Publications

For an up-to-date list of publications, see my Google Scholar profile. Student and postdoc co-authors are marked with *.

Peer-reviewed publications

• L. Alkema, H. Susmann, E. Ray, S. Mooney*, N. Cahill, K. Bietsch, A. Jayachandran, et al. (2026). Bayesian Statistical Modeling in Action for Estimation and Forecasting in Low- and Middle-income Countries: The Case of the Family Planning Estimation Tool. Statistics and Public Policy.

  • See https://alkemalab.github.io/fpet2/ for R package

• L. Alkema, S. Mooney*, S. Kagoye, L. Ferreira, R. Mady, E. Wilson, K. Bietsch, G. Adero, P. Kaberia, R. Kananura, M. Mutua, A. Njeri, E. Wekesa (2026). Model checks for Bayesian estimation and forecasting of health coverage indicators in low- and middle-income countries. Philosophical Transactions A 384 (2321): 20240609. https://doi.org/10.1098/rsta.2024.0609

  • See https://alkemalab.github.io/bayescoveragemodel/ for R package

• L.G. Garraza*, I.S. Speizer, L. Alkema (2026). Combining BART and Principal Stratification to estimate the effect of intermediate variables on primary outcomes with application to estimating the effect of family planning on employment in Nigeria and Senegal. Statistics and Public Policy. https://doi.org/10.1080/2330443X.2026.2672981.

  • See https://alkemalab.github.io/prince_BART/ for R package

• D. You, L. Hug, G. Fell, Y. Liu, D. Sharrow, P. Gerland, B. Masquelier, L. Alkema, …, E. Suzuki (2026). Global, Regional, and National Levels and Trends in Older Child, Adolescent, and Youth (5-24 Years) All Cause Mortality from 1990 to 2024: Modelling Study. BMJ 393: e088685. https://doi.org/10.1136/bmj-2025-088685.

• H. Comiskey, N. Cahill, L. Alkema, D.T. Frazier, W. Maneesoonthorn (2026). Bayesian Probabilistic Projections of Proportions with Limited Data: An Application to Subnational Contraceptive Method Supply Shares. PLOS ONE 21 (4): e0345413. https://doi.org/10.1371/journal.pone.0345413.

• H. Susmann^* and L. Alkema (2025). Flexible modeling of demographic transition processes with a Bayesian hierarchical B-splines model. Journal of the Royal Statistical Society Series C: Applied Statistics. See https://doi.org/10.48550/arXiv.2301.09694 and https://arxiv.org/abs/2301.09694.

• J.A. Cresswell, M. Alexander, M.Y.C. Chong, H.M. Link, M. Pejchinovska, U. Gazeley, S.A. Ahmed, D. Chou, A.B. Moller, D. Simpson, L. Alkema, G. Villanueva, Y. Sguassero, Ö. Tunçalp, Q. Long, S. Xiao, L. Say (2025). Global and Regional Causes of Maternal Deaths 2009–20: A WHO Systematic Analysis. The Lancet Global Health 13, no. 4 (April 1, 2025): e626–34. https://doi.org/10.1016/S2214-109X(24)00560-6.

• Amouzou, A.J.D. Barros, J. Requejo, C. Faye, .. , L. Alkema, …, D. You, M. Chopra, R.E. Black, T. Boerma (2025). The 2025 Report of the Lancet Countdown to 2030 for Women’s, Children’s, and Adolescents’ Health: Tracking Progress on Health and Nutrition. The Lancet 405(10488): 1505–54. https://doi.org/10.1016/S0140-6736(25)00151-5.

• L.G. Garraza*, C. Cardona, P. Gichangi, M. Thiongo, P. Anglewicz, L. Alkema (2025). Using Balancing Weights to Compare Performance across Facilities Providing Family Planning Services in Kenya. Health Services and Outcomes Research Methodology 2: 328–359. https://doi.org/10.1007/s10742-025-00342-z.

• E.N. Peterson^*, G. Guranich^*, J.A. Cresswell, L. Alkema (2024). A Bayesian approach to estimate maternal mortality globally using national civil registration vital statistics data accounting for reporting errors. Statistics and Public Policy 11 (1): 2286313.

• H Comiskey, L Alkema, N Cahill (2024). Estimating the proportion of modern contraceptives supplied by the public and private sectors using a Bayesian hierarchical penalized spline model. Journal of the Royal Statistical Society Series A: Statistics in Society https://doi.org/10.1093/jrsssa/qnae051.

• F. Chao, B. Masquelier, D. You, L. Hug, Y. Liu, D. Sharrow, H. Rue, H. Ombao, L. Alkema (2023). Sex Differences in Mortality among Children, Adolescents, and Young People Aged 0–24 Years: A Systematic Assessment of National, Regional, and Global Trends from 1990 to 2021. The Lancet Global Health 11 (10)): e1519–30. https://doi.org/10.1016/S2214-109X(23)00376-5.

• C.H. Lee, H. Susmann^*, L. Alkema (2023). New measures for family planning and exposure to risk of pregnancy based on sexual activity and contraceptive use data. Studies in Family Planning 54(1): 145–60. https://doi.org/10.1111/sifp.12225.

• J.M. Bearak, L. Alkema, V. Kantorova, J. Casterline (2023). Alignment between desires and outcomes among women wanting to avoid pregnancy: a global comparative study of ‘conditional’ unintended pregnancy rates. Studies in Family Planning 54(1): 265–80. https://doi.org/10.1111/sifp.12234.

• Z. Wang^*, M. Fix, L. Hug, A. Mishra, D. You, H. Blencowe, J. Wakefield, L. Alkema (2022). Estimating the stillbirth rate for 195 countries using a Bayesian sparse regression model with temporal smoothing. Annals of Applied Statistics 16(4): 2101-2121. DOI: 10.1214/21-AOAS1571.

• M. Alexander and L. Alkema (2022). A Bayesian cohort component projection model to estimate women of reproductive age at the subnational level in data-sparse settings. Demography 59 (5): 1713–1737. https://doi.org/10.1215/00703370-10216406.

• A. Dharamshi, B. Barakat, L. Alkema, M. Antoninis (2022). A Bayesian model for estimating Sustainable Development Goal indicator 4.1.2: School completion rates. Journal of the Royal Statistical Society: Series C 71(5): 1822-1864.

• J. Bearak, A. Popinchalk, B. Ganatra, A. Moller, Ö. Tunçalp, C. Beavin, L. Kwok, L. Alkema (2022). Country-specific estimates of unintended pregnancy and abortion incidence: a global comparative analysis of levels in 2015–2019. BMJ Global Health 7: e007151. https://gh.bmj.com/content/7/3/e007151.

• H. Susmann^*, M. Alexander, L. Alkema (2022). Temporal models for demographic and global health outcomes in multiple populations: Introducing a new framework to review and standardize documentation of model assumptions and facilitate model comparison. International Statistical Review 90(3): 437–67. https://doi.org/10.1111/insr.12491.

• E. Peterson^*, D. Chou, A.B. Moller, A. Gemmill, L. Say, L. Alkema (2022). Estimating misclassification errors in the reporting of maternal mortality in national civil registration vital statistics systems: A Bayesian hierarchical bivariate random walk model to estimate sensitivity and specificity for multiple countries and years with missing data. Statistics in Medicine 41:2483–2496. https://onlinelibrary.wiley.com/doi/full/10.1002/sim.9335.

• D. Sharrow, L. Hug, D. You, L. Alkema, R. Black, S. Cousens, T. Croft, V. Gaigbe-Togbe, P. Gerland, M. Guillot, K. Hill, B. Masquelier, C. Mathers, J. Pedersen, K. Strong, E. Suzuki, J. Wakefield, N. Walker (2022). Global, regional and national trends in under-5 mortality 1990-2019 with scenario-based projections to 2030: a systematic analysis by the United Nations Inter-agency Group for Child Mortality Estimation. The Lancet Global Health 10(2): e195–206. https://doi.org/10.1016/S2214-109X(21)00515-5.

• F. Chao^*, A.R. Cook, P. Gerland, L. Alkema (2021). Global estimation and scenario-based projections of sex ratio at birth and missing female births using a Bayesian hierarchical time series mixture model. Annals of Applied Statistics 15(3): 1499-1528.

• N. Cahill, E. Sonneveldt, P. Emmart, J. Williamson, R. Mbu, A. Barrière Fodjo Yetgang, I. Dambula, G. Azambuja, A. Mahumane Govo, B. Joshi, S. Felix, C. Makashaka, V. Ndaruhutse, J. Serucaca, B. Madzima, B. Muzavazi, L. Alkema (2021). Using family planning service statistics to inform model-based estimates of modern contraceptive prevalence. Plos One 16(10), e0258304.

• L. Hug, D. You, H. Blencowe, A. Mishra, Z. Wang^*, M. Fix, J. Wakefield, A. Moran, V. Gaigbe-Togbe, E. Suzuki, D. Blau, S. Cousens, A. Creanga, T. Croft, K. Hill, K Joseph, S. Maswime, E. McClure, R. Pattinson, J. Pedersen, L. Smith, J. Zeitlin, L. Alkema (2021). Global, regional, and national levels and trends in stillbirths from 2000 to 2019: a systematic assessment. The Lancet 398 (10302): 772–85.

• F. Chao^*, A.R. Cook, P. Gerland, C. Guilmoto, L. Alkema (2021). Projecting sex imbalances at birth at global, regional and national levels from 2021 to 2100: scenario-based Bayesian probabilistic projections of the sex ratio at birth and missing female births based on 3.26 billion birth records. BMJ Global Health (6): e005516.

• G. Guranich*, N. Cahill, L. Alkema (2021). Fpemlocal: Estimating family planning indicators in R for a single population of interest. Gates Open Research 5 (24).

• B. Masquelier, L. Hug, D. Sharrow, D. You, C. Mathers, P. Gerland, L. Alkema (2021). Global, regional, and national mortality trends in youth aged 15–24 years between 1990 and 2019: a systematic analysis. The Lancet Global Health 9 (4): e409–17.

• N. Cahill, M. Weinberger, L. Alkema (2020). What increase in modern contraceptive use is needed in FP2020 countries to reach 75% demand satisfied by 2030? An assessment using the Accelerated Transition Method and Family Planning Estimation Model. Gates Open Research 4 (113).

• J. Bearak, A. Popinchalk, B. Ganatra, A. Moller, Ö. Tunçalp, C. Beavin, L. Kwok, L. Alkema (2020). Unintended Pregnancy and Abortion by Income, Region, and the Legal Status of Abortion: Estimates from a Comprehensive Model for 1990–2019. The Lancet Global Health 8(9): e1152–61.

• 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.

• J. Bearak, A. Popinchalk, G. Sedgh, B. Ganatra, A. Moller, Ö. Tunçalp, L. Alkema (2019). Pregnancies, abortions, and pregnancy intentions: a protocol for modeling and reporting global, regional and country estimates. Reproductive Health 16(1) 36.

• L. Hug, M. Alexander^*, D. You, L. Alkema (2019). National, regional, and global levels and trends in neonatal mortality between 1990 and 2015, with scenario-based projections to 2030: a systematic analysis by the United Nations Inter-agency Group for Child Mortality Estimation. The Lancet Global Health 7(9), e710-e720.

• B. Masquelier, L. Hug, D. Sharrow, D. You, D. Hogan, K. Hill, J. Liu, J. Pedersen, L. Alkema (2018). Global, regional, and national levels and trends in mortality among older children (5-9) and young adolescents (10-14) from 1990 to 2016. The Lancet Global Health 6(10): e1087-e1099.

• F. Chao^*, D. You, J. Pedersen, L. Hug, L. Alkema (2018). National and regional under-5 mortality rate by economic status for low-income and middle-income countries: a systematic assessment. The Lancet Global Health 6(5): e535-e547.

• J. Bearak, A Popinchalk, L. Alkema, G. Sedgh (2018). Global, regional, and subregional trends in unintended pregnancy and its outcomes from 1990 to 2014: estimates from a Bayesian hierarchical model. The Lancet Global Health 6(4): e380 - e389.

• M. Alexander^*, L. Alkema (2018). Global estimation of neonatal mortality using a Bayesian hierarchical splines regression model. Demographic Research 38: 335 – 372.

• 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.

• B. Ganatra, C. Gerdts, C. Rossier, R. Johnson, Ö. Tunçalp, A. Assifi, G. Sedgh, S. Singh, A. Bankole, A. Popinchalk, J. Bearak, Z. Kang^*, L. Alkema (2017). Global, regional and sub-regional classification of abortions by safety: Estimates for 2010-14. The Lancet 390(10110): 2372-2381.

• L. Alkema, S. Zhang^*, D. Chou, A. Gemmill^*, A.B. Moller, D.M. Fat, L. Say, C.D. Mathers, D. Hogan. A Bayesian approach to the global estimation of maternal mortality (2017). The Annals of Applied Statistics 11(3): 1245 – 1274.

• V. Kantorova, J.R. New^*, A. Biddlecom, L. Alkema (2017). Setting ambitious yet achievable targets using probabilistic projections: meeting demand for family planning. Studies in Family Planning 48(3): 223 – 233.

• J.R. New^*, N. Cahill^*, J. Stover, Y.P. Gupta, L. Alkema (2017). Subnational Rates and Trends in Contraceptive Prevalence and Unmet Need for Family Planning from 1990 to 2020: An Analysis for All 29 States in India. The Lancet Global Health 5(3): e350-e358.

• 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.

• 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 386(10010): 2275–2286.

• 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.

• 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.

• P. Gerland, A.E. Raftery, H. Ševčíková, 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.

• 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.

• 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.

• L. Say, D. Chou, A. Gemmill^*, Ö. Tunçalp, A.B. Moller, J. Daniels, A.M. Gülmezoglu, M. Temmerman, L. Alkema (2014). Global causes of maternal deaths: A WHO systematic analysis. The Lancet Global Health 2(6): e323–e3332.

• 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.

• A.E. Raftery, L. Alkema, P. Gerland (2014). Bayesian population projections for the United Nations. Statistical Science, 29(1): 56–68.

• 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.

• 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.

• 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.

• 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.

• 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.

• 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.

• 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.

• 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.

• L. Alkema, W.L. Ann^* (2011). Estimating the under-5 mortality rate using a Bayesian hierarchical time series model. PLOS ONE 6(9): e23954.

• 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.

• H. Ševčíková, 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.

• 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.

• 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.

• 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.

• 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.

• 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.

Working papers and preprints

• L. Alkema, H. Susmann, E. Ray (2024). Temporal Models for Demographic and Global Health Outcomes in Multiple Populations: Introducing the Normal-with-Optional-Shrinkage Data Model Class. See https://doi.org/10.48550/arXiv.2411.18646.
• J. Bearak, L. Alkema, E. Sully, and O. Owolabi (2026). Methodological Considerations in Attributing Maternal Mortality Reduction to Contraception and Fertility Decline. Comment in The Lancet Global Health 14 (4): e493. https://doi.org/10.1016/S2214-109X(25)00523-6.
• L.G. Garraza*, L. Alkema (2025). Does fertility affect woman’s labor force participation in low- and middle-income settings? Findings from a Bayesian nonparametric analysis. See https://arxiv.org/abs/2508.10787.
• S. Mooney*, L. Alkema, E. Sonneveldt, K. Bietsch, J. Williamson, N. Cahill (2024). Enhancing the Use of Family Planning Service Statistics Using a Bayesian Modelling Approach to Inform Estimates of Modern Contraceptive Use in Low- and Middle-Income Countries. See https://doi.org/10.48550/arXiv.2412.08606.
• S. Mooney*, L. Alkema, H. Comiskey, E. Sonneveldt, K. Bietsch, J. Williamson, R. Rosenberg, M. Reeves, N. Cahill (2024). Considering the Role of the Private Sector Adjustment in Calculating Estimated Modern Use from Family Planning Service Statistics. See https://verixiv.org/articles/2-27/v1.
• H. Susmann and L. Alkema (2024). Flexibly Modeling Shocks to Demographic and Health Indicators with Bayesian Shrinkage Priors. See https://doi.org/10.48550/arXiv.2410.09217.