English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Plus monthly

Global: Zendy Tools annual

Global: Zendy Tools monthly

Global: Zendy Free Plan

Numerous studies have demonstrated that exposure to live poultry or live poultry markets is the significant risk factor for human infection with avian influenza A(H7N9). However, the specific live poultry markets that are major infection sources for A(H7N9) human cases have not been explored in detail. In this study, we extract data associated with poultry farms, live poultry markets and farmers’ markets from Baidu Map using the JavaScript language and then construct the live poultry transport network. From this, we establish our A(H7N9) transmission model over the network based upon probabilistic discrete-time Markov chain. On the basis of the obtained network and model, we propose spatiotemporal backward detection and forward transmission algorithms to detect the most likely infection sources and to compute the first arrival times of the infection sources. Our simulations use these algorithms to identify the specific locations of the infection sources, the first arrival times of the infection sources and the most likely transmission map of the A(H7N9) virus along the live poultry transport network. The results reveal that, in addition to the hazards posed by the live poultry markets, backyard poultry also contributed to A(H7N9) human infections; this risk source was significant especially in the newly affected provinces, in the fifth wave of infection. In particular, by analyzing the temperature characteristics at a given location when the infection source arrived, we find that the risk of human infection with the influenza A(H7N9) virus was high under 9°C~19°C; moderate under 0°C~9°C or 19°C~25°C; and low for temperatures < 0°C or >25°C. Our results suggest that strengthening the supervision of the live poultry market system and immunizing poultry at both live poultry markets and the backyard poultry operations under the high risk temperature band of 9°C~19°C, will be able to significantly contribute to the control of avian influenza A(H7N9) in the future.

Detection of Infection Sources for Avian Influenza A(H7N9) in Live Poultry Transport Network During the Fifth Wave in China