Leontine Alkema

Leontine Alkema

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My primary research focus is the development of statistical models to assess and interpret demographic and population-level health trends and differentials, generally on a national level, for all countries in the world. I have developed estimation and projection methods for key global indicators, such as child mortality, the total fertility rate, unmet need for contraceptive methods, and causes of maternal mortality. One of the main methodological challenges in this area of research arises from the need to capture data-driven trends in data-rich populations, while also producing reliable estimates and projections for population where data availability is limited and only proxy indicator data are available. My research has addressed these challenges for various indicators via the conceptualization, development, and validation of context-specific Bayesian models. Key components of these models are hierarchical submodels to allow for sharing of information across populations to inform the estimates and projections for data-sparse populations, and the parametrization of biases and measurement error variances to account for data quality issues.

Most publications and other reports are included in my Google scholar profile.

Peer-reviewed publications

  1. L. Alkema, D. Chou, D. Hogan, S. Zhang, A.B. Moller, A. Gemmill, D.M. Fat, T. Boerma, M. Temmerman, C.D. Mathers, L. Say (2015). Global, regional, and national levels and trends in maternal mortality between 1990 and 2015, with scenario-based projections to 2030: a systematic analysis by the UN Inter-agency Group for Maternal Mortality Estimation. The Lancet.
  1. D. You, L. Hug, S. Ejdemyr, P. Idele, D. Hogan, C. Mathers, P. Gerland, J.R. New, L. Alkema (2015). Global, regional, and national levels and trends in under-5 mortality between 1990 and 2015, with scenario-based projections to 2030: a systematic analysis by the UN Inter-agency Group for Child Mortality Estimation. The Lancet. http://dx.doi.org/10.1016/S0140-6736(15)00120-8.
  1. L. Alkema, P. Gerland, A.E. Raftery, J. Wilmoth (2015). The United Nations Probabilistic Population Projections: An Introduction to Demographic Forecasting with Uncertainty. Foresight: The International Journal of Applied Forecasting 37: 19–24.
  1. L. Alkema, J.R. New (2014). Global estimation of child mortality using a Bayesian B-spline bias-reduction method. The Annals of Applied Statistics 8(4): 2122–2149.
  1. P. Gerland, A.E. Raftery, H. Sevcikova, N. Li, D. Gu, T. Spoorenberg, L. Alkema, B.K. Fosdick, J. Chunn, N. Lalic, G. Bay, T. Buettner, G.K. Heilig, J. Wilmoth (2014). World population stabilization unlikely this century. Science 346(6206): 234-237.
  1. L. Alkema, F. Chao, D. You, J. Pedersen, C.C. Sawyer (2014). National, regional, and global sex ratios of infant, child, and under-5 mortality and identification of countries with outlying ratios: a systematic assessment. The Lancet Global Health 2(9): e521-e530.
  1. L. Alkema, J.R. New, J. Pedersen, D. You, on behalf of the members of the UN Inter-agency Group for Child Mortality Estimation and its Technical Advisory Group (2014). Child Mortality Estimation 2013: An overview of updates in estimation methods by the United Nations Inter-agency Group for Child Mortality Estimation. PLOS ONE 9(7): e101112.
  1. L. Say, D. Chou, A. Gemmill, O. Tuncalp, A. B. Moller, J. Daniels, A. M. Gulmezoglu, M. Temmerman, L. Alkema (2014). Global causes of maternal deaths: A WHO systematic analysis. The Lancet Global Health 2(6): e323-e3332.
  1. T.P. Phan, L. Alkema, E.S. Tai, K.H.X. Tan, Q. Yang, W.Y. Lim, Y.Y. Teo, C.Y. Cheng, X. Wang, T.Y. Wong, K.S. Chia, A.R. Cook (2014). Forecasting the burden of type 2 diabetes in Singapore using a demographic epidemiological model of Singapore. BMJ Open Diabetes Research and Care 2(1): e000012.
  1. A. E. Raftery, L. Alkema, P. Gerland (2014). Bayesian population projections for the United Nations. Statistical Science, 29(1): 56-68.
  1. F. Chao, L. Alkema (2014). How informative are vital registration data for estimating maternal mortality? A Bayesian analysis of WHO adjustment data and parameters. Statistics and Public Policy, 1(1): 6-14.
  1. L. Alkema , G. Jones, C. Rue (2013). Levels of urbanization in the world's countries: testing consistency of estimates based on national definitions. Journal of Population Research, 30(4): 291-304.
  1. M. Oestergaard, L. Alkema, J.E. Lawn (Editorial, 2013). Millennium Development Goals national targets are moving targets and the results will not be known until well after the 5 deadline of 2015. International Journal of Epidemiology 42(3): 645-647.
  1. L. Alkema, V. Kantorova, C. Menozzi, A. Biddlecom (2013). National, regional and global rates and trends in contraceptive prevalence and unmet need for family planning between 1990 and 2015: a systematic and comprehensive analysis. The Lancet 381(9878): 1642-1652.
  1. L. Alkema, J.R. New (2012). Progress toward global reduction in under-5 mortality: A bootstrap analysis of uncertainty in Millennium Development Goal 4 estimates. PLOS Medicine 9(12): e1001355.
  1. L. Alkema, D. You (2012). Child Mortality Estimation: a comparison of UN-IGME and IHME estimates of levels and trends in under-5 mortality rates and deaths. PLOS Medicine 9(8): e1001288.
  1. L. Alkema, M. Wong, P.R. Seah (2012). Monitoring progress towards Millennium Development Goal 4: A call for improved validation of under-5 mortality rate estimates. Statistics, Politics, and Policy 3(2): Art. 2.
  1. L. Alkema, A. E. Raftery, P. Gerland, S. J. Clark, F. Pelletier (2012). Estimating trends in the total fertility rate with uncertainty using imperfect data: Examples from West Africa. Demographic Research 26(15): 331-362.
  1. L. Alkema, W.L. Ann (2011). Estimating the under-5 mortality rate using a Bayesian hierarchical time series model. PLOS ONE 6(9): e23954.
  1. L. Alkema, A. E. Raftery, P. Gerland, S.J. Clark, F. Pelletier, T. Buettner, G. K. Heilig (2011). Probabilistic projections of the total fertility rate for all countries. Demography 48(3): 815-839.
  1. H. Sevcikova, L. Alkema, A. E. Raftery (2011). BayesTFR: An R package for probabilistic projections of the total fertility rate. Journal of Statistical Software 43: 1-29.
  1. L. Winowiecki, S. Smukler, K. Shirley, R. Remans, G. Peltier, E. Lothes, E. King, L. Comita, S. Baptista, L. Alkema (2011). Tools for enhancing interdisciplinary communication. Sustainability: Science, Practice & Policy 7(1): 74-80.
  1. L. F. Johnson, L. Alkema, R. E. Dorrington (2010). A Bayesian approach to uncertainty analysis of sexually transmitted infection models. Sexually Transmitted Infections 86: 169-174.
  1. L. Alkema, A. E. Raftery, T. Brown (2008). Bayesian melding for estimating uncertainty in national HIV prevalence estimates. Sexually Transmitted Infections 84 (Suppl I): i11-i16.
  1. T. Brown, J. A. Salomon, L. Alkema, A. E. Raftery, E. Gouws (2008). Progress and challenges in modelling country-level HIV/AIDS epidemics: the UNAIDS Estimation and Projection Package 2007. Sexually Transmitted Infections 84 (Suppl I): i5-i11.
  1. L. Alkema, A. E. Raftery, S. J. Clark (2007). Probabilistic projections of HIV prevalence using Bayesian melding. The Annals of Applied Statistics 1(1): 229-248.