How to contain #avian #flu #H5N1 if human-to-human spread begins ...
| #AvianInfluenza | #BirdFlu | #microsky | #AvianFlu | #microbiology | #pathogen | #outbreak | Via @sciencex.bsky.social
#People ill from E coli linked to raw #cheese from #California #farm ...
| #Ecoli | #pathogen | #microsky | #publichealth | Via @theguardian.com
Health warning issued after #measles detected on the Gold #Coast ...
| #virus | #microbiology | #pathogen | #publichealth | Via @9news.bsky.social
#Scientists identify new #Fusarium species behind #wheat #disease #outbreak in #Ethiopia ...
| #pathogen | #fungi | #microbiology | #toxins | By @plantdisease.bsky.social via eurekalert .org
Decoding the complete #genome of the #fungus responsible for #Cercospora leaf spot in #olive #trees ...
| #fungi | #pathogen | #CercosporaLeafSpot | #Pseudocercospora | Via @sciencex.bsky.social
E. Coli #outbreak linked to #cheeses grows ...
| #Ecoli | #bacteria | #microsky | #food | #pathogen | #publichealth | By @marywhnews.bsky.social via @usatoday.com
‘White plague’ is on the rise in the United States ...
| #TB | #infections | #pathogen | #tuberculosis | #Mycobacterium | #microbiology | #bacteria | Via @nypost.com
New #COVID-19 #variant 'Cicada' is spreading ...
| #coronavirus | #MicroSky | #Cicada | #SARSCoV2 | #mutant | #COVID19 | #pathogen | #infections | By @marywhnews.bsky.social via @usatoday.com
New #bacterial #disease in #corn and #sorghum mistaken for #iron deficiency ...
| #bacteria | #MicroSky | #pathogen | #Pantoea | Via agdaily .com
As #antibiotics fail, a new treatment targets the #host, not the #bacteria ...
| #MicroSky | #pathogen | #infections | #antibioticresistance | #microbes | By @tcddublin.bsky.social via @sciencex.bsky.social
#Skin's immune response could be key to fighting #dengue ...
| #virus | #pathogen | #virology | #infections | #ImmuneResponse | By @bristoluni.bsky.social via @sciencex.bsky.social
#Measles continues spread with exposure at #grocery stores, #medical #offices, #temple open house ...
| #virus | #pathogen | #publichealth | #infections | #MicroSky | Via @ksl.com
www.ksl.com/article/5147...
Another seven #measles cases reported in #Florida ...
| #virus | #infections | #pathogen | #publichealth | Via @floridaphoenix.com
floridaphoenix.com/2026/03/24/f...
What are they calling it....#TRUMP? ¯\_(ツ)_/¯
.
#Scientists created an #antibody that can #eradicate an #infection that affects 95% of the global #population.
#EpsteinBarr #virus (#EBV) is a #pervasive #pathogen, infecting nearly 95% of #humans & persisting for #life. #science #biology #health
#m6A #epigenetic modification controls #arbovirus #infection and transmission between #vertebrates and #mosquitoes ...
| #Arthropod | #arboviruses | #dengue | #pathogen | #Zika | #MicroSky | Via eurekalert .org
New #COVID #variant has been identified and is already spreading in the United States ...
| #SARSCoV2 | #MicroSky | #virology | #coronavirus | #COVID19 | #pathogen | #infections | By @juliaelenamusto.bsky.social via @the-independent.com
www.independent.co.uk/news/health/...
Eastern #Idaho sees ‘concerning increase’ in #HIV #infections ...
| #virus | #pathogen | #MicroSky | #HumanImmunodeficiencyVirus | Via eastidahonews .com
Processes that can potentially influence emergence risk. Simony and Kennedy investigate the role of spillover rate (λ in their model) and the timescale over which spillovers have happened (Tp in their model) on the probability that a disease circulating in a reservoir host (here, gorillas) emerges in humans. Red viruses and arrows indicate spillover events; infected individuals (gorillas and humans) are shown in red, and uninfected individuals are shown in gray. Time moves forward according to the black arrows, which are shown in gray when spillover is not possible, e.g., due to geographic barriers. Their results show the most informative comparison for adjudicating relative emergence risk, as indicated by the dark boxes, is spillover timescale: pathogens that recently began spilling over into humans (“recent” associations) are riskier than ones that have been spilling over for a long time (“old” associations). In contrast, little can be learned about emergence risk from comparing spillover rates (light boxes).
Can we predict which #pathogen will be responsible for the next #pandemic? Mete Yuksel & Nicole Mideo explore a new study in @plosbiology.org that challenges the idea that pathogens that frequently spill over are more likely to emerge 🧪 Paper: plos.io/4ss5WCY Primer: plos.io/4uOyh8f
New tool can warn #farmers before #bird #flu #infection spreads ...
| #cattle | #MicroSky | #AvianFlu | #BirdFlu | #AvianInfluenza | #pathogen | Via @sciencex.bsky.social
Processes that can potentially influence emergence risk. Simony and Kennedy investigate the role of spillover rate (λ in their model) and the timescale over which spillovers have happened (Tp in their model) on the probability that a disease circulating in a reservoir host (here, gorillas) emerges in humans. Red viruses and arrows indicate spillover events; infected individuals (gorillas and humans) are shown in red, and uninfected individuals are shown in gray. Time moves forward according to the black arrows, which are shown in gray when spillover is not possible, e.g., due to geographic barriers. Their results show the most informative comparison for adjudicating relative emergence risk, as indicated by the dark boxes, is spillover timescale: pathogens that recently began spilling over into humans (“recent” associations) are riskier than ones that have been spilling over for a long time (“old” associations). In contrast, little can be learned about emergence risk from comparing spillover rates (light boxes).
Can we predict which #pathogen will be responsible for the next #pandemic? Mete Yuksel & Nicole Mideo explore a new study in @plosbiology.org that challenges the idea that pathogens that frequently spill over are more likely to emerge 🧪 Paper: plos.io/4ss5WCY Primer: plos.io/4uOyh8f
#H5N1 in #marine #mammals is spreading ...
| #seals | #sealions | #HPAI | #avianinfluenza | #BirdFlu | #AvianFlu | #pathogen | #infections | By @ucdavis.bsky.social via @sciencex.bsky.social
Processes that can potentially influence emergence risk. Simony and Kennedy investigate the role of spillover rate (λ in their model) and the timescale over which spillovers have happened (Tp in their model) on the probability that a disease circulating in a reservoir host (here, gorillas) emerges in humans. Red viruses and arrows indicate spillover events; infected individuals (gorillas and humans) are shown in red, and uninfected individuals are shown in gray. Time moves forward according to the black arrows, which are shown in gray when spillover is not possible, e.g., due to geographic barriers. Their results show the most informative comparison for adjudicating relative emergence risk, as indicated by the dark boxes, is spillover timescale: pathogens that recently began spilling over into humans (“recent” associations) are riskier than ones that have been spilling over for a long time (“old” associations). In contrast, little can be learned about emergence risk from comparing spillover rates (light boxes).
Can we predict which #pathogen will be responsible for the next #pandemic? Mete Yuksel & Nicole Mideo explore a new study in @plosbiology.org that challenges the idea that pathogens that frequently spill over are more likely to emerge 🧪 Paper: plos.io/4ss5WCY Primer: plos.io/4uOyh8f
Conceptual framework for relating spillover rate and the past spillover window to host jump risk. In order to successfully host jump, a pathogen must overcome barriers to spillover and barriers to sustained transmission in the novel host. Pathogens may or may not be limited at either step in this process, leading conceptually to four classes of nonnative pathogens (A–D). In practice, and in the authors' model, spillover limitation and transmission limitation are continuous traits meaning that there is no discrete separation between the “types” of pathogens shown in A–D but thy discuss pathogens in this framework because it is useful for illustration.
Pathogen host-jumps pose major risks to health, but how can we predict them? This study shows that #pathogen novelty, rather than #spillover rate, is a stronger predictor of host-jump risk, so we should monitor emerging pathogens with limited spillover histories @plosbiology.org 🧪 plos.io/4ss5WCY
Trace levels of #food #pathogen do not always translate to #health risk ...
| #bacteria | #MicroSky | #microbes | #publichealth | By @frontiersin.bsky.social via @sciencex.bsky.social
Conceptual framework for relating spillover rate and the past spillover window to host jump risk. In order to successfully host jump, a pathogen must overcome barriers to spillover and barriers to sustained transmission in the novel host. Pathogens may or may not be limited at either step in this process, leading conceptually to four classes of nonnative pathogens (A–D). In practice, and in the authors' model, spillover limitation and transmission limitation are continuous traits meaning that there is no discrete separation between the “types” of pathogens shown in A–D but thy discuss pathogens in this framework because it is useful for illustration.
Pathogen host-jumps pose major risks to health, but how can we predict them? This study shows that #pathogen novelty, rather than #spillover rate, is a stronger predictor of host-jump risk, so we should monitor emerging pathogens with limited spillover histories @plosbiology.org 🧪 plos.io/4ss5WCY
Conceptual framework for relating spillover rate and the past spillover window to host jump risk. In order to successfully host jump, a pathogen must overcome barriers to spillover and barriers to sustained transmission in the novel host. Pathogens may or may not be limited at either step in this process, leading conceptually to four classes of nonnative pathogens (A–D). In practice, and in the authors' model, spillover limitation and transmission limitation are continuous traits meaning that there is no discrete separation between the “types” of pathogens shown in A–D but thy discuss pathogens in this framework because it is useful for illustration.
Pathogen host-jumps pose major risks to health, but how can we predict them? This study shows that #pathogen novelty, rather than #spillover rate, is a stronger predictor of host-jump risk, so we should monitor emerging pathogens with limited spillover histories @plosbiology.org 🧪 plos.io/4ss5WCY
No matter where they are performed, studies with infectious agents need ironclad biorisk management. This can be promoted through robust gatekeeping of funding and publication, using a new formal reporting standard for pathogen research.
What concrete steps can we take to reinforce #biorisk management? In this Perspective, an international group of experts advocate for better global standards for #pathogen research.
🧪 #MicroSky #DURC
plos.io/3NN7451
No matter where they are performed, studies with infectious agents need ironclad biorisk management. This can be promoted through robust gatekeeping of funding and publication, using a new formal reporting standard for pathogen research.
What concrete steps can we take to reinforce #biorisk management? In this Perspective, an international group of experts advocate for better global standards for #pathogen research.
🧪 #MicroSky #DURC
plos.io/3NN7451
First-of-its-kind #vaccine protects #children from deadly #intestinal #infections ...
| #ETVAX | #Ecoli | #pathogen | #enterotoxigenic | #diarrhea | Via @sciam.bsky.social
No matter where they are performed, studies with infectious agents need ironclad biorisk management. This can be promoted through robust gatekeeping of funding and publication, using a new formal reporting standard for pathogen research.
What concrete steps can we take to reinforce #biorisk management? In this Perspective, an international group of experts advocate for better global standards for #pathogen research.
🧪 #MicroSky #DURC
plos.io/3NN7451