Objective To explore the association between temperature and incidence of influenza-like illness (ILI) in Huai′an city, Jiangsu province and provide a scientific basis for the prevention and control of ILI.

Methods The ILI surveillance data of two national influenza surveillance sentinel hospitals and meteorological data in Huai′an from January 1, 2015 to December 31, 2022 were collected from the Chinese Influenza Surveillance Information System and China Meteorological Data Service Center, respectively. The associations between the weekly incidence of ILI and meteorological factors were tested by Spearman correlation analysis. The distributed lag non-linear model (DLNM) was utilized to analyze the association between the average temperature and ILI incidence among residents in Huai′an. The confounding factors such as long-term trends and holiday effects were controlled to analyze the lag effect of average temperature on the incidence of ILI.

Results In the influenza surveillance sentinel hospitals in Huai′an from 2015 to 2022, the weekly average incidence of ILI was (527.88 ± 444.83) cases. Spearman correlation analysis indicated that weekly average temperature and weekly average air pressure were negatively associated with weekly average incidence (r = −0.24 and 0.19, respectively, both P < 0.001). The results of the DLNM demonstrated that at a lag of 0 week, the heat effect (30 °C) would increase the risk of ILI in the 5–14 (RR = 2.02, 95%CI: 1.03–3.98), 15–24 (RR = 2.25, 95%CI: 1.17–4.32), 25–59 (RR = 2.08, 95%CI: 1.13–3.83), and ≥ 60 (RR = 3.01, 95%CI: 1.04–8.74) age groups; at a lag of 1 week, the cold effect (1 °C) would increase the risk of ILI in the overall population (RR = 1.96, 95%CI: 1.35–2.84), 0–4 (RR = 1.39, 95%CI: 1.00–1.94), 5–14 (RR = 1.70, 95%CI: 1.04–2.89), 15–24 (RR = 3.88, 95%CI: 2.30–6.57), 25–59 (RR = 4.02, 95%CI: 2.46–6.57), and ≥60 (RR = 13.02, 95%CI: 5.97–28.42) age groups; at a lag of 2 weeks, the cold effect (1 °C) would increase the risk of ILI in the 25–59 age group (RR = 1.58, 95%CI: 1.01–2.48); at a lag of 0–1 week, the cold effect (1 °C) would increase the risk of ILI in the overall population (RR = 2.51, 95%CI: 1.83–3.46), 0–4 (RR = 1.61, 95%CI: 1.20–2.14), 5–14 (RR = 2.50, 95%CI: 1.55–3.77), 15–24 (RR = 5.01, 95%CI: 3.19–7.87), 25–59 (RR = 5.25, 95%CI: 3.45–8.00), and ≥ 60 (RR = 17.13, 95%CI: 8.89–32.90) age groups, and the heat effect (30 °C) would increase the risk of ILI in the ≥ 60 age group (RR = 4.68, 95%CI: 1.46–15.01); at a lag of 0–2 weeks, the cold effect (1 °C) would increase the risk of ILI in the overall population (RR = 3.21, 95%CI: 2.34–4.40), 0–4 (RR = 1.96, 95%CI: 1.47–2.62), 5–14 (RR = 3.07, 95%CI: 2.02–4.67), 15–24 (RR = 5.86, 95%CI: 3.76–9.11), 25–59 (RR = 8.32, 95%CI: 5.60–12.46), and ≥ 60 (RR = 15.87, 95%CI: 8.12–31.03) age groups, and the heat effect (30 °C) would increase the risk of ILI in the 15–24 age group (RR = 2.18, 95%CI: 1.08–4.38); at a lag of 0–3 weeks, the cold effect (1 °C) would increase the risk of ILI in the overall population (RR = 2.10, 95%CI: 1.54–2.88), 0–4 (RR = 1.90, 95%CI: 1.44–2.51), 5–14 (RR = 2.16, 95%CI: 1.43–2.37), 15–24 (RR = 2.42, 95%CI: 1.51–3.86), 25–59 (RR = 3.43, 95%CI: 2.45–5.25), and ≥ 60 (RR = 6.18, 95%CI: 3.07–12.44) age groups.

Conclusions Temperature affects the risk of ILI in different age groups in Huai′an. The cold effect is the main risk factor and has a lag effect, demonstrating a greater effect on ILI in the elderly population, which suggests that more attention should be paid to the elderly in the future.