tfojo1/jheem_analyses
Nov 2024 – Apr 2026
15 Months active
Languages Used
RShellSQLBashBatchExcelUnknown
Technical Skills
CalibrationData AnalysisData CalibrationData ManagementData ModelingData Visualization
Parastu
PROFILE
Parastu
Over 15 months, contributed to the tfojo1/jheem_analyses repository by developing and refining epidemiological modeling tools for public health simulation and policy analysis. Focused on SHIELD model enhancements, calibration workflows, and robust data pipelines, the work integrated R and Bash scripting to automate demographic initialization, disease progression, and calibration routines. Emphasized maintainability through code refactoring, documentation management, and version control discipline, while improving model fidelity with statistical modeling and data visualization. Addressed complex challenges in parameterization, likelihood computation, and scenario analysis, resulting in more accurate, reproducible simulations and streamlined workflows that support scalable, data-driven decision-making for population health interventions.
Overall Statistics
Feature vs Bugs
72%Features
Repository Contributions
246Total
Bugs
28
Commits
246
Features
72
Lines of code
40,559
Activity Months15
Your Network
37 peopleShared Repositories
22
Andrew ZalesakMember
A-ZalesakMember
azalesakMember
Lauren ZallaMember
Lucia CilloniMember
Melissa SchnureMember
mschnureMember
nsizemo1Member
nsizemo1Member
Work History
April 2026
1 Commits
Apr 1, 2026April 2026 — tfojo1/jheem_analyses: no substantive feature deliveries or bug fixes. A no-op placeholder commit was recorded to preserve the sprint timeline and establish a baseline for upcoming work. The month prioritized repository hygiene, traceability, and planning for May feature development, setting the stage for Q2. Key outcomes include a clean commit history, readiness for future work, and adherence to release processes. Technologies/skills demonstrated include Git version control discipline, timeline alignment, and plan-driven development.
1 Commits
Apr 1, 2026April 2026 — tfojo1/jheem_analyses: no substantive feature deliveries or bug fixes. A no-op placeholder commit was recorded to preserve the sprint timeline and establish a baseline for upcoming work. The month prioritized repository hygiene, traceability, and planning for May feature development, setting the stage for Q2. Key outcomes include a clean commit history, readiness for future work, and adherence to release processes. Technologies/skills demonstrated include Git version control discipline, timeline alignment, and plan-driven development.
April 2026
March 2026
5 Commits • 2 Features
Mar 1, 2026March 2026 performance summary for tfojo1/jheem_analyses: Delivered two core feature enhancements and accompanying reliability work to the SHIELD-based analyses pipeline, with a focus on improving diagnostic realism and the usability of calibration visuals for planning decisions. The work enhances modeling precision, reduces maintenance risk, and provides clearer, actionable visuals for stakeholders. Key outcomes: - Syphilis diagnosis modeling improvements: refined SHIELD diagnosis parameters and care-seeking behavior to increase accuracy and realism (commits: c9b2229c3ea12f8bce409d81f6986f3b0e39d3be; 3174b641608cbe26f91b687590d94ca38a73924b). - Likelihood handling and prop-testing stabilization: cleaned up likelihood calculations and completed prop testing revision to improve model reliability. - Calibration plotting enhancements: improved plot generation, color theming, and outcome filtering for stratification (commits: 9241d978246dcd26827fdae4406aea20538ba1d1; 76d447dc6d576f9a91263e4cc370f3c895a04142). - Calibration tooling maintenance: cleanup of obsolete scripts and calibration folder to reduce technical debt and maintainability risk (commit: 76d447dc6d576f9a91263e4cc370f3c895a04142). Technologies/skills demonstrated: Python-based model tuning, statistical calibration, data visualization and theming, code maintenance and refactoring, version-control traceability, and end-to-end workflow support for model validation and stakeholder-ready visuals.
March 2026
5 Commits • 2 Features
Mar 1, 2026March 2026 performance summary for tfojo1/jheem_analyses: Delivered two core feature enhancements and accompanying reliability work to the SHIELD-based analyses pipeline, with a focus on improving diagnostic realism and the usability of calibration visuals for planning decisions. The work enhances modeling precision, reduces maintenance risk, and provides clearer, actionable visuals for stakeholders. Key outcomes: - Syphilis diagnosis modeling improvements: refined SHIELD diagnosis parameters and care-seeking behavior to increase accuracy and realism (commits: c9b2229c3ea12f8bce409d81f6986f3b0e39d3be; 3174b641608cbe26f91b687590d94ca38a73924b). - Likelihood handling and prop-testing stabilization: cleaned up likelihood calculations and completed prop testing revision to improve model reliability. - Calibration plotting enhancements: improved plot generation, color theming, and outcome filtering for stratification (commits: 9241d978246dcd26827fdae4406aea20538ba1d1; 76d447dc6d576f9a91263e4cc370f3c895a04142). - Calibration tooling maintenance: cleanup of obsolete scripts and calibration folder to reduce technical debt and maintainability risk (commit: 76d447dc6d576f9a91263e4cc370f3c895a04142). Technologies/skills demonstrated: Python-based model tuning, statistical calibration, data visualization and theming, code maintenance and refactoring, version-control traceability, and end-to-end workflow support for model validation and stakeholder-ready visuals.
February 2026
12 Commits • 4 Features
Feb 1, 2026February 2026 monthly summary for tfojo1/jheem_analyses focusing on delivering robust STI/HIV testing model enhancements, PRP symptomatic testing framework improvements, and scalable calibration maintainability. Improvements emphasize business value, accuracy, and maintainability to support public health decision-making.
12 Commits • 4 Features
Feb 1, 2026February 2026 monthly summary for tfojo1/jheem_analyses focusing on delivering robust STI/HIV testing model enhancements, PRP symptomatic testing framework improvements, and scalable calibration maintainability. Improvements emphasize business value, accuracy, and maintainability to support public health decision-making.
February 2026
January 2026
8 Commits • 2 Features
Jan 1, 2026January 2026 monthly summary for tfojo1/jheem_analyses focused on delivering core SHIELD modeling enhancements and data usability improvements that directly enable more accurate intervention assessment and streamlined result sharing.
January 2026
8 Commits • 2 Features
Jan 1, 2026January 2026 monthly summary for tfojo1/jheem_analyses focused on delivering core SHIELD modeling enhancements and data usability improvements that directly enable more accurate intervention assessment and streamlined result sharing.
December 2025
8 Commits • 4 Features
Dec 1, 2025December 2025: Consolidated improvements across modeling, documentation, and data management in tfojo1/jheem_analyses. Key features delivered strengthened model calibration and transmission parameter handling, improved documentation accessibility, and introduced persistent data storage for Doxy. A calculation typo was fixed to ensure results are correct. These changes increase forecast accuracy, policy relevance, maintainability, and auditability, while showcasing the team's skills in modeling, data engineering, and documentation discipline.
8 Commits • 4 Features
Dec 1, 2025December 2025: Consolidated improvements across modeling, documentation, and data management in tfojo1/jheem_analyses. Key features delivered strengthened model calibration and transmission parameter handling, improved documentation accessibility, and introduced persistent data storage for Doxy. A calculation typo was fixed to ensure results are correct. These changes increase forecast accuracy, policy relevance, maintainability, and auditability, while showcasing the team's skills in modeling, data engineering, and documentation discipline.
December 2025
November 2025
7 Commits • 1 Features
Nov 1, 2025November 2025 monthly summary for tfojo1/jheem_analyses focusing on model parameterization and data processing enhancements for demographic stratifications, sexual mixing, and age-based sexual activity. Consolidated seven commits into a single user-impacting feature, improving model accuracy, calibration, and data handling, and enabling more reliable scenario analyses.
November 2025
7 Commits • 1 Features
Nov 1, 2025November 2025 monthly summary for tfojo1/jheem_analyses focusing on model parameterization and data processing enhancements for demographic stratifications, sexual mixing, and age-based sexual activity. Consolidated seven commits into a single user-impacting feature, improving model accuracy, calibration, and data handling, and enabling more reliable scenario analyses.
July 2025
41 Commits • 14 Features
Jul 1, 2025July 2025 monthly performance summary for tfojo1/jheem_analyses focused on delivering robust modeling fidelity, scalable calibration workflows, and data governance to support policy-relevant scenario analysis. The month delivered a set of feature-driven advancements, calibration improvements, and targeted bug fixes that enhance reliability, throughput, and traceability of results.
41 Commits • 14 Features
Jul 1, 2025July 2025 monthly performance summary for tfojo1/jheem_analyses focused on delivering robust modeling fidelity, scalable calibration workflows, and data governance to support policy-relevant scenario analysis. The month delivered a set of feature-driven advancements, calibration improvements, and targeted bug fixes that enhance reliability, throughput, and traceability of results.
July 2025
June 2025
19 Commits • 2 Features
Jun 1, 2025June 2025 (2025-06) monthly summary for tfojo1/jheem_analyses: Key SHIELD model enhancements completed to improve realism, calibration, and stability. Implemented start-year alignment and data-driven seeding for demographic initialization. Achieved a more robust forecasting workflow through enhanced diagnostics and bug fixes, enabling reliable scenario analysis and decision support. Focused on business value by improving accuracy of disease progression, testing timing, and population dynamics while reducing run-time errors.
June 2025
19 Commits • 2 Features
Jun 1, 2025June 2025 (2025-06) monthly summary for tfojo1/jheem_analyses: Key SHIELD model enhancements completed to improve realism, calibration, and stability. Implemented start-year alignment and data-driven seeding for demographic initialization. Achieved a more robust forecasting workflow through enhanced diagnostics and bug fixes, enabling reliable scenario analysis and decision support. Focused on business value by improving accuracy of disease progression, testing timing, and population dynamics while reducing run-time errors.
May 2025
55 Commits • 20 Features
May 1, 2025May 2025 monthly summary for tfojo1/jheem_analyses: Delivered measurable improvements in code quality, calibration reliability, and experimental capability across the core analysis engine. Highlights include a comprehensive code cleanup and refactor clarifying data extraction vs model fitting, calibration workflow enhancements (including reading package choices from JHEEM, updated transmission parameters, dynamic weights, and improved result review), and SHIELD/Rockfish integration (new SHIELD path and shield prep script) along with Rockfish readiness. Documentation scaffolding was added to improve onboarding and governance. Engine tests confirmed all likelihoods compute reliably, supporting robust model outputs. A new Starting Point option (1940 vs 1970) was added, with 1940 runs validated. A parameter block structure was introduced for clarity, and stability improvements were pursued via solver tolerance tuning and likelihood weighting adjustments. Fixed immigration start year bug and several parameter-related issues; removed unintended immigration changes. Collaboration with Andrew advanced, and broader test coverage was expanded with MCMC test scripts. Business value: more stable, transparent, and faster calibration cycles, better historical scenario coverage, and easier maintenance.
55 Commits • 20 Features
May 1, 2025May 2025 monthly summary for tfojo1/jheem_analyses: Delivered measurable improvements in code quality, calibration reliability, and experimental capability across the core analysis engine. Highlights include a comprehensive code cleanup and refactor clarifying data extraction vs model fitting, calibration workflow enhancements (including reading package choices from JHEEM, updated transmission parameters, dynamic weights, and improved result review), and SHIELD/Rockfish integration (new SHIELD path and shield prep script) along with Rockfish readiness. Documentation scaffolding was added to improve onboarding and governance. Engine tests confirmed all likelihoods compute reliably, supporting robust model outputs. A new Starting Point option (1940 vs 1970) was added, with 1940 runs validated. A parameter block structure was introduced for clarity, and stability improvements were pursued via solver tolerance tuning and likelihood weighting adjustments. Fixed immigration start year bug and several parameter-related issues; removed unintended immigration changes. Collaboration with Andrew advanced, and broader test coverage was expanded with MCMC test scripts. Business value: more stable, transparent, and faster calibration cycles, better historical scenario coverage, and easier maintenance.
May 2025
April 2025
35 Commits • 12 Features
Apr 1, 2025Month: 2025-04 — In April, delivered significant robustness in the likelihood modeling stack, improved performance, and expanded sampling capabilities. The work focused on stabilizing the core probability machinery, fixing calibration aging integration, and accelerating the end-to-end workflow, enabling larger-scale experiments with reduced setup time. Key business value includes more reliable models, faster turnarounds for experiments, and scalable MCMC pipelines for planning and decision support.
April 2025
35 Commits • 12 Features
Apr 1, 2025Month: 2025-04 — In April, delivered significant robustness in the likelihood modeling stack, improved performance, and expanded sampling capabilities. The work focused on stabilizing the core probability machinery, fixing calibration aging integration, and accelerating the end-to-end workflow, enabling larger-scale experiments with reduced setup time. Key business value includes more reliable models, faster turnarounds for experiments, and scalable MCMC pipelines for planning and decision support.
March 2025
19 Commits • 2 Features
Mar 1, 2025This month focused on advancing prenatal care modeling and stabilizing the likelihood engine, delivering robust priors, improved projection accuracy, and diagnostic uncertainty integration. Key activities included completing Prenatal Care Data Modeling, Priors, and Likelihoods enhancements with priors fitted from Wonder and fixes to age dimension and weighted-mean handling; addressing misclassification and diagnostics in Syphilis and prenatal estimates; refining the Likelihood Engine and HIV Testing Priors to improve initialization and validation; migrating to the jheem2 package to resolve desolve-related issues and stabilize engine runs; and introducing preliminary variance estimation at the MSA level for prenatal projections. The work has improved model fidelity, reduced runtime issues, and positioned the project for Todd's review and broader deployment.
19 Commits • 2 Features
Mar 1, 2025This month focused on advancing prenatal care modeling and stabilizing the likelihood engine, delivering robust priors, improved projection accuracy, and diagnostic uncertainty integration. Key activities included completing Prenatal Care Data Modeling, Priors, and Likelihoods enhancements with priors fitted from Wonder and fixes to age dimension and weighted-mean handling; addressing misclassification and diagnostics in Syphilis and prenatal estimates; refining the Likelihood Engine and HIV Testing Priors to improve initialization and validation; migrating to the jheem2 package to resolve desolve-related issues and stabilize engine runs; and introducing preliminary variance estimation at the MSA level for prenatal projections. The work has improved model fidelity, reduced runtime issues, and positioned the project for Todd's review and broader deployment.
March 2025
February 2025
10 Commits • 3 Features
Feb 1, 2025February 2025 monthly summary for tfojo1/jheem_analyses. Focused on solidifying SHIELD model integration, delivering consolidated parameterization and specification for SYPHILIS progression, congenital syphilis parameters, and contact tracing, while improving accuracy, maintainability, and visualization.
February 2025
10 Commits • 3 Features
Feb 1, 2025February 2025 monthly summary for tfojo1/jheem_analyses. Focused on solidifying SHIELD model integration, delivering consolidated parameterization and specification for SYPHILIS progression, congenital syphilis parameters, and contact tracing, while improving accuracy, maintainability, and visualization.
January 2025
8 Commits • 2 Features
Jan 1, 2025January 2025 monthly summary for tfojo1/jheem_analyses: Delivered substantial SHIELD model enhancements to improve disease progression modeling, staging, and transition rates, with calibration refinements and integration of HIV testing calculations to strengthen policy impact assessments. Parametrized congenital syphilis transmission by stage and prenatal screening timing, aligning HIV testing and contact tracing parameters with congenital syphilis modeling improvements. Fixed critical stability issues observed during HIV testing outcome and data-pull workflows, restoring reliable runs and enabling policy scenario analyses. Prepared the model for Todd's contact tracing work and established groundwork for Nick's engine run readiness. Overall impact: higher model accuracy, better policy insight for public health interventions, and improved data workflows for reproducibility and collaboration.
8 Commits • 2 Features
Jan 1, 2025January 2025 monthly summary for tfojo1/jheem_analyses: Delivered substantial SHIELD model enhancements to improve disease progression modeling, staging, and transition rates, with calibration refinements and integration of HIV testing calculations to strengthen policy impact assessments. Parametrized congenital syphilis transmission by stage and prenatal screening timing, aligning HIV testing and contact tracing parameters with congenital syphilis modeling improvements. Fixed critical stability issues observed during HIV testing outcome and data-pull workflows, restoring reliable runs and enabling policy scenario analyses. Prepared the model for Todd's contact tracing work and established groundwork for Nick's engine run readiness. Overall impact: higher model accuracy, better policy insight for public health interventions, and improved data workflows for reproducibility and collaboration.
January 2025
December 2024
2 Commits • 2 Features
Dec 1, 2024Month: 2024-12. Key features delivered: - Enhanced Calibration and Plotting for USA Demographics: updated calibration to use US location and US calibration code; adjusted data loading date; extended plotting outputs to include deaths and fertility.rate; configured plots by race and age. Commits: 05691a71678701db94cfd3cf26a70c27d5525bd8 (tracking issue with the fertility rate outcome). - Automated Synchronization with JHEEM_ANALYSIS Repository: added automation to shield_source_code.R to detect JHEEM_ANALYSIS directory and automatically pull latest analysis code. Commits: ca88c4d852ae7cee089977a4c048e41939284cee (adding script to pull JHEEM_analysis). Major bugs fixed: None reported this month. Overall impact and accomplishments: Improved accuracy of US demographic analyses and richer visual outputs, with automated code synchronization reducing manual steps and drift, enabling faster iteration and more reliable reporting. Technologies/skills demonstrated: R scripting (shield_source_code.R and US calibration code), data loading workflow adjustments, plotting by race and age, automation scripting for repository synchronization, Git-based traceability and issue tracking.
December 2024
2 Commits • 2 Features
Dec 1, 2024Month: 2024-12. Key features delivered: - Enhanced Calibration and Plotting for USA Demographics: updated calibration to use US location and US calibration code; adjusted data loading date; extended plotting outputs to include deaths and fertility.rate; configured plots by race and age. Commits: 05691a71678701db94cfd3cf26a70c27d5525bd8 (tracking issue with the fertility rate outcome). - Automated Synchronization with JHEEM_ANALYSIS Repository: added automation to shield_source_code.R to detect JHEEM_ANALYSIS directory and automatically pull latest analysis code. Commits: ca88c4d852ae7cee089977a4c048e41939284cee (adding script to pull JHEEM_analysis). Major bugs fixed: None reported this month. Overall impact and accomplishments: Improved accuracy of US demographic analyses and richer visual outputs, with automated code synchronization reducing manual steps and drift, enabling faster iteration and more reliable reporting. Technologies/skills demonstrated: R scripting (shield_source_code.R and US calibration code), data loading workflow adjustments, plotting by race and age, automation scripting for repository synchronization, Git-based traceability and issue tracking.
November 2024
16 Commits • 2 Features
Nov 1, 2024Summary for 2024-11: Focused on stabilizing aging parameterization, integrating fertility rate calibration, and strengthening data workflow automation. These efforts reduced calibration failures, improved forecast accuracy for demographic scenarios, and elevated data integrity and reproducibility. Notable technical work included creating a Slurm-based calibration script for rockfish, refining calibration pipelines, and enhancing ontology mappings. Business value: more reliable planning data, faster turnaround on model runs, and reduced risk from pipeline failures.
16 Commits • 2 Features
Nov 1, 2024Summary for 2024-11: Focused on stabilizing aging parameterization, integrating fertility rate calibration, and strengthening data workflow automation. These efforts reduced calibration failures, improved forecast accuracy for demographic scenarios, and elevated data integrity and reproducibility. Notable technical work included creating a Slurm-based calibration script for rockfish, refining calibration pipelines, and enhancing ontology mappings. Business value: more reliable planning data, faster turnaround on model runs, and reduced risk from pipeline failures.
November 2024
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Quality Metrics
Correctness81.6%
Maintainability82.2%
Architecture78.0%
Performance69.0%
AI Usage21.8%
Skills & Technologies
Programming Languages
BashBatchExcelRSQLShellUnknown
Technical Skills
Batch ScriptingBayesian AnalysisBug FixingCalibrationCluster ComputingCode RefactoringCode ReviewConditional LogicConfiguration ManagementCross-platform compatibilityData AnalysisData CalibrationData CleaningData EngineeringData Integration
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