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Consistent partnership formation: application to a sexually transmitted disease model.

Marc Artzrouni1, Eva Deuchert

  • 1Department of Mathematics, University of Pau, France. marc.artzrouni@univ-pau.fr

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This study modeled sexual partnerships using UK data, revealing that assuming male partners accurately report numbers leads to higher modeled incidences of genital herpes (HSV-2) compared to assuming female partners do. Misreported sexual behavior significantly impacts incidence estimates.

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Area of Science:

  • Epidemiology
  • Mathematical Modeling
  • Sexual Health

Background:

  • Accurate reporting of sexual behavior and partner preferences is crucial for understanding disease transmission dynamics.
  • Inconsistent findings in epidemiological studies may arise from biases in self-reported sexual activity data.
  • Sexual partnership formation models are essential tools for simulating disease spread.

Purpose of the Study:

  • To investigate the impact of gender-dominant reporting assumptions within a sexual partnership formation model on the estimated incidence of genital herpes (HSV-2).
  • To assess how misreported sexual activity and age preferences influence disease incidence modeling.
  • To compare modeled HSV-2 incidence using male-dominant versus female-dominant reporting scenarios.

Main Methods:

  • A consistent sexual partnership formation model was developed, incorporating either male-dominant or female-dominant reporting assumptions.
  • The model was calibrated using sexual behavior data from the United Kingdom.
  • A simple incidence model for HSV-2 was applied using the fitted partnership formation model.

Main Results:

  • A male-dominant model, assuming accurate male reports on partner numbers, yielded a 77% higher modeled incidence of HSV-2 for men and a 50% higher incidence for women compared to a female-dominant model.
  • The choice of which gender's reports are assumed accurate significantly alters the projected disease incidence.
  • The findings highlight the sensitivity of epidemiological models to reporting biases.

Conclusions:

  • Gender-dominant assumptions in sexual partnership models lead to substantial discrepancies in estimated disease incidence, particularly for HSV-2.
  • Misreporting of sexual activity and age preferences can create significant inconsistencies in epidemiological outcomes.
  • Even stylized models demonstrate the critical need for robust data and careful consideration of reporting biases in sexual health research.