Transforming Healthcare in Africa: The Role of Artificial Intelligence in Combatting Infectious Diseases, Neglected Tropical Diseases, and Antimicrobial Resistance

  1. ANGYIBA ANDIGEMA
  2. NGNOTOUOM NGNOKAM Tania Cyrielle
  3. NDJIE Daniel Laetitia
  4. EWANE Ekwelle

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Abstract

This review article focuses on the role of Artificial Intelligence (AI) in transforming healthcare in Africa, specifically in combatting infectious diseases, neglected tropical diseases (NTDs), and antimicrobial resistance. We provide a comprehensive overview of the significance of AI in the healthcare industry, highlighting its urgency and importance in addressing these specific health challenges in Africa. We begin by discussing the role of AI in infectious disease surveillance and outbreak detection. We explore how AI technology can be employed for real-time tracking and prediction of outbreaks, providing examples of successful AI applications in infectious disease surveillance within the African context.Next, we examine the potential of AI-enabled diagnosis and treatment for faster and more accurate diagnoses of infectious diseases and NTDs. We highlight specific examples of AI applications in diagnosing and treating these diseases in Africa, showcasing the potential of AI to improve clinical outcomes and save lives.Furthermore, we focus on how AI-driven drug discovery and development can expedite the search for new treatments for infectious diseases and combat antimicrobial resistance. We present examples of AI applications in drug discovery within the African context, illustrating the potential for AI to revolutionize the development of effective therapeutics.In addition, we delve into how AI-powered public health interventions can enhance the design and implementation of targeted interventions. We explore how AI can optimize resource allocation and facilitate data-driven decision-making processes, providing examples of AI applications in public health in Africa.Finally, we address the challenges and limitations of implementing AI in combatting infectious diseases, NTDs, and antimicrobial resistance in Africa. We discuss potential barriers and ethical concerns surrounding AI applications in healthcare, aiming to encourage informed and responsible utilization of AI technologies.Overall, this review emphasizes the importance and potential of AI in combatting infectious diseases, NTDs, and antimicrobial resistance in Africa. It positions AI as a catalyst for revolutionizing healthcare in the region, leading to more effective disease surveillance, diagnosis, treatment, drug discovery, and public health interventions.

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  1. PREreview

    This Zenodo record is a permanently preserved version of a PREreview. You can view the complete PREreview at https://prereview.org/reviews/14672939.

    Review by Mehdi Zoghaib of: "Transforming Healthcare in Africa: The Role of Artificial Intelligence in Combatting Infectious Diseases, Neglected Tropical Diseases, and Antimicrobial Resistance"

    Source: ANDIGEMA, A., Tania Cyrielle, N. N., Daniel Laetitia, N., & Ekwelle, E. (2024). "Transforming Healthcare in Africa: The Role of Artificial Intelligence in Combatting Infectious Diseases, Neglected Tropical Diseases, and Antimicrobial Resistance", Preprint

    Keywords: AI, Africa, Healthcare

    Abstract: Artificial Intelligence (AI) has the potential to revolutionize healthcare in Africa by addressing critical challenges, including infectious diseases, neglected tropical diseases (NTDs), and antimicrobial resistance (AMR). This review explores AI's applications, benefits, and the challenges of integrating AI into African healthcare systems.

    Introduction - Africa faces significant healthcare challenges due to infectious diseases (e.g., malaria, HIV/AIDS), NTDs, and AMR. - AI offers transformative opportunities in early detection, diagnosis, and treatment, especially in resource-limited settings. - Objectives: - Highlight AI's potential in disease control and healthcare delivery. - Address barriers to AI integration, such as infrastructure and ethical considerations. - AI technologies can improve health outcomes and align with sustainable development goals.

    2. Role of AI in Infectious Disease Surveillance and Outbreak Detection -

    AI facilitates real-time tracking and prediction of disease outbreaks using diverse data sources, such as social media, electronic health records, and news reports.

    Examples of successful AI applications:

    mPedigree: Verifies the authenticity of medicines to prevent counterfeit drugs.

    AfriHealth: Monitors disease outbreaks by analyzing multiple data sources. - PREDICT Program: Identifies pandemic threats in wildlife populations.

    - epitrack: Uses mobile data to model disease spread and guide interventions. - AI's adaptability and predictive power enhance outbreak management and resource allocation.

    3. AI-Enabled Diagnosis and Treatment

    AI-powered tools provide faster and more accurate diagnoses by analyzing imaging scans, genetic information, and health records. - Examples: - AI diagnosing malaria from blood samples. AI improving tuberculosis detection via chest X-rays but also Satellite imagery to manage diseases like schistosomiasis.

    AI enables personalized treatment plans by leveraging patient-specific data. - Challenges: - Limited infrastructure for data collection in Africa. - Potential biases in AI models due to incomplete or skewed datasets. - Ethical concerns, such as privacy and transparency in AI algorithms.

    4. AI-Driven Drug Discovery and Development

    AI accelerates the discovery of new drugs and combats AMR through:

    Target identification: Pinpointing pathogen characteristics for drug development. Virtual screening: Rapidly assessing compound libraries for potential drug candidates. Predictive analytics: Monitoring resistance trends and supporting proactive interventions. - Drug repositioning: Identifying alternative uses for existing medications. African projects utilizing AI for HIV drug discovery and NTD treatments show promising results.

    5. Challenges and Limitations of AI in Africa - Technological Constraints:

    Limited access to computational resources. Shortage of trained AI professionals. Data Accessibility: Lack of robust healthcare infrastructure and inconsistent data collection methods. Need for improved data-sharing frameworks.

    Cultural and Ethical Barriers: Resistance to AI adoption due to privacy concerns and lack of trust. Algorithmic biases that could exacerbate health disparities.

    Establishing ethical guidelines and sustainable partnerships is crucial for successful AI implementation.

    Conclusion

    AI presents immense potential to transform African healthcare, improving disease surveillance, diagnosis, treatment, and drug discovery. We have to understand the necessity of addressing ethical, infrastructural, and data-related challenges is essential for realizing AI's benefits. The authors of this paper Recommendates to develop tailored AI solutions for Africa's healthcare context. They Encourage collaborations among governments, tech companies, and local communities. Furthermore, they priorioritize ethical regulations and data governance frameworks. Finally,The future of AI in African healthcare is promising, contingent upon overcoming implementation challenges.

    Competing interests

    The author declares that they have no competing interests.

  2. Version published to 10.20944/preprints202403.1679.v1