Plasmodium knowlesi malaria risk

August 2014 - July 2015

The risk of an individual being infected by the Plasmodium knowlesi parasite is largely unknown but the impact of this infection can be severe. This type of malaria is currently classified as a zoonotic disease that is transmitted from animals (monkeys) to humans. This project uses data on the 1) distribution of the monkey species that host the parasite, 2) the mosquitoes that transmit the parasite, and 3) environmental and socioeconomic factors, to answer questions about the spatial variation in infection risk. This project will also start to consider the impact of deforestation on disease risk, and whether human to human transmission is happening in the absence of monkey hosts. Catherine Moyes and Nick Golding work on this project.

The risk of an individual being infected by the Plasmodium knowlesi parasite is largely unknown but the impact of this infection can be severe. This type of malaria is currently classified as a zoonotic disease that is transmitted from animals (monkeys) to humans. This project uses data on the 1) distribution of the monkey species that host the parasite, 2) the mosquitoes that transmit the parasite, and 3) environmental and socioeconomic factors, to answer questions about the spatial variation in infection risk. This project will also start to consider the impact of deforestation on disease risk, and whether human to human transmission is happening in the absence of monkey hosts. Catherine Moyes and Nick Golding work on this project.

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The risk of an individual being infected by the Plasmodium knowlesi parasite is largely unknown but the impact of this infection can be severe. This type of malaria is currently classified as a zoonotic disease that is transmitted from animals...

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Sir Richard Southwood Graduate Scholarship from the Department of Zoology
Mapping the global diversity of infectious diseases and the potential for disease emergence

October 2012 - July 2015

David Pigott's work is aimed at identifying ways of improving the current means by which we map infectious diseases and using these outputs to assess the determinants of global disease diversity. Previous studies have worked at a very coarse spatial resolution, which current techniques can dramatically improve upon. David will also use similar methods to identify potential regions of disease emergence across the globe and see if knowledge of the current state of disease diversity can help inform our predicitons of novel pathogen emergence.

David Pigott's work is aimed at identifying ways of improving the current means by which we map infectious diseases and using these outputs to assess the determinants of global disease diversity. Previous studies have worked at a very coarse spatial resolution, which current techniques can dramatically improve upon. David will also use similar methods to identify potential regions of disease emergence across the globe and see if knowledge of the current state of disease diversity can help inform our predicitons of novel pathogen emergence.

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David Pigott's work is aimed at identifying ways of improving the current means by which we map infectious diseases and using these outputs to assess the determinants of global disease diversity. Previous studies have worked at a very coarse spatial...

Read more