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Aniruddha Belsare @anyadoc
, 6 tweets, 4 min read Read on Twitter
Unrealistic assumptions (baseline scenario: random disease distribution, random sampling) overestimate the detection probability (~ confidence in detecting #CWD). Agent-based framework for wildlife disease surveillance Belsare et. al ow.ly/6U7M30mQFTc #bioRxiv #gganimate
The model was simulated for Franklin County Missouri deer population. Alternate scenario simulates clustering of cases and non-random sampling. Very low prevalence thresholds reflect recent CWD introduction. User-friendly-sliders to set age-sex class specific harvest and testing.
Can be used to calculate region-specific sample sizes for efficient and sustainable CWD surveillance. Also facilitates inferring negative surveillance outcomes. #AdaptiveManagementApproach
This ABM framework can be readily adapted to other regions as well as other host-pathogen systems (e.g. bTB-deer, brucellosis-elk). Open access models, certified & peer-reviewed ow.ly/xlVM30mQGbn & ow.ly/PXOQ30mQGdE #OpenABM Enquires welcome!@coatiwhisperer
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The University of Puerto Rico’s administration is blocking @DialogoUPR’s journalists from having access to the outlet’s webpage and social media. It also fired director @Viktor_Rodz.

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Dozens of former @DialogoUPR journalists, editors, photographers and other staff — myself included — have signed this letter in solidarity with the newspaper as the @UPR_Oficial administration keeps trying to dismantle this beloved institution. #DiálogoAbierto
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Twitter Thread - #NewStartforLibya

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Chapter 3: Network sampling

- Effects of sampling on network analysis
- Different kinds of network sampling
- How to account for sampling mathematically
- Consistency under subsampling (general definition)
Illustration in non-networks setting.

1- simple random sampling
2- size-biased sampling

Easy observation: population model same in both cases, but sampling distribution different because of different sampling mechanism.

Situation much more complicated for networks.
A model defined for the population network should induce a model for observed network, but this induced model depends on the observation/sampling mechanism.

Leaving sampling/observation mechanism unspecified (as in most treatments) leaves sampling distribution ambiguous.
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207. UCHE DIKE was an odd ball with a mild distasteful sense of fashion when he first gained admission into Nnamdi Azikiwe university in Anambra State, Nigeria.

Uche was one of those students in school who occasionally wore bogus long sleeved shirts...
208... and carton-coloured trousers that looked like something that came out of a thrift shop in the
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209. Uche was an awkward young man which made him an easy target for bullies.

Sometimes he felt there was a mental sticker on his head that screamed
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Uche was the real definition of "Fashion makes you stand out." His mentality...
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