Posts by TReNDS Staff
Bangladeshi slums reduce maternal and infant mortality with the help of innovative health data

International nonprofit BRAC developed a data-driven approach to account and care for mothers and young children in Bangladeshi slums through healthcare initiative Manoshi. Manoshi built the capacity of local health workers in Bangladesh to derive actionable data from social mapping, local censuses, and real-time data-sharing via mobile technology, contributing to more timely and effective maternal health interventions in urban slums.

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Data sharing via SMS strengthens Uganda’s health system

The Ugandan government, with the support of UNICEF, began leapfrogging its outmoded health system in 2011 by introducing an SMS-based health reporting program called mTRAC. This program has supported significant improvements in the country’s health system, including halving of response time to disease outbreaks and reducing medication stockouts, the latter of which resulted in fewer malaria-related deaths.

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Data modeling helps reduce risk of violent crime in Atlantic City

High rates of violent crime dealt a blow to Atlantic City’s citizens and businesses in the late 2000s and early 2010s. Hamstrung by a reduced force, the Atlantic City Police Department turned to new solutions to optimize resources for predicting and preventing crime. This included risk terrain modeling (RTM), an analytical technique combining crime data and environmental risk factors to identify high-risk areas.

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Achieving coherence between data policies for reporting against the Sendai Framework and the Sustainable Development Goals

The number and scope of organizations and disciplines involved in disasters is large, and the different ways in which they approach loss measurement can prove challenging to manage. However, in order for countries to report their progress on these issues against the Sendai Framework and the SDGs, robust data and information systems will be crucial.

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Open Algorithms: Participatory Design for Data Projects

The Open Algorithms project is a socio-technological innovation to leverage private sector data for public good purposes by “sending the code to the data” in a privacy-preserving, participatory, commercially sensible, scalable, and sustainable manner. This brief highlights replicable lessons from the experiences of OPAL pilot projects in Senegal and Colombia in terms of participatory design of data projects.

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Calculating the Percent of Households Earning a Living Wage to Monitor Progress for Achieving SDG 8

With the support of the USA Sustainable Cities Initiative and Baltimore Neighborhood Indicators Alliance — Jacob France Institute, Baltimore developed a comprehensive set of localized indicators for achieving the global Sustainable Development Goals in Baltimore. Among the indicators is a “living wage” measure, which was developed by MIT. Learn more about the process of calculating this measure in this brief.

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Getting the Most Out of SDG Data Investments: A Living Manual for Increasing Value by Focusing on Decision Needs and Portfolio Function

This guide provides an initial platform to meet the demand for useful and user-friendly criteria prioritizing investments of financial and human resources in data systems. It focuses on two crucial aspects of the designing for action question: how best to tailor data systems to decision-maker needs, and how best to combine data technologies to create the most value.

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Building a Local SDG Data Monitoring System for Baltimore: Insights from the US National Reporting Platform and New York City

The National Reporting Platform for the SDGs, which is an open-source website with code available on GitHub for developers to potentially use for local reporting, is a welcomed advance for local jurisdictions to interactively track progress on the Global Goals. Read this brief for recommendations on subnational reporting and engagement with open data portals.

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