Estimation of the basic reproductive number (R0) for epidemic, highly pathogenic avian influenza subtype H5N1 spread

2008 ◽  
Vol 137 (2) ◽  
pp. 219-226 ◽  
Author(s):  
M. P. WARD ◽  
D. MAFTEI ◽  
C. APOSTU ◽  
A. SURU

SUMMARYThree different methods were used for estimating the basic reproductive number (R0) from data on 110 outbreaks of highly pathogenic avian influenza (HPAI) subtype H5N1 that occurred in village poultry in Romania, 12 May to 6 June 2006. We assumed a village-level infectious period of 7 days. The methods applied were GIS-based identification of nearest infectious neighbour (based on either Euclidean or road distance), the method of epidemic doubling time, and a susceptible–infectious (SI) modelling approach. In general, the estimated basic reproductive numbers were consistent: 2·14, 1·95, 2·68 and 2·21, respectively. Although the true basic reproductive number in this epidemic is unknown, results suggest that the use of a range of methods might be useful for characterizing epidemics of infectious diseases. Once the basic reproductive number has been estimated, better control strategies and targeted surveillance programmes can be designed.

2020 ◽  
Vol 7 (3) ◽  
pp. 107
Author(s):  
Roderick Salvador ◽  
Neil Tanquilut ◽  
Kannika Na Lampang ◽  
Warangkhana Chaisowwong ◽  
Dirk Pfeiffer ◽  
...  

Highly pathogenic avian influenza virus (HPAIV) is a major problem in the poultry industry. It is highly contagious and is associated with a high mortality rate. The Philippines experienced an outbreak of avian influenza (AI) in 2017. As there is always a risk of re-emergence, efforts to manage disease outbreaks should be optimal. Linked to this is the need for an effective surveillance procedure to capture disease outbreaks at their early stage. Risk-based surveillance is the most effective and economical approach to outbreak management. This study evaluated the potential of commercial poultry farms in Central Luzon to transmit HPAI by calculating their respective reproductive ratios (R0). The reproductive number for each farm is based on the spatial kernel and the infectious period. A risk map has been created based on the calculated R0. There were 882 (76.63%) farms with R0 < 1. Farms with R0 ≥ 1 were all located in Pampanga Province. These farms were concentrated in the towns of San Luis (n = 12) and Candaba (n = 257). This study demonstrates the utility of mapping farm-level R0 estimates for informing HPAI risk management activities.


Viruses ◽  
2020 ◽  
Vol 12 (12) ◽  
pp. 1389 ◽  
Author(s):  
Sol Jeong ◽  
Dong-Hun Lee ◽  
Jung-Hoon Kwon ◽  
Yu-Jin Kim ◽  
Sun-Hak Lee ◽  
...  

In October 2020, a highly pathogenic avian influenza (HPAI) subtype H5N8 virus was identified from a fecal sample of a wild mandarin duck (Aix galericulata) in South Korea. We sequenced all eight genome segments of the virus, designated as A/Mandarin duck/Korea/K20-551-4/2020(H5N8), and conducted genetic characterization and comparative phylogenetic analysis to track its origin. Genome sequencing and phylogenetic analysis show that the hemagglutinin gene belongs to H5 clade 2.3.4.4 subgroup B. All genes share high levels of nucleotide identity with H5N8 HPAI viruses identified from Europe during early 2020. Enhanced active surveillance in wild and domestic birds is needed to monitor the introduction and spread of HPAI via wild birds and to inform the design of improved prevention and control strategies.


2021 ◽  
Vol 50 (Supplement_1) ◽  
Author(s):  
Dae-sung Yoo ◽  
Chun Byung Chul

Abstract Background Highly pathogenic avian influenza (HPAI), a zoonotic infectious disease, has been considered a severe threat to public health. The fundamental prevention and control strategy against HPAI includes minimizing the outbreaks of poultry holdings where the virus primarily spreads through animal trade and poultry production associated vehicle movement (PPVM). However, very few attempts have been made to elucidate the association between PPVM and HPAI transmission compared to studies on poultry trade. Therefore, our study aimed to elucidate the role of PPVM on HPAI transmission. Methods We performed network analysis using PPVM data based on a global positioning system (GPS), with phylogenetic information of the HPAI virus for reliable estimation. Moreover, the contribution of PPVM to HPAI infection was estimated by Bayesian inference. Results The network analysis revealed that the connection via PPVM between the same genetic group of infected premises (IPs) was more prevalent than that of different genotype IPs. Moreover, the similarity of farm poultry species and the overlapped integrators between inter-linked IPs was associated with potential transmission route formation. Additionally, the contribution of PPVM among phylogenetically clustered IPs was estimated to have 28.25% of HPAI infections in IPs on average. Conclusions HPAI control strategies including targeted movement restriction and standstill should be established against the HPAI transmission via PPVM. Key messages This is a solid and novel study depicting the need for combining epidemiological analysis with data regarding molecular epidemiology of pathogens.


2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Dae-Sung Yoo ◽  
Byung chul Chun ◽  
Younjung Kim ◽  
Kwang-Nyeong Lee ◽  
Oun-Kyoung Moon

AbstractHighly pathogenic avian influenza (HPAI) in poultry holdings commonly spreads through animal trade, and poultry production and health-associated vehicle (PPHaV) movement. To effectively control the spread of disease, it is essential that the contact structure via those movements among farms is thoroughly explored. However, few attempts have been made to scrutinize PPHaV movement compared to poultry trade. Therefore, our study aimed to elucidate the role of PPHaV movement on HPAI transmission. We performed network analysis using PPHaV movement data based on a global positioning system, with phylogenetic information of the isolates during the 2016–2017 HPAI H5N6 epidemic in the Republic of Korea. Moreover, the contribution of PPHaV movement to the spread of HPAI was estimated by Bayesian modeling. The network analysis revealed that there was the relationship between phylogenetic clusters and the contact network via PPHaV movement. Furthermore, the similarity of farm poultry species and the shared integrators between inter-linked infected premises (IPs) were associated with ties within the same phylogenetic clusters. Additionally, PPHaV movement among phylogenetically clustered IPs was estimated to contribute to approximately 30% of HPAI H5N6 infections in IPs on average. This study provides insight into how HPAI spread via PPHaV movement and scientific basis for control strategies.


2010 ◽  
Vol 8 (61) ◽  
pp. 1079-1089 ◽  
Author(s):  
G. Fournié ◽  
F. J. Guitian ◽  
P. Mangtani ◽  
A. C. Ghani

Live bird markets (LBMs) act as a network ‘hub’ and potential reservoir of infection for domestic poultry. They may therefore be responsible for sustaining H5N1 highly pathogenic avian influenza (HPAI) virus circulation within the poultry sector, and thus a suitable target for implementing control strategies. We developed a stochastic transmission model to understand how market functioning impacts on the transmission dynamics. We then investigated the potential for rest days—periods during which markets are emptied and disinfected—to modulate the dynamics of H5N1 HPAI within the poultry sector using a stochastic meta-population model. Our results suggest that under plausible parameter scenarios, HPAI H5N1 could be sustained silently within LBMs with the time spent by poultry in markets and the frequency of introduction of new susceptible birds' dominant factors determining sustained silent spread. Compared with interventions applied in farms (i.e. stamping out, vaccination), our model shows that frequent rest days are an effective means to reduce HPAI transmission. Furthermore, our model predicts that full market closure would be only slightly more effective than rest days to reduce transmission. Strategies applied within markets could thus help to control transmission of the disease.


Epidemics ◽  
2019 ◽  
Vol 28 ◽  
pp. 100340 ◽  
Author(s):  
Alessio Andronico ◽  
Aurélie Courcoul ◽  
Anne Bronner ◽  
Axelle Scoizec ◽  
Sophie Lebouquin-Leneveu ◽  
...  

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