Faculty Opinions recommendation of Harvesting can increase severity of wildlife disease epidemics.

Author(s):  
Rachel Norman
Antibiotics ◽  
2021 ◽  
Vol 10 (3) ◽  
pp. 335
Author(s):  
Anssi Karvonen ◽  
Ville Räihä ◽  
Ines Klemme ◽  
Roghaieh Ashrafi ◽  
Pekka Hyvärinen ◽  
...  

Environmental heterogeneity is a central component influencing the virulence and epidemiology of infectious diseases. The number and distribution of susceptible hosts determines disease transmission opportunities, shifting the epidemiological threshold between the spread and fadeout of a disease. Similarly, the presence and diversity of other hosts, pathogens and environmental microbes, may inhibit or accelerate an epidemic. This has important applied implications in farming environments, where high numbers of susceptible hosts are maintained in conditions of minimal environmental heterogeneity. We investigated how the quantity and quality of aquaculture enrichments (few vs. many stones; clean stones vs. stones conditioned in lake water) influenced the severity of infection of a pathogenic bacterium, Flavobacterium columnare, in salmonid fishes. We found that the conditioning of the stones significantly increased host survival in rearing tanks with few stones. A similar effect of increased host survival was also observed with a higher number of unconditioned stones. These results suggest that a simple increase in the heterogeneity of aquaculture environment can significantly reduce the impact of diseases, most likely operating through a reduction in pathogen transmission (stone quantity) and the formation of beneficial microbial communities (stone quality). This supports enriched rearing as an ecological and economic way to prevent bacterial infections with the minimal use of antimicrobials.


2021 ◽  
Vol 83 (5) ◽  
Author(s):  
F. M. Hamelin ◽  
B. Bowen ◽  
P. Bernhard ◽  
V. A. Bokil

2013 ◽  
Vol 9 (1) ◽  
pp. 20120900 ◽  
Author(s):  
Katrina Morris ◽  
Jeremy J. Austin ◽  
Katherine Belov

The Tasmanian devil ( Sarcophilus harrisii ) is at risk of extinction owing to the emergence of a contagious cancer known as devil facial tumour disease (DFTD). The emergence and spread of DFTD has been linked to low genetic diversity in the major histocompatibility complex (MHC). We examined MHC diversity in historical and ancient devils to determine whether loss of diversity is recent or predates European settlement in Australia. Our results reveal no additional diversity in historical Tasmanian samples. Mainland devils had common modern variants plus six new variants that are highly similar to existing alleles. We conclude that low MHC diversity has been a feature of devil populations since at least the Mid-Holocene and could explain their tumultuous history of population crashes.


2014 ◽  
Vol 10 (6) ◽  
pp. e1003668 ◽  
Author(s):  
Jake M. Ferguson ◽  
Jessica B. Langebrake ◽  
Vincent L. Cannataro ◽  
Andres J. Garcia ◽  
Elizabeth A. Hamman ◽  
...  

2021 ◽  
Vol 2021 (1) ◽  
Author(s):  
Mohammed A. Aba Oud ◽  
Aatif Ali ◽  
Hussam Alrabaiah ◽  
Saif Ullah ◽  
Muhammad Altaf Khan ◽  
...  

AbstractCOVID-19 or coronavirus is a newly emerged infectious disease that started in Wuhan, China, in December 2019 and spread worldwide very quickly. Although the recovery rate is greater than the death rate, the COVID-19 infection is becoming very harmful for the human community and causing financial loses to their economy. No proper vaccine for this infection has been introduced in the market in order to treat the infected people. Various approaches have been implemented recently to study the dynamics of this novel infection. Mathematical models are one of the effective tools in this regard to understand the transmission patterns of COVID-19. In the present paper, we formulate a fractional epidemic model in the Caputo sense with the consideration of quarantine, isolation, and environmental impacts to examine the dynamics of the COVID-19 outbreak. The fractional models are quite useful for understanding better the disease epidemics as well as capture the memory and nonlocality effects. First, we construct the model in ordinary differential equations and further consider the Caputo operator to formulate its fractional derivative. We present some of the necessary mathematical analysis for the fractional model. Furthermore, the model is fitted to the reported cases in Pakistan, one of the epicenters of COVID-19 in Asia. The estimated value of the important threshold parameter of the model, known as the basic reproduction number, is evaluated theoretically and numerically. Based on the real fitted parameters, we obtained $\mathcal{R}_{0} \approx 1.50$ R 0 ≈ 1.50 . Finally, an efficient numerical scheme of Adams–Moulton type is used in order to simulate the fractional model. The impact of some of the key model parameters on the disease dynamics and its elimination are shown graphically for various values of noninteger order of the Caputo derivative. We conclude that the use of fractional epidemic model provides a better understanding and biologically more insights about the disease dynamics.


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