Peter Hudson
WILLAMAN PROFESSOR of Biology, Director of Huck Institutes of Life Sciences | Pennsylvania State University
University Park, PA, UNITED STATES
Peter Hudson is an expert in wildlife diseases.
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Industry Expertise (2)
Research
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Areas of Expertise (4)
Parasite Interactions
Epidemiology and Population Dynamics
Wildlife Diseases
Heterogeneities
Biography
Peter Hudson's work focuses on the ecology of wildlife diseases, including zoonoses. His group uses a mixture of fieldwork, laboratory studies, and mathematical modeling to explore disease dynamics in three main study areas: Epidemiology and Population Dynamics, Heterogeneities, and Parasite Interactions.
Education (1)
University of Oxford: Ph.D.
Links (2)
Articles (5)
Seasonal variation of tsetse fly species abundance and prevalence of trypanosomes in the Maasai Steppe, Tanzania
Journal of Vector Ecology
Happiness J Nnko, Anibariki Ngonyoka, Linda Salekwa, Anna B Estes, Peter J Hudson, Paul S Gwakisa, Isabella M Cattadori
2017 Tsetse flies, the vectors of trypanosomiasis, represent a threat to public health and economy in sub-Saharan Africa. Despite these concerns, information on temporal and spatial dynamics of tsetse and trypanosomes remain limited and may be a reason that control strategies are less effective. The current study assessed the temporal variation of the relative abundance of tsetse fly species and trypanosome prevalence in relation to climate in the Maasai Steppe of Tanzania in 2014–2015. Tsetse flies were captured using odor-baited Epsilon traps deployed in ten sites selected through random subsampling of the major vegetation types in the area. Fly species were identified morphologically and trypanosome species classified using PCR. The climate dataset was acquired from the African Flood and Drought Monitor repository. Three species of tsetse flies were identified: G. swynnertoni (70.8%), G. m. morsitans (23.4%), and G.pallidipes (5.8%). All species showed monthly changes in abundance with most of the flies collected in July.
Variation of tsetse fly abundance in relation to habitat and host presence in the Maasai Steppe, Tanzania
Journal of Vector Ecology
Anibariki Ngonyoka, Paul S Gwakisa, Anna B Estes, Happiness J Nnko, Peter J Hudson, Isabella M Cattadori
2017 Human activities modify ecosystem structure and function and can also alter the vital rates of vectors and thus the risk of infection with vector-borne diseases. In the Maasai Steppe ecosystem of northern Tanzania, local communities depend on livestock and suitable pasture that is shared with wildlife, which can increase tsetse abundance and the risk of trypanosomiasis. We monitored the monthly tsetse fly abundance adjacent to Tarangire National Park in 2014–2015 using geo-referenced, baited epsilon traps. We examined the effect of habitat types and vegetation greenness (NDVI) on the relative abundance of tsetse fly species.
Pathways to zoonotic spillover
Nature Reviews Microbiology
Raina K Plowright, Colin R Parrish, Hamish McCallum, Peter J Hudson, Albert I Ko, Andrea L Graham, James O Lloyd-Smith
2017 Zoonotic spillover, which is the transmission of a pathogen from a vertebrate animal to a human, presents a global public health burden but is a poorly understood phenomenon. Zoonotic spillover requires several factors to align, including the ecological, epidemiological and behavioural determinants of pathogen exposure, and the within-human factors that affect susceptibility to infection. In this Opinion article, we propose a synthetic framework for animal-to-human transmission that integrates the relevant mechanisms. This framework reveals that all zoonotic pathogens must overcome a hierarchical series of barriers to cause spillover infections in humans. Understanding how these barriers are functionally and quantitatively linked, and how they interact in space and time, will substantially improve our ability to predict or prevent spillover events. This work provides a foundation for transdisciplinary investigation of spillover and synthetic theory on zoonotic transmission.
Age‐specific infectious period shapes dynamics of pneumonia in bighorn sheep
Ecology Letters
Raina K Plowright, Kezia R Manlove, Thomas E Besser, David J Páez, Kimberly R Andrews, Patrick E Matthews, Lisette P Waits, Peter J Hudson, E Frances Cassirer
2017 Superspreading, the phenomenon where a small proportion of individuals contribute disproportionately to new infections, has profound effects on disease dynamics. Superspreading can arise through variation in contacts, infectiousness or infectious periods. The latter has received little attention, yet it drives the dynamics of many diseases of critical public health, livestock health and conservation concern. Here, we present rare evidence of variation in infectious periods underlying a superspreading phenomenon in a free-ranging wildlife system. We detected persistent infections of Mycoplasma ovipneumoniae, the primary causative agent of pneumonia in bighorn sheep (Ovis canadensis), in a small number of older individuals that were homozygous at an immunologically relevant genetic locus. Interactions among age-structure, genetic composition and infectious periods may drive feedbacks in disease dynamics that determine the magnitude of population response to infection. Accordingly, variation in initial conditions may explain divergent population responses to infection that range from recovery to catastrophic decline and extirpation.
Patterns of tsetse abundance and trypanosome infection rates among habitats of surveyed villages in Maasai steppe of northern Tanzania
Infectious Diseases of Poverty
Anibariki Ngonyoka, Paul S Gwakisa, Anna B Estes, Linda P Salekwa, Happiness J Nnko, Peter J Hudson, Isabella M Cattadori
2017 We trapped tsetse flies in dry and wet seasons between October 2014 and May 2015 in selected habitats across four villages: Emboreet, Loiborsireet, Kimotorok and Oltukai adjacent to protected areas. Data collected include number and species of tsetse flies caught in baited traps, PCR identification of trypanosome species and extraction of monitored Normalized Difference Vegetation Index (NDVI) data from Moderate Resolution Imaging Spectrometer (MODIS).
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