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Data fitting results for the HCV dynamics model.

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Author(s): Tinashe Victor Mupedza; Laurette Mhlanga; Dennis Mamutse; Mlyashimbi Helikumi; Paride Oresto Lolika; Shingirai Tangakugara Murambiwa; Adquate Mhlanga
Subject Terms:
Medicine; Sociology; Cancer; Science Policy; Environmental Sciences not elsewhere classified; Biological Sciences not elsewhere classified; Mathematical Sciences not elsewhere classified; Chemical Sciences not elsewhere classified; public health policy; lmic ); despite; including patient education; hepatitis c virus; acutely infected individuals; predicting disease progression; treatment adherence challenges; poor treatment adherence; improve treatment adherence; curbing hcv proliferation; stronger health interventions; lmics like zimbabwe; div >< p; infectious disease modeling; hcv transmission dynamics; hcv model indicates; treatment adherence; transmission dynamics; disease spread; well understood; vital metric
Document Type:
still image
Language:
unknown

Additional Information
- Publication Date:
  2025
- Collection:
  The Open University: Figshare
- Abstract:
  The blue markers represent observed data points, while the red line illustrates the model’s predictions. This is an extension of the model fits Fig 3, with projections for the year 2019 to 2028.
- Relation:
  https://figshare.com/articles/figure/Data_fitting_results_for_the_HCV_dynamics_model_/29872965
- Accession Number:
  10.1371/journal.pone.0329543.g003
- Online Access:
  https://doi.org/10.1371/journal.pone.0329543.g003
  https://figshare.com/articles/figure/Data_fitting_results_for_the_HCV_dynamics_model_/29872965
- Rights:
  CC BY 4.0
- Accession Number:
  edsbas.36802E9D

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