tfojo1/jheem_analyses
Jun 2025 – Apr 2026
5 Months active
Languages Used
RBashShell
Technical Skills
CalibrationData AnalysisR ProgrammingSimulationStatistical ModelingR programming
pkasaie
PROFILE
Pkasaie
Over five months, contributed to the tfojo1/jheem_analyses repository by building and refining calibration frameworks for public health simulation, focusing on multi-city and disease-specific modeling. Leveraged R and Bash to extend calibration workflows, enhance data visualization, and implement robust statistical modeling techniques. Developed multi-source variance estimation, improved MCMC diagnostics, and introduced tools for geographic analysis and parameter tuning, supporting more accurate and reproducible simulations. Addressed bugs and stabilized large-scale runs, enabling reliable scenario analysis across locations. The work emphasized maintainability, traceability, and reproducibility, delivering production-ready enhancements that support actionable insights for public health decision-making and surveillance.
Overall Statistics
Feature vs Bugs
91%Features
Repository Contributions
38Total
Bugs
1
Commits
38
Features
10
Lines of code
2,979
Activity Months5
Your Network
36 peopleShared Repositories
22
Andrew ZalesakMember
A-ZalesakMember
azalesakMember
Lauren ZallaMember
Lucia CilloniMember
Melissa SchnureMember
mschnureMember
nsizemo1Member
nsizemo1Member
Work History
April 2026
20 Commits • 4 Features
Apr 1, 2026April 2026 monthly summary for tfojo1/jheem_analyses focused on expanding calibration capabilities, strengthening visualization and export flows, and refining disease modeling parameters to deliver more accurate, location-aware insights for public health decisions. The work delivered broad, production-ready enhancements across calibration, plotting, and regional analysis, along with concrete fixes to improve robustness and reproducibility. Key features delivered: - Comprehensive Calibration Framework Expansion and Multi-Location Support: Extended calibration to support new simulation stages, Phoenix dataset, and multi-location calibration with improved progress tracking and data retrieval. Enabled running stage0-2 across cities and streamlined data handling for cross-location comparisons (commit traces include progress-related refinements and table-driven updates). - Calibration Visualization, Plotting, and Data Export Enhancements: Upgraded plotting to support comparison plots between calibrations, enhanced data handling and export capabilities, and added capabilities to save simulation sets and compare calibration datasets. - Public Health Geographic Analysis Tools: New tooling to identify MSAs with significant syphilis diagnoses and support regional public health surveillance. - Disease Modeling Parameter Enhancements and Accuracy Improvements: Introduced misclassification error as a calibration parameter; added doxycycline coverage and age-target correlations; fixed likelihood denom issues and other edge-case robustness improvements. Included workflow refinements to ensure stability when switching correlation settings. Major bugs fixed: - Fixed errors in rr.prp.symptomatic.primary.female handling and corrected small denominator issues in likelihood calculations. - Stabilized calibration stage progression (e.g., avoiding unintended repeats when correlation.by.strata is adjusted for fertility) and ensured consistent stage execution across locations. Overall impact and accomplishments: - Broadened calibration applicability to multiple locations with improved data retrieval and visibility, enabling faster, more reliable decision support. - Improved calibration accuracy and reliability through parameter refinements and robust plotting/export workflows. - Enhanced public health insight generation via new regional analysis tooling, supporting surveillance and targeted interventions. Technologies/skills demonstrated: - Python-based calibration framework development, data modeling and parameter tuning - Data visualization and plotting for cross-calibration comparisons - Data export and reproducibility enhancements - Version-control-driven workflow improvements and multi-location experimentation
20 Commits • 4 Features
Apr 1, 2026April 2026 monthly summary for tfojo1/jheem_analyses focused on expanding calibration capabilities, strengthening visualization and export flows, and refining disease modeling parameters to deliver more accurate, location-aware insights for public health decisions. The work delivered broad, production-ready enhancements across calibration, plotting, and regional analysis, along with concrete fixes to improve robustness and reproducibility. Key features delivered: - Comprehensive Calibration Framework Expansion and Multi-Location Support: Extended calibration to support new simulation stages, Phoenix dataset, and multi-location calibration with improved progress tracking and data retrieval. Enabled running stage0-2 across cities and streamlined data handling for cross-location comparisons (commit traces include progress-related refinements and table-driven updates). - Calibration Visualization, Plotting, and Data Export Enhancements: Upgraded plotting to support comparison plots between calibrations, enhanced data handling and export capabilities, and added capabilities to save simulation sets and compare calibration datasets. - Public Health Geographic Analysis Tools: New tooling to identify MSAs with significant syphilis diagnoses and support regional public health surveillance. - Disease Modeling Parameter Enhancements and Accuracy Improvements: Introduced misclassification error as a calibration parameter; added doxycycline coverage and age-target correlations; fixed likelihood denom issues and other edge-case robustness improvements. Included workflow refinements to ensure stability when switching correlation settings. Major bugs fixed: - Fixed errors in rr.prp.symptomatic.primary.female handling and corrected small denominator issues in likelihood calculations. - Stabilized calibration stage progression (e.g., avoiding unintended repeats when correlation.by.strata is adjusted for fertility) and ensured consistent stage execution across locations. Overall impact and accomplishments: - Broadened calibration applicability to multiple locations with improved data retrieval and visibility, enabling faster, more reliable decision support. - Improved calibration accuracy and reliability through parameter refinements and robust plotting/export workflows. - Enhanced public health insight generation via new regional analysis tooling, supporting surveillance and targeted interventions. Technologies/skills demonstrated: - Python-based calibration framework development, data modeling and parameter tuning - Data visualization and plotting for cross-calibration comparisons - Data export and reproducibility enhancements - Version-control-driven workflow improvements and multi-location experimentation
April 2026
March 2026
8 Commits • 2 Features
Mar 1, 2026March 2026 monthly summary for tfojo1/jheem_analyses: Delivered major calibration enhancements for SHIELD and CT models with cross-city support and scalable simulations, plus robust debugging and visualization utilities. This enabled faster, policy-ready scenario analysis across multiple cities and more accurate population-health insights.
March 2026
8 Commits • 2 Features
Mar 1, 2026March 2026 monthly summary for tfojo1/jheem_analyses: Delivered major calibration enhancements for SHIELD and CT models with cross-city support and scalable simulations, plus robust debugging and visualization utilities. This enabled faster, policy-ready scenario analysis across multiple cities and more accurate population-health insights.
February 2026
3 Commits • 2 Features
Feb 1, 2026February 2026 monthly summary for tfojo1/jheem_analyses: Delivered enhancements to multi-city calibration with richer outputs, and refined Atlanta model parameters to improve transmission predictions. Significant debugging and validation work underpinned stable improvements, with expanded simulation sets and outputs for cross-city comparisons, enabling more actionable policy insights.
3 Commits • 2 Features
Feb 1, 2026February 2026 monthly summary for tfojo1/jheem_analyses: Delivered enhancements to multi-city calibration with richer outputs, and refined Atlanta model parameters to improve transmission predictions. Significant debugging and validation work underpinned stable improvements, with expanded simulation sets and outputs for cross-city comparisons, enabling more actionable policy insights.
February 2026
December 2025
2 Commits • 1 Features
Dec 1, 2025December 2025: Focused on reliability and robustness of variance estimation in tfojo1/jheem_analyses. Delivered a multi-source input pathway for estimating diagnosis error variance, significantly improving robustness and accuracy of variance calculations. Fixed a MCMC index subscript out-of-bounds error and added a configurable verbosity toggle for error term output, enhancing usability and debugging. Performed targeted code cleanup of the diagnosis error variance path to improve maintainability. Maintained clear traceability with commit references for completed work.
December 2025
2 Commits • 1 Features
Dec 1, 2025December 2025: Focused on reliability and robustness of variance estimation in tfojo1/jheem_analyses. Delivered a multi-source input pathway for estimating diagnosis error variance, significantly improving robustness and accuracy of variance calculations. Fixed a MCMC index subscript out-of-bounds error and added a configurable verbosity toggle for error term output, enhancing usability and debugging. Performed targeted code cleanup of the diagnosis error variance path to improve maintainability. Maintained clear traceability with commit references for completed work.
June 2025
5 Commits • 1 Features
Jun 1, 2025June 2025: Delivered substantial SHIELD calibration enhancements for demographic and syphilis diagnosis, consolidating and extending the calibration workflow, improving visualization, registration, and MCMC diagnostics. Achieved a stable, reproducible calibration pipeline with clear convergence signals, enabling more accurate and timely clinical decision support.
5 Commits • 1 Features
Jun 1, 2025June 2025: Delivered substantial SHIELD calibration enhancements for demographic and syphilis diagnosis, consolidating and extending the calibration workflow, improving visualization, registration, and MCMC diagnostics. Achieved a stable, reproducible calibration pipeline with clear convergence signals, enabling more accurate and timely clinical decision support.
June 2025
Activity
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Quality Metrics
Correctness81.6%
Maintainability81.0%
Architecture81.0%
Performance76.4%
AI Usage21.0%
Skills & Technologies
Programming Languages
BashRShell
Technical Skills
CalibrationData AnalysisR ProgrammingR programmingSimulationStatistical Modelingbash scriptingdata analysisdata visualizationmultiprocessingpublic healthpublic health simulationscriptingsimulationsimulation modeling
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