DTRA-CTR TRIP REPORT

Transcription

1 DIRECTIONS A CTR Trip Report is used to record the history of activities, overseas and domestic, of CTR projects and programs. These records are then used for reports to Congress, training of employees, and for the integration of knowledge and experience into more efficient processes. Each team must complete a trip report within 5 days of return from TDY. Exception: A&E Trip Reports to be submitted within 30 days of return. Distribute the trip report, by sending it via to the following address: {CTR Trip Reports}; {CTR Trip Reports Supplemental} as well as to the appropriate Program Manager. I. GENERAL Trip Title: GG-17/GG-18 GIS Training and Poster development Purpose of Trip (Check at least One): Project Discussions X Contract Negotiations Audit and Examination X Other Project Name: GG-17/GG-18 Project Officer Name: Program Manager: Executive Summary: Report Objectives This report provides an account of the GIS training/collaboration for GG-17 and GG-18: 1. To give a detailed summary of activities during the May 02, 2011 May 06, 2011 trip to Tbilisi, Georgia for GG-17 and GG-18 regarding scientific engagement, GIS data entry training, and data development. 2. To identify potential data sources GG-17 and GG-18 for future project development and training. 3. A brief description of the datasets completed during the course of the week and the dataset development that was initiated. 1

2 Summary of visit to Tbilisi, Georgia GG-17/GG-18 As part of a continuing effort to engage scientists on the GG-17 and GG-18 projects concerning GIS analyses and data development training, the team from Jason K. Blackburn s lab visited the Laboratory of Ministry of Agriculture (LMA) in Tbilisi, Georgia. This trip built upon the previous collaboration by introducing new GIS analytical techniques that will facilitate research and scientific cooperation. Specifically, this trip provided training to CBR participants on how to incorporate advanced data analysis and incidence disease mapping into their research. Since there is only one floating ArcGIS license at LMA and NCDC, only one person at a time can use the software, despite the fact that the GIS lab was built with seven work stations. In order to maneuver around the licensing issue we conducted a new GIS training in disease mapping and incidence/prevalence smoothing using the GeoDa freeware software package. This training format allowed participants to use multiple computers simultaneously during the training rather than having to take turns. Although new conceptual ideas and material were introduced during the course of the week the primary goal of the training was to facilitate the development of materials/figures for their posters, which are to be presented at the URISA GIS and Public Health conference in June. One of the objectives of all the GIS trainings is to have all GIS CBR participants trained in techniques that are presented in posters and manuscripts, thus a portion of the week was spent introducing new cartographic methods for disease mapping. This provides participants with the skills needed to create or reproduce any analysis that is used in publications and/or proceedings. The training format for the week consisted of alternating days at the Laboratory of the Ministry of Agriculture (LMA) and the National Centers for Disease Control (NCDC) to allow participants a day in between visits to work on material and compose questions. A suggested fix for the ArcGIS licensing issue is to purchase additional seats for the floating license that will allow multiple users to operate the software at the same time. This is crucial for future training and facilitating independent research. Attachments: Figure 1. CBR participants working with GIS at LMA. Figure 2. LMA GIS laboratory consisting of seven computers. Figure 3. Presentation of training material at NCDC. Figure 4. Preliminary mapping of human isolates, in green, and environment isolates, in yellow. Graduated circles represent the total number of isolates obtained at each location, human samples n=70 and environmental samples n=102. Figure 5. Map A displays the crude prevalence of brucellosis infections among all livestock obtained from the seroprevalence sampling study. Red dots on the map represent locations of positive sample n=552. Map B displays the smoothed prevalence using the Empirical Bayes Smoothing estimator in GeoDa, which corrects for population variance in the denominator data. 2

3 Figure 6. Kernel density estimation shown in the top two maps displays the density of positive cases, upper left, and the density of negative cases, upper right, per decimal degree squared. The odds of Brucella spp. was calculated as the ratio of the density of positives to negatives. Figure 7. Project participants at LMA mapping and analyzing data related to their brucellosis research. Figure 8. Spatial distribution of average incidence rates per 100,000 for human cutaneous anthrax are shown in map A for the time period and map B for the time period Smoothed incidence rates per 100,000 were calculated using a spatial EBS algorithm with a Rook contiguity matrix and are displayed in maps C and D. LISA values were calculated for each time period and are shown in maps E and F with red portraying High-High areas, blue Low-Low areas and light blue Low-High areas. Figure 9. Participants working GIS data analysis at NCDC. Figure 10. SaTScan analysis using a Bernoulli case/control model with seropositives and seronegative location data. The open circle in red represents the most likely cluster and its corresponding radius. Red stars and black circle represent secondary clusters while the yellow dots represent controls or seronegatives and green dots represent seronegatives. Figure 11. Geographic distribution of tularemia isolates taken from samples collected during the time period Different colored dots represent varying sources of the bacterium II. TRIP DISCUSSIONS Full meeting minutes from this trip are available upon request to the Project Officer and/or Program Manager. A. LOCATION-ITEM #1 LMA May 2, Discussion The meeting for the 2 nd of May was held at LMA. We began the day by discussing the format for the posters that will be presented at the URISA conference in June as well as the expectations for the week. It seemed as though most of the participants had a grasp of the basic elements of a poster i.e. the intro, methods, etc. I provided a template for the GG-17 brucellosis and the GG-18 anthrax posters and showed them examples of previous DTRA CBR GIS posters that have been presented at conferences. Ideally we would like the project participants/scientists to create their own figures using methods that we teach them although this isn t always possible due to time constraints. I set aside a part of the morning before the GeoDa training to answer questions regarding any methods that have been presented to them in order to address any issues they may have. There were a few questions regarding some the more advanced techniques, but for the most part they were 3

4 comfortable with a majority of the material thus far. Future trainings on the use of GIS and ecological models may help in answering a lot their questions. A good portion of the morning was spent presenting and discussing the Empirical Bayesian Smoothing (EBS) technique as well as the idea of incidence instability. While the notion of small populations numbers was somewhat of a difficult concept to understand at first, they caught on quickly after we worked through a few examples. We were able to complete the EBS portion of the training and we also presented generating a spatial weights matrix. The rest of the day was spent working on the computers using the GeoDa and ArcGIS software package. We were also able, with the help of the group participants, to put together an outline of the LMA GG-17 brucellosis and GG-18 anthrax posters. The group participants are showing a marked increase in their GIS proficiency and have taken the initiative to create many of their own maps and figures. The GIS facility at LMA is composed of six operational machines with one ArcGIS license, which at times proposes a challenge for researchers to complete tasks (Figure 2). While the facility is modern and well equipped the addition of internet access and more ArcGIS licenses would be prudent for long term maintenance of the lab. 3. Issues ArcGIS computer Software accessibility and licensing. 4. Participants Goginashvili,Ketevan Kerdzevadze, Lena Mamisashvili, Eliso Garuchava, Nato Tigilauri, Tamar A. LOCATION-ITEM #2 NCDC May 3, Discussion The meeting on the 3 rd of May was held at NCDC. We began the day similar to yesterday, just repeated for the NCDC participants, by discussing the format for the posters that will be presented at the URISA conference in June as well as the expectations for the week. The lab practical portion of the training seemed to go well although I think the participants would like more time to work with the software. Again, this is a limitation of the lab setup at NCDC, which only supports one ArcGIS license. Although time was limited the participants took the training seriously and were able to learn the material quickly (Figure 3). In order to allow for more access to the software during the training we allowed the participants to work on our laptop. The level of skill in using the software is also increasing significantly at NCDC. Many of the CBR participants are taking the initiative to work on data analysis on their own. We were able to complete some of the preliminary mapping for the GG- 4

5 17 human anthrax poster showing the number of laboratory isolates collected from all samples (Figure 4 ). 3. Issues ArcGIS computer Software accessibility and licensing. 4. Participants Chubinidze, Svetlana Mamuchishvili,Nana Manavelyan, Julieta Navdarashvili,Archil Sanodze, Lia Dr. Niko A. LOCATION-ITEM #3 LMA May 4, Discussion Training for the day at LMA was focused on completing figures for the posters and reviewing the material from the training on Monday. As part of the training the scientists worked on completing a prevalence map of the brucellosis infections in livestock as well as a smoothed prevalence map adjusting for population variance (Figure 5). In addition to the maps of prevalence we were able to also begin mapping all of the brucellosis negatives that were collected during their seroprevalence sampling effort. These negatives were entered into the GIS database by the CBR participants and converted into a format that could mapped. The mapped positive and negative collection sites where then converted into a Kernel density output using ArcGIS and a surface representing the odds of Brucella spp. was created (Figure 6). All of the group members were engaged in the training and each one took an interest in being able to perform the designated tasks (Figure 7). While the day was mostly comprised of data analysis it was a fairly productive, which speaks volumes about the GIS ability of the LMA group since it is not always easy to enter data and analyze it in the same day. 3. Issues ArcGIS computer Software accessibility and licensing. 4. Participants Goginashvili,Ketevan Kerdzevadze, Lena Mamisashvili, Eliso Garuchava, Nato Tigilauri, Tamar 5

6 A. LOCATION-ITEM #4 NCDC May 5, Discussion Training for the day at NCDC was focused on completing figures for the posters and reviewing material from the training on Tuesday. We were worked on mapping and analyzing the incidence of human cutaneous anthrax during the time period as well as mapping the location of tularemia isolates. In addition to the poster items we also helped some of the participants with their data management. As the scope of the data analysis increases on these projects the participants have become better at data management although future trainings or a brief review may be beneficial. During the course of the day we were able to produce maps of average anthrax incidence in addition to identifying clusters or hotspots of incidence (Figure 8). The group also began putting together the poster for the GG-18 tularemia mapping poster. Overall everyone at NCDC seemed engaged was interested in increasing their skill set as well as producing quality work (Figure 9). Their ability and willingness to perform these tasks on their own while maintaining quality is an important aspect of being able to sustain their GIS skills for years to come. 3. Issues ArcGIS computer Software accessibility and licensing. 4. Participants Chubinidze, Svetlana Mamuchishvili,Nana Manavelyan, Julieta Navdarashvili,Archil Sanodze, Lia Dr. Niko A. LOCATION-ITEM #5 LMA & NCDC May 6, Discussion May 6 th marked the final day of training with half the day spent at LMA and the other half of the day spent at NCDC. The group at LMA continued their work on analyzing and mapping the brucellosis seroprevalence data. The brucellosis data were formatted for the SaTScan software package and a cluster analysis was run on the positive and negative samples using a Bernoulli case/control model (Figure 10). The participants at LMA performed well throughout the week given the time constraints and work load. The second portion of the day was spent at NCDC continuing the work on mapping and analysis. We were able to construct a map of tularemia isolates indicating the geographic distribution of 6

7 the sample sources (Figure 11). While there is still some work that needs to be done on the posters they are coming along nicely. Overall each group, LMA and NCDC, did well in the training and practical portion of the lab exercises. The group decided that we would tentatively set a date for another training/collaboration June 20 -June 24, Although a lot of work was completed this week the posters still need to be edited and refined before being submitted to DTRA. 3. Issues ArcGIS computer Software accessibility and licensing. 4. Participants Chubinidze, Svetlana Garuchava, Nato Goginashvili,Ketevan Kerdzevadze, Lena Mamisashvili, Eliso Mamuchishvili,Nana Manavelyan, Julieta Navdarashvili,Archil Sanodze, Lia Garuchava, Natalia Tigilauri, Tamar Dr. Niko NCDC Attachments: 7

8 Figure 1. CBR participants working with GIS at LMA. Figure 2. LMA GIS laboratory consisting of seven computers. 8

9 Figure 3. Presentation of training material at NCDC. Figure 4. Preliminary mapping of human isolates, in green, and environment isolates, in yellow. Graduated circles represent the total number of isolates obtained at each location, human samples n=70 and environmental samples n=102. 9

10 Figure 5. Map A displays the crude prevalence of brucellosis infections among all livestock obtained from the seroprevalence sampling study. Red dots on the map represent locations of positive sample n=552. Map B displays the smoothed prevalence using the Empirical Bayes Smoothing estimator in GeoDa, which corrects for population variance in the denominator data. 10

11 Figure 6. Kernel density estimation shown in the top two maps displays the density of positive cases, upper left, and the density of negative cases, upper right, per decimal degree squared. The odds of Brucella spp. was calculated as the ratio of the density of positives to negatives. Figure 7. Project participants at LMA mapping and analyzing data related to their brucellosis research. 11

12 Figure 8. Spatial distribution of average incidence rates per 100,000 for human cutaneous anthrax are shown in map A for the time period and map B for the time period Smoothed incidence rates per 100,000 were calculated using a spatial EBS algorithm with a Rook contiguity matrix and are displayed in maps C and D. LISA values were calculated for each time period and are shown in maps E and F with red portraying High-High areas, blue Low-Low areas and light blue Low-High areas. 12

13 Figure 9. Participants working GIS data analysis at NCDC Figure 10. SaTScan analysis using a Bernoulli case/control model with seropositives and seronegative location data. The open circle in red represents the most likely cluster and its corresponding radius. Red stars and black circle represent secondary clusters while the yellow dots represent controls or seronegatives and green dots represent seronegatives. 13

14 Figure 11. Geographic distribution of tularemia isolates taken from samples collected during the time period Different colored dots represent varying sources of the bacterium. END OF TRIP REPORT 14