Published in:
Open Access 01-12-2017 | Research article
Characterizing measles transmission in India: a dynamic modeling study using verbal autopsy data
Published in: BMC Medicine | Issue 1/2017
Login to get accessAbstract
Background
Decreasing trends in measles mortality have been reported in recent years. However, such estimates of measles mortality have depended heavily on assumed regional measles case fatality risks (CFRs) and made little use of mortality data from low- and middle-income countries in general and India, the country with the highest measles burden globally, in particular.
Methods
We constructed a dynamic model of measles transmission in India with parameters that were empirically inferred using spectral analysis from a time series of measles mortality extracted from the Million Death Study, an ongoing longitudinal study recording deaths across 2.4 million Indian households and attributing causes of death using verbal autopsy. The model was then used to estimate the measles CFR, the number of measles deaths, and the impact of vaccination in 2000–2015 among under-five children in India and in the states of Bihar and Uttar Pradesh (UP), two states with large populations and the highest numbers of measles deaths in India.
Results
We obtained the following estimated CFRs among under-five children for the year 2005: 0.63% (95% confidence interval (CI): 0.40–1.00%) for India as a whole, 0.62% (0.38–1.00%) for Bihar, and 1.19% (0.80–1.75%) for UP. During 2000–2015, we estimated that 607,000 (95% CI: 383,000–958,000) under-five deaths attributed to measles occurred in India as a whole. If no routine vaccination or supplemental immunization activities had occurred from 2000 to 2015, an additional 1.6 (1.0–2.6) million deaths for under-five children would have occurred across India.
Conclusions
We developed a data- and model-driven estimation of the historical measles dynamics, CFR, and vaccination impact in India, extracting the periodicity of epidemics using spectral and coherence analysis, which allowed us to infer key parameters driving measles transmission dynamics and mortality.