tfojo1/jheem_analyses
Nov 2024 – Jul 2025
6 Months active
Languages Used
R
Technical Skills
Data AnalysisR ProgrammingStatistical ModelingData ManagementEpidemiological ModelingData Modeling
Lucia Cilloni
PROFILE
Lucia Cilloni
Over six months, Lcillon1 developed and refined depression epidemiological modeling features in the tfojo1/jheem_analyses repository, focusing on calibration workflows and outcome tracking. Using R and leveraging skills in data analysis and statistical modeling, Lcillon1 implemented new calibration scripts, updated likelihood calculations, and introduced point-level tracking for both HIV-positive and HIV-negative cohorts. The work included enhancements to model fidelity, integration of bias-estimate data assets, and improvements in traceability and reproducibility. By iteratively refining specification parameters and analytical weighting, Lcillon1 delivered deeper, more reliable analyses that support risk stratification and informed decision-making in mental health modeling pipelines.
Overall Statistics
Feature vs Bugs
100%Features
Repository Contributions
10Total
Bugs
0
Commits
10
Features
6
Lines of code
240
Activity Months6
Your Network
29 people
Work History
July 2025
1 Commits • 1 Features
Jul 1, 2025July 2025 monthly summary focusing on key enhancements in depression calibration and outcome tracking within tfojo1/jheem_analyses. Key refactors improved data integration, introduced new point-level outcome tracking for infected and uninfected depressed individuals, updated integrated outcome calculation to reference these point outcomes, and adjusted end-year calibration and weighting for proportion likelihood calculations. These changes increase tracking accuracy, support more reliable analytics, and enable better decision-making for end-of-year planning.
1 Commits • 1 Features
Jul 1, 2025July 2025 monthly summary focusing on key enhancements in depression calibration and outcome tracking within tfojo1/jheem_analyses. Key refactors improved data integration, introduced new point-level outcome tracking for infected and uninfected depressed individuals, updated integrated outcome calculation to reference these point outcomes, and adjusted end-year calibration and weighting for proportion likelihood calculations. These changes increase tracking accuracy, support more reliable analytics, and enable better decision-making for end-of-year planning.
July 2025
June 2025
1 Commits • 1 Features
Jun 1, 2025June 2025 performance summary focusing on delivering precise, business-value oriented improvements in the depression likelihood analysis and strengthening pipeline traceability.
June 2025
1 Commits • 1 Features
Jun 1, 2025June 2025 performance summary focusing on delivering precise, business-value oriented improvements in the depression likelihood analysis and strengthening pipeline traceability.
May 2025
3 Commits • 1 Features
May 1, 2025In May 2025, focused on delivering enhancements to depression epidemiological modeling within the tfojo1/jheem_analyses repository. Key work included refining specification parameters, updating likelihood integration, improving the calibration workflow, and setting up locations, plus adding a data asset with bias estimates to strengthen analyses. These changes improve model fidelity, calibration reliability, and data provenance. The work was accompanied by targeted updates to modeling files, calibration code and tests, and data assets to support reproducible analyses.
3 Commits • 1 Features
May 1, 2025In May 2025, focused on delivering enhancements to depression epidemiological modeling within the tfojo1/jheem_analyses repository. Key work included refining specification parameters, updating likelihood integration, improving the calibration workflow, and setting up locations, plus adding a data asset with bias estimates to strengthen analyses. These changes improve model fidelity, calibration reliability, and data provenance. The work was accompanied by targeted updates to modeling files, calibration code and tests, and data assets to support reproducible analyses.
May 2025
April 2025
1 Commits • 1 Features
Apr 1, 2025April 2025: Focused feature work in tfojo1/jheem_analyses on depression calibration and integrated outcome tracking enhancements to improve accuracy of analyses and reporting around depression treatment parameters.
April 2025
1 Commits • 1 Features
Apr 1, 2025April 2025: Focused feature work in tfojo1/jheem_analyses on depression calibration and integrated outcome tracking enhancements to improve accuracy of analyses and reporting around depression treatment parameters.
February 2025
1 Commits • 1 Features
Feb 1, 2025February 2025 monthly summary for tfojo1/jheem_analyses: Focused on preparing the depression model calibration by updating priors and specification files; enabled calibration run readiness; refined incidence and treatment parameter estimates; improved outcome tracking for HIV-positive and HIV-negative cohorts. Delivery aligns modeling with upcoming calibration milestones and data-driven projections.
1 Commits • 1 Features
Feb 1, 2025February 2025 monthly summary for tfojo1/jheem_analyses: Focused on preparing the depression model calibration by updating priors and specification files; enabled calibration run readiness; refined incidence and treatment parameter estimates; improved outcome tracking for HIV-positive and HIV-negative cohorts. Delivery aligns modeling with upcoming calibration milestones and data-driven projections.
February 2025
November 2024
3 Commits • 1 Features
Nov 1, 2024Monthly summary for 2024-11 focused on the tfojo1/jheem_analyses repository. Delivered enhancements to the depression calibration workflow and spec integration, improving model calibration accuracy and traceability.
November 2024
3 Commits • 1 Features
Nov 1, 2024Monthly summary for 2024-11 focused on the tfojo1/jheem_analyses repository. Delivered enhancements to the depression calibration workflow and spec integration, improving model calibration accuracy and traceability.
Activity
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Quality Metrics
Correctness80.0%
Maintainability82.0%
Architecture74.0%
Performance64.0%
AI Usage20.0%
Skills & Technologies
Programming Languages
R
Technical Skills
Data AnalysisData ManagementData ModelingEpidemiological ModelingR ProgrammingStatistical AnalysisStatistical Modeling
Repositories Contributed To
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