Online misinformation and vaccine hesitancy

R Garett, SD Young - Translational behavioral medicine, 2021 - academic.oup.com
Although rates of vaccination have increased worldwide, the rise in nonmedical exemptions
for vaccination may have caused a resurgence of childhood vaccine-preventable diseases …

It's just not that simple: an empirical study of the accuracy-explainability trade-off in machine learning for public policy

A Bell, I Solano-Kamaiko, O Nov… - Proceedings of the 2022 …, 2022 - dl.acm.org
To achieve high accuracy in machine learning (ML) systems, practitioners often use complex
“black-box” models that are not easily understood by humans. The opacity of such models …

The possibility of fairness: Revisiting the impossibility theorem in practice

A Bell, L Bynum, N Drushchak… - Proceedings of the …, 2023 - dl.acm.org
The “impossibility theorem”—which is considered foundational in algorithmic fairness
literature—asserts that there must be trade-offs between common notions of fairness and …

Predicting vaccine hesitancy from area‐level indicators: A machine learning approach

V Carrieri, R Lagravinese, G Resce - Health Economics, 2021 - Wiley Online Library
Vaccine hesitancy (VH) might represent a serious threat to the next COVID‐19 mass
immunization campaign. We use machine learning algorithms to predict communities at a …

Think about the stakeholders first! Toward an algorithmic transparency playbook for regulatory compliance

A Bell, O Nov, J Stoyanovich - Data & Policy, 2023 - cambridge.org
Increasingly, laws are being proposed and passed by governments around the world to
regulate artificial intelligence (AI) systems implemented into the public and private sectors …

Associating measles vaccine uptake classification and its underlying factors using an ensemble of machine learning models

MK Hasan, MT Jawad, A Dutta, MA Awal… - IEEE …, 2021 - ieeexplore.ieee.org
Measles is one of the significant public health issues responsible for the high mortality rate
around the globe, especially for developing countries. Using nationally representative …

Performance of predictive algorithms in estimating the risk of being a zero-dose child in India, Mali and Nigeria

A Biswas, J Tucker, S Bauhoff - BMJ Global Health, 2023 - gh.bmj.com
Introduction Many children in low-income and middle-income countries fail to receive any
routine vaccinations. There is little evidence on how to effectively and efficiently identify and …

The Algorithmic Transparency Playbook: A Stakeholder-first Approach to Creating Transparency for Your Organization's Algorithms

A Bell, O Nov, J Stoyanovich - Extended Abstracts of the 2023 CHI …, 2023 - dl.acm.org
Welcome to 2033, the year when AI, while not yet sentient, can finally be considered
responsible. Only systems that work well, improve efficiency, are fair, law abiding, and …

An analysis of COVID-19 vaccine hesitancy in the US

H Bui, S Ekşioğlu, R Proano, S Nurre Pinkley - IISE Transactions, 2024 - Taylor & Francis
Reluctance or refusal to get vaccinated, commonly known as Vaccine Hesitancy (VH), poses
a significant challenge to COVID-19 vaccination campaigns. Understanding the factors …

A Graph Based Deep Learning Framework for Predicting Spatio-Temporal Vaccine Hesitancy

SA Moon, R Datta, T Ferdousi, H Baek, A Adiga… - medRxiv, 2023 - medrxiv.org
Predicting vaccine hesitancy at a fine spatial level assists local policymakers in taking timely
action. Vaccine hesitancy is a heterogeneous phenomenon that has a spatial and temporal …