Non-communicable diseases (NCDs)

Decision-analytic tool for early detection of cancer in low and middle income countries


 World Health Organization, 2014-current

Progress and reports

  • Gopalappa, C., Guo*, J., Meckoni*, P., Munkhbat*, B., Pretorius, C., Lauer, J., Ilbawi, A., Bertram, M., A two-step Markov processes approach for parameterization of cancer state-transition models for low- and middle- income countries, Medical Decision Making, PDF technical-suppl LINK
  • Used by the WHO to update the analyses for the Appendix 3 of the Global Action Plan for Non-Communciale Diseases, for the World Health Assembly.
  • WHO Technical Briefing to the 70th World Health Assembly here.
  • Ambinintsoa H. RalaidovyChaitra  GopalappaAndré  Ilbawi, Carel  Pretorius and Jeremy A. Lauer, Cost-effective interventions for breast cancer, cervical cancer, and colorectal cancer: new results from WHO-CHOICE, Cost Effectiveness and Resource Allocation, 18 (38), 2018 LINK LINK
  • Cost-effectiveness analyses for regions Eastern Sub-Saharan Africa (AFRE) and Southeast Asia (SEARB) (manuscript in preparation).
  • Future work is to consider more country-specific implementation and analyses.

Model Access

 part of NCD module in Spectrum software a desktop application software (Work in Progress)


World Health Organization, International Agency for research on CancerAvenir Health, Pan-American Health Organization


    •  Implementation of organized cancer screening and prevention programmes in high-income countries (HICs) has considerably decreased cancer related incidence and mortality. In low- and middle-income countries (LMICs), screening and early diagnosis programmes are generally unavailable, and a majority of cancers are diagnosed in late stages when survival is very low. Analyzing cost-effectiveness of alternative cancer control programmes and estimating resource needs will help health planner prioritize interventions in LMICs. However, mathematical models of natural cancer onset and progression, for conducting the economic analyses, are predominantly based on populations in HICs because the longitudinal data on screening and diagnoses required for parameterization are unavailable in LMICs. Models currently used for LMICs mostly concentrate on directly calculating the shift in distribution of cancer diagnosis as an evaluation measure of screening.

Work at UMass

    • At UMass Amherst we are developing new methodologies based for parameterization of natural cancer onset and progression, specifically for LMICs that do not have longitudinal data on screening and diagnoses.


    •  Health planners can use the model to conduct economic analyses, i.e., compare costs and impact of alternative intervention options based on region-specific resource availabilities and disease burden, to prioritize program implementation. Alternative intervention options that health planners encounter could include (i) different types of screening modalities such as colonoscopy versus faecal immunochemical test for colorectal cancer; (ii) different screening intervals such as mammography every 1 year versus every 2 years to test for breast cancer; or (iii) combinations of interventions such as frequency of PapSmear to screen for cervical cancer in addition to HPV (human papillomavirus) vaccination to prevent cervical cancer.

Technical methods

    •  stochastic processes, non-linear simulation-based optimization, dynamic programming, and population-level simulation;


    •  MATLAB