The consequences of climate change at an avian influenza ‘hotspot’

Brown, V. L.; Rohani, Pejman

doi:10.1098/rsbl.2012.0635

Cited by 15 publications

(17 citation statements)

References 15 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Stenseth & Mysterud ; Memmott et al . ), but it has only recently been discussed in the context of host–parasite interactions and disease (Brown & Rohani ; Paull et al . ).…”

Section: Discussionmentioning

confidence: 99%

Experimental warming drives a seasonal shift in the timing of host‐parasite dynamics with consequences for disease risk

Paull

Johnson

2014

Ecology Letters

View full text Add to dashboard Cite

Multi-species experiments are critical for identifying the mechanisms through which climate change influences population dynamics and community interactions within ecological systems, including infectious diseases. Using a host-parasite system involving freshwater snails, amphibians and trematode parasites, we conducted a year-long, outdoor experiment to evaluate how warming affected net parasite production, the timing of infection and the resultant pathology. Warming of 3 °C caused snail intermediate hosts to release parasites 9 months earlier and increased infected snail mortality by fourfold, leading to decreased overlap between amphibians and parasites. As a result, warming halved amphibian infection loads and reduced pathology by 67%, despite comparable total parasite production across temperature treatments. These results demonstrate that climate-disease theory should be expanded to account for predicted changes in host and parasite phenology, which may often be more important than changes in total parasite output for predicting climate-driven changes in disease risk.

show abstract

“…Stenseth & Mysterud ; Memmott et al . ), but it has only recently been discussed in the context of host–parasite interactions and disease (Brown & Rohani ; Paull et al . ).…”

Section: Discussionmentioning

confidence: 99%

Experimental warming drives a seasonal shift in the timing of host‐parasite dynamics with consequences for disease risk

Paull

Johnson

2014

Ecology Letters

View full text Add to dashboard Cite

show abstract

“…The Delaware Bay has been identified as a “hotspot” for AIV prevalence, from May to June, in shore birds, particularly the ruddy turnstone, however, the surveying time period excludes this population. Migratory waterfowl also travel up the Atlantic Flyway and arrive late July through October with peak AIV prevalence detected in August [22], [23]. A study on the Eastern Shore of Maryland sampled cloacal swabs from resident ducks for 3 weeks between May 28 and Sept 2, 1998.…”

Section: Discussionmentioning

confidence: 99%

Avian Influenza Seroprevalence and Biosecurity Risk Factors in Maryland Backyard Poultry: A Cross-Sectional Study

et al. 2013

View full text Add to dashboard Cite

Major implications on a country's economy, food source, and public health. With recent concern over the highly pathogenic avian influenza outbreaks around the world, government agencies are carefully monitoring and inspecting live bird markets, commercial flocks, and migratory bird populations. However, there remains limited surveillance of non-commercial poultry. Therefore, a cross-sectional study was conducted in backyard poultry flocks using a convenience sampling method across three regions of Maryland from July 2011 to August 2011. The objective of this study was to develop a better understanding of the ecology and epidemiology of avian influenza by investigating the prevalence and seroprevalence in this potentially vulnerable population and by evaluating biosecurity risk factors associated with positive findings. Serum, tracheal, and cloacal swabs were randomly collected from 262 birds among 39 registered premises. Analysis indicated bird and flock seroprevalence as 4.2% (11/262) and 23.1% (9/39), respectively. Based on RT-qPCR analysis, none of the samples were found to be positive for AI RNA and evidence of AI hemagglutinin subtypes H5, H7, or H9 were not detected. Although no statistically significant biosecurity associations were identified (p≤0.05), AI seroprevalence was positively associated with exposure to waterfowl, pest control, and location. AI seropositive flocks exposed to waterfowl were 3.14 times as likely to be AI seropositive than those not exposed (p = 0.15). AI seropositive flocks that did not use pest control were 2.5 times as likely to be AI seropositive compared to those that did and AI seropositive flocks located in the Northern region of Maryland were 2.8 times as likely to be AI seropositive than those that were located elsewhere.

show abstract

“…These authors suggest that the outbreak occurred in different waves. Brown & Rohani [32] have studied the effect of alteration between migratory shorebird and horseshoe crabs as a result of climate change.…”

Section: Discussionmentioning

confidence: 99%

Epidemiological analysis of spatially misaligned data: a case of highly pathogenic avian influenza virus outbreak in Nigeria

Adegboye

Kotzé

2013

Epidemiol. Infect.

View full text Add to dashboard Cite

SummaryThis research is focused on the epidemiological analysis of the transmission of the highly pathogenic avian influenza (HPAI) H5N1 virus outbreak in Nigeria. The data included 145 outbreaks together with the locations of the infected farms and the date of confirmation of infection. In order to investigate the environmental conditions that favoured the transmission and spread of the virus, weather stations were realigned with the locations of the infected farms. The spatial KolmogorovSmirnov test for complete spatial randomness rejects the null hypothesis of constant intensity (P < 0·0001). Preliminary exploratory analysis showed an increase in the incidence of H5N1 virus at farms located at high altitude. Results from the Poisson log-linear conditional intensity function identified temperature (−0·9601) and wind speed (0·6239) as the ecological factors that influence the intensity of transmission of the H5N1 virus. The model also includes distance from the first outbreak (−0·9175) with an Akaike's Information Criterion of −103·87. Our analysis using a point process model showed that geographical heterogeneity, seasonal effects, temperature, wind as well as proximity to the first outbreak are very important components of spread and transmission of HPAI H5N1.

show abstract

The consequences of climate change at an avian influenza ‘hotspot’

Cited by 15 publications

References 15 publications

Experimental warming drives a seasonal shift in the timing of host‐parasite dynamics with consequences for disease risk

Experimental warming drives a seasonal shift in the timing of host‐parasite dynamics with consequences for disease risk

Avian Influenza Seroprevalence and Biosecurity Risk Factors in Maryland Backyard Poultry: A Cross-Sectional Study

Epidemiological analysis of spatially misaligned data: a case of highly pathogenic avian influenza virus outbreak in Nigeria

Contact Info

Product

Resources

About