Proceedings of the 2018 Winter Simulation Conference
M. Rabe, A. A. Juan, N. Mustafee, A. Skoogh, S. Jain, and B. Johansson, eds.
PARAMETERIZATION AND CALIBRATION OF MICRO-SIMULATION MODEL FOR
CERVICAL CANCER AND HIV IN ZAMBIA
Kasey Jones
Joey Morris
Georgiy Bobashev
Center for Data Science
RTI International
3040 E Cornwallis Rd
Durham, NC 27709, USA
Sujha Subramanian
Public Health Research Division
RTI International
307 Waverley Oaks Road
Waltham, MA 02452, USA
ABSTRACT
Zambia has one of the highest rates of cervical cancer in the world. To help policy makers make future
intervention decisions regarding cervical cancer, we created a micro-simulation model to simulate cervical
cancer and HIV in Zambia. Model calibration faced two major challenges: (1) Much of the available
input data was on women in the United States, which do not allow calibration to align to the age-specific
targets from Zambia; (2) Significant computational resources were not always available. We addressed
issue one by creating age-specific calibration parameters to help better match specific targets. Issue two
was addressed by using predictive models before conducting calibration simulations to discard parameter
sets that are likely to produce poor results. This paper will demonstrate these two modeling strategies and
show the dramatic effect they had on our ability to accurately calibrate to model targets.
1 INTRODUCTION
Cervical cancer lead to almost 266,000 deaths in 2012 (Subramanian et al. 2008). This is particular a
problem in countries where resources and screening programs are scarce. Among women in Sub-Saharan
Africa, cervical cancer is the most common cause of cancer-related deaths (GLOBOCAN 2014). A high-
prevalence of HIV, mixed with the fact that women who have HIV are six times more likely to get cervical
cancer, make this region prone to higher cervical cancer rates (Martel et al. 2012).
There are low-cost strategies available to prevent cervical cancer. Testing the impact of these strategies
is expensive and in countries with already limited resources may not be possible. Micro-simulations can
model the progress of human papillomavirus (HPV) and human immunodeficiency virus (HIV) in Zambia
and can access the impact and cost of intervention strategies. For the result of these tests to be trusted, the
micro-simulation needs to calibrate well to known rates of cervical cancer, HPV, and HIV in Zambia. Our
goal is develop a micro-simulaiton that will allow researches to assess the cost-effectiveness of interventions
for fighting cervical cancer in Zambia and build a bases for conducting similar research in other countries.
1.1 Micro-Simulation Basics
On top of modeling HPV and HIV, our micro-simulation models cancer detection, cancer progression, and
current life status. Each component is made up of states. For example, if a woman is alive, her life state
is alive. The current state for a woman is advanced through monthly time-steps from age nine until death
or age 100. Transitions among the five states (HIV, HPV, cancer detection, cancer progression, and life)
are generated using probabilities that account for the woman’s other states and current age.
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