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Alyssa-Lois M. Gehman

Publications and source records attributed to Alyssa-Lois M. Gehman.

3 recordsLinked to original sources

From understanding to action: Integrating new and old methodologies to manage marine infectious disease

Marine diseases can have far-reaching effects on population, community and ecosystem health; however, our ability to track, predict and manage these diseases has, historically, been poor. As a result, the fields of disease ecology and epidemiology have developed at a slower pace for marine than terrestrial systems [ 1 ]. New methodologies, including genomic tools for diagnostics [ 2 , 3 ], transcriptomic tools for measuring host and pathogen responses to infection (e.g. [ 4 , 5 ]), regional oceanic modelling systems that estimate environmental conditions influencing pathogen dispersal and disease progression [ 6 ], artificial intelligence methods for quantifying pathology from images (e.g. [ 7 ]) and advanced disease modelling techniques [ 8 , 9 ] are precipitating a rapid increase in our understanding of marine pathosystems. In 2016, these efforts led to the first special issue of Philosophical Transactions of the Royal Society B ( Marine diseases, volume 371, issue 1689) focused entirely on marine disease ecology and evolution, and in 2020, the first book, Marine disease ecology, was devoted to this topic [ 10 ]. This special issue, focused on marine disease management , is being published a decade after the first Philosophical Transactions special issue on marine diseases. The shift to a management focus reflects an urgent need for management strategies to address high-impact diseases and the rapid methodological advances that have resulted. The papers included in this issue demonstrate the value of combining classical approaches (e.g. routine disease surveillance, reductionistic pathogen challenge trials, rapid throughput diagnostics) with cutting-edge technologies (e.g. high-resolution oceanographic models, Bayesian models, replicated transcriptomic studies) to identify drivers of disease, quantify impacts and suggest management strategies.

Philosophical Transactions of the Royal Society, S

Vibrio pectenicida strain FHCF-3 is a causative agent of sea star wasting disease

More than 10 years following the onset of the sea star wasting disease (SSWD) epidemic, affecting over 20 asteroid species from Mexico to Alaska, the causative agent has been elusive. SSWD killed billions of the most susceptible species, sunflower sea stars ( Pycnopodia helianthoides ), initiating a trophic cascade involving unchecked urchin population growth and the widespread loss of kelp forests. Identifying the causative agent underpins the development of recovery strategies. Here we induced disease and subsequent mortality in exposure experiments using tissue extracts, coelomic fluid and effluent water from wasting sunflower sea stars, with no mortality in controls. Deep sequencing of diseased sea star coelomic fluid samples from experiments and field outbreaks revealed a dominant proportion of reads assigned to the bacterium Vibrio pectenicida . Fulfilling Koch’s postulates, V. pectenicida strain FHCF-3, cultured from the coelomic fluid of a diseased sunflower sea star, caused disease and mortality in exposed sunflower sea stars, demonstrating that it is a causative agent of SSWD. This discovery will enable recovery efforts for sea stars and the ecosystems affected by their decline by facilitating culture-based experimental research and broad-scale screening for pathogen presence and abundance in the laboratory and field.

Nature Ecology & Evolution

Temperature impacts on dengue incidence are nonlinear and mediated by climatic and socioeconomic factors: A meta-analysis

Temperature can influence mosquito-borne diseases like dengue. These effects are expected to vary geographically and over time in both magnitude and direction and may interact with other environmental variables, making it difficult to anticipate changes in response to climate change. Here, we investigate global variation in temperature–dengue relationship by analyzing published correlations between temperature and dengue and matching them with remotely sensed climatic and socioeconomic data. We found that the correlation between temperature and dengue was most positive at intermediate (near 24°C) temperatures, as predicted from an independent mechanistic model. Positive temperature–dengue associations were strongest when temperature variation and population density were high and decreased with infection burden and rainfall mean and variation, suggesting alternative limiting factors on transmission. Our results show that while climate effects on diseases are context-dependent they are also predictable from the thermal biology of transmission and its environmental and social mediators.

PLOS Climate