Data Challenges in Disease Response: The 2014 Ebola Outbreak

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1 Data Challenges in Disease Response: The 2014 Ebola Outbreak Authors: KUSH R. VARSHNEY, DENNIS WEI, KARTHIKEYAN NATESAN RAMAMURTHY AND ALEKSANDRA MOJSILOVIC, IBM Thomas J. WATSON RESEARCH CENTER Presentation by : Kalhan Dhar

2 Authors address: K. R. Varshney, D. Wei, K. N. Ramamurthy, and A. Mojsilovic, IBM T. J. Watson Research Center, 1101 Kitchawan Road, Yorktown Heights, NY Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies show this notice on the first page or initial screen of a display along with the full citation. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted.

3 Paper References 1. I. Belluz No One Knows Exactly How Bad West Africa s Ebola Epidemic Is. Retrieved May 11, 2015, from 2. R. Chunara, M. S. Smolinski, and J. S. Brownstein Why we need crowdsourced data in infectious disease surveillance. Current Infectious Disease Reports 15, 4, Y.-A. de Montjoye, Z. Smoreda, R. Trinquart, C. Ziemlicki, and V. D. Blondel D4D-Senegal: The second mobile phone data for development challenge. arxiv: M. Haklay and P. Weber OpenStreetMap: User-generated street maps. IEEE Pervasive Computing 7, 4, E. B. Hook and R. R. Regal Capture-recapture methods in epidemiology: Methods and limitations. Epidemiologic Reviews 17, 2, M. I. Meltzer, C. Y. Atkins, S. Santibanez, B. Knust, B. W. Petersen, E. D. Ervin, S. T. Nichol, I. K. Damon, and M. L. Washington Estimating the future number of cases in the Ebola epidemic Liberia and Sierra Leone, Morbidity and Mortality Weekly Report 63, Suppl. 3, L. Raschid Information integration and dissemination for disaster data management. In Proceedings of the 8th Annual International Conference on Digital Government Research: Bridging Disciplines and Domains K. R. Varshney, G. H. Chen, B. Abelson, K. Nowocin, V. Sakhrani, L. Xu, and B. L. Spatocco Targeting villages for rural development using satellite image analysis. Big Data 3, 1, A. Wesolowski, C. O. Buckee, L. Bengtsson, E. Wetter, X. Lu, and A. J. Tatem Commentary: Containing the Ebola outbreak the potential and challenge of mobile network data. PLOS Currents Outbreaks WHO Ebola Response Team Ebola virus disease in West Africa the first 9 months of the epidemic and forward projections. New England Journal of Medicine 371, 16,

figure out better results Illuminate causal factors of disease propagation Engage

4 Introduction Benefits of data in disease outbreaks Track status of a crisis on the ground Inform resource allocation Inform intervention decisions Feed simulations to figure out better results Illuminate causal factors of disease propagation Engage citizenry Problems with data in disease outbreaks Data collection challenges Quality challenges

5 Focus of the Paper The authors discuss a variety of data quality issues in disease response. The discussion is organized around three broad categories of data source: Disease incidence Interventions and general conditions Responses involving the mobility of individuals

Disease Incidence Challenges related to disease incidence Ensuring accuracy of data: Getting data with sufficient temporal and spatial granularity.

Dependent upon success failure of small number of workers Under-Reporting: Underreporting will seriously impact the measurement of the gravity of the ground situation and the estimating the

6 Disease Incidence Challenges related to disease incidence Ensuring accuracy of data: Getting data with sufficient temporal and spatial granularity. Case Scenario: Though we had various national level statistics, details at subnational level were less available. Dependent upon success failure of small number of workers Under-Reporting: Underreporting will seriously impact the measurement of the gravity of the ground situation and the estimating the amount of spread Case Scenario: Official counts were significantly lower than what WHO believed. In fact Meltzer estimated 2.5 times the cases as predicted by WHO Reasons: Resistance to interact health agents; patients hiding due to fear of authority; not enough disease surveillance and workers; poor information infrastructure

7 Proposed Responses Education Engagement of Citizenry Better Coordination among health ministries and aid organizations Stronger Information and Communication systems Deployment of mobile apps and SMS based data connection (statistics can be applied)

8 Intervention and General Condition Challenges These data are not centralized or there is no common repository. Other Issues: Redundancy Provenance Some data issues had terms that prohibited publishing of the data. Can be solved by talking to owners and proposing terms they may agree to. Working with people with different set of motivations, targeted volunteering

9 Intervention and General Conditions Responses Case Scenario: In Oct 2014 in New York Coty, Ebola Open Data Jam, volunteers group was led to tag metadata, possible analytics from Open data. It uncovered 50 heterogeneous data sets having the same quality issues mentioned above. These data sets were published on platform built on DKAN, a Drupal based open data platform and metadata structured using WWW Consortiums Data Catalog Vocabulary. Disease response can be aided by data sources related to intervention and general condition. News Reports Improvements in: Medical facility capacity, inventory Transportation maps, maps and locations enhanced using Satellite Image Analysis by crowd sourcing algorithms

10 Mobility of Individuals Mobile Penetration is very high in Africa Call Records: Source Number, Destination Number, Call Duration, Completion status Challenges Lack of a consolidated and properly cataloged data repository Legal issues

11 Using Mobility as a means of Response Contact tracing : Identification of people who have recently interacted with individuals infected by a disease to control outbreaks. This can be used to predict disease spread and plan responses. Case Scenario: African mobile providers are releasing data in such a way that individual privacy is preserved. Governments often don t permit lobbying but it may help in some cases.

12 Summary and looking ahead. Need for unified platforms. Integrated and centralized toolkits for: Collection Publishing Curation Federation Validation Management of data collection mechanisms including mobile apps, SMS, surveys, etc.

13 Presentation Image References

14 Thank you The man who will use his skill and constructive imagination to see how much he can give for a dollar, instead of how little he can give for a dollar, is bound to succeed Henry Ford Q & A

Ebola by the Numbers: Not a Small-scale Killer Anymore

Ebola by the Numbers: Not a Small-scale Killer Anymore Ebola in West Africa Previously confined to Central African countries Emerged in Guinea at end of 2013 Source: Feldmann & Geisbert, Lancet 2011 Two