?url_ver=Z39.88-2004&rft_id=10.5204%2Fthesis.eprints.206172&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Adc&rft.title=Using+big+data+to+enhance+pertussis+surveillance+and+response+in+Shandong+Province%2C+China&rft.creator=Zhang%2C+Yuzhou&rft.subject=pertussis&rft.subject=surveillance&rft.subject=internet+search+query&rft.subject=socio-environmental+factors&rft.subject=prediction&rft.description=Pertussis+imposes+a+substantial+global+health+burden+and+has+been+reported+to+resurge+over+the+next+few+years+in+many+countries.+The+thesis+used+big+data+to+predict+pertussis+infection+in+Shandong+province%2C+China.+The+research+quantified+the+associations+of+internet+query+data+and+socio-environmental+factors+with+pertussis+infection+and+developed+spatial+and+temporal+predictive+models+based+on+big+data.+The+findings+of+the+thesis+may+enhance+traditional+pertussis+surveillance+and+response+via+the+development+of+an+early+warning+system+based+on+big+data.&rft.publisher=Queensland+University+of+Technology&rft.date=2020&rft.type=Thesis&rft.format=application%2Fpdf&rft.relation=https%3A%2F%2Feprints.qut.edu.au%2F206172%2F1%2FYuzhou_Zhang_Thesis.pdf&rft.rights=free_to_read&rft.rights=http%3A%2F%2Fcreativecommons.org%2Flicenses%2Fby-nc-nd%2F4.0%2F&rft.relation=doi%3A10.5204%2Fthesis.eprints.206172&rft.relation=Zhang%2C+Yuzhou+(2020)+Using+big+data+to+enhance+pertussis+surveillance+and+response+in+Shandong+Province%2C+China.+PhD+by+Publication%2C+Queensland+University+of+Technology.&rft.id_number=https%3A%2F%2Feprints.qut.edu.au%2F206172%2F&rft.identifier=Faculty+of+Health%3B+School+of+Public+Health+%26+Social+Work