American
International
University-
Bangladesh

Students & Supervisors

Abstract

Big data analytics plays a very important role in the area of public health where it is mainly helpful in prediction of disease outbreaks, monitoring health and decision-making on policy improvements. In Bangladesh, predictive analytics can be used to find out the risk and implement better decision in healthcare problems. His new data-crunching muscle pumps health and computing together in a way that can more accurately predict public health outcomes. The evolution of predictive analytics in public health in the long run has not been examined systematically for Bangladesh. The 1994–2023 dataset enables an analysis of trends in innovation index, research output, adoption rate, simulation accuracy and impact score reflecting the influence of big data approaches on public health policies practiced in developing country. This article aims to explore the contribution of predictive analytics based on big data to the improvement in Bangladesh's public health by investigating evolution of innovation, adoption and research productivity; testing simulation's accuracy as an indicator for prediction reliability; and assessing overall impact these advances have on public health response and preparedness. We analyze cross-temporal influence among innovation index, research output, adoption rate, simulation accuracy and impact score based on longitudinal data from 1994 to 2023. It draws attention to important technology progresses, adoption peaks and challenges of implementation. Important years in innovation (1997, 2017, and 2023) and adoption (2001, 2016, and 2019) imply breaking points by which predictive analytics influenced public health application. The results illustrate volatility but net positive trend on the use of predictive analytics for public health outcomes in Bangladesh. High innovation level was maintained even in years 1997 (94.72), 2017 (96.56) and 2023 (91.32) with a strong research contribution in big data applications. There was, however, variability in the rates of adoption with a peak recorded in s2001 (83.08), 2016 (82.97) and 2019 (80.51), followed by declines and 2018) and forecasted for2033), which may reflect obstacles to continued implementation. For a critical period with very good prediction accuracy and p>90%% in terms of model performance, five years (1996, 1997, 2007, 2017 and 2021) were stored. The impact scores were maximum in 1997 (9.39), 2015(9.19), 2017 (9.57), and by 2023 (9.71); reflecting the tectonic shift predictive analytics has brought on public health tactics. The trajectory seems to be more in the direction that big data-powered predictive analytics is becoming core to public health decision-making with ups and downs. Predictive analytics using big data has been very effective in improving public health outcomes in Bangladesh as per the findings of the study. Although innovation and quality of prediction are strong, uneven levels of adoption only serve to reinforce systemic challenges such as infrastructure preparedness, data handling and policy coordination. Addressing these hurdles will be critical for long-term implementation. The findings indicate that policymakers can be empowered with predictive analytics for timely insights, preparedness during health emergencies and long-term planning in health forecasting of Bangladesh.

Keywords

Publication Details

• Type of Publication:
• Conference Name: 7th International Conference on Integrated Sciences (ICIS) 2025
• Date of Conference: 25/10/2025 - 25/10/2025
• Venue: Eastern University, Dhaka, Bangladesh
• Organizer: Eastern University, Dhaka, Bangladesh