Implementation of Quantum Computing for Enhancing Data Analytics in Nigerian Public Health Sector at Nigeria Centre for Disease Control (NCDC), Abuja
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Background of the Study
The Nigerian public health sector increasingly depends on advanced data analytics to monitor, predict, and respond to disease outbreaks. The Nigeria Centre for Disease Control (NCDC) in Abuja is tasked with managing vast amounts of health-related data from various sources, including epidemiological reports, laboratory data, and field surveillance. However, classical computing methods often struggle with the complexity and volume of this data, leading to delays and inaccuracies in outbreak prediction and response. Quantum computing offers a transformative solution by leveraging quantum phenomena such as superposition and entanglement to process large datasets at unprecedented speeds (Adebayo, 2023). With its ability to run complex algorithms in parallel, quantum computing can significantly enhance the accuracy of data analytics, facilitating early detection of disease trends and enabling more informed decision-making. Integrating quantum computing into the NCDC’s data analytics framework could revolutionize public health surveillance by uncovering hidden patterns and correlations that are not detectable through conventional methods (Emeka, 2024). Moreover, quantum-enhanced analytics can improve resource allocation during health crises and optimize the deployment of preventive measures. This integration is particularly crucial in a country with diverse health challenges and a growing population, where timely and precise data analysis is essential for effective public health interventions. Nonetheless, the practical implementation of quantum computing in public health faces challenges such as high operational costs, limited technical expertise, and the need to harmonize quantum systems with existing data infrastructure (Nwankwo, 2025). This study will investigate the feasibility, potential benefits, and technical challenges of deploying quantum computing to enhance data analytics at the NCDC, aiming to develop a strategic framework for its effective integration into public health operations.
Statement of the Problem
Despite significant advancements in data analytics, the Nigerian public health sector continues to encounter challenges in processing and interpreting vast and complex health data using classical computing methods. The NCDC’s reliance on traditional analytical tools has resulted in delays in disease outbreak detection and resource allocation, ultimately compromising the effectiveness of public health responses (Okafor, 2023). The limitations of classical systems hinder the early identification of emerging health threats, leading to suboptimal decision-making and increased public health risks. While quantum computing offers a promising alternative with its superior processing capabilities, its integration into existing public health data systems remains largely unexplored. Technical challenges—including algorithm optimization, data integration, and system scalability—as well as high implementation costs and a shortage of skilled professionals, impede the practical adoption of quantum solutions in the public health sector (Chukwu, 2024). These barriers contribute to persistent inefficiencies in surveillance and outbreak prediction, undermining the NCDC’s ability to respond effectively to health crises. Consequently, there is an urgent need to explore and implement quantum computing technologies to bridge this gap. This study aims to assess the feasibility and effectiveness of quantum computing in enhancing data analytics at the NCDC, with the goal of developing a strategic framework that improves the accuracy, speed, and scalability of public health data processing, thereby enabling more effective disease surveillance and response (Akinlade, 2024).
Objectives of the Study
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To implement quantum computing techniques to enhance data analytics in the Nigerian public health sector.
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To evaluate the performance and scalability of quantum algorithms in processing public health data.
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To develop a strategic framework for integrating quantum computing into NCDC's data analytics systems.
Research Questions
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How can quantum computing improve the accuracy and speed of data analytics in the public health sector?
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What are the key challenges in integrating quantum computing with existing data systems at the NCDC?
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How effective is the proposed quantum computing framework in enhancing disease surveillance and outbreak prediction?
Significance of the Study
This study is significant as it investigates the transformative potential of quantum computing in enhancing data analytics within the Nigerian public health sector. By implementing quantum techniques at the NCDC, the research aims to improve the accuracy and speed of disease surveillance and outbreak prediction, ultimately contributing to more effective public health responses. The findings will provide valuable insights for policymakers and healthcare professionals, guiding the integration of advanced computational technologies into public health infrastructure and paving the way for innovative, data-driven approaches to health crisis management.
Scope and Limitations of the Study
This study is limited to implementing quantum computing for enhancing data analytics at the Nigeria Centre for Disease Control in Abuja, focusing on the stated objectives, existing data systems, and selected Local Government Areas only.
Definitions of Terms
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Quantum Computing: A computational paradigm that utilizes quantum mechanical phenomena to perform operations on data at unprecedented speeds.
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Data Analytics: The process of examining large datasets to uncover hidden patterns, correlations, and insights.
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Public Health Sector: The system responsible for protecting and improving community health through organized efforts and informed choices.
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