Using empirical dynamic modeling to identify the impact of meteorological factors on hemorrhagic fever with renal syndrome in Weifang, Northeastern China, from 2011 to 2020.

Background: Renal Syndrome Hemorrhagic Fever (HFRS) continues to pose a significant public health threat to the well-being of the population. Given that the spread of HFRS is susceptible to meteorological factors, we aim to probe into the meteorological drivers of HFRS. Thus, novel techniques that can discern time-delayed non-linear relationships from nonlinear dynamical systems are compulsory. Methods: We analyze the epidemiological features of HFRS in Weifang City, 2011–2020, via the employment of the Empirical Dynamic Modeling (EDM) method. Our analysis delves into the intricate web of time-delayed non-linear associations between meteorological factors and HFRS. Additionally, we investigate the repercussions of minor perturbations in meteorological variables on future HFRS incidence. Results: A total of 2515 HFRS cases were reported in Weifang from 2011 to 2020. The average weekly incidence was 4.81, and the average weekly incidence was 0.52 per 1,000,000. The propagation of HFRS is significantly impacted by the mean weekly temperature, relative humidity, cumulative rainfall, and wind speed, and the ρCCM converges to 0.55,0.48,0.38 and 0.39, respectively. The graphical representation of the relationship between temperature (lagged by 2 weeks) and the incidence of HFRS exhibits an inverted U-shaped curve, whereby the incidence of HFRS culminates as the temperature reaches 10 °C. Moreover, temperature, relative humidity, cumulative rainfall, and wind speed exhibit a positive correlation with HFRS incidence, with a time lag of 4–6 months. Conclusions: Our discoveries suggest that meteorological factors can drive the transmission of HFRS both at a macroscopic and microscopic scale. Prospective alterations in meteorological conditions, for instance, elevations in temperature, relative humidity, and precipitation will instigate an upsurge in the incidence of HFRS after 4–6 months, and thus, timely public health measures should be taken to mitigate these changes. Author summary: Renal Syndrome Hemorrhagic Fever (HFRS) is a serious disease caused by the Hantavirus and transmitted by rodents. Meteorological factors, such as temperature, humidity, precipitation, and wind speed, can influence the occurrence, spread, and outbreak of HFRS. However, the relationship between climate change and its impact on the disease is complex, and more research is needed to provide a strong scientific basis for the development of adaptation strategies. This study employs a novel technique called Empirical Dynamic Modeling (EDM) to investigate the time-delayed non-linear relationships between meteorological factors and HFRS outbreaks in Weifang. The results show that meteorological factors can drive the transmission of HFRS both at a macroscopic and microscopic scale. The relationship between temperature (lagged by 2 weeks) and HFRS incidence exhibits an inverted U-shaped curve, with the highest incidence occurring at 10 °C. Changes in meteorological conditions, such as increases in temperature, relative humidity, and precipitation, can lead to an upsurge in the incidence of HFRS after 4–6 months. The findings of this study are crucial for public health officials and policymakers to take timely measures to mitigate the impact of climate change on the spread of HFRS. [ABSTRACT FROM AUTHOR]