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Recommendations Summary

Smarter Crowdsourcing for Zika

Assess communications platform penetration

Conduct an assessment of social media penetration to understand who can be reached by digital listening activities and how

Timeframe
Resources: Low investment ($10k or less)
monetization_on

Resource Offset: Already low to no cost. Can leverage existing research and expertise at universities, UN, World Bank, IDB, and other institutions

Contacts

Josh Tucker, New York University, Lee Rainie, Pew Research, We Are Social UK, We Are Social UK

Focus Area ASSESSING UNDERSTANDING

Impacted Areas BEHAVIOR CHANGE
SURVEILLANCE AND DATA SHARING

Establish committee for digital listening prioritization

Convene an interagency committee to assess and prioritize demand for digital listening insights across government

Timeframe
Resources: Low investment ($10k or less)
monetization_on

Resource Offset: Already low to no cost. Reduce time investment by getting expert advice ahead of time

Contacts

Beth Simone Noveck, GovLab

Focus Area ASSESSING UNDERSTANDING

Impacted Areas SURVEILLANCE AND DATA SHARING

Hire chief analytics officer

Appoint a Chief Analytics Officer to drive implementation of data-driven policies and projects such as digital listening and predictive analytics platforms

Timeframe
Resources: Moderate Investment ($100k-$500k)
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Resource Offset: The salary for this role could be offset by assigning her data-driven efficiency projects that save money

Contacts

Jeff Chen, Chief Data Scientist, Department of Commerce

Focus Area ASSESSING UNDERSTANDING

Impacted Areas SURVEILLANCE AND DATA SHARING
PREDICTIVE ANALYTICS

Forge digital listening partnerships

Partner with research organizations, technology platform partners, and commercial analytics providers to develop the supply of desired digital listening insights

Timeframe
Resources: Low investment ($10k or less)
monetization_on

Resource Offset: This can be low to no cost. Can save money by using existing research funds to support academics conducting digital listening

Contacts

Eugene Yi, MiT Media Lab, Molly Jackman, Public Policy Research Manager, Facebook, David Broniatowski, Assistant Professor, George Washington University

Focus Area ASSESSING UNDERSTANDING

Impacted Areas BEHAVIOR CHANGE
SURVEILLANCE AND DATA SHARING
PREDICTIVE ANALYTICS

Launch prize-backed challenges for community engagement

Create prize-backed challenges to promote engagement and innovation in Zika control at both the community and individual levels

Timeframe
Resources: Moderate Investment ($100k-$500k)
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Resource Offset: The cost of a prize varies. Save money by using micro-prizes such as donated mobile phone minutes

Contacts

Jaykumar Menon, McGill University, Patricio Fuentes and Reko Niimi, UNICEF Brazil Country Office

Focus Area BEHAVIOR CHANGE

Impacted Areas TRASH ACCUMULATION
PREDICTIVE ANALYTICS

Create research clearinghouse for behavior change

Compile peer-reviewed best practices in Zika / MBD public communications and present them in a way that is accessible for policymakers seeking actionable ideas

Timeframe
Resources: Moderate Investment ($100k-$500k)
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Resource Offset: This can be low to not cost. Save money by convening a wide array of stakeholders in universities and other institutions to crowdsource this project

Contacts

Karen Lyons, Pew Trusts

Focus Area BEHAVIOR CHANGE

Design Serious Games

Explore the use of “serious games” to raise awareness and change behavior by organizing hackathons and/or partnering with game designers to deploy effective platforms

Timeframe
Resources: Low investment ($10k or less)
monetization_on

Resource Offset: Games can be expensive to design and build. The memo recommends strategies for adapting existing games and/or seeking philanthropic support for production

Contacts

Jude Ower, CEO, Playmob, Julián Ugarte, Luis E. Loria, Marina Spindler, and Matías Rojas, Socialab, Sarah Cornish and Emily Treat, Games for Change

Focus Area BEHAVIOR CHANGE

Impacted Areas ASSESSING UNDERSTANDING
TRASH ACCUMULATION
SURVEILLANCE AND DATA SHARING
LONG-TERM CARE
PREDICTIVE ANALYTICS

Crowdsource waste removal

Involve communities in locating and removing litter

Timeframe
Resources: Some Investment ($10k-$100k)
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Resource Offset: This is low to no cost with only a small outlay for coordination and significant potential for savings in sanitation costs

Contacts

Jeff Kirschner, Litterati, Daniel Lombrana, Crowdcrafting

Focus Area TRASH ACCUMULATION

Impacted Areas BEHAVIOR CHANGE

Conduct drone-based garbage surveillance

Use drones to identify and map areas with accumulated trash

Timeframe
Resources: Some Investment ($10k-$100k)
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Resource Offset: This requires an investment in hardware. But money can be saved by sharing the use of surveillance drones designed for other purposes

Contacts

Joe Eyerman, RTI international

Focus Area TRASH ACCUMULATION

Establish public-private partnerships with manufacturers

Commit to private-public partnerships (PPP’s) with manufacturers to reduce trash accumulation

Timeframe
Resources: Some Investment ($10k-$100k)
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Resource Offset: The costs of container remediation are borne by the private sector

Contacts

Dr. Graham Alabaster, World Health Organization

Focus Area TRASH ACCUMULATION

Impacted Areas BEHAVIOR CHANGE

Adopt trash coll. adaptive vehicles

Collect trash in hard-to-reach areas using adaptive vehicles

Timeframe
Resources: Moderate Investment ($100k-$500k)
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Resource Offset: Cost of removing trash using alternative vehicles could be offset through use of those tax revenues used to pay for trash collection; this collection could also be done by the communities themselves, with communities earning revenues by selling recyclables to recycling companies

Contacts

Dr. Graham Alabaster, World Health Organization

Focus Area TRASH ACCUMULATION

Mobile tech–assisted surveillance

Improve the speed and reliability of surveillance data by integrating flexible mobile technologies like SMS and smartphone app reporting into surveillance activities

Timeframe
Resources: Moderate Investment ($100k-$500k)
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Resource Offset: mHealth technologies, including participatory digital surveillance and mobile-assisted case reporting, have the potential to expand surveillance at low cost compared to traditional methods. Investments in mobile devices and human resources can be offset by broad integration with other government activities like disaster response

Contacts

Gordon Cressman, RTI International, John Brownstein, Healthmap, Harvard Medical School, Brian Lee, U.S. Centers for Disease Control Health Information Innovation Consortium

Focus Area SURVEILLANCE AND DATA SHARING

Impacted Areas ASSESSING UNDERSTANDING
LONG-TERM CARE

Form disease surveillance data collaborative

Collaborate with companies and universities to identify new sources of disease surveillance data

Timeframe
Resources: Some Investment ($10k-$100k)
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Resource Offset: Data collaboratives are, by definition, corporate data philanthropy

Contacts

Richard Benjamins, Director of External Positioning & Big Data for Social Good, LUCA: Data-Driven Decisions (Telefonica), Stefaan Verhulst, GovLab

Focus Area SURVEILLANCE AND DATA SHARING

Impacted Areas ASSESSING UNDERSTANDING
PREDICTIVE ANALYTICS

Develop data-sharing playbook

Promote openness and participation in surveillance data collection, storage, sharing, and use by developing a data governance playbook for epidemic response and building broad commitment to use it

Timeframe
Resources: Moderate Investment ($100k-$500k)
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Resource Offset: More open and participatory surveillance data can generate cost savings through faster and more accurate epidemic detection and modeling. In addition, insights generated from data sharing can lead to more efficient use of public health resources

Contacts

Michael Johansson, U.S Centers for Disease Control

Focus Area SURVEILLANCE AND DATA SHARING

Impacted Areas ASSESSING UNDERSTANDING
PREDICTIVE ANALYTICS

Establish online support communities

Use online support communities akin to Patients Like Me to provide patient-to-patient support

Timeframe
Resources: Moderate Investment ($100k-$500k)
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Resource Offset: Research suggests that peer to peer support reduces hospitalizations and ER visits

Contacts

Anita McGahan, University of Toronto

Focus Area LONG-TERM CARE

Impacted Areas ASSESSING UNDERSTANDING
SURVEILLANCE AND DATA SHARING
PREDICTIVE ANALYTICS

Use SMS-based long-term care

Develop 2-way SMS-based support systems like Text4Baby to provide long-term medical care and support cost-effectively

Timeframe
Resources: Moderate Investment ($100k-$500k)
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Resource Offset: Text messages can be donated or purchased in bulk; open source platform like RapidPro can safe software costs; long term savings derive from reduced hospitalizations

Contacts

Alejandra Ruiz del Rio Prieto and Eduardo Clark, Prospera Digital (Presidencia de Mexico)

Focus Area LONG-TERM CARE

Impacted Areas ASSESSING UNDERSTANDING
BEHAVIOR CHANGE
SURVEILLANCE AND DATA SHARING
PREDICTIVE ANALYTICS

Build predictive analytics data platform

Improve Zika response by building a predictive analytics platform

Timeframe
Resources: Moderate Investment ($100k-$500k)
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Resource Offset: Analytics platforms are designed to reduce medium to long term costs, as the data they generate can help optimize resource deployment (e.g., preemptively sending health workers to where an outbreak is likely to occur can avoid the costs associated with an outbreak)

Contacts

Lakshminarayanan Subramanian, Professor, Courant Institute, NYU

Focus Area PREDICTIVE ANALYTICS

Impacted Areas ASSESSING UNDERSTANDING
BEHAVIOR CHANGE
SURVEILLANCE AND DATA SHARING

Launch prized-backed data science challenges

Use prize-backed challenges to rapidly develop predictive models and leverage outside expertise

Timeframe
Resources: Some Investment ($10k-$100k)
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Resource Offset: Prizes can be donated, and the challenge should be formulated to produce results that decrease costs. Challenges can also work with small prizes (or no prizes), provided the work is compelling enough and there is sufficient non-financial recognition of participants’ contributions

Contacts

Michael Johansson, Biologist, CDC

Focus Area PREDICTIVE ANALYTICS

Impacted Areas BEHAVIOR CHANGE

Train public health officials in data science

Increase data analytics literacy among public health officials by training them in data science (through partnerships with research institutions, universities, and other training providers)

Timeframe
Resources: Moderate Investment ($100k-$500k)
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Resource Offset: More data science training can enable these officials to analyze their own agencies’ work and identify cost savings

Contacts

Jesse Bell, North Carolina Institute for Climate Studies, Gianluca Fontana, Centre for Health Policy, Institute of Global Health Innovation, Imperial College, Daniel Ray, Chief Data Scientist, UK National Health Service, Michael Johansson, Biologist, CDC

Focus Area PREDICTIVE ANALYTICS

Impacted Areas ASSESSING UNDERSTANDING
BEHAVIOR CHANGE
SURVEILLANCE AND DATA SHARING
LONG-TERM CARE

Launch regional open data portal

Collaborate on creation of a Zika-related data portal that compiles national and other open datasets

Timeframe
Resources: Some Investment ($10k-$100k)
monetization_on monetization_on

Resource Offset: Money can be saved by using existing open source platforms and prioritizing datasets designed to generate insights that reduce costs

Contacts

Anita McGahan, University of Toronto