TY - JOUR
T1 - Avian influenza transmission risk along live poultry trading networks in Bangladesh
AU - Moyen, Natalie
AU - Hoque, Md. Ahasanul
AU - Mahmud, Rashed
AU - Hasan, Mahmudul
AU - Sarkar, Sudipta
AU - Biswas, Paritosh Kumar
AU - Mehedi, Hossain
AU - Henning, Joerg
AU - Mangtani, Punam
AU - Flora, Meerjady Sabrina
AU - Rahman, Mahmudur
AU - Debnath, Nitish C.
AU - Giasuddin, Mohammad
AU - Barnett, Tony
AU - Pfeiffer, Dirk U.
AU - Fournié, Guillaume
PY - 2021
Y1 - 2021
N2 - Live animal markets are known hotspots of zoonotic disease emergence. To mitigate those risks, we need to understand how networks shaped by trading practices influence disease spread. Yet, those practices are rarely recorded in high-risk settings. Through a large cross-sectional study, we assessed the potential impact of live poultry trading networks’ structures on avian influenza transmission dynamics in Bangladesh. Networks promoted mixing between chickens sourced from different farming systems and geographical locations, fostering co-circulation of viral strains of diverse origins in markets. Viral transmission models suggested that the observed rise in viral prevalence from farms to markets was unlikely explained by intra-market transmission alone, but substantially influenced by transmission occurring in upstream network nodes. Disease control interventions should therefore alter the entire network structures. However, as networks differed between chicken types and city supplied, standardised interventions are unlikely to be effective, and should be tailored to local structural characteristics.
AB - Live animal markets are known hotspots of zoonotic disease emergence. To mitigate those risks, we need to understand how networks shaped by trading practices influence disease spread. Yet, those practices are rarely recorded in high-risk settings. Through a large cross-sectional study, we assessed the potential impact of live poultry trading networks’ structures on avian influenza transmission dynamics in Bangladesh. Networks promoted mixing between chickens sourced from different farming systems and geographical locations, fostering co-circulation of viral strains of diverse origins in markets. Viral transmission models suggested that the observed rise in viral prevalence from farms to markets was unlikely explained by intra-market transmission alone, but substantially influenced by transmission occurring in upstream network nodes. Disease control interventions should therefore alter the entire network structures. However, as networks differed between chicken types and city supplied, standardised interventions are unlikely to be effective, and should be tailored to local structural characteristics.
UR - http://www.scopus.com/inward/record.url?scp=85114602981&partnerID=8YFLogxK
UR - https://www.scopus.com/record/pubmetrics.uri?eid=2-s2.0-85114602981&origin=recordpage
U2 - 10.1038/s41598-021-98989-4
DO - 10.1038/s41598-021-98989-4
M3 - RGC 21 - Publication in refereed journal
C2 - 34620890
SN - 2045-2322
VL - 11
JO - Scientific Reports
JF - Scientific Reports
M1 - 19962
ER -