BioIntelli 2026: World Congress on Artificial Intelligence, Bioinformatics & Computational Biology

Theme: AI-Driven Discoveries: Shaping the Future of Bioinformatics and Computational Biology

19-20, November 2026 Tokyo, Japan
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Ussi Hamza
Featured Speaker

Ussi Hamza

Invited Speaker

Tanzania

Biography

Ussi Hamza Ussi is a Medical Laboratory Histoscientist, educator, and global public health researcher from Zanzibar, Tanzania. He holds a Bachelor of Medical Laboratory Sciences in Histotechnology from Muhimbili University of Health and Allied Sciences (MUHAS) and is currently pursuing a Master of Science in Global Public Health at Southern Medical University, China. Since 2017, he has served at the State University of Zanzibar (SUZA), where he is involved in teaching, research, histopathology laboratory management, and student mentorship. His research focuses on histopathology, infectious disease epidemiology, One Health, and global public health. Ussi has authored several peer-reviewed publications, presented his work at national scientific conferences, and actively contributes to professional associations and public health initiatives in Tanzania.      

Abstract Title

Epidemiological Trends And Risk Factors Of Hepatitis B Viral Infection In Zanzibar: A Retrospective Analysis (2021–2023) With Implications For Ai-Driven Public Health Surveillance Background :Hepatitis B virus (HBV) infection remains a silent public health threat in sub-Saharan Africa, including Zanzibar. Despite the availability of effective vaccines, transmission persists due to behavioral, healthcare-related, and socioeconomic factors. Understanding the local epidemiology is critical for targeted interventions. Furthermore, integrating bioinformatics and artificial intelligence (AI) into infectious disease surveillance offers new opportunities for predicting outbreak patterns and optimizing resource allocation. Objective: This study aimed to determine the prevalence and associated risk factors of HBV infection among individuals screened at Mnazi Mmoja Hospital,Zanzibar, between 2021 and 2023, and to discuss how computational methods can enhance future public health strategies. Methods: A retrospective analysis was conducted on secondary data from 24,431 individuals screened for hepatitis B surface antigen (HBsAg) at Mnazi Mmoja Referral Hospital. Demographic, behavioral, healthcare-related, and awareness variables were extracted from hospital records (2021–2023) and analyzed using IBM SPSS version 27. Results: The overall prevalence of HBV infection was 7.6%, placing Zanzibar at the upper margin of intermediate endemicity. The highest prevalence (8.3%) was observed in 2022. Key risk factors included: age 31–45 years (53.0% of positives), urban residence (68.5%), unemployment (42.4%), lack of awareness (79.9% unaware of HBV), ear/nose piercing (18.0%), multiple hospitalizations (11.9%), shaving at barbershops (8.6%), and multiple sexual partners (6.6%). Healthcare-related exposures such as dental procedures (5.6%) and dialysis attendance (5.3%) were also significant. Conclusions HBV infection in Zanzibar is driven by a complex interplay of behavioral, healthcare, and socioeconomic factors, compounded by low public awareness. The moderate-to-high prevalence calls for urgent public health interventions, including expanded vaccination, community education, and routine screening Keywords: Hepatitis B, prevalence, risk factors, Zanzibar, artificial intelligence, public health surveillance, computational epidemiology, bioinformatics.