For a complete list of publications, please see my Google Scholar profile. Below preprints and journal publications are listed by research area ( denotes student, * denotes equal contribution).


  1. Levin, A., Owusu-Boaitey, N., Pugh, S., Fosdick, B.K., Zwi, A.B., Malani, A., Soman, S., Besançon, L., Kashnitsky, I., Ganesh, S., McLaughlin, A., Song, G., Uhm, R., Meyerowitz-Katz, G., Assessing the Burden of COVID-19 in Developing Countries: Systematic Review, Meta-Analysis, and Public Policy Implications. to appear in BMJ Global Health [preprint]

  1. Fosdick, B.K., Bayham, J., Dilliott, J., Ebel, G.D and Ehrhart, N., Model-based Evaluation of Continued COVID-19 Risk at Long Term Care Facilities. [preprint] [interactive tool]

  1. Lopez, C.A, Cunningham, C.H., Pugh, S. , Brandt, K., Vanna, U.P.,..., Fosdick, B.K, ..., Markmann, A.J., (2022) Disparities in SARS-CoV-2 seroprevalence among individuals presenting for care in central North Carolina over a six-month period. to appear in mSphere. [preprint]

  1. Gallichotte, E.N., Nehring, M., Young, M.C., Pugh, S., Sexton, N.R., Fitzmeyer, E., Quicke, K.M., Richardson, M., Pabilonia, K.L., Ehrhart, N., Fosdick, B.K., VandeWoude, S., and Ebel, G.D., (2021) Durable antibody responses in staff at two long-term care facilities, during and post SARS-CoV-2 outbreaks. Microbiology Spectrum. 9(1):e00224-21. [DOI]

  1. Larremore, D.B.*, Fosdick, B.K.*, Zhang, S., and Grad, Y.H., Jointly modeling prevalence, sensitivity and specificity for optimal sample allocation. [preprint]

  2. Fout, A., Bayham, J., Gutilla, M., Fosdick, B.K., Pidcoke, H., Kirby, M., van Leeuwen, P.J., and Anderson, C., Estimating COVID-19 cases on university campuses prior to semester. [preprint]

  1. Nelson, T.L., Fosdick B.K., Biela, L., Shoenberg, H., Mast, S., McGinnis, E., Young, M., Lynn, L., Fahrner, S., Nolt, L., Ebel, G.D., Pabilonia, K., Ehrhart, N., and VandeWoude, S., (2021) Association between COVID-19 exposure and self-reported compliance with public health guidelines among essential employees at an institute of higher education. JAMA Network Open. 4(7):e2116543. [DOI]

  1. Nisar, M.I., Ansari, N., Khalid, F., Amin, M., Shahbaz, H., Hotwani, A., Rehman, N., Pugh, S., Mehmood, U., Rizvi, A., Memon, A., Ahmed, Z., Ahmed, A., Iqbal, J., Saleem, A.F., Aamir, U.B., Larremore, D.B., Fosdick, B.K., and Jehan, F., (2021) Serial population-based sero-surveys for COVID-19 in two neighborhoods of Karachi, Pakistan. International Journal of Infectious Diseases. 106:176-182. [DOI]

  1. Larremore, D.B, Fosdick, B.K., Bubar, K.M., Zhang, S., Kissler, S.M., Metcalf, J.E., Buckee, C.O., and Grad, Y.H., (2021) Estimating SARS-CoV-2 seroprevalence and epidemiological parameters with uncertainty from serological surveys. eLife [DOI] [interactive calculation tool][code]

  1. Layer, R.M., Fosdick, B.K., Bradshaw, M., Larremore, D.B., and Doherty, P., (2020) Case study: Using Facebook data to monitor adherence to stay-at-home orders in Colorado and Utah. ACM SIGKDD Conference on Knowledge Discovery and Data Mining, Workshop on Humanitarian Data Mapping [link]

Relational Data/Networks

  1. Marrs, F.W., Fosdick, B.K., and McCormick, T.H., (2022) Standard errors for regression on relational data with exchangeable errors. Biometrika [preprint][code]

  2. Marrs, F.W. and Fosdick, B.K., Regression of binary network data with exchangeable latent errors. [preprint]

  3. Pan, M., McCormick, T.H., and Fosdick, B.K., (2021) Inference for network regression models with community structure. Proceedings of the 38th International Conference on Machine Learning. PMLR 139.

  4. Ng, T.L.J., Murphy, T.B., Westling, T., McCormick, T.H., and Fosdick, B.K., (2021) Modeling the social media relationships of Irish politicians using a generalized latent space stochastic blockmodel. Annals of Applied Statistics. 15(4): 1923-1944.

  5. Fout, A., Fosdick, B.K., and Hitt, M., (2020) Non-uniform sampling of fixed margin binary matrices. Proceedings of the 2020 ACM-IMS on Foundations of Data Science Conference (FODS ’20). Association for Computing Machinery, New York, NY, USA, 95–105. [DOI]

  6. Marrs, F.W., Campbell, B.W., Fosdick, B.K., Cranmer, S.J., and Böhmelt, T., (2020) Inferring influence networks from longitudinal bipartite relational data. Journal of Computational and Graphical Statistics. 29(3), 419-431. [DOI][code]

  7. Campbell, B.W., Marrs, F.W., Böhmelt, T., Fosdick, B.K., and Cranmer, S.J., (2019) Latent influence networks in global environmental politics. PLOS One. 14(3). [DOI]

  8. Fosdick, B.K., McCormick, T.H., Murphy, T.B., Ng T.L.J., and Westling, T., (2019) Multiresolution network models. Journal of Computational and Graphical Statistics. 28(1), 185-196. [DOI][code]

  9. Fosdick, B.K.*, Larremore, D.B.*, Nishimura, J.* and Ugander, J.*, (2018) Configuring random graph models with fixed degree sequences. SIAM Review. 60(2):315-355. [DOI][code]

  10. Lee, W., Fosdick, B.K., and McCormick, T.H., (2018) Inferring social structure from continuous-time interaction data. Applied Stochastic Models in Business and Industry. 34(2):87-104. [DOI][code]

  11. Scharf, H.R., Hooten, M.B., Fosdick, B.K., Johnson, D.S., London, J.M., and Durban, J.W., (2016) Dynamic social networks based on movement. Annals of Applied Statistics. 10(4):2182-2202. [DOI][code]

  12. Fosdick, B.K. and Hoff, P.D., (2015) Testing and jointly modeling dependencies between a network and nodal attributes. Journal of the American Statistical Association. 110(511):1047-1056.

  13. Hoff, P.D., Fosdick, B.K., Volfovsky, A., and Stovel, K., (2013) Likelihoods for fixed rank nomination networks. Network Science. 1:253-277. [DOI]

Multivariate Analysis

  1. Fosdick, B.K., De Yoreo, M., and Reiter, J.P., (2016) Categorical data fusion using auxiliary information. Annals of Applied Statistics. 10(4):1907-1929. [DOI][code]

  2. Fosdick, B.K. and Perlman, M.D., (2014) Variance-stabilizing and confidence-stabilizing transformations for the normal correlation coefficient with known variances. Communications in Statistics - Simulation and Computation. Published online. [DOI]

  3. Fosdick, B.K. and Hoff, P.D., (2014) Separable factor analysis with applications to mortality data. Annals of Applied Statistics. 8(1):120-147. [DOI]

  4. Fosdick, B.K. and Perlman, M.D., (2013) Covariate and Newton-Raphson adjustments for a normal correlation coefficient when the variances are known. Statistics and Probability Letters. 83(12):2627-2633. [DOI]

  5. Fosdick, B.K. and Raftery, A.E., (2012) Estimating the correlation in bivariate normal data with known variances and small sample sizes. The American Statistician. 66(1):34-41. [DOI]


  1. Safran, R.J., Levin, I.I., Fosdick, B.K., McDermott, M.T., Semenov, G.A., Hund, A.K., Scordato, E.S.C., and Turbek, S.P., (2019) Using networks to connect individual-level reproductive behavior to population patterns. Trends in Ecology and Evolution. 34(6):497-501. [DOI]

  2. Levin, I.I., Fosdick, B.K., Tsunekage, T., Aberle, M.A., Bergeon-Burns, C.M., Hund, A.K., and Safran, R.J., (2018) Experimental manipulation of a signal trait reveals complex phenotype-behaviour coordination. Scientific Reports. 8:15533. [DOI]

  3. Levin, I., Zonana, D., Fosdick, B.K., Song, S.J., Knight, R. and Safran, R., (2015) Stress response, gut microbial diversity, and sexual signals correlate with social interactions. Biology Letters. 12(6). [DOI]

Team Science

  1. Love, H.B., Fosdick, B.K., Cross, J.E., Suter, M., Eagan, D., Scofidio, E., and Fisher, E., Evaluation of Science of Team Science (SciTS) Methods: Significant Metrics and Measures. Submitted.

  1. Love, H.B., Cross, J.E., Fosdick, B.K., Scofidio, E., and Dickmann, E.M., Teaching team science: Preparing students for global knowledge-economy teams. [preprint]

  1. Love, H.B., Cross, J.E., Fosdick, B.K., Crooks, K., VandeWoude, S., and Fisher, E., (2021) Interpersonal relationships drive successful team science: an exemplary case-based study. Humanities & Social Sciences Communications. 8(106). [DOI]


  1. Gerland, P., Raftery, A.E., Sevcikova, H., Li, N., Gu, D., Spoorenber, T., Alkema, L., Fosdick, B.K., Chunn, J., Lalic, N., Bay, G., Buettner, T., Heilig, G., Wilmoth, J., (2014) World population stablilization unlikely this century. Science. 346:234-237. [reprint][DOI]

  2. Fosdick, B.K. and Raftery, A.E., (2014) Regional probabilistic fertility forecasting by modeling between-country correlations. Demographic Research. 30:1011-1034. [DOI]

STEM Education

  1. Ellis, J., Johnson, E., and Fosdick, B.K., (2017) Factors contributing to students and instructors experiencing a lack of time in college calculus. International Journal of STEM Education. 4(12). [DOI]

  2. Ellis, J, Fosdick, B.K., and Rasmussen, C., (2015) Women 1.5 times more likely to leave STEM pipeline after calculus compared to men: Lack of mathematical confidence a potential culprit. PLoS ONE. 11(7): e0157447. [DOI]

  3. Hagman, J., Basile, PV., Birmingham, D., and Fosdick, B.K., (2018) Challenging the sigma of a small N: Experiences of students of color in Calculus I. Proceedings of the 40th annual meeting of the North American Chapter of the International Group for the Psychology of Mathematics Education (n T.E. Hodges, G. J. Roy, and Tyminski, A. M.), pp. 1339-1342.

Sports Statistics

  1. Manzione, K. , Elmore, R., Fosdick, B.K., and Gibbs, C., The Impact of Altitude Training on NCAA Division I Female Swimmers’ Performance. Submitted.

  1. Gibbs, C.P., Elmore, R., and Fosdick, B.K., (2022+) The causal effect of a timeout at stopping an opposing run in the NBA. [preprint] To appear in Annals of Applied Statistics.


  1. Buckee, C. et al. (2020) Women in science are battling both COVID-19 and the patriarchy. Times Higher Education. [link]

  1. Fosdick, B.K. and Anderson, G.B., (2020) Review of "Modern Statistics in Modern Biology". The American Statistician. 74:3, 309-311 [link]

  1. Huzurbazar, S., Cisewski, J., Fosdick, B.K., and Wang, X. (2014) Opportunities at SAMSI and NISS. Chance. [link]

  1. von Fischer, J.C., Rhew, R.C., Ames, G.M., Fosdick, B.K., von Fischer, P. E., (2010) Vegetation height and other controls of spatial variability in methane emissions from the Arctic coastal tundra at Barrow, Alaska. Journal of Geophysical Research. 115, G00103. [DOI]

  1. Draper (Fosdick), B., Marcin, D., Margolskee, A., Murden, R., Attarian, A., Evans, M.V., and Yokley, K.A., (2009) Feasibility of metabolic parameter estimation in pharmacokinetic models of carbon tetrachloride exposure in rats. Toxicological & Environmental Chemistry. 91(3):521-546. [DOI]