Hilton, J., Riley, H., Pellis, L., Aziza, R., Brand, S. P. C., K. Kombe, I., Ojal, J., Parisi, A., Keeling, M. J., Nokes, D. J., Manson-Sawko, R., & House, T. (2022). A computational framework for modelling infectious disease policy based on age and household structure with applications to the COVID-19 pandemic. PLo S Computational Biology, 18(9), 1-38. https://doi.org/10.1371/journal.pcbi.1010390

HILTON, Joe, RILEY, Heather, PELLIS, Lorenzo, AZIZA, Rabia, BRAND, Samuel P. C., K. KOMBE, Ivy, OJAL, John, PARISI, Andrea, KEELING, Matt J., NOKES, D. James, MANSON-SAWKO, Robert und HOUSE, Thomas, 2022. A computational framework for modelling infectious disease policy based on age and household structure with applications to the COVID-19 pandemic. PLo S Computational Biology. 6 September 2022. Vol. 18, no. 9, p. 1-38. DOI 10.1371/journal.pcbi.1010390.

Hilton, J., H. Riley, L. Pellis, R. Aziza, S. P. C. Brand, I. K. Kombe, J. Ojal, A. Parisi, M. J. Keeling, D. J. Nokes, R. Manson-Sawko, und T. House. „A Computational Framework for Modelling Infectious Disease Policy Based on Age and Household Structure With Applications to the COVID-19 Pandemic.“. PLo S Computational Biology, Bd. 18, Nr. 9, September 2022, S. 1-38, https://doi.org/10.1371/journal.pcbi.1010390.

Hilton, Joe/Riley, Heather/Pellis, Lorenzo/Aziza, Rabia/Brand, Samuel P. C./K. Kombe, Ivy u. a.: A computational framework for modelling infectious disease policy based on age and household structure with applications to the COVID-19 pandemic., PLo S Computational Biology 2022, 1-38.

Hilton, J., Riley, H., Pellis, L., Aziza, R., Brand, S.P.C., K. Kombe, I., Ojal, J., Parisi, A., Keeling, M.J., Nokes, D.J., Manson-Sawko, R. und House, T. (2022), „A computational framework for modelling infectious disease policy based on age and household structure with applications to the COVID-19 pandemic.“, PLo S Computational Biology, Vol. 18 No. 9, S. 1-38.