Asymmetric association between meteorological factors and human infections with hemorrhagic fever with renal syndrome: A 16-year ecological trend study in Shaanxi, China - Chenlu Xue; Bingjie Zhang; Yanyan Li; Xinxiao Li; Chunjie Xu; Yongbin Wang (One Health)
Objective: Hemorrhagic fever with renal syndrome (HFRS) continues to pose a significant threat to global health. This study aimed to investigate both the long- and short-term asymmetric impacts of variations in meteorological variables on HFRS. Methods: The reported monthly HFRS incidence data from Shaanxi between 2004 and 2019, along with corresponding meteorological data, were collected to conduct an ecological trend analysis. Subsequently, the autoregressive distributed lag (ARDL) and nonlinear ARDL (NARDL) models were used to examine the long- and short-term asymmetric effects of climate variables on HFRS incidence. Results: Overall, a reduction in HFRS incidence was observed in Shaanxi from 2004 to 2019, with an average annual percentage change of −0.498 % (95 %CI -13.247 % to 12.602 %). HFRS incidence peaked in December and reached its lowest point in March each year. A 1 mm increase in aggregate precipitation (AP) was associated with a 4.3 % rise in HFRS incidence, while a 1 mm decrease contributed to a 3.7 % increase, indicating a long-term asymmetric impact (Wald long-term asymmetry test [WLT] = 9.072, P = 0.003). In the short term, a 1 % decrease in mean relative humidity (MRH) led to a 5.7 % decline in HFRS incidence (Wald short-term asymmetry test [WSR] = 5.978, P = 0.015). Additionally, changes in meteorological variables showed varied effects: ΔMWV(+) at a 1-month lag had a significant positive short-term effect on HFRS; ΔMRH(+) at a 3-month lag, ΔAP(+) at a 2-month lag, ΔAP(−) at a 1-month lag, ΔASH(+) at a 1-month lag, and ΔASH(−) at a 3-month lag all exhibited strong negative short-term impacts on HFRS incidence. Conclusions: Weather variability plays a significant role in influencing HFRS incidence, with both long- and short-term asymmetric and/or symmetric effects. Utilizing the NARDL model through a One Health lens offers promising opportunities for enhancing HFRS control measures.