Environmental bioaerosol surveillance as an early warning system for pathogen detection in North Carolina swine farms: A pilot study.

Disease outbreaks can readily threaten swine production operations sometimes resulting in large economic losses. Pathogen surveillance in swine farms can be an effective approach for the early identification of new disease threats and the mitigation of transmission before broad dissemination among a herd occurs. Non-invasive environmental bioaerosol sampling could be an effective and affordable approach for conducting routine surveillance in farms, providing an additional tool for farmers to protect their animals and themselves from new disease threats. In this pilot study, we implemented a non-invasive, prospective bioaerosol sampling strategy in a swine farm located in the United States to detect economically important swine pathogens. Farm personnel collected air samples from two swine barns for 23 weeks between July and December 2017. Samples were then tested within 24 hr of collection by molecular techniques for a number of economically important swine pathogens. Of the 86 bioaerosol samples collected, 4 (4.7%) were positive for influenza A, 1 (1.2%) was positive for influenza D, 13 (15.1%) were positive for PCV2, and 13 (15.1%) were positive for PCV3. Overall, this pilot study showed that our bioaerosol surveillance strategy was feasible and able to generate data that could be quickly disseminated back to the farm stakeholders (within 24 hr). We were also able to identify PCV2, PCV3 and influenza A virus in air samples as clinical disease became apparent in the pigs, strongly suggesting that bioaerosol sampling can be used as an effective non-invasive surveillance approach for the detection of multiple pathogens in this and likely other animal production environments.

Molecular surveillance of respiratory viruses with bioaerosol sampling in an airport.

Recognizing that crowded, high-traffic airports and airplanes have been implicated in respiratory disease transmission, we partnered with administrators of Raleigh Durham International Airport (RDU) in conducting a pilot study of aerosol surveillance for respiratory viruses at RDU. From January to March 2018 we used NIOSH 2-stage samplers to collect 150 min aerosol samples in crowded areas at RDU. Four (17%) of the 24 samples were positive for known respiratory pathogens including influenza D virus and adenovirus. These results suggest the feasibility of employing bioaerosol surveillance techniques in public transportation areas, such as airports, as a noninvasive way to detect and characterize novel respiratory viruses.

Aerosol Sampling in a Hospital Emergency Room Setting: A Complementary Surveillance Method for the Detection of Respiratory Viruses.

This study aimed to evaluate environmental air sampling as an alternative form of active surveillance for respiratory pathogens in clinical settings. Samples were collected from three locations in the Emergency Department at Duke University Hospital Systems from October 2017 to March 2018. Of the 44 samples collected, 12 were positive for known respiratory pathogens including influenza A, influenza D, and adenovirus. Results suggest bioaerosol sampling may serve as a complement to active surveillance in clinical settings. Additionally, since respiratory viruses were detected in aerosol samples, our results suggest that hospital infection control measures, including the use of N95 respirators, could be used to limit the spread of infectious viruses in the air.

Rapid Influenza Testing in an Austere Setting, Mongolia.

In 2015-2017, we helped rural Mongolian clinicians with poor infrastructure adopt rapid influenza diagnostic tests (RIDTs). In their hands, the Quidel Sofia Influenza A Test was both sensitive (75%) and specific (100%). If made widely available, such RIDTs would have the potential to markedly reduce influenza morbidity and mortality in Mongolia.

Equine influenza A(H3N8) virus isolated from Bactrian camel, Mongolia.

Because little is known about the ecology of influenza viruses in camels, 460 nasal swab specimens were collected from healthy (no overt illness) Bactrian camels in Mongolia during 2012. One specimen was positive for influenza A virus (A/camel/Mongolia/335/2012[H3N8]), which is phylogenetically related to equine influenza A(H3N8) viruses and probably represents natural horse-to-camel transmission.

Isolation and characterization of H3N8 equine influenza A virus associated with the 2011 epizootic in Mongolia.

BACKGROUND: Equine influenza virus (EIV) epizootics affect 2.1 million Mongolian horses approximately every 10 years and critically impact economy and nomadic livelihood of Mongolia. OBJECTIVES: An active surveillance program was established in 2011 to monitor influenza viruses circulating among Mongolian horses. METHODS: Nasal swabs were collected from horses in free-ranging horse herds in Töv, Khentii, and Dundgovi aimags (provinces) from January to September 2011. Real-time reversetranscriptase-polymerase chain reaction (rRT-PCR) was used to determine the presence of influenza A virus. Influenza A-positive specimens were cultured to amplify virus; viral RNA was extracted, and gene segments were amplified and sequenced by Sanger sequencing. RESULTS: A total of 745 horses were swabbed; most horses were without clinical signs of illness. In July 2011, reports of influenza-like illnesses emerged among horses in Mongolia's capital, and subsequently, surveillance efforts were adjusted to swab horses associated with the epizootic. Thirty-four specimens of rRT-PCR influenza-positive virus were collected in May, June, August, and September. Three specimens yielded detectable virus. Gene sequence studies suggested that all three isolates were identical H3N8 viruses. Phylogenetic analyses indicated the strain was very similar to other H3N8 EIVs circulating in central Asia between 2007 and 2008. CONCLUSIONS: As large Mongolian equine herds often seem to suffer from EIV epizootics, it seems prudent to continue such routine equine influenza surveillance. Doing so will provide an early warning system, should novel viruses emerge, help in assessing if EIV is crossing over to infect humans and provide data to assess the likely effectiveness of current EIV vaccines.