Published April 24, 2020
| Version 2
Dataset
Open
Predicting the presence and titer of rabies virus neutralizing antibodies from low-volume serum samples in low-containment facilities
Description
Python Script. Cell count outputs were converted into a standardized spreadsheet using a Python version 3.7.2 script
Codes for binomial and lognormal model
code to obtain the images from the model results
data to run the models, data result from the models
Files
bat_data.csv
Files
(16.1 MB)
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md5:71e1754e55c93954c3713c937fe18043
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md5:44ac915b19080d181aa885697c22dfb6
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md5:ef8dace27fcc76bdc51cdfb858dc84d5
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md5:fa7c39348390d8cbb2f90c87085247dd
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md5:f371c549f1a9258b697b14144112cb05
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md5:8c043fa1999e2badd113ea4fc255eb5a
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md5:b8447e6f7f339a477f37d8055b9c2713
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md5:39ba0c5cc6c6910697e035773180bfc0
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md5:00224a40eddfb0b9264cc042132bf8ec
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md5:0231202b667b70f55a99874d000cb76f
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md5:6429070cb724658909768c3b28fb51a3
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Additional details
References
- Meza DK, Broos A, Becker DJ, et al. Predicting the presence and titre of rabies virus-neutralizing antibodies from low-volume serum samples in low- containment facilities. Transbound. Emerg. Dis. 2020;00:1–13