The integration of Artificial Intelligence (AI) in public health surveillance is transforming the identification and management of outbreaks. Traditional systems typically suffer from delay, isolated data, and reactive designs, which hamper their potential for timely detection of emerging threats. Recent developments in machine learning, natural language processing, and real-time data fusion are shifting the paradigm to proactive and programmatic surveillance. This article analyzes the technical basis, current application, and strategic implications of AI-based surveillance for outbreak identification. A modular approach is proposed to guide implementation across contexts. Drawing on international case studies, from COVID-19 early detection onwards, the article lays out the promise and risks of embedding AI in modern public health systems.
public health surveillance, artificial intelligence, outbreak detection, digital epidemiology, early warning systems
Gabriel Acheampong, Adwoa Agyeiwaah Ampomah-Britwum
The idea of using after-school mathematics and robotics competitions to boost participation in STEM has become a popular policy and educational measure among policymakers and educators. This approach is based on the idea that early, low-stakes experience with competitive problem solving instills the identity and self-efficacy needed to sustain a path in STEM disciplines. This review compiles existing peer-reviewed research on the link between competitive STEM enrichment and persistence among women, racial/ethnic minority students, and low-income students in the United States. Instead of systematically exploring one type of intervention, we combined results from three related literatures (mathematics contests, educational robotics leagues, and science fairs) to empirically describe what each of these literatures can teach about persistence among students. The more evidence is found and the stronger the causal connection, the more effective the comprehensive STEM summer enrichment programs are in leading to measurable increases in college STEM persistence. In contrast, the results of mathematics competitions are descriptive and frequently show a significant and pervasive demographic gap. Evidence on the impact of robotics leagues is mixed in terms of the nature of the data found and the statistical power behind the findings. Evidence shows a consistent positive short-term impact on student attitudes, while evidence of long-term impact on identity and demographic outcomes is less consistent and less statistically powerful. There is an ongoing debate on the role of competitive framing in supporting or impeding persistence among students who may be at risk for math anxiety and stereotype threat. The field has invested heavily in scaling competitive STEM programs without first determining if competition is the "active ingredient. There is a great deal of investment in scaling up competitive STEM programs without establishing either if there is or isn't a competition effect as the "active ingredient", which has serious implications for the allocation of limited enrichment resources.
STEM persistence, math competitions, educational robotics, underrepresented minorities, after-school enrichment…
