Health Economics & Artificial Intelligence for Public Health

Ruth Manuela
Pérez Hernández

PhD in Health Systems Sciences

Associate Researcher B · Mexican Social Security Institute

I generate evidence on the cost, impact, and sustainability of chronic disease, mental health, and work disability within Mexico's social security system, and I build artificial intelligence models to anticipate them.

Portrait of Ruth Manuela Pérez Hernández
Profile

Her research examines the efficiency, impact, and sustainability of health interventions, labor productivity, and institutional spending, with an emphasis on chronic disease, mental health, and work disability.

She applies quantitative and artificial intelligence tools to turn clinical and epidemiological evidence into information useful for decision-making in social security, and she leads interinstitutional collaborations that connect academia with institutional practice.

184 Citations accrued across peer‑reviewed scientific output
27 Years of service with the Mexican Social Security Institute
5 Master's theses supervised through to the awarding of the degree

Four areas of work

  1. 01

    Political economy of health and social security

    Financial sustainability of the health system and the social costs of chronic disease.

  2. 02

    Health and the labor market

    The impact of illness on productivity, work disability, and occupational structure.

  3. 03

    Social determinants of health

    Sedentary behavior as a socio‑occupational phenomenon: lifestyles and institutional contexts.

  4. 04

    Data analytics and artificial intelligence

    Predictive models built on large health datasets to support public decision‑making.

EpiForecast‑MX

A methodological, AI‑based model for the predictive and comparative analysis of epidemiological time series for priority conditions in Mexico.

It turns public epidemiological data into reproducible predictive intelligence, with transferable criteria for progressively incorporating new disease families into the national analysis. Its purpose is for the models to be integrated into epidemiological surveillance systems, strengthening risk anticipation and the planning of public health interventions.

  • Depression
  • Alzheimer's disease
  • Parkinson's disease

Visit epiforecast.mx

Interinstitutional collaboration

  • Mexican Social Security Institute
  • Tecnológico de Monterrey
  • National Institute of Public Health
  • Ramón de la Fuente Muñiz National Institute of Psychiatry

Ongoing presentation — ALASS Congress 2026, Montreal, Canada

Selected scientific output

  • Lead author

    Glycemic and Blood Pressure Control in Type 2 Diabetes Mellitus: Disability Costs Covered by Social Security, Evidence From Mexico

    Value in Health Regional Issues · 2025

    DOI ↗
  • Corresponding author

    Sedentarismo laboral en distintos contextos ocupacionales en México: prevalencia y factores asociados

    Salud Pública de México · 2021

    DOI ↗
  • Cost of the Cervical Cancer Screening Program at the Mexican Social Security Institute

    Salud Pública de México · 2014 · Co‑author

    DOI ↗
  • HPV testing for cervical cancer screening appears more cost‑effective than Papanicolau cytology in Mexico

    Cancer Causes & Control · 2011 · Co‑author

    DOI ↗
  • Estimating the cost of treating patients with liver cirrhosis at the Mexican Social Security Institute

    Salud Pública de México · 2010 · Co‑author

    PubMed ↗
View full profile on Google Scholar ↗

Training of human resources

Supervision of master's theses at the Instituto Tecnológico y de Estudios Superiores de Monterrey, all completed with the degree awarded, on epidemiological forecasting with machine learning methods.

  • Generalización de modelos nacionales de pronóstico epidemiológico hacia un enfoque modular con desagregación por sexo y entidad federativa en México

    Javier Augusto Rebull Saucedo

    2026
  • Predicción de brotes de sarampión en México mediante modelos de aprendizaje automático (2010–2023)

    Gerardo Miguel Pérez Solís

    2026
  • Análisis y pronóstico de la depresión en México: de la evidencia epidemiológica a la inteligencia predictiva

    Stephanie Fortiz de Ita

    2026
  • Análisis y pronóstico epidemiológico de enfermedades neurológicas y trastornos mentales con enfoque a la enfermedad de Parkinson

    Oscar Mauricio Becerra Alegra

    2026
  • Análisis y pronóstico epidemiológico de la enfermedad de Alzheimer en México

    Jorge Steven Reyes Londoño

    2026

Graduate teaching

  • Introduction to qualitative methods applied to public health Master's · 2018 and 2025–2026
  • Application of quantitative and qualitative methods to health systems research Doctorate in Health Systems · 2022 and 2023
  • Doctoral seminars Epistemology (2024) · Research (2018)

Peer review

  • Modelos de regresión para el análisis del gasto catastrófico en salud, con énfasis en regresión cuantílica Academic review · Colombia · 2026
  • Household cost of accessing contraceptive services among women in urban communities in Ghana External peer reviewer · 2024

Recent outreach

  1. Upcoming

    ALASS Congress 2026

    Montreal, Canada · 2026

    Presentation of the EpiForecast‑MX project: artificial intelligence models for predictive epidemiological surveillance.

  2. Talk

    Public Health Futures — 2nd Public Health Conference

    Skopje, North Macedonia · May 21–22, 2026

    “AI‑Based Forecasting to Shift Epidemiological Surveillance Toward Predictive Approaches: Depression, Alzheimer's, and Parkinson's as Use Cases.”

  3. Talk

    Helix Summit México 2026

    Mexico · May 20, 2026

    “Predicción basada en IA para transitar la vigilancia epidemiológica clásica hacia enfoques predictivos: los casos de la depresión, el Alzheimer y el Parkinson.”

  4. Poster

    20th Congress on Public Health Research

    Mexico · March 5, 2025

    “Costos de las incapacidades laborales: diabetes y los controles de la hipertensión y glucosa. México.”

Let's talk

Open to interinstitutional collaboration, peer review, and applied research projects in health economics and artificial intelligence.

Send an email Save contact