This DATSETNAMEreadme.txt file was generated on [2021-02-21] by [Adrianna Tompros] ------------------- GENERAL INFORMATION ------------------- 1. Title of Dataset: Frequency-dependent transmission of Batrachochytrium salamandrivorans in eastern newts 2. Author Information Principal Investigator Contact Information Name: Matthew J. Gray Institution: Center for Wildlife Health, University of Tennessee Institute of Agriculture, Knoxville, Tennessee, USA Address:University of Tennessee Department of Forestry, Wildlife and Fisheries
 2505 E. J. Chapman Drive Rm 427 Plant Biotech Building, Knoxville, TN 37996 Email:mgray11@utk.edu Principal Investigator Contact Information Name: Andy Fenton Institution: Institute of Integrative Biology, University of Liverpool, Liverpool, UK Address: University of Liverpool, Liverpool L69 3BX, United Kingdom Email: A.Fenton@liverpool.ac.uk Principal Investigator Contact Information Name: Mark Wilber Institution: Center for Wildlife Health, University of Tennessee Institute of Agriculture, Knoxville, Tennessee, USA Address:University of Tennessee Department of Forestry, Wildlife and Fisheries
 2505 E. J. Chapman Drive Rm 427 Plant Biotech Building, Knoxville, TN 37996 Email:mwilber@utk.edu Associate or Co-investigator Contact Information Name: Andrew D. Dean Institution: Institute of Integrative Biology, University of Liverpool, Liverpool, UK Address: University of Liverpool, Liverpool L69 3BX, United Kingdom Email: Andrew.Dean@liverpool.ac.uk Associate or Co-investigator Contact Information Name: E. Davis Carter Institution: Center for Wildlife Health, University of Tennessee Institute of Agriculture, Knoxville, Tennessee, USA Address: University of Tennessee Department of Forestry, Wildlife and Fisheries
 2505 E. J. Chapman Drive Rm 427 Plant Biotech Building, Knoxville, TN 37996 Email: ecarte27@utk.edu Associate or Co-investigator Contact Information Name: Adrianna Tompros Institution: Center for Wildlife Health, University of Tennessee Institute of Agriculture, Knoxville, Tennessee, USA Address: University of Tennessee Department of Forestry, Wildlife and Fisheries
 2505 E. J. Chapman Drive Rm 427 Plant Biotech Building, Knoxville, TN 37996 Email: atompros@vols.utk.edu 3. Date of data collection (single date, range, approximate date) 2019-10-28 to 2019-12-27 4. Geographic location of data collection (where was data collected?): University of Tennessee, Knoxville, TN 5. Information about funding sources that supported the collection of the data: Our research was supported by the U.S. National Science Foundation (NSF Division of Environmental Biology [DEB] Award 1814520), USDA National Institute of Food and Agriculture (Hatch Project 1012932) and U.S. Fish and Wildlife Service competitive state wildlife grant TN-U2-F19AP00047 (administered by the Tennessee Wildlife Resources Foundation). Dr. Andy Fenton and Dr. Andrew D. Dean were funded through a NSF DEB-UK Natural Environment Research Council Grant (NE/S013369/1) awarded to AF and Dr. Pieter Johnson, University of Colorado, Boulder. 6. Abstract/description of the dataset: Transmission is the fundamental process whereby pathogens infect their hosts and spread through populations, and can be characterized using mathematical functions. The functional form of transmission for emerging pathogens can determine pathogen impacts on host populations and can inform the efficacy of disease management strategies. By directly measuring transmission between infected and susceptible adult eastern newts (Notophthalmus viridescens) in aquatic mesocosms, we identified the most plausible transmission function for the emerging amphibian fungal pathogen Batrachochytrium salamandrivorans (Bsal). Although we considered a range of possible transmission functions, we found that Bsal transmission was best explained by pure frequency-dependence. We observed that >90% of susceptible newts became infected within 17 days post-exposure to an infected newt across a range of host densities and initial infection prevalence treatments. Under these conditions, we estimated R0 = 4.9 for Bsal in an eastern newt population. Our results suggest that Bsal has the capability of driving eastern newt populations to extinction, and that managing host density may not be an effective management strategy. Intervention strategies that prevent Bsal introduction or increase host resistance or tolerance to infection may be more effective. Our results add to the growing empirical evidence that 28 transmission of wildlife pathogens can saturate and be functionally frequency-dependent. ***Andy TEXT*** Optimization of proposed transmission functions for Bsal infection data in eastern newts. Optimization carried out over the initial stages of infection, before any fatalities had occurred. Probability distribution of number of susceptibles at time t calculated via numerical integration of the associated ordinary differential equations, and optimal parameter values selected through minimizing the log-likelihood of the data. AIC used to select the best fit, with likelihood profiles calculated for each parameter in the two best fitting transmission functions. ****** 7: Keywords for the dataset (provide 3 - 5): amphibian, Batrachochytrium, disease, fungus, model, density-dependent -------------------------- SHARING/ACCESS INFORMATION -------------------------- 1. Licenses/restrictions placed on the data: NA 2. Links to publications that cite or use the data: NA 3. Links to other publicly accessible locations of the data: NA 4. Links/relationships to ancillary data sets: NA 5. Was data derived from another source? No If yes, list source(s): 6. Recommended citation for the data: NA --------------------- DATA & FILE OVERVIEW --------------------- 1. File List A. Filename: CodeFile1_PreProcess.R Short description: Preprocess experimental data in DataFile1.csv. Convert to record numbers susceptible and infected at each time step and remove false positives/negatives. Save days 0, 2 and 5 in DataFile2_Days0to5.RData for optimisation. Save days 5 and 8 treatments with no deaths by day 8 in DataFile3_Day8_NoDeaths.RData for verification. B. Filename: CodeFile2_SusceptibleDistribution.R Short description: Define various proposed transmission functions. Calculate the associated distribution of susceptible individuals by numerical integration of the associated ordinary differential equations. C. Filename: CodeFile3_Optimisation.R Short description: Minimise the log-likelihood for a particular (user-selected) choice of transmission function. D. Filename: CodeFile4_FreqDependentProfile.R Short description: Calculate the likelihood profile for the single parameter appearing in the best fit transmission function, frequency-dependent transmission. E. Filename: CodeFile5_QuadraticSaturationProfile.R Short description: Calculate the likelihood profile for the three parameters appearing in the second-best fit transmission function, quadratic saturation transmission. F. Filename: DataFile1.csv Short description: Experimental data from infection of eastern newts with BSal at various initial densities and infection prevalences. G. Filename: DataFile2_Days0to5.RData Short description: Susceptible/infected data from days 0, 2 and 5 of the experiment. H. Filename: DataFile3_Day8_NoDeaths.RData Short description: Susceptible/infected data from days 5 and 8 of the experiment. I. Filename: CodeFile6_DensityInfPrevSurvival.R Short description: This R file contains code for analysis of File A. J. Filename: CodeFile7_BsalLoad.R Short description: This R file contains code for analysis of File C. K. Filename: DataFile4_DensityInfPrevSurvival.csv Short description: Includes survival data for all susceptible newts including density and infection prevalence treatments, mortality during or after experiment, and total days survived during experiment. L. Filename: DataFile5_BsalLoad.csv Short description: Contains mean log Bsal load data per mesocosm for all susceptible newts. This datafile includes density and infection prevalence treatments, average Bsal load per mesocosm (the overall average of the mean loads of each susceptible newt in the mesocosm), average log Bsal load per mesocosm (the overall average of the mean log loads of each susceptible newt in the mesocosm), and the number of initially infected newts per mesocosm. 2. Relationship between files: 1) A uses F to generate G and H, the data for optimization and verification. 2) C uses G and B to optimize each transmission function. 3) C uses H and B for verification of the results. 4) D uses G and B to calculate the likelihood profile for frequency-dependent transmission. 5) E uses G and B to calculate the likelihood profile for quadratic saturation transmission. 6) I uses K to perform survival analyses. 7) J uses L to perform Bsal load analyses. 3. Additional related data collected that was not included in the current data package: NA 4. Are there multiple versions of the dataset? No If yes, list versions: Name of file that was updated: i. Why was the file updated? ii. When was the file updated? Name of file that was updated: i. Why was the file updated? ii. When was the file updated? -------------------------- METHODOLOGICAL INFORMATION -------------------------- 1. Description of methods used for collection/generation of data: 290 adult eastern newts (Notophthalmus viridescens) were housed in 20 circular, 1-m^2 aquatic mesocosms (depth = 30cm, temperature = 14oC) with varying density and initial infection prevalence treatments to directly measure Bsal transmission and identify the most plausible transmission function. We crossed each host density with 1 – 3 initial infection prevalence treatments (12.5%, 25%, 50%) to evaluate how the force of infection was impacted by change in prevalence. This range of initial infection prevalence treatments was typical for amphibian studies modeling pathogen transmission (Greer et al., 2008; Rachowicz & Briggs, 2007). This design sought to maximize the overall range of density and prevalence combinations for subsequent model fitting, rather than to maximize replication at a more limited number of combinations. All newts were uniquely marked via toe clipping and randomly assigned to one of the mesocosms. Newts used to initiate the epidemic in each tank were randomly selected and exposed to a high dose of Bsal zoospores (2.56 x 10^6 zoospores/mL) for 24 hours. After the 24-hour exposure, infected newts were placed into tanks with susceptible newts corresponding to their randomly assigned infection prevalence and density treatment. Every three days for up to 60 days, newts were removed from tanks using a clean net, identified, and swabbed using a standardized protocol to detect Bsal infection status and infection intensity (i.e. load) on the skin (Blooi et al., 2013; Boyle, Boyle, Olsen, Morgan, & Hyatt, 2004). All swabs were placed in a microcentrifuge tube labeled with the individual’s identification number and swab date, and stored at -80oC until processed. To detect Bsal and estimate loads, genomic DNA was extracted from each swab using the QIAamp 96 DNA QIAcube HT kit (Qiagen, Hilden, Germany) and qPCR performed similar to Blooi et al. (2013) using the Applied Biosystems Quantstudio 6 Flex qPCR instrument (Thermo Fisher Scientific Inc). All samples were run in duplicates and declared positive if both replicates reached cycle threshold prior to 50 amplification cycles (Carter et al., 2020). We used qPCR to estimate pathogen load per treatment by averaging loads among individuals per experimental unit (i.e., mesocosm). We also monitored survival twice daily for 62 days and removed infected individuals that died in <12 hours. During these checks, dead individuals would be collected and identified and their date of mortality would be recorded. References Blooi, M., Pasmans, F., Longcore, J. E., Spitzen-Van Der Sluijs, A., Vercammen, F., & Martel, A. (2013). Duplex real-time PCR for rapid simultaneous detection of Batrachochytrium dendrobatidis and Batrachochytrium salamandrivorans in amphibian samples. Journal of Clinical Microbiology, 51(12), 4173-4177. doi: https://doi.org/10.1128/JCM.02313-13 Boyle, D. G., Boyle, D., Olsen, V., Morgan, J., & Hyatt, A. (2004). Rapid quantitative detection of chytridiomycosis (Batrachochytrium dendrobatidis) in amphibian samples using real-time Taqman PCR assay. Diseases of aquatic organisms, 60(2), 141-148. Carter, E. D., Miller, D. L., Peterson, A. C., Sutton, W. B., Cusaac, J. P. W., Spatz, J. A., Rollins-Smith, L., Reinert, L., Bohanon, M., Williams, L. A., Upchurch, A., & Gray, M. J. (2020). Conservation risk of Batrachochytrium salamandrivorans to endemic lungless salamanders. Conservation Letters, 13(1), e12675. doi:https://doi.org/10.1111/conl.12675 Greer, A. L., Briggs, C. J., & Collins, J. P. (2008). Testing a key assumption of host‐pathogen theory: density and disease transmission. Oikos, 117(11), 1667-1673. doi: https://doi.org/10.1111/j.1600-0706.2008.16783.x Rachowicz, L. J., & Briggs, C. J. (2007). Quantifying the disease transmission function: effects of density on Batrachochytrium dendrobatidis transmission in the mountain yellow‐legged frog Rana muscosa. Journal of Animal Ecology, 76(4), 711-721. doi:https://doi.org/10.1111/j.1365-2656.2007.01256.x Methods for processing the data: Files A-H: Experimental data was used to generate a log-likelihood for various proposed transmission functions. The R function optim() was used to minimize this to determine the maximum likelihood estimator (MLE) parameter set for each transmission function. Each (MLE) was ranked using AIC. Files I & K: Experimental data was used to determine each when each susceptible individual died during the experiment or if they survived the entire experiment duration. Files J & L: Experimental data was used to determine each susceptible individual’s Bsal log load during each swab. These log loads were averaged for each individual and then averaged per mesocosm. 3. Instrument- or software-specific information needed to interpret the data: No Files A-H: R with packages deSolve, tidyverse (and ggplot2, latex2exp to generate plots) Files I-L: R with packages survival, survminer (and ggplot2, ggpubr, gridExtra to generate plots) 4. Standards and calibration information, if appropriate: NA 5. Environmental/experimental conditions: All newts were housed in a biosecure animal research facility at the University of Tennessee. All newts were housed 1-m^2 circular aquatic mesocosms (depth = 30cm, temperature = 14oC, which were connected to a flow-through, dechlorinating water system and heat-chilling unit. Water flow into tanks was approximately 20 L per hour, hence water in tanks turned over approximately 2 times per day. Every three days, newts were fed frozen bloodworms and tanks were scooped with nets to remove waste and other debris. 6. Describe any quality-assurance procedures performed on the data: Files C & D: Negative and positive PCR controls were included for qPCR to ensure quality of sequencing data and control for possible contamination. All samples were run in duplicate. 7. People involved with sample collection, processing, analysis and/or submission: Matthew J. Gray, Andy Fenton, Andy Dean, Mark Wilber, Davis Carter, Adrianna Tompros, Kurt Ash, Markese Bohanon, Wesley Siniard, Caleb Keoho, Megan Wilson, Carlin Frost, Tan Watcharaanantapong -------------------------------------------- DATA-SPECIFIC INFORMATION FOR: DataFile1.csv -------------------------------------------- 1. Number of variables: 13 2. Number of cases/rows: 2911 3. Variable List A. Name: Sample Description: Identifier code for each individual B. Name: Treatment Description: Starting condition for individuals: 2.5x10^6 (infected) or Susceptible (uninfected) C. Name: Tank Description: Mesocosm codes 1-20 D. Name: Infection Description: Starting infection prevalence (0.5, 0.25 or 0.125) E. Name: Day Description: Number of days since start of experiment (integer between 2 and 62) or Necropsy, indicating the individual has died and the result is a necropsy F. Name: CT 1 Description: G. Name: CT 2 Description: H. Name: Ct Mean Description: I. Name: Quantity Description: J. Name: Pos Description: Tested positive (1) or negative (0) for infection K. Name: Neg Description: Tested positive (0) or negative (1) for infection L. Name: DDE Description: Died during experiment (1) or survived (0) M. Name: DaysSurvival Description: Days survived by individual ------------------------------------------------------- DATA-SPECIFIC INFORMATION FOR: DataFile2_Days0to5.RData ------------------------------------------------------- 1. Number of variables: 4 2. Number of cases/rows: 60 3. Variable List A. Name: Tanks Description: Mesocosm codes 1-20 B. Name: Days Description: Number of days since start of experiment (0,2 or 5) C. Name: S Description: Number of susceptible (uninfected) individuals in tank D. Name: I Description: Number of infected individuals in tank ----------------------------------------- DATA-SPECIFIC INFORMATION FOR: DataFile3_Day8_NoDeaths.RData ----------------------------------------- 1. Number of variables: 4 2. Number of cases/rows: 20 3. Variable List A. Name: Tanks Description: Mesocosm codes 1-20 B. Name: Days Description: Number of days since start of experiment (5 or 8) C. Name: S Description: Number of susceptible (uninfected) individuals in tank D. Name: I Description: Number of infected individuals in tank DATA-SPECIFIC INFORMATION FOR: [DataFile4_DensityInfPrevSurvival.csv] ----------------------------------------- 1. Number of variables: 6 2. Number of cases/rows: 189 3. Variable List A. Name: Sample Description: Identification number for each newt (only susceptible individuals included). B. Name: Tank Description: The mesocosm the newt was housed in (1-20). C. Name: Infection Prev Description: Infection Prevalence treatment within the mesocosm (12.5%, 25%, or 50% initially infected newts). D. Name: Density Description: Density treatment within the mesocosm (2-32 newts per mesocosm). E. Name: DDE Description: “Died During Experiment”. This was coded as “1” for died during experiment and “0” for survived for entirety of experiment (humanely euthanized at end of experiment) F. Name: DaySurvival Description: Number of days an individual survived during the experiment. If the individual survived for the entirety of the experiment, it was included as “62” days (the remaining newts were euthanized on day 62 post-exposure to Bsal). ----------------------------------------- DATA-SPECIFIC INFORMATION FOR: [DataFile5_BsalLoad.csv] ----------------------------------------- 1. Number of variables: 6 2. Number of cases/rows: 20 3. Variable List A. Name: Tank Description: Mesocosm that newts were housed in (1-20). B. Name: InfectionPrev Description: Infection Prevalence treatment within the mesocosm (12.5%, 25%, or 50% initially infected newts). C. Name: Density Description: Density treatment within the mesocosm (2-32 newts per mesocosm). D. Name: Tank Avg Description: Average load of Bsal per mesocosm (overall mean of the average loads of each susceptible newt in the mesocosm) E. Name: Log_Tank_Avg Description: Log average load of Bsal per mesocosm (overall mean of the log average loads of each susceptible newt in the mesocosm) F. Name: N Description: Number of initially infected newts per mesocosm (initial infection prevalence treatment per specific density)