Health Forecasting

Forecasts mortality and life expectancy are needed to plan for health and social services and pensions. We develop novel methods for mortality forecasting, and for analysing how policy scenarios, for example those related to disease prevention, may modify the forecasted trends, at scales from subnational to global. Recent work has expanded to forecasting using Bayesian model ensembles, which have not been frequently  used in population health and incorporate uncertainty about the choice of models themselves.

Related Publications

17 entries « 1 of 4 »

Kontis V, Bennet JE, Parks RM, Rashid T, Pearson-Stuttard J, Asaria P, Zhou B Guillot M, Mathers CD, Khang YH, McKee M, Ezzati M

Lessons learned and lessons missed: impact of the coronavirus disease 2019 (COVID-19) pandemic on all-cause mortality in 40 industrialised countries prior to mass vaccination

Wellcome Open Research, 6 (279), 2021.

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Davies B, Parkes BL, Bennett J, Fecht D, Blangiardo M, Ezzati M, Elliott P

Community factors and excess mortality in first wave of the COVID-19 pandemic in England

Nature Communications, 12 (3755), 2021.

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Kontis V, Bennett JE, T Rashid, Parks RM, Pearson-Stuttard J, Guillot M, Asaria P, Zhou B, Battaglini M, Corsetti G, Mckee M, Di Cesare M, Mathers CD, Ezzati M

Age- and sex-specific total mortality impacts of the early weeks of the Covid-19 pandemic in England and Wales: Application of a Bayesian model ensemble to mortality statistics.

Nature Medicine , 26 (12), pp. 1919-1928, 2020.

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Kontis V, Bennett JE, Rashid T, Parks RM, Pearson-Stuttard J, Guillot M, Asaria P, Zhou B, Battaglini M, Corsetti G, McKee M, Di Cesare M, Mathers CD, Ezzati M

Magnitude, demographics and dynamics of the effect of the first wave of the COVID-19 pandemic on all-cause mortality in 21 industrialized countries

Nature Medicine, 26 , pp. 1919–1928, 2020.

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Boulieri A, Bennett JE, Blangiardo M

A Bayesian mixture modeling approach for public health surveillance

Biostatistics, 2018.

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17 entries « 1 of 4 »
Health Forecasting