@article{de:2016,
author = {de, Figueiredo A and Johnston, IG and Smith, DMD and Agarwal, S and Larson, HJ and Jones, NS},
journal = {Lancet Global Health},
title = {Forecasting time-series trends in vaccination coverage and their links with socio-economic factors: A global analysis over 30 years},
url = {http://hdl.handle.net/10044/1/34487},
year = {2016}
}

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TY  - JOUR
AB  - Background Incomplete immunisation coverage causes preventable illness and death in both the developing anddeveloped world. Identifying factors that may modulate coverage can inform effective immunisation programmes andpolicies.Methods We perform a data-driven analysis of unprecedented scale, examining time-varying trends in Diphtheriatetanus-pertussiscoverage across 190 countries over the past three decades. Gaussian process regression is employedto forecast future coverage rates and provide a Vaccine Performance Index: a summary measure of the strength ofimmunisation coverage in a country.Findings Overall vaccine coverage has increased in all five world regions between 1980 and 2010, with markedvariation in volatility and trends. Our Vaccine Performance Index identifies 53 countries with a less than 50% chanceof missing the Global Vaccine Action Plan (GVAP) target of 90% worldwide DTP3 coverage by 2015, in agreementwith recent immunisation data. These countries are mostly sub-Saharan and South Asian, but Austria and Ukraine inEurope also feature. Factors associated with DTP3 immunisation coverage vary by world-region: personal income(! = 0.66, ' < 0.001) and government health spending (! = 0.66, ' < 0.01) are particularly informative in theEastern Mediterranean between 1980 and 2010, whilst primary school completion is informative in Africa (! =0.56, ' < 0.001) over the same time. The fraction of births attended by skilled health staff is significantly informativeacross many world regionsInterpretation A Vaccine Performance Index can highlight countries at risk identifying the strength and resilience ofimmunisation programmes. Weakening correlations with socio-economic factors indicate a need to tackle vaccineconfidence whereas strengthening correlations points to clear factors to address.
AU  - de,Figueiredo A
AU  - Johnston,IG
AU  - Smith,DMD
AU  - Agarwal,S
AU  - Larson,HJ
AU  - Jones,NS
PY  - 2016///
SN  - 2214-109X
TI  - Forecasting time-series trends in vaccination coverage and their links with socio-economic factors: A global analysis over 30 years
T2  - Lancet Global Health
UR  - http://hdl.handle.net/10044/1/34487
ER  - 

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