M.S., Delft University of Technology, the Netherlands, 2003; Ph.D., University of Washington, 2008; Postdoctoral, Columbia University, 2008-09.
Area(s) of Specialization:
Bayesian inference, Statistical Demography, Global child, maternal and reproductive health.
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 globally, but also sub-nationally, focusing on developing countries. I have developed estimation and projection methods for key global indicators, including child and maternal mortality rates, the total fertility rate, and the unmet need for contraceptive methods. 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 populations where data availability is limited and where 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. I collaborate with various United Nations agencies to make available improved estimation methods and resulting estimates to diverse international audiences.
F. Chao, A.R. Cook, P. Gerland, L. Alkema (2019). A systematic assessment of the sex ratio at birth for all countries and estimation of national imbalances and regional reference levels. Proceedings of the National Academy of Sciences 116 (19), 9303-9311
N. Cahill, E. Sonneveldt, J. Stover, M. Weinberger, J. Williamson, C. Wei, W. Brown, L. Alkema (2018). Modern contraceptive use, unmet need, and demand satisfied among women of reproductive age who are married or in a union in the focus countries of the Family Planning 2020 initiative: a systematic analysis using the Family Planning Estimation Tool. The Lancet 391 (10123): 870 – 882.
G. Sedgh, J. Bearak, S. Singh, A. Bankole, A. Popinchalk, B. Ganatra, C. Rossier, C. Gerdts, Ö. Tunçalp, R. Johnson, H.B. Johnston, L. Alkema (2016). Abortion incidence between 1990 and 2014: global, regional, and subregional levels and trends. The Lancet 388(10041): 258 – 267.
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 (2016). 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 387(10017): 462 – 474.
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.
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.