Timeline of Malaria Atlas Project

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This is a timeline of Malaria Atlas Project, a project aimed at developing the science of malaria cartography.[1][2]

Big picture

Time period Development summary
2006 The Malaria Atlas Project (MAP) is launched.
2009 MAP starts creating repositories on GitHub.
2012 MAP publishes the first global maps for Plasmodium vivax endemicity.
2013 MAP launches its Repository of Open Access Data (ROAD-MAP) resource.
2017 MAP releases new interactive malaria tools, making easier to download a wealth of malariometric data and covariates from its website.
2018 MAP launches global map of travel time to cities to assess inequalities in accessibility. The World Health Organization's 2018 World Malaria Report is published using maps produced by MAP.

Full timeline

Year Month and date Event type Details
2005 Founding MAP is founded by Bob Snow and Simon I. Hay with the purpose of filling the niche for the malaria control community at a global scale.[3]MAP initially focuses on Plasmodium falciparum.[4]
2006 May 1 Release The Malaria Atlas Project (MAP) is launched with the goal of collecting and verifying data for a new, detailed model of Plasmodium falciparum and Plasmodium vivax malarial infection incidence throughout the globe.[5] The MAP Web site (map.ox.ac.uk) launches to further the aims and ambitions of MAP.[6]
2007 May Progress As of date, MAP has 3670 parasite rate surveys from 79 countries.[5]
2007 Research Research by MAP reports about 451 million clinical cases of Plasmodium falciparum malaria worldwide.[7]
2008 Staff Peter Gething, Professor of Epidemiology at the The Big Data Institute, University of Oxford, joins MAP. As of 2019, Gething is Head of the Malaria Atlas Project.[8]
2008 Research MAP researchers construct a map that stratifies the world into three levels of malaria risk: no risk, unstable transmission risk (occasional focal outbreaks), and stable transmission risk (endemic areas where the disease is always present).[9]
2009 April 2 Code repository MAP creates repository on GitHub containing a simpler version of MAP's Plasmodium falciparum cartography code. The purpose to make code available to people willing to check or extend MAP work, and to synchronize it across multiple computers.[10][11]
2009 April 7 Code repository MAP creates repositories on GitHub containing MAP's duffy negativity cartography code[12][13] as well as combined Duffy negativity and Plasmodium Vivax endemicity mapping.[14][15] On the same date, MAP's inherited blood disorder cartography code repository is created.[16][17]
2009 June 2 Code repository MAP creates repository on GitHub containing MAP's Anopheles vector cartography code.[18][19]
2009 September 1 Code repository MAP creates repository on GitHub containing low-level geostatistical utilities that run on a GPU.[20][21]
2009 Research MAP assembles all available data from Plasmodium falciparum parasite rate (PfPR) surveys, and uses model-based geostatistics (MBG) to generate a global map of estimated PfPR for the year 2007.[22][23]
2009 Research MAP estimates 12 million cases of Plasmodium falciparum alone in the year.[24]
2009 December 2 Code repository MAP creates repository on GitHub containing a bayesian statistical model relating clinical malaria incidence to parasite rate.[25][26]
2010 March 12 Code repository MAP creates repository on GitHub containing its population attribution uncertainty code.[27][28]
2010 June 3 Code repository MAPcreates repository on GitHub containing MAP's ITN cartography code for Kenya.[29][30]
2011 November Collaboration The Asia Pacific Malaria Elimination Network (APMEN) funds its first GIS training in Shanghai, China, in collaboration with the National Institute of Parasitic Diseases, Chinese Center for Disease Control and Prevention (NIPD, China CDC), the University of Queensland, and the Malaria Atlas Project/Oxford University.[31]
2012 January Research Researchers from MAP, funded mainly by the Wellcome Trust, present the results of a two-year effort to assemble all available data worldwide on the risk of Plasmodium falciparum malaria, the most deadly form of the disease. Using computer modelling and data on climate and human populations, it is revealed the complex landscape of malaria across the globe.[32]
2012 October Research Research by MAP maps the geographical contemporary distribution of sickle haemoglobin, a genetic disorder causing sickle cell anemia. It also estimates the number of newborns affected by this condition.[33] A molecular mechanism was revealed whereby sickle cell hemoglobin confers a survival advantage against malaria.[34]
2012 Release MAP publishes the first global maps for Plasmodium vivax endemicity.[35]
2013 Release MAPlaunches its Repository of Open Access Data (ROAD-MAP) resource, with support from a Wellcome Biomedical Resources grant, and then funding from the Bill & Melinda Gates Foundation.[36]
2015 Research MAP research shows that 80.7% of all people worldwide live within an hour of a city.[37]
2015 September Research A study by MAP finds that “by far the most important intervention” in reducing malaria cases and deaths has been the use of insecticide-treated bednets (ITNs), around a billion of which have been distributed in Africa since 2000.[38][39][40]
2015 Research Study by MAP published in Nature finds that Plasmodium falciparum infection prevalence in endemic Africa halved and the incidence of clinical disease fell by 40% between 2000 and 2015.[41]
2015 August 12 Code rerpository MAP creates repository named modis-acquisition on GitHub. It contains scripts used to go from the NASA MODIS DAAC website to WGS84 global geotiffs of LST, EVI, TCB, and TCW data.[42][43]
2015 August 14 Code repository MAP creates DHS-DataExtraction repository on GitHub. It contains code for parsing hierarchical data in CSPro format.[44]
2016 April 28 Code repository MAP creates Temperature-Suitability-Model on GitHub. The repository contains a parallelised re-implementation of the temperature suitability model.[45]
2016 July 20 Code repository MAP creates DHS-Indicators repository on GitHub. It contains SQL code for generating certain indicators by the United States Department of Homeland Security. The code is used in some collaborative work between MAP and DHS.[46][47]
2016 November 2 Research Study by MAP quantifies the attributable effect of malaria disease control efforts in Africa, and finds that Plasmodium falciparum infection prevalence in endemic Africa halved and the incidence of clinical disease fell by 40% between 2000 and 2015.[48]
2017 March 13 Code repository MAP releases MAP-raster-utilities on GitHub. The repository contains several ipython notebooks developed to process raster datasets in line with MAP requirements.[49]
2017 December 5 Research MAP collates georeferenced time-series data from peer-reviewed articles and routine case reporting, and constructs an inferential model to relate transmission data to a suite of temporally dynamic environmental covariates (temperature, vegetation, humidity etc.) from a remote sensing platform, with the aim at being able to accurately predict seasonal malaria transmission patterns (onset, duration, magnitude) in locations where malaria survey data are sparse.[50]
2017 December 11 Release MAP releases new interactive malaria tools, making easier to download a wealth of malariometric data and covariates from its website.[51]
2018 January 10 Release MAP releases a global map of accessibility to cities for the year 2015, showing the estimated travel time to the nearest city globally. The map is created in collaboration with Google, the Joint Research Centre of the European Union, and the University of Twente. The map provides a useful dataset, which includes those exploring beneficial aspects related to high accessibility such as increased wealth, educational attainment, and utilization of healthcare, as well as the negative aspects of high accessibility such as easing resource extraction and thus amplifying environmental degradation.[52][53]
2018 January 28 Collaboration MAP researchers collaborate with Google to produce a global accessibility map.[54]
2018 January 31 Application project A Repository of Open Access Data – Malaria Atlas Project team builds a set of applications and tools to support the global malaria community. A key aspect of this work is the development of a relational database for epidemiological data.[55]
2018 February 28 Research MAP starts developing disaggregation models that use surveillance data alongside pixel-level environmental and human covariates in order to produce high-resolution burden estimates.[56]
2018 March 1 Data gathering project The ROAD-MAP team (Repository of Open Access Data – Malaria Atlas Project) gathers routine case data from ministry of health reports and other sources and makes a coherent global dataset of reported incidence and deaths at a sub-national level.[57]
2018 March 8 Research MAP starts working to integrate serological data within its risk mapping framework using novel semi-mechanistic models based.[58]
2018 March 15 Research MAP starts developing a statistical framework for simultaneous estimation of malaria risk maps and health facility catchments based on a modified ‘gravity model’.[59]
2018 April 12 Aplication project MAP releases the malaria Atlas R package, which enables users to download, visualize and manipulate global parasite rate survey data and modelled raster outputs within R, a freely available and widely used statistical software environment.[60]
2018 April 15 Code repository malariaAtlas is released on GitHub as an R interface to open-access malaria data. It is hosted by MAP.[61][62]
2018 July 19 Application After data provided by MAP, Glasgow, Montana is revealed to be the most isolated town in the United States. MAP researchers are able to calculate the travel time to get to every single square kilometer on earth, based on transportation options and terrain. Their database can predict ground transit times between any two places on the planet.[63][64][65]
2018 November 19 Application The World Health Organisation's 2018 World Malaria Report is published using maps produced by MAP.[66]
2018 September 28 Data gathering project MAP gathers evidence that shows malaria parasite Plasmodium vivax to be prevalent across Africa. clinical case reports, cross-sectional prevalence surveys, entomological and serological studies as well as documented infections in naïve travellers.[67]
2018 September 27 Data gathering project MAP gathers data to describe the spatial epidemiology of glucose-6-phosphate dehydrogenase deficiency.[68]
2018 October 11 Release MAP releases a package to provide users of the R programming language with a convenient application programming interface to interact with MAP's publicly-available data holdings.[69]
2018 November 21 Collaboration The Wellcome Trust’s Data Re-Use Prize: Malaria, is launched in collaboration with MAP and with support from Sage Bionetworks, with a cash prize of £15,000. It is aimed at data-scientists and modellers to bring their perspective to MAP data and collectively provide insights.[70]
2019 March Research Study led by the London School of Hygiene & Tropical Medicine, Imperial College London and MAP, reveals that improved housing has doubled on the African continent between 2000 and 2015.[71]
2019 May Collaboration Facebook partners with several organizations, including MAP, to launch maps covering demographics, human movement, and network coverage, with the purpose to help health organizations respond to emergencies. The project uses real-time maps powered by satellite imagery, computer vision, census data, and Facebook’s proprietary data. [72][73][74]

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How the timeline was built

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Funding information for this timeline is available.

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What the timeline is still missing

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See also

External links

References

  1. ↑ Hay, Simon I; Snow, Robert W. "The Malaria Atlas Project: Developing Global Maps of Malaria Risk". PMC 1762059Freely accessible. PMID 17147467. doi:10.1371/journal.pmed.0030473. 
  2. ↑ "Malaria Atlas Project". bdi.ox.ac.uk. Retrieved 4 March 2019. 
  3. ↑ "The Malaria Atlas Project: Cartographic approaches to estimating populations at risk, burden and elimination feasibility". healthdata.org. Retrieved 5 March 2019. 
  4. ↑ Gething, Peter W.; Elyazar, Iqbal R. F.; Moyes, Catherine L.; Smith, David L.; Battle, Katherine E.; Guerra, Carlos A.; Patil, Anand P.; Tatem, Andrew J.; Howes, Rosalind E.; Myers, Monica F.; George, Dylan B.; Horby, Peter; Wertheim, Heiman F. L.; Price, Ric N.; Müeller, Ivo; Baird, J. Kevin; Hay, Simon I. "A Long Neglected World Malaria Map: Plasmodium vivax Endemicity in 2010". PMC 3435256Freely accessible. PMID 22970336. doi:10.1371/journal.pntd.0001814. 
  5. ↑ 5.0 5.1 "Parasites and pestilence". web.stanford.edu. Retrieved 8 March 2019. 
  6. ↑ Hay, Simon I; Snow, Robert W. "The Malaria Atlas Project: Developing Global Maps of Malaria Risk". doi:10.1371/journal.pmed.0030473. 
  7. ↑ "Malaria: double the suffering". ox.ac.uk. Retrieved 18 March 2019. 
  8. ↑ "PROFESSOR PETER GETHING". map.ox.ac.uk. Retrieved 5 March 2019. 
  9. ↑ Hay, Simon I; Guerra, Carlos A; Gething, Peter W; Patil, Anand P; Tatem, Andrew J; Noor, Abdisalan M; Kabaria, Caroline W; Manh, Bui H; Elyazar, Iqbal R. F; Brooker, Simon; Smith, David L; Moyeed, Rana A; Snow, Robert W. "A World Malaria Map: Plasmodium falciparum Endemicity in 2007". doi:10.1371/journal.pmed.1000048. 
  10. ↑ "covariate-testbed". github.com. Retrieved 31 May 2019. 
  11. ↑ "covariate-testbed". github.com. Retrieved 31 May 2019. 
  12. ↑ "MAP's duffy negativity cartography code". github.com. Retrieved 31 May 2019. 
  13. ↑ "duffy". github.com. Retrieved 31 May 2019. 
  14. ↑ "Combined Duffy negativity and P. Vivax endemicity mapping". github.com. Retrieved 31 May 2019. 
  15. ↑ "dufvax". github.com. Retrieved 31 May 2019. 
  16. ↑ "MAP's inherited blood disorder cartography code". github.com. Retrieved 31 May 2019. 
  17. ↑ "ibd-world". github.com. Retrieved 31 May 2019. 
  18. ↑ "anopheles". github.com. Retrieved 31 May 2019. 
  19. ↑ "anopheles". github.com. Retrieved 31 May 2019. 
  20. ↑ "Low-level geostatistical utilities that run on a GPU". github.com. Retrieved 31 May 2019. 
  21. ↑ "geo-gpu". github.com. Retrieved 31 May 2019. 
  22. ↑ Burgert, Clara R; Bradley, Sarah EK; Arnold, Fred; Eckert, Erin. "Improving estimates of insecticide-treated mosquito net coverage from household surveys: using geographic coordinates to account for endemicity". Malaria Journal. 
  23. ↑ Gething, Peter W; Patil, Anand P; Smith, David L; Guerra, Carlos A; Elyazar, Iqbal RF; Johnston, Geoffrey L; Tatem, Andrew J; Hay, Simon I. "A new world malaria map: Plasmodium falciparum endemicity in 2010". PMC 3274487Freely accessible. PMID 22185615. doi:10.1186/1475-2875-10-378. 
  24. ↑ Oxford Textbook of Global Public Health (Roger Detels, Martin Gulliford, Quarraisha Abdool Karim, Chorh Chuan Tan ed.). 
  25. ↑ "pr-incidence". github.com. Retrieved 31 May 2019. 
  26. ↑ "pr-incidence". github.com. Retrieved 31 May 2019. 
  27. ↑ "The Malaria Atlas Project's population attribution uncertainty code". github.com. Retrieved 31 May 2019. 
  28. ↑ "pop". github.com. Retrieved 31 May 2019. 
  29. ↑ "MAP's ITN cartography code for Kenya". github.com. Retrieved 31 May 2019. 
  30. ↑ "itn-kenya". github.com. Retrieved 31 May 2019. 
  31. ↑ "GEOGRAPHIC INFORMATION SYSTEMS". apmen.org. Retrieved 5 March 2019. 
  32. ↑ "New malaria maps to guide battle against the disease". eurekalert.org. Retrieved 1 June 2019. 
  33. ↑ "Sickle cell anemia: Maps and newborn estimates released". sciencedaily.com. Retrieved 5 March 2019. 
  34. ↑ "Mystery solved: How sickle hemoglobin protects against malaria". eurekalert.org. INSTITUTO GULBENKIAN DE CIENCIA. Retrieved 8 May 2019. 
  35. ↑ Gething, P.W.; Elyazar, I.R.F.; Moyes, C.M; Smith, D.L.; Battle, K.E.; Guerra, C.A.; Patil, A.P; Tatem, A.J.; Howes, R.E.; Myers, M.F.; George, D.B.; Horby, P.; Wertheim, H.F.; Price, R., Müller.I; Baird, J.K.; HAY, S.I (6 September 2012). "A long neglected world malaria map: Plasmodium vivax endemicity". PLoS Neglected Tropical Diseases. 6 (9): e1814. PMC 3435256Freely accessible. PMID 22970336. doi:10.1371/journal.pntd.0001814. 
  36. ↑ "New Wellcome Data Re-use Prizes to help unlock the value of research". wellcome.ac.uk. Retrieved 4 March 2019. 
  37. ↑ "New Map Shows How Long It Takes People Around the World to Travel to the Nearest City". mymodernmet.com. Retrieved 4 March 2019. 
  38. ↑ "Millions of children's lives saved as malaria deaths plunge: U.N.". reuters.com. Retrieved 4 March 2019. 
  39. ↑ "La malaria, por el buen camino". elpais.com. Retrieved 5 March 2019. 
  40. ↑ "Malaria deaths cut by 60% since 2000 but UN says $6bn a year boost needed". theguardian.com. Retrieved 5 March 2019. 
  41. ↑ "THE IMPACT OF MALARIA CONTROL ON PLASMODIUM FALCIPARUM IN AFRICA, 2000-2015". map.ox.ac.uk. Retrieved 18 March 2019. 
  42. ↑ "modis-acquisition". github.com. Retrieved 31 May 2019. 
  43. ↑ "modis-acquisition". github.com. Retrieved 31 May 2019. 
  44. ↑ "DHS-DataExtraction". github.com. Retrieved 31 May 2019. 
  45. ↑ "Temperature-Suitability-Model". github.com. Retrieved 31 May 2019. 
  46. ↑ "DHS-Indicators". github.com. Retrieved 31 May 2019. 
  47. ↑ "DHS-Indicators". github.com. Retrieved 31 May 2019. 
  48. ↑ "MALARIA IN AFRICA HALVED IN 15 YEARS". map.ox.ac.uk. Retrieved 5 March 2019. 
  49. ↑ "all code in notebooks - non-tiled". github.com. Retrieved 31 May 2019. 
  50. ↑ "PREDICTING THE EFFECT OF SEASONALITY ON MALARIA TRANSMISSION". map.ox.ac.uk. Retrieved 4 March 2019. 
  51. ↑ "NEW INTERACTIVE MALARIA DATA TOOLS RELEASED". map.ox.ac.uk. Retrieved 5 March 2019. 
  52. ↑ "ACCESSIBILITY TO CITIES". map.ox.ac.uk. Retrieved 5 March 2019. 
  53. ↑ "ACCESSIBILITY TO CITIES". map.ox.ac.uk. Retrieved 4 March 2019. 
  54. ↑ "New Map Shows How Connected Cities Are To Their Surroundings". forbes.com. Retrieved 4 March 2019. 
  55. ↑ "A RELATIONAL DATABASE FOR MALARIOMETRIC DATA". map.ox.ac.uk. Retrieved 4 March 2019. 
  56. ↑ "PIXEL-LEVEL MODELLING IN LOW BURDEN AREAS". map.ox.ac.uk. Retrieved 4 March 2019. 
  57. ↑ "ROUTINE MALARIA CASES". map.ox.ac.uk. Retrieved 4 March 2019. 
  58. ↑ "SEMI-MECHANISTIC MODELLING FOR SEROLOGICAL SURVEY DATA". map.ox.ac.uk. Retrieved 4 March 2019. 
  59. ↑ "CATCHMENT MODELLING FOR AREA-AVERAGED MALARIA DATA". map.ox.ac.uk. Retrieved 4 March 2019. 
  60. ↑ "MAP DATA R PACKAGE". map.ox.ac.uk. Retrieved 4 March 2019. 
  61. ↑ "malariaAtlas". github.com. Retrieved 16 May 2019. 
  62. ↑ "malariaAtlas". github.com. Retrieved 16 May 2019. 
  63. ↑ "Glasgow, Montana Is America's Most Isolated Town". cntraveler.com. Retrieved 4 March 2019. 
  64. ↑ "Researchers Pinpoint the Geographic Location of "The Middle of Nowhere"". mentalfloss.com. Retrieved 4 March 2019. 
  65. ↑ "This is where the middle of nowhere is, according to the best data possible". denverpost.com. Retrieved 4 March 2019. 
  66. ↑ "2018 WORLD MALARIA REPORT IS PUBLISHED USING MAPS PRODUCED BY THE MALARIA ATLAS PROJECT". map.ox.ac.uk. Retrieved 5 March 2019. 
  67. ↑ "COLLATING EVIDENCE OF PLASMODIUM VIVAX IN AFRICA". map.ox.ac.uk. Retrieved 4 March 2019. 
  68. ↑ "map.ox.ac.uk". G6PD DEFICIENCY DATA GATHERING PROJECT. Retrieved 4 March 2019. 
  69. ↑ "MALARIAATLAS R PACKAGE FOR ACCESSING DATA". map.ox.ac.uk. Retrieved 5 March 2019. 
  70. ↑ "WELLCOME TRUST DATA RE-USE PRIZE: MALARIA". map.ox.ac.uk. Retrieved 5 March 2019. 
  71. ↑ "Improved housing doubles in Sub-Saharan Africa". africanews.com. Retrieved 1 June 2019. 
  72. ↑ "Facebook launches Maps to help organisations respond to health emergencies". theeagleonline.com.ng. Retrieved 1 June 2019. 
  73. ↑ "Facebook is mapping demographics, human movement, and network coverage to combat diseases". venturebeat.com. Retrieved 1 June 2019. 
  74. ↑ "Facebook launches three maps for health organizations dealing with health emergencies". thenews.com. Retrieved 1 June 2019. 
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