Abstract

This research looks at how weather (temp, air pressure, humidity, UV index and the like) and population density affect influenza A/B in Hong Kong through analysis of 539 observations (Jan 2015–Apr 2025). By means of Ordinary least squares (OLS) regression and Granger causality tests, weekly data obtained from the Hong Kong’s Open Data Platform, the Hong Kong Observatory and the Centre for Health Protection was analyzed. According to the findings, cases was found to be negatively associated with temperature (β = -36.85, p < 0.001) and air pressure (β = -6.998, p < 0.001), while it was found to be positively associated with relative humidity (β = 6.43, p = 0.009), UV index (β = 58.35, p = 0.003), and population density (β = 1.10, p < 0.001) through regression analysis. The evidence of Granger causality has shown that the temperature, air pressure, and UV index influence influenza. However, humidity and UV index affects flu in the opposite way. This is probably due to behavioral feedback leading to indoor crowding. The findings informed targeted surveillance in subtropical urban settings, highlighting the impact of temperature-driven risks and density-adapted interventions. Public health alerts should be triggered by temperature declines and pressure rises for policy implications and early warning systems. The Hong Kong government should upgrades take priority in crowded districts during cold-humid seasons.

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