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. 2022 Feb 22:10:833710.
doi: 10.3389/fpubh.2022.833710. eCollection 2022.

Effects and Interaction of Meteorological Parameters on Influenza Incidence During 2010-2019 in Lanzhou, China

Jinyu Wang  1 , Ling Zhang  2 , Ruoyi Lei  2 , Pu Li  3 , Sheng Li  4
Affiliations

Effects and Interaction of Meteorological Parameters on Influenza Incidence During 2010-2019 in Lanzhou, China

Jinyu Wang et al. Front Public Health. .

Abstract

Background: Influenza is a seasonal infectious disease, and meteorological parameters critically influence the incidence of influenza. However, the meteorological parameters linked to influenza occurrence in semi-arid areas are not studied in detail. This study aimed to clarify the impact of meteorological parameters on influenza incidence during 2010-2019 in Lanzhou. The results are expected to facilitate the optimization of influenza-related public health policies by the local healthcare departments.

Methods: Descriptive data related to influenza incidence and meteorology during 2010-2019 in Lanzhou were analyzed. The exposure-response relationship between the risk of influenza occurrence and meteorological parameters was explored according to the distributed lag no-linear model (DLNM) with Poisson distribution. The response surface model and stratified model were used to estimate the interactive effect between relative humidity (RH) and other meteorological parameters on influenza incidence.

Results: A total of 6701 cases of influenza were reported during 2010-2019. DLNM results showed that the risk of influenza would gradually increase as the weekly mean average ambient temperature (AT), RH, and absolute humidity (AH) decrease at lag 3 weeks when they were lower than 12.16°C, 51.38%, and 5.24 g/m3, respectively. The low Tem (at 5th percentile, P5) had the greatest effect on influenza incidence; the greatest estimated relative risk (RR) was 4.54 (95%CI: 3.19-6.46) at cumulative lag 2 weeks. The largest estimates of RRs for low RH (P5) and AH (P5) were 4.81 (95%CI: 3.82-6.05) and 4.17 (95%CI: 3.30-5.28) at cumulative lag 3 weeks, respectively. An increase in AT by 1°C led to an estimates of percent change (95%CI) of 3.12% (-4.75% to -1.46%) decrease in the weekly influenza case counts in a low RH environment. In addition, RH showed significant interaction with AT and AP on influenza incidence but not with wind speed.

Conclusion: This study indicated that low AT, low humidity (RH and AH), and high air pressure (AP) increased the risk of influenza. Moreover, the interactive effect of low RH with low AT and high AP can aggravate the incidence of influenza.

Keywords: distributed lag non-linear model; influenza; interaction; meteorology; seasonally.

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Conflict of interest statement

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Figures

Figure 1
Figure 1
Time-series distribution of daily influenza case counts and daily meteorological parameters in Lanzhou, China during 2010–2019.
Figure 2
Figure 2
Exposure-response relationship between the risk of influenza and AT (A), AH (B), RH (C), AP (D), SH (E), and WS (F) at a three-week lag in Lanzhou, China during 2010–2019. The red line represents the cumulative relative risk (RR) of influenza, and the gray shaded region represents the 95% confidence interval (CI).
Figure 3
Figure 3
Cumulative lag effect of meteorological parameters on the onset of influenza under extreme conditions at different lag weeks in Lanzhou, China during 2010–2019. P5 represents the 5th percentile. P95 represents the 95th percentile.
Figure 4
Figure 4
Three-dimensional map of the interaction effect of relative humidity (RH) with other meteorological parameters on influenza incidence in Lanzhou, China during 2010–2019 after a lag of 3 weeks. (A) Interaction effect of RH with AT. (B) Interaction effect of RH with AP. (C) Interaction effect of RH with WS.
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