TY - JOUR
T1 - Impacts of road traffic network and socioeconomic factors on the diffusion of 2009 pandemic influenza a (H1N1) in mainland China
AU - Xu, Bo
AU - Tian, Huaiyu
AU - Sabel, Clive Eric
AU - Xu, Bing
N1 - Funding Information:
Funding: This research was partially supported by the National Research Program of the Ministry of Science and Technology of the People’s Republic of China (2016YFA0600104), donations from Delos Living LLC and the Cyrus Tang Foundation to Tsinghua University, the National Natural Science Foundation of China (81673234), the Beijing Natural Science Foundation (JQ18025), and the Young Elite Scientist Sponsorship Program by CAST (YESS) (2018QNRC001). H.T. acknowledges support from the Oxford Martin School.
Funding Information:
This research was partially supported by the National Research Program of the Ministry of Science and Technology of the People’s Republic of China (2016YFA0600104), donations from Delos Living LLC and the Cyrus Tang Foundation to Tsinghua University, the National Natural Science Foundation of China (81673234), the Beijing Natural Science Foundation (JQ18025), and the Young Elite Scientist Sponsorship Program by CAST (YESS) (2018QNRC001). H.T. acknowledges support from the Oxford Martin School.
Publisher Copyright:
© 2019 by the authors. Licensee MDPI, Basel, Switzerland.
PY - 2019/4/1
Y1 - 2019/4/1
N2 - The 2009 pandemic influenza virus caused the majority of the influenza A virus infections in China in 2009. It arrived in several Chinese cities from imported cases and then spread as people travelled domestically by all means of transportation, among which road traffic was the most commonly used for daily commuting. Spatial variation in socioeconomic status not only accelerates migration across regions but also partly induces the differences in epidemic processes and in responses to epidemics across regions. However, the roles of both road travel and socioeconomic factors have not received the attention they deserve. Here, we constructed a national highway network for and between 333 cities in mainland China and extracted epidemiological variables and socioeconomic factors for each city. We calculated classic centrality measures for each city in the network and proposed two new measures (SumRatio and Multicenter Distance). We evaluated the correlation between the centrality measures and epidemiological features and conducted a spatial autoregression to quantify the impacts of road network and socioeconomic factors during the outbreak. The results showed that epidemics had more significant relationships with both our new measures than the classic ones. Higher population density, higher per person income, larger SumRatio and Multicenter Distance, more hospitals and college students, and lower per person GDP were associated with higher cumulative incidence. Higher population density and number of slaughtered pigs were found to advance epidemic arrival time. Higher population density, more colleges and slaughtered pigs, and lower Multicenter Distance were associated with longer epidemic duration. In conclusion, road transport and socioeconomic status had significant impacts and should be considered for the prevention and control of future pandemics.
AB - The 2009 pandemic influenza virus caused the majority of the influenza A virus infections in China in 2009. It arrived in several Chinese cities from imported cases and then spread as people travelled domestically by all means of transportation, among which road traffic was the most commonly used for daily commuting. Spatial variation in socioeconomic status not only accelerates migration across regions but also partly induces the differences in epidemic processes and in responses to epidemics across regions. However, the roles of both road travel and socioeconomic factors have not received the attention they deserve. Here, we constructed a national highway network for and between 333 cities in mainland China and extracted epidemiological variables and socioeconomic factors for each city. We calculated classic centrality measures for each city in the network and proposed two new measures (SumRatio and Multicenter Distance). We evaluated the correlation between the centrality measures and epidemiological features and conducted a spatial autoregression to quantify the impacts of road network and socioeconomic factors during the outbreak. The results showed that epidemics had more significant relationships with both our new measures than the classic ones. Higher population density, higher per person income, larger SumRatio and Multicenter Distance, more hospitals and college students, and lower per person GDP were associated with higher cumulative incidence. Higher population density and number of slaughtered pigs were found to advance epidemic arrival time. Higher population density, more colleges and slaughtered pigs, and lower Multicenter Distance were associated with longer epidemic duration. In conclusion, road transport and socioeconomic status had significant impacts and should be considered for the prevention and control of future pandemics.
KW - 2009 H1N1 pandemic
KW - Gravity model
KW - Highway network
KW - Mainland China
KW - Network node centrality
KW - Socioeconomic factors
KW - Spatial autoregressive model
KW - Spatiotemporal transmission
UR - http://www.scopus.com/inward/record.url?scp=85064532202&partnerID=8YFLogxK
UR - https://www.mdpi.com/journal/ijerph/about
U2 - 10.3390/ijerph16071223
DO - 10.3390/ijerph16071223
M3 - Article
C2 - 30959783
AN - SCOPUS:85064532202
SN - 1660-4601
VL - 16
SP - 1
EP - 14
JO - International Journal of Environmental Research and Public Health
JF - International Journal of Environmental Research and Public Health
IS - 7
M1 - 1223
ER -