Knowledge, Perceptions, and Willingness to use Artificial Intelligence in Disease Surveillance among Primary Health Care Workers in Calabar Metropolis, Cross River State, Nigeria: A Cross-sectional Study.

Abstract

Background: Artificial Intelligence (AI) has emerged as a transformative tool in the health sector, offering the potential to revolutionize how diseases are monitored and managed. Despite its growing relevance, the adoption of AI in public health practice remains limited in many parts of the world. Most existing studies had focused on technological development or implementation in tertiary health institutions, with limited attention paid to frontline health workers who play a critical role in early disease detection and reporting. Objective: This study assessed the knowledge, perceptions, and willingness to use Artificial Intelligence in disease surveillance among Primary Healthcare workers in Calabar Metropolis, Cross River State, Nigeria. Methods: A cross-sectional study design using quantitative method of data collection was used to survey 135 primary healthcare workers, recruited using a multi-stage sampling technique, via a semi-structured validated questionnaire and analyzed with SPSS Version 25.  Descriptive statistics was used to summarize the data as frequencies, percentages. Association between selected socio-demographic characteristics of the respondents and their willingness to use AI in disease surveillance was ascertained using chi-square statistical test at 0.05 significant level. Results: Majority of the participants, 73(54.1%) were community health workers, majority, 77(57.0%) demonstrated good knowledge of AI use in disease surveillance. The Primary Health Care workers’ perception of the use of AI in disease surveillance was negative, 110(81.5%). However, majority of the participants were willing to adopt the use of AI in disease surveillance, and the primary health care workers’ willingness to use AI in disease surveillance was associated with their educational level and professional category. Conclusion: Health Care Workers had good knowledge of AI used in disease surveillance, negative perceptions of AI use in disease surveillance, but willing to adopt AI in disease surveillance. The findings of this study reiterate the need for Policymakers to develop comprehensive frameworks to facilitate AI integration in disease surveillance and healthcare delivery.