Approximating missing epidemiological data for cervical cancer through Footprinting: A case study in India

Area of Science:

• Epidemiology
• Public Health
• Biostatistics

Background:

• Cervical cancer prevention strategies require accurate local epidemiological data, which is often unavailable.
• Estimating human papillomavirus (HPV) prevalence and cervical cancer incidence is crucial for targeted interventions.

Purpose of the Study:

• To develop and apply a framework (Footprinting) for approximating missing cervical cancer and HPV data in India.
• To enable context-specific impact projections for cervical cancer preventive measures.

Main Methods:

• Clustering Indian states based on cervical cancer incidence patterns.
• Classifying states with missing data using sexual behavior similarities.
• Approximating missing incidence and prevalence data using cluster-based means.

Main Results:

• Identified two main cervical cancer incidence patterns: high and low.
• Classified all states with missing data into the low-incidence cluster based on sexual behavior.
• Successfully approximated missing cervical cancer incidence and HPV prevalence data.

Conclusions:

• The Footprinting framework effectively approximates missing epidemiological data for cervical cancer.
• This approach supports informed public health decisions and planning for cervical cancer prevention in data-limited settings.
• The methodology can be adapted for cervical cancer prevention initiatives in other countries.