Space-time smoothing models for sub-national measles routine immunization coverage estimation with complex survey data

by   Tracy Qi Dong, et al.

Despite substantial advances in global measles vaccination, measles disease burden remains high in many low- and middle-income countries. A key public health strategy for controling measles in such high-burden settings is to conduct supplementary immunization activities (SIAs) in the form of mass vaccination campaigns, in addition to delivering scheduled vaccination through routine immunization (RI) programs. To achieve balanced implementations of RI and SIAs, robust measurement of sub-national RI-specific coverage is crucial. In this paper, we develop a space-time smoothing model for estimating RI-specific coverage of the first dose of measles-containing-vaccines (MCV1) at sub-national level using complex survey data. The application that motivated this work is estimation of the RI-specific MCV1 coverage in Nigeria's 36 states and the Federal Capital Territory. Data come from four Demographic and Health Surveys, three Multiple Indicator Cluster Surveys, and two National Nutrition and Health Surveys conducted in Nigeria between 2003 and 2018. Our method incorporates information from the SIA calendar published by the World Health Organization and accounts for the impact of SIAs on the overall MCV1 coverage, as measured by cross-sectional surveys. The model can be used to analyze data from multiple surveys with different data collection schemes and construct coverage estimates with uncertainty that reflects the various sampling designs. Implementation of our method can be done efficiently using integrated nested Laplace approximation (INLA).



page 8

page 11

page 12

page 13

page 14

page 16


Space-Time Smoothing of Demographic and Health Indicators using the R Package SUMMER

The increasing availability of complex survey data, and the continued ne...

Modeling and presentation of vaccination coverage estimates using data from household surveys

It is becoming increasingly popular to produce high-resolution maps of v...

Estimating Global Household Air Pollution: A Multivariate Hierarchical Model for Cooking Fuel Prevalence

Globally, an estimated 3.8 million deaths per year can be attributed to ...

Prediction of neonatal mortality in Sub-Saharan African countries using data-level linkage of multiple surveys

Existing datasets available to address crucial problems, such as child m...

Estimation of Health and Demographic Indicators with Incomplete Geographic Information

In low and middle income countries, household surveys are a valuable sou...

Accounting for Spatial Anonymization in DHS Household Surveys

The household surveys conducted by the Demographic and Health Surveys (D...
This week in AI

Get the week's most popular data science and artificial intelligence research sent straight to your inbox every Saturday.