2024

Gamal, Y. , Elsenbroich, C. , Gilbert, N., Heppenstall, A. and Zia, K. (2024) A behavioural agent-based model for housing markets: impact of financial shocks in the UK. Journal of Artificial Societies and Social Simulation, 27(4), 5. (doi: 10.18564/jasss.5518) (Accepted for Publication)

Bullock, S. et al. (2024) Artificial intelligence for collective intelligence: A national-scale research strategy. Knowledge Engineering Review, (Accepted for Publication)

Squires, H. et al. (2024) The PHEM-IB toolbox of methods for incorporating the influences on behaviour within public health economic models. BMC Public Health, (Accepted for Publication)

Olmez, S., Birks, D., Heppenstall, A. and Ge, J. (2024) Learning the rational choice perspective: a reinforcement learning approach to simulating offender behaviours in criminological agent-based models. Computers, Environment and Urban Systems, 112, 102141. (doi: 10.1016/j.compenvurbsys.2024.102141)

Olmez, S., Heppenstall, A. , Ge, J., Elsenbroich, C. and Birks, D. (2024) Mitigating housing market shocks: an agent-based reinforcement learning approach with implications for real-time decision support. Journal of Simulation, (doi: 10.1080/17477778.2024.2375446) (Early Online Publication)

Lewis, D., Comrie, E., Hoehn, A. , Lomax, N., Heppenstall, A. , Purshouse, R., Zia, K. and Meier, P. (2024) SIPHER Synthetic Population for Individuals in Great Britain (2019-2021) - Interactive R-Shiny Dashboard. [Website]

Kopasker, D. et al. (2024) Evaluating the influence of taxation and social security policies on psychological distress: a microsimulation study of the UK during the COVID-19 economic crisis. Social Science and Medicine, 351, 116953. (doi: 10.1016/j.socscimed.2024.116953) (PMID:38759385)

Heppenstall, A. , Wang, M. , Demsar, U., Lemmens, R. and Yao, J. (2024) Preface. AGILE: GIScience Series, 5, 1. (doi: 10.5194/agile-giss-5-1-2024)

Heppenstall, A. , Wang, M. , Demsar, U., Lemmens, R. and Yao, J. (Eds.) (2024) 27th AGILE Conference on Geographic Information Science “Geographic Information Science for a Sustainable Future”. AGILE: GIScience Series. 5 [Edited Journal]

Wolf, L. J., Harris, R. and Heppenstall, A. (Eds.) (2024) A Research Agenda for Spatial Analysis. Series: Elgar Research Agendas. Edward Elgar. ISBN 9781802203226

Brown, H. et al. (2024) Association between individual level characteristics and take-up of a Minimum Income Guarantee for Pensioners: Panel Data Analysis using data from the British Household Panel survey 1999–2002. Social Sciences & Humanities Open, 9, 100847. (doi: 10.1016/j.ssaho.2024.100847)

2023

Wijermans, N., Scholz, G., Chappin, E., Heppenstall, A. , Filatova, T., Polhill, J. G., Semeniuk, C. and Stöppler, F. (2023) Agent decision-making: the elephant in the room: enabling the justification of decision model fit in social-environmental models. Environmental Modelling and Software, 170, 105850. (doi: 10.1016/j.envsoft.2023.105850)

Griffiths, C. et al. (2023) A complex systems approach to obesity: a transdisciplinary framework for action. Perspectives in Public Health, 143(6), pp. 305-309. (doi: 10.1177/17579139231180761) (PMID:37395317) (PMCID:PMC10683338)

Antosz, P., Birks, D., Edmonds, B., Heppenstall, A. , Meyer, R., Polhill, J. G., O’Sullivan, D. and Wijermans, N. (2023) What do you want theory for? A pragmatic analysis of the roles of “theory” in agent-based modelling. Environmental Modelling and Software, 168, 105802. (doi: 10.1016/j.envsoft.2023.105802)

Heppenstall, A. , Polhill, J. G., Batty, M., Hare, M., Salt, D. and Milton, R. (2023) Exascale Agent-Based Modelling for Policy Evaluation in Real-Time (ExAMPLER). In: 12th International Conference on Geographic Information Science (GIScience 2023), Leeds, UK, 12-15 Sept 2023, 38:1-38:5. ISBN 9783959772884 (doi: 10.4230/LIPIcs.GIScience.2023.38)

Feng, Z. , Zhao, Q. and Heppenstall, A. (2023) Understanding the Complex Behaviours of Electric Vehicle Drivers with Agent-Based Models in Glasgow. In: 12th International Conference on Geographic Information Science (GIScience 2023), Leeds, UK, 14-19 Sept 2023, 29:1-29:6. ISBN 9783959772884 (doi: 10.4230/LIPIcs.GIScience.2023.29)

Höhn, A. et al. (2023) Systems science methods in public health: what can they contribute to our understanding of and response to the cost-of-living crisis? Journal of Epidemiology and Community Health, 77(9), pp. 610-616. (doi: 10.1136/jech-2023-220435) (PMID:37328262) (PMCID:PMC10423532)

An, L. et al. (2023) Modeling agent decision and behavior in the light of data science and artificial intelligence. Environmental Modelling and Software, 166, 105713. (doi: 10.1016/j.envsoft.2023.105713)

Franklin, R. S. et al. (2023) Making space in geographical analysis. Geographical Analysis, 55(2), pp. 325-341. (doi: 10.1111/gean.12325)

2022

Sucharyna Thomas, L., Wickham-Jones, C. R. and Heppenstall, A. J. (2022) Combining agent-based modelling and geographical information systems to create a new approach for modelling movement dynamics: a case study of Mesolithic Orkney. Open Archaeology, 8, pp. 987-1009. (doi: 10.1515/opar-2022-0257)

Boyd, J., Wilson, R., Elsenbroich, C. , Heppenstall, A. and Meier, P. (2022) Agent-based modelling of health inequalities following the complexity turn in public health: a systematic review. International Journal of Environmental Research and Public Health, 19(24), 16807. (doi: 10.3390/ijerph192416807) (PMID:36554687) (PMCID:PMC9779847)

Wallace, R., Franklin, R., Grant-Muller, S., Heppenstall, A. and Houlden, V. (2022) Estimating the social and spatial impacts of Covid mitigation strategies in United Kingdom regions: synthetic data and dashboards. Cambridge Journal of Regions, Economy and Society, 15(3), pp. 683-702. (doi: 10.1093/cjres/rsac019)

Ternes, P., Ward, J. A., Heppenstall, A. , Kumar, V., Kieu, L.-M. and Malleson, N. (2022) Data assimilation and agent-based modelling: towards the incorporation of categorical agent parameters. Open Research Europe, 1, 131. (doi: 10.12688/openreseurope.14144.2)

Olmez, S., Thompson, J., Marfleet, E., Suchak, K., Heppenstall, A. , Manley, E., Whipp, A. and Vidanaarachchi, R. (2022) An agent-based model of heterogeneous driver behaviour and its impact on energy consumption and costs in urban space. Energies, 15(11), 4031. (doi: 10.3390/en15114031)

Urquhart, R., Newing, A., Hood, N. and Heppenstall, A. (2022) Last-mile capacity constraints in online grocery fulfilment in Great Britain. Journal of Theoretical and Applied Electronic Commerce Research, 17(2), pp. 636-651. (doi: 10.3390/jtaer17020033)

Arnold, K. F., Gilthorpe, M. S., Alwan, N. A., Heppenstall, A. J. , Tomova, G. D., McKee, M. and Tennant, P. W.G. (2022) Estimating the effects of lockdown timing on COVID-19 cases and deaths in England: a counterfactual modelling study. PLoS ONE, 17(4), e0263432. (doi: 10.1371/journal.pone.0263432) (PMID:35421094) (PMCID:PMC9009677)

Gadd, S. C., Comber, A., Gilthorpe, M. S., Suchak, K. and Heppenstall, A. J. (2022) Simplifying the interpretation of continuous time models for spatio-temporal networks. Journal of Geographical Systems, 24(2), pp. 171-198. (doi: 10.1007/s10109-020-00345-z)

McCulloch, J., Ge, J., Ward, J. A., Heppenstall, A. , Polhill, J. G. and Malleson, N. (2022) Calibrating agent-based models using uncertainty quantification methods. Journal of Artificial Societies and Social Simulation, 25(2), 1. (doi: 10.18564/jasss.4791)

Wu, G., Heppenstall, A. , Meier, P. , Purshouse, R. and Lomax, N. (2022) A synthetic population dataset for estimating small area health and socio-economic outcomes in Great Britain. Scientific Data, 9, 19. (doi: 10.1038/s41597-022-01124-9) (PMID:35058471) (PMCID:PMC8776798)

Gadd, S. C., Comber, A., Tennant, P., Gilthorpe, M. S. and Heppenstall, A. J. (2022) The utility of multilevel models for continuous-time feature selection of spatio-temporal networks. Computers, Environment and Urban Systems, 91, 101728. (doi: 10.1016/j.compenvurbsys.2021.101728)

Yang, Y., Beecham, R., Heppenstall, A. , Turner, A. and Comber, A. (2022) Understanding the impacts of public transit disruptions on bikeshare schemes and cycling behaviours using spatiotemporal and graph-based analysis: a case study of four London Tube strikes. Journal of Transport Geography, 98, 103255. (doi: 10.1016/j.jtrangeo.2021.103255)

Malleson, N., Birkin, M., Birks, D., Ge, J., Heppenstall, A. , Manley, E., McCulloch, J. and Ternes, P. (2022) Agent-based modelling for urban analytics: state of the art and challenges. AI Communications, 35(4), pp. 393-406. (doi: 10.3233/AIC-220114)

2021

An, L. et al. (2021) Challenges, tasks, and opportunities in modeling agent-based complex systems. Ecological Modelling, 457, 109685. (doi: 10.1016/j.ecolmodel.2021.109685)

Smith, D. M., Heppenstall, A. and Campbell, M. (2021) Estimating health over space and time: a review of spatial microsimulation applied to public health. J - An Open Access Journal of Multidisciplinary Science, 4(2), pp. 182-192. (doi: 10.3390/j4020015)

Olmez, S., Douglas-Mann, L., Manley, E., Suchak, K., Heppenstall, A. , Birks, D. and Whipp, A. (2021) Exploring the impact of driver adherence to speed limits and the interdependence of roadside collisions in an urban environment: an agent-based modelling approach. Applied Sciences, 11(12), 5336. (doi: 10.3390/app11125336)

Crooks, A., Heppenstall, A. , Malleson, N. and Manley, E. (2021) Agent-based modeling and the city: A gallery of applications. In: Shi, W., Goodchild, M. F., Batty, M., Kwan, M.-P. and Zhang, A. (eds.) Urban Informatics. Series: Urban book series. Springer, pp. 885-910. ISBN 9789811589836 (doi: 10.1007/978-981-15-8983-6_46)

Whipp, A., Malleson, N., Ward, J. and Heppenstall, A. (2021) Estimates of the ambient population: assessing the utility of conventional and novel data sources. ISPRS International Journal of Geo-Information, 10(3), 131. (doi: 10.3390/ijgi10030131)

Heppenstall, A. , Crooks, A., Malleson, N., Manley, E., Ge, J. and Batty, M. (2021) Future developments in geographical agent‐based models: challenges and opportunities. Geographical Analysis, 53(1), pp. 76-91. (doi: 10.1111/gean.12267) (PMID:33678813) (PMCID:PMC7898830)

Roxburgh, N., Stringer, L. C., Evans, A., GC, R. K., Malleson, N. and Heppenstall, A. J. (2021) Impacts of multiple stressors on mountain communities: Insights from an agent-based model of a Nepalese village. Global Environmental Change, 66, 102203. (doi: 10.1016/j.gloenvcha.2020.102203)

Roxburgh, N., Evans, A., GC, R. K., Malleson, N., Heppenstall, A. and Stringer, L. (2021) An empirically informed agent-based model of a Nepalese smallholder village. MethodsX, 8, 101276. (doi: 10.1016/j.mex.2021.101276) (PMID:34434796) (PMCID:PMC8374244)

2020

Yang, Y., Heppenstall, A. , Turner, A. and Comber, A. (2020) Using graph structural information about flows to enhance short-term demand prediction in bike-sharing systems. Computers, Environment and Urban Systems, 83, 101521. (doi: 10.1016/j.compenvurbsys.2020.101521)

Hood, N., Urquhart, R., Newing, A. and Heppenstall, A. (2020) Sociodemographic and spatial disaggregation of e-commerce channel use in the grocery market in Great Britain. Journal of Retailing and Consumer Services, 55, 102076. (doi: 10.1016/j.jretconser.2020.102076)

Malleson, N., Minors, K., Kieu, L.-M., Ward, J. A., West, A. and Heppenstall, A. (2020) Simulating crowds in real time with agent-based modelling and a particle filter. Journal of Artificial Societies and Social Simulation, 23(3), p. 3. (doi: 10.18564/jasss.4266)

Olner, D., Mitchell, G., Heppenstall, A. and Pryce, G. (2020) The spatial economics of energy justice: modelling the trade impacts of increased transport costs in a low carbon transition and the implications for UK regional inequality. Energy Policy, 140, 111378. (doi: 10.1016/j.enpol.2020.111378)

Owen, A. and Heppenstall, A. (2020) Making the case for simulation: Unlocking carbon reduction through simulation of individual ‘middle actor’ behaviour. Environment and Planning B: Urban Analytics and City Science, 47(3), pp. 457-472. (doi: 10.1177/2399808318784597)

Xiang, L., Stillwell, J., Burns, L. and Heppenstall, A. (2020) Measuring and assessing regional education inequalities in China under changing policy regimes. Applied Spatial Analysis and Policy, 13(1), pp. 91-112. (doi: 10.1007/s12061-019-09293-8)

Manson, S. et al. (2020) Methodological issues of spatial agent-based models. Journal of Artificial Societies and Social Simulation, 23(1), 3. (doi: 10.18564/jasss.4174)

Kieu, L.-M., Malleson, N. and Heppenstall, A. (2020) Dealing with uncertainty in agent-based models for short-term predictions. Royal Society Open Science, 7(1), 191074. (doi: 10.1098/rsos.191074) (PMID:32218939) (PMCID:PMC7029931)

2019

Levine, S. Z., Gadd, S. C., Tennant, P. W. G., Heppenstall, A. J. , Boehnke, J. R. and Gilthorpe, M. S. (2019) Analysing trajectories of a longitudinal exposure: A causal perspective on common methods in lifecourse research. PLoS ONE, 14(12), e0225217. (doi: 10.1371/journal.pone.0225217) (PMID:31800576) (PMCID:PMC6892534)

Meier, P. et al. (2019) The SIPHER Consortium: introducing the new UK hub for systems science in public health and health economic research. Wellcome Open Research, 4, 174. (doi: 10.12688/wellcomeopenres.15534.1) (PMID:31815191) (PMCID:PMC6880277)

Yang, Y., Heppenstall, A. , Turner, A. and Comber, A. (2019) A spatiotemporal and graph-based analysis of dockless bike sharing patterns to understand urban flows over the last mile. Computers, Environment and Urban Systems, 77, 101361. (doi: 10.1016/j.compenvurbsys.2019.101361)

Yang, Y., Heppenstall, A. , Turner, A. and Comber, A. (2019) Who, where, why and when? Using smart card and social media data to understand urban mobility. ISPRS International Journal of Geo-Information, 8(6), 271. (doi: 10.3390/ijgi8060271)

Arnold, K.F., Ellison, G.T.H., Gadd, S., Textor, J., Tennant, P.W.G., Heppenstall, A. and Gilthorpe, M.S. (2019) Adjustment for time-invariant and time-varying confounders in ‘unexplained residuals’ models for longitudinal data within a causal framework and associated challenges. Statistical Methods in Medical Research, 28(5), pp. 1347-1364. (doi: 10.1177/0962280218756158) (PMID:29451093) (PMCID:PMC6484949)

Heppenstall, A. and Crooks, A. (2019) Guest editorial for spatial agent-based models: current practices and future trends. GeoInformatica, 23(2), pp. 163-167. (doi: 10.1007/s10707-019-00349-y)

Heppenstall, A. and Crooks, A. (Eds.) (2019) Special Issue on Spatial Agent-Based Models: Current Practices and Future Trends. Geoinformatica. 23(2) [Edited Journal]

Gulma, U. L., Evans, A., Heppenstall, A. and Malleson, N. (2019) Diversity and burglary: Do community differences matter? Transactions in GIS, 23(2), pp. 181-202. (doi: 10.1111/tgis.12511)

Alotaibi, N. I., Evans, A. J., Heppenstall, A. J. and Malleson, N. S. (2019) How well does Western environmental theory explain crime in the Arabian context? The case study of Riyadh, Saudi Arabia. International Criminal Justice Review, 29(1), pp. 5-32. (doi: 10.1177/1057567717709497)

Articles

Gamal, Y. , Elsenbroich, C. , Gilbert, N., Heppenstall, A. and Zia, K. (2024) A behavioural agent-based model for housing markets: impact of financial shocks in the UK. Journal of Artificial Societies and Social Simulation, 27(4), 5. (doi: 10.18564/jasss.5518) (Accepted for Publication)

Bullock, S. et al. (2024) Artificial intelligence for collective intelligence: A national-scale research strategy. Knowledge Engineering Review, (Accepted for Publication)

Squires, H. et al. (2024) The PHEM-IB toolbox of methods for incorporating the influences on behaviour within public health economic models. BMC Public Health, (Accepted for Publication)

Olmez, S., Birks, D., Heppenstall, A. and Ge, J. (2024) Learning the rational choice perspective: a reinforcement learning approach to simulating offender behaviours in criminological agent-based models. Computers, Environment and Urban Systems, 112, 102141. (doi: 10.1016/j.compenvurbsys.2024.102141)

Olmez, S., Heppenstall, A. , Ge, J., Elsenbroich, C. and Birks, D. (2024) Mitigating housing market shocks: an agent-based reinforcement learning approach with implications for real-time decision support. Journal of Simulation, (doi: 10.1080/17477778.2024.2375446) (Early Online Publication)

Kopasker, D. et al. (2024) Evaluating the influence of taxation and social security policies on psychological distress: a microsimulation study of the UK during the COVID-19 economic crisis. Social Science and Medicine, 351, 116953. (doi: 10.1016/j.socscimed.2024.116953) (PMID:38759385)

Heppenstall, A. , Wang, M. , Demsar, U., Lemmens, R. and Yao, J. (2024) Preface. AGILE: GIScience Series, 5, 1. (doi: 10.5194/agile-giss-5-1-2024)

Brown, H. et al. (2024) Association between individual level characteristics and take-up of a Minimum Income Guarantee for Pensioners: Panel Data Analysis using data from the British Household Panel survey 1999–2002. Social Sciences & Humanities Open, 9, 100847. (doi: 10.1016/j.ssaho.2024.100847)

Wijermans, N., Scholz, G., Chappin, E., Heppenstall, A. , Filatova, T., Polhill, J. G., Semeniuk, C. and Stöppler, F. (2023) Agent decision-making: the elephant in the room: enabling the justification of decision model fit in social-environmental models. Environmental Modelling and Software, 170, 105850. (doi: 10.1016/j.envsoft.2023.105850)

Griffiths, C. et al. (2023) A complex systems approach to obesity: a transdisciplinary framework for action. Perspectives in Public Health, 143(6), pp. 305-309. (doi: 10.1177/17579139231180761) (PMID:37395317) (PMCID:PMC10683338)

Antosz, P., Birks, D., Edmonds, B., Heppenstall, A. , Meyer, R., Polhill, J. G., O’Sullivan, D. and Wijermans, N. (2023) What do you want theory for? A pragmatic analysis of the roles of “theory” in agent-based modelling. Environmental Modelling and Software, 168, 105802. (doi: 10.1016/j.envsoft.2023.105802)

Höhn, A. et al. (2023) Systems science methods in public health: what can they contribute to our understanding of and response to the cost-of-living crisis? Journal of Epidemiology and Community Health, 77(9), pp. 610-616. (doi: 10.1136/jech-2023-220435) (PMID:37328262) (PMCID:PMC10423532)

An, L. et al. (2023) Modeling agent decision and behavior in the light of data science and artificial intelligence. Environmental Modelling and Software, 166, 105713. (doi: 10.1016/j.envsoft.2023.105713)

Franklin, R. S. et al. (2023) Making space in geographical analysis. Geographical Analysis, 55(2), pp. 325-341. (doi: 10.1111/gean.12325)

Sucharyna Thomas, L., Wickham-Jones, C. R. and Heppenstall, A. J. (2022) Combining agent-based modelling and geographical information systems to create a new approach for modelling movement dynamics: a case study of Mesolithic Orkney. Open Archaeology, 8, pp. 987-1009. (doi: 10.1515/opar-2022-0257)

Boyd, J., Wilson, R., Elsenbroich, C. , Heppenstall, A. and Meier, P. (2022) Agent-based modelling of health inequalities following the complexity turn in public health: a systematic review. International Journal of Environmental Research and Public Health, 19(24), 16807. (doi: 10.3390/ijerph192416807) (PMID:36554687) (PMCID:PMC9779847)

Wallace, R., Franklin, R., Grant-Muller, S., Heppenstall, A. and Houlden, V. (2022) Estimating the social and spatial impacts of Covid mitigation strategies in United Kingdom regions: synthetic data and dashboards. Cambridge Journal of Regions, Economy and Society, 15(3), pp. 683-702. (doi: 10.1093/cjres/rsac019)

Ternes, P., Ward, J. A., Heppenstall, A. , Kumar, V., Kieu, L.-M. and Malleson, N. (2022) Data assimilation and agent-based modelling: towards the incorporation of categorical agent parameters. Open Research Europe, 1, 131. (doi: 10.12688/openreseurope.14144.2)

Olmez, S., Thompson, J., Marfleet, E., Suchak, K., Heppenstall, A. , Manley, E., Whipp, A. and Vidanaarachchi, R. (2022) An agent-based model of heterogeneous driver behaviour and its impact on energy consumption and costs in urban space. Energies, 15(11), 4031. (doi: 10.3390/en15114031)

Urquhart, R., Newing, A., Hood, N. and Heppenstall, A. (2022) Last-mile capacity constraints in online grocery fulfilment in Great Britain. Journal of Theoretical and Applied Electronic Commerce Research, 17(2), pp. 636-651. (doi: 10.3390/jtaer17020033)

Arnold, K. F., Gilthorpe, M. S., Alwan, N. A., Heppenstall, A. J. , Tomova, G. D., McKee, M. and Tennant, P. W.G. (2022) Estimating the effects of lockdown timing on COVID-19 cases and deaths in England: a counterfactual modelling study. PLoS ONE, 17(4), e0263432. (doi: 10.1371/journal.pone.0263432) (PMID:35421094) (PMCID:PMC9009677)

Gadd, S. C., Comber, A., Gilthorpe, M. S., Suchak, K. and Heppenstall, A. J. (2022) Simplifying the interpretation of continuous time models for spatio-temporal networks. Journal of Geographical Systems, 24(2), pp. 171-198. (doi: 10.1007/s10109-020-00345-z)

McCulloch, J., Ge, J., Ward, J. A., Heppenstall, A. , Polhill, J. G. and Malleson, N. (2022) Calibrating agent-based models using uncertainty quantification methods. Journal of Artificial Societies and Social Simulation, 25(2), 1. (doi: 10.18564/jasss.4791)

Wu, G., Heppenstall, A. , Meier, P. , Purshouse, R. and Lomax, N. (2022) A synthetic population dataset for estimating small area health and socio-economic outcomes in Great Britain. Scientific Data, 9, 19. (doi: 10.1038/s41597-022-01124-9) (PMID:35058471) (PMCID:PMC8776798)

Gadd, S. C., Comber, A., Tennant, P., Gilthorpe, M. S. and Heppenstall, A. J. (2022) The utility of multilevel models for continuous-time feature selection of spatio-temporal networks. Computers, Environment and Urban Systems, 91, 101728. (doi: 10.1016/j.compenvurbsys.2021.101728)

Yang, Y., Beecham, R., Heppenstall, A. , Turner, A. and Comber, A. (2022) Understanding the impacts of public transit disruptions on bikeshare schemes and cycling behaviours using spatiotemporal and graph-based analysis: a case study of four London Tube strikes. Journal of Transport Geography, 98, 103255. (doi: 10.1016/j.jtrangeo.2021.103255)

Malleson, N., Birkin, M., Birks, D., Ge, J., Heppenstall, A. , Manley, E., McCulloch, J. and Ternes, P. (2022) Agent-based modelling for urban analytics: state of the art and challenges. AI Communications, 35(4), pp. 393-406. (doi: 10.3233/AIC-220114)

An, L. et al. (2021) Challenges, tasks, and opportunities in modeling agent-based complex systems. Ecological Modelling, 457, 109685. (doi: 10.1016/j.ecolmodel.2021.109685)

Smith, D. M., Heppenstall, A. and Campbell, M. (2021) Estimating health over space and time: a review of spatial microsimulation applied to public health. J - An Open Access Journal of Multidisciplinary Science, 4(2), pp. 182-192. (doi: 10.3390/j4020015)

Olmez, S., Douglas-Mann, L., Manley, E., Suchak, K., Heppenstall, A. , Birks, D. and Whipp, A. (2021) Exploring the impact of driver adherence to speed limits and the interdependence of roadside collisions in an urban environment: an agent-based modelling approach. Applied Sciences, 11(12), 5336. (doi: 10.3390/app11125336)

Whipp, A., Malleson, N., Ward, J. and Heppenstall, A. (2021) Estimates of the ambient population: assessing the utility of conventional and novel data sources. ISPRS International Journal of Geo-Information, 10(3), 131. (doi: 10.3390/ijgi10030131)

Heppenstall, A. , Crooks, A., Malleson, N., Manley, E., Ge, J. and Batty, M. (2021) Future developments in geographical agent‐based models: challenges and opportunities. Geographical Analysis, 53(1), pp. 76-91. (doi: 10.1111/gean.12267) (PMID:33678813) (PMCID:PMC7898830)

Roxburgh, N., Stringer, L. C., Evans, A., GC, R. K., Malleson, N. and Heppenstall, A. J. (2021) Impacts of multiple stressors on mountain communities: Insights from an agent-based model of a Nepalese village. Global Environmental Change, 66, 102203. (doi: 10.1016/j.gloenvcha.2020.102203)

Roxburgh, N., Evans, A., GC, R. K., Malleson, N., Heppenstall, A. and Stringer, L. (2021) An empirically informed agent-based model of a Nepalese smallholder village. MethodsX, 8, 101276. (doi: 10.1016/j.mex.2021.101276) (PMID:34434796) (PMCID:PMC8374244)

Yang, Y., Heppenstall, A. , Turner, A. and Comber, A. (2020) Using graph structural information about flows to enhance short-term demand prediction in bike-sharing systems. Computers, Environment and Urban Systems, 83, 101521. (doi: 10.1016/j.compenvurbsys.2020.101521)

Hood, N., Urquhart, R., Newing, A. and Heppenstall, A. (2020) Sociodemographic and spatial disaggregation of e-commerce channel use in the grocery market in Great Britain. Journal of Retailing and Consumer Services, 55, 102076. (doi: 10.1016/j.jretconser.2020.102076)

Malleson, N., Minors, K., Kieu, L.-M., Ward, J. A., West, A. and Heppenstall, A. (2020) Simulating crowds in real time with agent-based modelling and a particle filter. Journal of Artificial Societies and Social Simulation, 23(3), p. 3. (doi: 10.18564/jasss.4266)

Olner, D., Mitchell, G., Heppenstall, A. and Pryce, G. (2020) The spatial economics of energy justice: modelling the trade impacts of increased transport costs in a low carbon transition and the implications for UK regional inequality. Energy Policy, 140, 111378. (doi: 10.1016/j.enpol.2020.111378)

Owen, A. and Heppenstall, A. (2020) Making the case for simulation: Unlocking carbon reduction through simulation of individual ‘middle actor’ behaviour. Environment and Planning B: Urban Analytics and City Science, 47(3), pp. 457-472. (doi: 10.1177/2399808318784597)

Xiang, L., Stillwell, J., Burns, L. and Heppenstall, A. (2020) Measuring and assessing regional education inequalities in China under changing policy regimes. Applied Spatial Analysis and Policy, 13(1), pp. 91-112. (doi: 10.1007/s12061-019-09293-8)

Manson, S. et al. (2020) Methodological issues of spatial agent-based models. Journal of Artificial Societies and Social Simulation, 23(1), 3. (doi: 10.18564/jasss.4174)

Kieu, L.-M., Malleson, N. and Heppenstall, A. (2020) Dealing with uncertainty in agent-based models for short-term predictions. Royal Society Open Science, 7(1), 191074. (doi: 10.1098/rsos.191074) (PMID:32218939) (PMCID:PMC7029931)

Levine, S. Z., Gadd, S. C., Tennant, P. W. G., Heppenstall, A. J. , Boehnke, J. R. and Gilthorpe, M. S. (2019) Analysing trajectories of a longitudinal exposure: A causal perspective on common methods in lifecourse research. PLoS ONE, 14(12), e0225217. (doi: 10.1371/journal.pone.0225217) (PMID:31800576) (PMCID:PMC6892534)

Meier, P. et al. (2019) The SIPHER Consortium: introducing the new UK hub for systems science in public health and health economic research. Wellcome Open Research, 4, 174. (doi: 10.12688/wellcomeopenres.15534.1) (PMID:31815191) (PMCID:PMC6880277)

Yang, Y., Heppenstall, A. , Turner, A. and Comber, A. (2019) A spatiotemporal and graph-based analysis of dockless bike sharing patterns to understand urban flows over the last mile. Computers, Environment and Urban Systems, 77, 101361. (doi: 10.1016/j.compenvurbsys.2019.101361)

Yang, Y., Heppenstall, A. , Turner, A. and Comber, A. (2019) Who, where, why and when? Using smart card and social media data to understand urban mobility. ISPRS International Journal of Geo-Information, 8(6), 271. (doi: 10.3390/ijgi8060271)

Arnold, K.F., Ellison, G.T.H., Gadd, S., Textor, J., Tennant, P.W.G., Heppenstall, A. and Gilthorpe, M.S. (2019) Adjustment for time-invariant and time-varying confounders in ‘unexplained residuals’ models for longitudinal data within a causal framework and associated challenges. Statistical Methods in Medical Research, 28(5), pp. 1347-1364. (doi: 10.1177/0962280218756158) (PMID:29451093) (PMCID:PMC6484949)

Heppenstall, A. and Crooks, A. (2019) Guest editorial for spatial agent-based models: current practices and future trends. GeoInformatica, 23(2), pp. 163-167. (doi: 10.1007/s10707-019-00349-y)

Gulma, U. L., Evans, A., Heppenstall, A. and Malleson, N. (2019) Diversity and burglary: Do community differences matter? Transactions in GIS, 23(2), pp. 181-202. (doi: 10.1111/tgis.12511)

Alotaibi, N. I., Evans, A. J., Heppenstall, A. J. and Malleson, N. S. (2019) How well does Western environmental theory explain crime in the Arabian context? The case study of Riyadh, Saudi Arabia. International Criminal Justice Review, 29(1), pp. 5-32. (doi: 10.1177/1057567717709497)

Book Sections

Crooks, A., Heppenstall, A. , Malleson, N. and Manley, E. (2021) Agent-based modeling and the city: A gallery of applications. In: Shi, W., Goodchild, M. F., Batty, M., Kwan, M.-P. and Zhang, A. (eds.) Urban Informatics. Series: Urban book series. Springer, pp. 885-910. ISBN 9789811589836 (doi: 10.1007/978-981-15-8983-6_46)

Edited Books

Wolf, L. J., Harris, R. and Heppenstall, A. (Eds.) (2024) A Research Agenda for Spatial Analysis. Series: Elgar Research Agendas. Edward Elgar. ISBN 9781802203226

Edited Journals

Heppenstall, A. , Wang, M. , Demsar, U., Lemmens, R. and Yao, J. (Eds.) (2024) 27th AGILE Conference on Geographic Information Science “Geographic Information Science for a Sustainable Future”. AGILE: GIScience Series. 5 [Edited Journal]

Heppenstall, A. and Crooks, A. (Eds.) (2019) Special Issue on Spatial Agent-Based Models: Current Practices and Future Trends. Geoinformatica. 23(2) [Edited Journal]

Conference Proceedings

Heppenstall, A. , Polhill, J. G., Batty, M., Hare, M., Salt, D. and Milton, R. (2023) Exascale Agent-Based Modelling for Policy Evaluation in Real-Time (ExAMPLER). In: 12th International Conference on Geographic Information Science (GIScience 2023), Leeds, UK, 12-15 Sept 2023, 38:1-38:5. ISBN 9783959772884 (doi: 10.4230/LIPIcs.GIScience.2023.38)

Feng, Z. , Zhao, Q. and Heppenstall, A. (2023) Understanding the Complex Behaviours of Electric Vehicle Drivers with Agent-Based Models in Glasgow. In: 12th International Conference on Geographic Information Science (GIScience 2023), Leeds, UK, 14-19 Sept 2023, 29:1-29:6. ISBN 9783959772884 (doi: 10.4230/LIPIcs.GIScience.2023.29)

Website

Lewis, D., Comrie, E., Hoehn, A. , Lomax, N., Heppenstall, A. , Purshouse, R., Zia, K. and Meier, P. (2024) SIPHER Synthetic Population for Individuals in Great Britain (2019-2021) - Interactive R-Shiny Dashboard. [Website]