Information collection (or data collection) is vital during an epidemic, especially for purposes such as contact tracing and quarantine monitoring. However, it also poses challenges such as keeping up with the spread of the infectious disease, and the need to protect personally identifiable information. We explore some of the methods of information collection deployed in Sri Lanka and Thailand during the COVID-19 pandemic, and offer policy recommendations for future pandemics.
Rohan Samarajiva and Ramathi Bandaranayake presented preliminary findings from our work on risk communication during COVID-19.
Key considerations and recommendations for public health officials in developing wearable contact tracing solutions during COVID-19
This policy brief details guidance on making decisions in a pandemic.
Wijeratne, Y., de Silva, N. (2020). Sinhala Language Corpora and Stopwords from a Decade of Sri Lankan Facebook. LIRNEasia.
A research brief which explores the key data sources, algorithmic techniques and roadblocks in applying remote sensing techniques for development.
A white paper exploring how bias in algorithms and data affect development problems, especially when they interact with socio-legal systems
This tour d’horizon examines the possible of uses of data to help stop or slow the spread of COVID-19 directly. It gives weight to what can be done in the short term.
A research paper exploring an alternative approach to address the concern of privacy in sharing big data datasets by generating privacy-preserving artificial call detail records (CDRs) in accordance with the desired macro features of the dataset.
A whitepaper outlining the development of an alternative socioeconomic index for Sri Lanka, using principal component analysis (PCA) and publicly available census data
An extended research abstract which identifies several criteria that can be used to identify mobile network call detail records (CDRs) affected by load sharing and establishes why that is a prevalent issue, especially in urban areas.
A research brief exploring the possibility of using remote sensing and neural networks to estimate the paddy crop extent in Sri Lanka
LIRNEasia's comments on the Framework for a Proposed Data Protection Legislation for Sri Lanka of June 2019
This document is intended to understand the extant policy context in relation to healthcare data protection, providing international comparisons, and raise important questions for Sri Lanka to consider in relation to data protection, albeit within a narrow sector specific scope.
A whitepaper distilling LIRNEasia's current thoughts on the possibilities and issues with the computation extraction of syntactic and semantic language from digital text.
Presented by Rohan Samarajiva at Data Governance event at Royal School of Public Administration, Phnom Penh, Cambodia, March 4, 2019.