THE DATA REVOLUTION HAS BEGUN On the front lines with geospatial data and tools

Transcription

1 THE DATA REVOLUTION HAS BEGUN On the front lines with geospatial data and tools Slidedoc of presentation for MEASURE Evaluation End of Project Meeting Washington DC May 22, 2014 John Spencer Geospatial Coordinator MEASURE Evaluation

2 Table of Contents This is a slidedoc of the presentation The Data Revolution Has Begun which was given at the May 22, 2014 MEASURE Evaluation Phase III End of Project Meeting in Washington DC. This slidedoc contains graphics and content from the presentation, but as opposed to a traditional presentation handout, a slidedoc presents the content in a more readable format. This presentation discusses the ideas behind the need for a data revolution and uses examples from MEASURE Evaluation GIS activities to make the case that the data revolution has already gotten underway. page page page What is a data revolution? Building capacity for use of GIS Mapping HIV hotspots in Iringa,Tanzania page Spatial analysis of intimate partner violence page The data revolution has begun 2

3 What is a data revolution?

4 What is a data revolution? We call for a data revolution for sustainable development... to improve the quality of statistics and information available to people and governments. The Report of the High-Level Panel of Eminent Persons on the Post-2015 Development Agenda Published by the United Nations in 2013, this report focused on what the post milenium development goal agenda should look like. In it the authors called for a data revolution. One that improved the quality of statistics and information where the data was broken down in many ways to ensure no one is left behind. This set off a very interesting discussion about data and its role in development. Many people began trying to figure out what a data revolution might look like. The following pages highlight some of the views from key thought leaders on what a data revolution means. The value of data, the importance of it s effective use were emphasized repeatedly. data gathered will need to be disaggregated by gender, geography, income, disability, and other categories, to make sure that no group is being left behind. 4

5 The panel s emphasis was welcome recognition that improving the quality, opening up access, and making better use of data and statistics are fundamental to achieving transformative development results. -- Tony Pipa Deputy Assistant Administrator Bureau for Policy, Planning and Learning USAID 5

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7 There are data sets and information resources across the government that could serve a greater good and be effective tools for change if they were made more accessible and usable We want to collect these data these potential change agents and present them in their most creative and effective forms. -- Dr. Rajiv Shah Administrator, USAID 7

8 What is a data revolution? The UN 2015 report said a data revolution should include improved statistics broken down in many ways such as by gender, geography, income, disability, and other categories, to make sure that no group is being left behind. Tony Pipa and Dr. Shah emphasized that accessible data presented and used effectively was fundamental to tranformative results. The Gates Foundation pointed out that a data revolution must be focused on relevant, measureable benefit. To paraphrase: Access to better data and effective use of data can lead to better results 8

9 The data revolution has already begun Access to data and effective use of data can lead to better results. These are watchwords with GIS and other spatial tools. Because GIS makes it possible to easily link data together using geography, data becomes more accessible. GIS can improve the use of data as well. It makes it possible to link multiple, independent datasets using a common geographic context. This type of linking allows data users to identify previously unknown links between data. Spatial analysis can identify patterns in the data and make it possible to better understand the story the data is telling. GIS can then be used to produce maps and additional data tools that convey that story to others. In short, GIS makes data more accessible, more usable and makes it possible to use the data to achieve better results. This presentation shows how MEASURE Evaluation is making GIS accessible to public health professionals throughout the world and also presents two examples of how the tool can be used to improve understanding of data and inform decision making leading to measurable benefits. 9

10 Building capacity for use of GIS

11 High demand for GIS skills To use spatial tools effectively health professionals must be qualified and trained in the use of data and data tools such as GIS. MEASURE Evaluation helps build capacity for global health professionals in the use of GIS to help meet that need. During Phase III there s been a growing demand for GIS skills from global health professionals. Since 2008, MEASURE Evaluation has provided direct person to person training or technical assistance to more than 500 people. This is important because it gives health professionals specific examples relevant to their work using an affordable, accessible GIS package. The data that follows is from MEASURE Evaluation GIS capacity building activities over the last 5 years, but the MEASURE Evaluation experience isn t unique and the trends play out across the global health and development field. Because the need for practical, applied training in the use of GIS was so great MEASURE Evaluation worked with staff from MEASURE DHS (now known as The DHS Program) to develop one of the first curriculum focused on Global Health that uses free GIS software. Photo: Participants doing hands-on exercises using the Global Health and GIS Curriculum jointly developed by MEASURE Evaluation and DHS Project International Workshop GIS Applications in Public Health, Delhi India 11

12 The demand is widespread throughout health professions 15% 19% Health professionals across a wide range of positions are wanting to develop and strengthen GIS skills. In MEASURE Evaluation capacity building activities for the period of 2008 to 2012 participants job categories break down fairly evenly across a variety of jobs program managers, M&E specialists, data staff and health officers. This means that more people in global health are able to make maps, link data and produce decision tools to support program decisions and M&E. 23% 18% 25% Program Specialist Data Manager M&E Specialist Other Health Officer 12

13 The interest is global, the impact is real The ways in which global health professionals use what they learned as a result of MEASURE Evaluation capacity building demonstrate how geospatial tools and data are leading to effective use of data with real, measureable results. Kenya: The workshop has helped me incorporate a Spatial Information Management System into the National M&E System for the National AIDS Control Council in Kenya. Zambia: Using what I ve learned about QGIS, I ve been able to combine population distribution, malaria morbidity and mortality, and analyze which interventions are viable. Niger: The training has allowed me to use the mapping data in the analysis of results of the Survey of Second Generation Surveillance on HIV/AIDS and to see the use of GIS software for analysis, interpretation, and presentation of data. Burma: I ve been able to integrate disease surveillance, public health intervention, and program valuation using GIS. We are developing a geo-database for Health Care Delivery Services. Map: MEASURE Evaluation Phase III GIS Capacity Building Efforts have benefitted public health professionals working in more than 45 countries. Quotes: Quotes from recipients of MEASURE Evaluation GIS capacity building during Phase III. 13

14 Mapping HIV hotspots in Iringa, Tanzania

15 Where are the HIV hotspots? Where are the prevention services? Photo: GPS data collection in Iringa, Tanzania Iringa is a region in central Tanzania. It suffers from the highest HIV prevalence rate of any region in the country. MEASURE Evaluation, worked with USAID Tanzania and the government of Tanzania to use GIS as tool to help align HIV prevention programs with areas of need. Geospatial tools helped identify the areas of greatest need and locations of prevention services. 15

16 Improving preventative HIV care with GIS There were two stages to the Iringa activity: 1. Map locations of areas at high risk of spreading HIV as well as the location of prevention services. 2. Train district health staff in the use of GIS. Using the PLACE protocol district health teams visited locations that were at high risk for increased HIV transmission and collected GPS coordinates. Locations where HIV preventative services were available were also visited and their coordinates collected. District health staff, using GIS produced maps from the data and convinced decision makers to add four new care and treatment centers and locate them where they were most needed. District health staff were trained in the use of GIS. The data was then mapped to look at patterns of HIV risk and the relationship to prevention services. Photo: District health staff review maps from the Iringa Mapping Activity 16

17 Spatial analysis of intimate partner violence

18 Does a context of violence increase risk of intimate partner violence? Intimate partner violence (IPV) has a destructive effect on its victims and on communities. While the risk factors associated with IPV are becoming better understood, there are opportunities to refine and improve that understanding. What is the relationship between endemic violence and intimate partner violence? MEASURE Evaluation is using innovative spatial analysis techniques to look at factors associated with IPV and relationship between IPV and civil violent conflict. 18

19 Linking DHS and violent conflict data Violent Conflict DHS The spatial analysis used two datasets. The 2010 DHS survey was used to provide data on IPV and other socio-demographic factors. Data on violent conflicts was obtained from the armed conflict and location of event database (ACLED). ACLED has the location of civil violent conflicts throughout the world. Conflicts are classified by type such as guerilla action or riot. GIS Layers These two datasets were combined in a GIS making it possible to analyze potential relationships between the two datasets. 19

20 Controlling for exposure to violent conflict Two models were developed to identify key risk factors for reported IPV, one accounting for exposure to nearby violent conflict, one that did not. D. R. C. D. R. C. Rwanda Rwanda Not controlling for violent conflict Controlling for violent conflict The first model looked at the explanatory power of traditional risk factors for IPV such as education or income. The red dots on the map above are locations of DHS clusters where the model did not effectively explain the risk of IPV, while gray dots indicate clusters where the model does a better job of explaining IPV risk. The second model added a variable for exposure to nearby violent conflict. In the area near the DRC border, controlling for violence improves the model. For this research we wanted to explore the effect of exposure to nearby violent conflict. In the areas around the border with Democratic Republic of Congo there are many incidents of violent conflict. These incidents are represented by a V symbol on the map. The border area with DRC has seen intense conflict for many years. In the map with results from the second model, the analysis indicates that for clusters in this area, exposure to violent conflict is related to increased risk of reported IPV. 20

21 Spatial analysis of intimate partner violence Study findings: An increase of ten days with nearby violent conflicts in a year increases the odds of an individual reporting IPV by 11% For the areas near the DRC border, the findings indicate that exposure to violent conflict does increase risk of reported IPV. This means that in the area with the highest amount of violent conflict, the border area with DRC, reported IPV is affected by violent conflict. This study is still in process and represents an incremental understanding of the risk factors of IPV. Future analysis will add other risk factors for IPV to improve the model. This type of analysis can help guide policy makers and relief organizations to consider IPV risk as they plan and implement postconflict recovery efforts. Spatial analysis such as this is possible because there are data sources available that have spatial referencing. There are also tools that are more accessible that support this type of spatial analysis. These changes mean that public health staff with moderate GIS skills can replicate this analysis. That wasn t the case five years ago. 21

22 The data revolution has begun

23 The data revolution has begun There are many other examples of MEASURE Evaluation GIS activities beyond what is presented in this presentation: GIS has been used to help strengthen the upcoming national HIV Program evaluation in Rwanda Spatial analysis was used to explore issues around early marriage in Bangladesh. MEASURE Evaluation cosponsored mapping summits both at a national level in Nigeria and pan-african. The E2G tool makes it easy to map Excel data in Google Earth Photo: Details on these activities can be found on the MEASURE Evaluation web site. To conclude, the data revolution called for in the UN report and envisioned by important thought leaders are marked by improved data that is used effectively to lead to better results. During Phase III at MEASURE Evaluation we ve seen evidence, some of which has been presented here, that the data revolution is already underway and GIS is one of the tools making it happen. For more information about these activities visit the MEASURE Evaluation web site. 23

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