'Footprinting' missing epidemiological data for cervical cancer: a case study in India

BackgroundContext-specific cervical cancer epidemiological data are essential to derive local impact projections of cervical cancer preventive measures. However, these are not always available, in particular in low- and middle-income countries (LMICs), where impact projections are essential to plan cervical cancer control programs.Methods and FindingsWe developed a framework, hereafter named Footprinting, to approximate the sexual behavior, human papillomavirus (HPV) prevalence, and/or cervical cancer incidence data needed for impact projections. The framework was applied to a case study in India, the country with the highest expected cervical cancer burden but still limited access to cervical cancer prevention. With our Footprinting framework, we 1) identified clusters of Indian states with similar cervical cancer incidence patterns, 2) classified states without incidence data to the identified clusters based on similarity in sexual behavior data, 3) approximated missing cervical cancer incidence and HPV prevalence data based on available data within each cluster. Two main patterns of cervical cancer incidence, characterized by high and low incidence, were identified for 6 and 8 Indian states, respectively. States in the low-incidence cluster were characterized by less sexual activity with non-regular partners in men and earlier sexual debut in women. Based on these patterns, all 11 Indian states with missing cervical cancer incidence data were classified to the low-incidence cluster. Finally, missing data on cervical cancer incidence and HPV prevalence were approximated based on the mean of the available data within each cluster.ConclusionsWith the Footprinting framework, we enabled approximation of missing cervical cancer epidemiological data and derivation of context-specific impact projection of cervical cancer prevention measures, assisting public health decisions on cervical cancer prevention in India and other LMICs.