Association between meteorological factors, spatiotemporal effects, and prevalence of influenza A subtype H7 in environmental samples in Zhejiang province, China
Graphical abstract
Introduction
Human infection with an avian-origin influenza virus (H7N9) was first reported in Shanghai, China in spring 2013 (Gao et al., 2013). Since then there have been continual reports in the territory. As of 21 Apr 2018, a total of 1567 cases of human H7N9 infection were reported globally (Centre for Health Protection of the Department of Health, n.d.). China, where the vast majority of cases were reported, has experienced five epidemics (Subbarao, 2018), in which Zhejiang (310 cases), Guangdong (259 cases), and Jiangsu provinces (252 cases) were the most affected areas (Centre for Health Protection of the Department of Health, n.d.). In the first four outbreaks, the virus mainly affected eastern to southern China, and the magnitude of the epidemic decreased over time. In the fifth wave, however, westward spread and surge in the number of reported cases were observed, causing widespread concern on the change of the epidemiological characteristic of the virus (Zhou et al., 2017; Yang et al., 2018).
Exposure to poultry, either directly or indirectly, has been regarded as a primary source of human H7N9 infection (Lai et al., 2013; Liu et al., 2013a). In fact, the majority of infected individuals recalled history of exposure to poultry (Wang et al., 2015; Xiang et al., 2016). Substantial fall in the incidence of human H7N9 infection following the closure of live poultry markets provides evidence for exposure to live birds as an important risk factor for human infection (Yu et al., 2014; He et al., 2015). The epidemic of human H7N9 infection exhibited seasonal trends: the number rose in winter and spring and fell in summer and autumn (Huo et al., 2017; Lau et al., 2018). It has been postulated that meteorological factors drive the dynamic of the epidemic (Wang et al., 2015). Numerous research studies have shown that, despite diverse conclusion in the nature of association, relative humidity (Fang et al., 2013; Li et al., 2015), temperature (Fang et al., 2013; Li et al., 2015; Qiu et al., 2014; Zhang et al., 2015; Hu et al., 2015), rainfall (Lau et al., 2018; Qiu et al., 2014; Hu et al., 2015; Xu et al., 2016), and wind speed (Lau et al., 2018; Li et al., 2015) are associated with the epidemic pattern of human H7N9 infection.
Given low pathogenicity of the H7N9 virus in poultry in general (Liu et al., 2013b), outbreaks of the virus in the environment cannot be noticed easily until a human infection is reported. Experimental studies and field investigation have shown that avian influenza viruses are detectable in water and contaminated surfaces such as mud, water plants, and soil swab (Brown et al., 2007; Vong et al., 2008; Khalenkov et al., 2008). In particular, there have been studies showing that environmental samples such as chopping board swabs, cage surface swabs, faeces, and de-feathering machines collected from live poultry markets, poultry breeding farms, backyard poultry pens, poultry processing factories, and wild bird habitats were H7-positive in different extents (Wang et al., 2015; Kang et al., 2015). With a high correlation between the proportion of H7-positive environmental samples and the number of human H7N9 infection (Wang et al., 2015), an active environmental surveillance program can serve as an essential and more effective preventive measure, allowing for early detection of silent transmission of the virus in poultry and timely discovery of virus variation for better preparation for the disease outbreak (Fournié et al., 2016; Wang et al., 2017). Knowing how meteorological factors are associated with the prevalence of the virus in the environment is likely to provide insights for better planning of the surveillance program; nevertheless, little is known about it as previous studies mainly focused on meteorological association with human infection. This study aims to fill this research gap.
Section snippets
Data
Zhejiang province in China was chosen to be the study site due to its special geographic location, which is situated in the core part of Yangtze River Delta well recognized as the source of H7N9 outbreaks, having the highest prevalence of H7N9 among all the provinces in China (Chen et al., 2013; Wang et al., 2016), and a well-established environmental surveillance system for avian influenza viruses since 2011. The period from Oct 2013 to Jun 2017, which covers wave 2 to wave 5 of the epidemic (
Descriptive analysis
From Oct 2013 to Dec 2013, 10–144 monthly samples were collected from each sampled city, and since 2014, 10–577 monthly samples were collected from each city. As shown in Fig. 2a, <30% of the total samples were detected H7-positive most of the time, except in Jan 2016, Feb 2016, Apr 2016, Dec 2016, and Jan 2017, where 52.74%, 36.12%, 31.13%, 43.83% and 46.58% of the samples were H7-positive. Further examination reveals that in some cities (Fig. 2b), the proportion of H7-postitive samples can be
Discussion
Since the first ever reported case of human H7N9 infection in China, there have been recurrent outbreaks of the virus in the country. It has been found that human H7N9 infection is associated with meteorological factors (Lau et al., 2018; Fang et al., 2013; Li et al., 2015; Qiu et al., 2014; Zhang et al., 2015; Hu et al., 2015; Xu et al., 2016), at the same time, the proportion of H7-positive environmental samples is associated with the number of human H7N9 infection (Wang et al., 2015).
Conclusion
In this study, we analyzed the data on environmental samples and meteorological factors collected during Oct 2013–Jun 2017 in Zhejiang province, China, and demonstrated their associations: higher relative humidity, moderately long sunshine duration, and low temperature are statistically significantly associated with higher prevalence of the virus, whereas lower relative humidity, short and moderately short sunshine duration, and high temperature are statistically significantly associated lower
Abbreviations
- AOR
adjusted odds ratio
- CAR model
conditional autoregressive model
- CDC
Centre for Disease Control and Prevention
- MCMC
Markov chain Monte Carol
- MAE
Mean Absolute Error
- PRECIP
Precipitation
- RH
Relative humidity
- SUN
Sunshine duration
- TEMP
Temperature
- WAIC
Watanabe-Akaike information criterion
- WINDSPD
Wind speed
Funding
The work was supported by National Natural Science Foundation of China (Grant number: 81473035) and Medical Research Programme of Zhejiang Province (2016RCA008).
Ethics approval and consent to participate
This study was reviewed and approved by the Medical Ethics Committee of the Zhejiang Centre for Disease Control and Prevention (CDC). Informed consents were exempt from the ethics committee in accordance to the CDC policy of continuing public health investigations of notifiable infectious diseases.
Consent for publication
Not applicable.
Availability of data and material
The datasets are available from the corresponding author on reasonable request.
Competing interests
The authors declare that they have no competing interests.
Authors' contributions
EC, WC, ZY, and XW collected the data. SYFL, MW, BCYZ, XH, and RS analyzed the data. SYFL drafted the manuscript and wrote the final version. KCC revised the manuscript. All authors read and approved the final manuscript.
Acknowledgements
We thank Prof. Chan Kay Sheung in Department of Microbiology and Dr. Lee Tsz Cheung from Hong Kong Observatory for providing the virological and meteorological advice on the interpretation of study results. We thank the physicians and staff at Hangzhou, Huzhou, Jiaxing Wenzhou, Shaoxing, Ningbo, Quzhou, Jinhua, Zhoushan, Lishui, Taizhou municipal center for disease control and prevention for their support and assistance with this investigation.
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