Diagnostics and surveillance methods

Spackman, Erica; Cattoli, Giovanni; Suarez, David L.

doi:10.1002/9781118924341.ch2

Cited by 2 publications

(2 citation statements)

References 68 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Second the domestic duck infected with the HPAI H5N6 virus did not show apparent clinical signs and took a longer time to death while the infected chicken was showing apparently clinical signs 17 . Third, each poultry holding took a weekly mandatory test under nationwide active surveillance with the uncertainty of sensitivity (i.e., false negative) concerning different sample sizes, especially in the low prevalent phase 18 . Additionally, it was supposed that IPs were infectious from one day after the onset of infection and remained infectious until reporting or sampling date, because all both entries and exits from IPs come to be banned immediately after confirmed.…”

Section: Methodsmentioning

confidence: 99%

Dynamics of inter-farm transmission of highly pathogenic avian influenza H5N6 integrating vehicle movements and phylogenetic information

Yoo

Chun

Kim

et al. 2021

Sci Rep

View full text Add to dashboard Cite

Highly 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.

show abstract

Section: Methodsmentioning

confidence: 99%

Dynamics of inter-farm transmission of highly pathogenic avian influenza H5N6 integrating vehicle movements and phylogenetic information

Yoo

Chun

Kim

et al. 2021

Sci Rep

View full text Add to dashboard Cite

show abstract

“…Influenza A (H1 N1) virus was first identified in April 2009, when real-time RT-PCR was a relatively new technique. [48] Since then RT-PCR protocols were largely established and validated following industry-standard criteria. The lower limit of detection of the assay was 384 copies of viral RNA per ml of viral transport medium (95% confidence interval: 273-876 RNA copies/ml).…”

Section: Aerosol Viral Rna (H1 N1 and Covid-19) Detection By Rt-pcrmentioning

confidence: 99%

Sensors and Analytical Technologies for Air Quality: Particulate Matters and Bioaerosols

Sutarlie

Loh

2020

Chemistry An Asian Journal

View full text Add to dashboard Cite

Particulate matters (PMs), e. g. dusts, fibres, smokes, fumes, mists, liquid droplets and airborne respirable solid or liquid particles, are the major sources of air pollution concerning outdoor and indoor air quality. Among various PMs, bioaerosols are airborne particles that are either living organisms (bacteria, viruses, and fungi) or originate from living organisms (endotoxin, allergen, etc). PMs and/or bioaerosols have adverse health effects of infection, allergy, and irritation. Proper management and source identification of PMs and bioaerosols will reduce their negative health impact. In this review, we will discuss the analytical technologies and sensors for PMs and bioaerosols. We will first introduce four types of PM analysers, namely, filter-based gravimetric method (GMM), optical method, β-ray absorption method (BAM), and tapered element oscillating microbalance (TEOM). We will provide examples of how commercial PM analyzers of different principles have been compared and calibrated for specific applications under different climate conditions of specific geographic locations. For bioaerosols, having more complex biological and biochemical identity, we will start from air sampling techniques, followed by a discussion of various detection methods (plate culture, molecular methods, immunoassays and biosensors) in association with compatible sampling technologies. Using Influenza A (H1 N1) virus and SARS-CoV-2 (COVID-19) virus as examples, we have highlighted air sampling and detection challenges for viral aerosols relative to bacterial and fungal aerosols. Finally, we provide a perspective for future trends according to the limitation of current commercial products and the key challenges in this field.

show abstract

Diagnostics and surveillance methods

Cited by 2 publications

References 68 publications

Dynamics of inter-farm transmission of highly pathogenic avian influenza H5N6 integrating vehicle movements and phylogenetic information

Dynamics of inter-farm transmission of highly pathogenic avian influenza H5N6 integrating vehicle movements and phylogenetic information

Sensors and Analytical Technologies for Air Quality: Particulate Matters and Bioaerosols

Contact Info

Product

Resources

About