Publications
2025
The impacts of Liverpool Citizen's Advice on Prescription (CAP) on mental health outcomes– an Instrumental Variable (IV) approach
Gebremariam, A., Piroddi, R., Daras, K., Anderson De Cuevas, R., Abba, K., Gabbay, M., . . . Barr, B. (2025). The impacts of Liverpool Citizen's Advice on Prescription (CAP) on mental health outcomes– an Instrumental Variable (IV) approach. SSM - Population Health, 30, 101785. doi:10.1016/j.ssmph.2025.101785
Mobilising UK Data and AI for All with a National Grid of Civic Learning Systems
Buchan, I., Ainsworth, J., Angione, C., Ardern, K., Atkinson, K., Ball, S., . . . Zhang, X. (2025). Mobilising UK Data and AI for All with a National Grid of Civic Learning Systems (2025/03). https://www.thenhsa.co.uk/about/publications/: Northern Health Science Alliance. Retrieved from https://www.thenhsa.co.uk/
Social Return on Investment (SROI) Evaluation of Citizens Advice on Prescription: A Whole-Systems Approach to Mitigating Poverty and Improving Wellbeing.
Granger, R., Hartfiel, N., Ezeofor, V., Abba, K., Corcoran, R., Anderson de Cuevas, R., . . . Edwards, R. T. (2025). Social Return on Investment (SROI) Evaluation of Citizens Advice on Prescription: A Whole-Systems Approach to Mitigating Poverty and Improving Wellbeing.. International journal of environmental research and public health, 22(2), 301. doi:10.3390/ijerph22020301
Identifying households with children who have complex needs: a segmentation model for integrated care systems.
Piroddi, R., Astbury, A., Baker, W., Daras, K., Rafferty, J., Buchan, I., & Barr, B. (2025). Identifying households with children who have complex needs: a segmentation model for integrated care systems.. BMC health services research, 25(1), 152. doi:10.1186/s12913-024-12100-x
2024
Improving equitable healthcare resource use: developing a neighbourhood district nurse needs index for staffing allocation.
Filipe, L., Piroddi, R., Baker, W., Rafferty, J., Buchan, I., & Barr, B. (2024). Improving equitable healthcare resource use: developing a neighbourhood district nurse needs index for staffing allocation.. BMC health services research, 24(1), 1362. doi:10.1186/s12913-024-11832-0
System-wide health needs segmentation: innovating integrated care for complex needs households
Piroddi, R., Baker, W., Daras, K., Buchan, I., Rafferty, J., Astbury, A., & Barr, B. (2024). System-wide health needs segmentation: innovating integrated care for complex needs households. In European Journal of Public Health Vol. 34. Oxford University Press (OUP). doi:10.1093/eurpub/ckae144.036
OP01 Trends in inequalities in self-harm in young people over the COVID-19 pandemic period. A population-based linkage study of half a million people in Cheshire and Merseyside between 2018 and 2022
Piroddi, R., Astbury, A., Baker, W., Buchan, I., Daras, K., Garcia-Finana, M., . . . Barr, B. (2024). OP01 Trends in inequalities in self-harm in young people over the COVID-19 pandemic period. A population-based linkage study of half a million people in Cheshire and Merseyside between 2018 and 2022. In SSM Annual Scientific Meeting (pp. A1.1-A1). BMJ Publishing Group Ltd. doi:10.1136/jech-2024-ssmabstracts.1
2023
Identifying households with the most complex needs
Piroddi, R., Barr, B., & Daras, K. (2023). Identifying households with the most complex needs [Computer Software]. Internet - Git Hub repository: Git Hub. Retrieved from https://github.com/cipha-uk/complex_households
Can you tell we care? Identifying unpaid carers using local authority and GP data
Knight, H., Peytrignet, S., Alcock, B., Brownrigg, A., Davies, A., Chisambi, M., . . . Tallack, C. (2023). Can you tell we care? Identifying unpaid carers using local authority and GP data. The Health Foundation. Retrieved from https://www.health.org.uk/publications/long-reads/can-you-tell-we-care
Evaluating the impact of using mobile vaccination units to increase COVID-19 vaccination uptake in Cheshire and Merseyside, UK: a synthetic control analysis.
Zhang, X., Tulloch, J. S. P., Knott, S., Allison, R., Parvulescu, P., Buchan, I. E., . . . Barr, B. (2023). Evaluating the impact of using mobile vaccination units to increase COVID-19 vaccination uptake in Cheshire and Merseyside, UK: a synthetic control analysis.. BMJ open, 13(10), e071852. doi:10.1136/bmjopen-2023-071852
Effects on mortality of shielding clinically extremely vulnerable patients in Liverpool, UK, during the COVID-19 pandemic
Filipe, L., Barnett, L. A., Piroddi, R., Buchan, I., Duckworth, H., & Barr, B. (2023). Effects on mortality of shielding clinically extremely vulnerable patients in Liverpool, UK, during the COVID-19 pandemic. PUBLIC HEALTH, 222, 54-59. doi:10.1016/j.puhe.2023.06.037
2022
R code for NDL report: Improving children and young people's mental health services
Barr, B., O'Brien, J., & Piroddi, R. (2022). R code for NDL report: Improving children and young people's mental health services [Computer Software]. Retrieved from https://github.com/HFAnalyticsLab/NDL_CYPMH_Liverpool_Wirral
R code for NDL topic 2: Children and Young People Mental Health in Liverpool and Wirral
Barr, B., O'Brien, J., & Piroddi, R. (2022). R code for NDL topic 2: Children and Young People Mental Health in Liverpool and Wirral [Computer Software]. GitHub: The Health Foundation. Retrieved from https://github.com/HFAnalyticsLab/NDL_CYPMH_Liverpool_Wirral/tree/main/Report
Improving children and young people’s mental health services
Grimm, F., Alcock, B., Butler, J., Fernandez Crespo, R., Davies, A., Peytrignet, S., . . . Tallack, C. (2022). Improving children and young people’s mental health services. The Health Foundation. doi:10.37829/hf-2022-ndl1
Technical appendix: improving children and young people's mental health services
Grimm, F., Alcock, B., Butler, J., Davies, A., Fernandez Crespo, R., Peytrignet, S., . . . Tallack, C. (2022). Technical appendix: improving children and young people's mental health services. The Health Foundation. Retrieved from https://www.health.org.uk/sites/default/files/2022-07/technical_appendix_web.pdf
Children and young people mental health in Liverpool and Wirral between 2018 and 2021
Barr, B., O'Brien, J., & Piroddi, R. (2022). Children and young people mental health in Liverpool and Wirral between 2018 and 2021: Children and young people mental health in Liverpool and Wirral between 2018 and 2021 (NDL1_topic2_LW). GitHub. Retrieved from https://github.com/HFAnalyticsLab/NDL_CYPMH_Liverpool_Wirral/tree/main/Report
The impact of an integrated care intervention on mortality and unplanned hospital admissions in a disadvantaged community in England: a difference-in-differences study
Piroddi, R., Downing, J., Duckworth, H., & Barr, B. (2022). The impact of an integrated care intervention on mortality and unplanned hospital admissions in a disadvantaged community in England: A difference-in-differences study. HEALTH POLICY, 126(6), 549-557. doi:10.1016/j.healthpol.2022.03.009
SQL code to generically process secure MHSDS data
Fox, S., Piroddi, R., & Jones, K. (2022). SQL code to generically process secure MHSDS data [Computer Software]. GitHub. Retrieved from https://github.com/HFAnalyticsLab/MHSDS-cleaning-pipeline
2021
Excess mortality in Glasgow: further evidence of ‘political effects’ on population health
Schofield, L., Walsh, D., Bendel, N., & Piroddi, R. (2021). Excess mortality in Glasgow: further evidence of ‘political effects’ on population health. Public Health, 201, 61-68. doi:10.1016/j.puhe.2021.10.004
Computer code for Networked Data Lab: Hospital use for clinically extremely vulnerable population, the impact of the pandemic
Networked Data Lab partners, N. D. L. (2021). Computer code for Networked Data Lab: Hospital use for clinically extremely vulnerable population, the impact of the pandemic [Computer Software]. GitHub: The Health Foundation. Retrieved from https://github.com/HFAnalyticsLab/NDL_Output3_Hospital_care_CEV
Assessing the impact of COVID-19 on the clinically extremely vulnerable population
Hodgson, K., Butler, J. E., Davies, A., Houston, S., Marszalek, K., Peytrignet, S., . . . Deeny, S. (2021). Assessing the impact of COVID-19 on the clinically extremely vulnerable population. The Health Foundation. Retrieved from https://www.health.org.uk/
Assessing the impact of COVID-19 on the clinically extremely vulnerable population
Assessing the impact of COVID-19 on the clinically extremely vulnerable population (2021). . The Health Foundation. doi:10.37829/hf-2021-ndl01
Liverpool and Wirral antidepressant prescribing: January 2018 to February 2021
Chambers, S., Piroddi, R., & Barnett, L. (2021). Liverpool and Wirral antidepressant prescribing: January 2018 to February 2021: Liverpool and Wirral antidepressant prescribing: January 2018 to February 2021 (NDL1_Sat1). GitHub. Retrieved from https://github.com/
R code for NDL: The impact of Covid-19 on hospital utilisation by Clinically Extremely Vulnerable patients
Networked Data Lab partners, N. D. L. (2021). R code for NDL: The impact of Covid-19 on hospital utilisation by Clinically Extremely Vulnerable patients [Computer Software]. GitHub: The Health Foundation. Retrieved from https://github.com/HFAnalyticsLab/NDL_Output3_Hospital_care_CEV
How has hospital use by those clinically extremely vulnerable to Covid-19 been impacted by the pandemic?
Hodgson, K., Peytrignet, S., & Marszalek, K. (2021). How has hospital use by those clinically extremely vulnerable to Covid-19 been impacted by the pandemic?. The Health Foundation. Retrieved from https://www.health.org.uk/
R code for NDL: Comorbidities of CEV people from hospital admission records
Networked Data Lab, N. D. L. P. (2021). R code for NDL: Comorbidities of CEV people from hospital admission records [Computer Software]. GitHub: The Health Foundation. Retrieved from https://github.com/HFAnalyticsLab/NDL_Output2_Morbidity/tree/main/Analysis
Who was advised to shield from Covid-19?
Hodgson, K., & Peytrignet, S. (2021). Who was advised to shield from Covid-19?. The Health Foundation. Retrieved from https://www.health.org.uk/
Networked Data Lab: Demographic variations across Britain among those advised to shield from Covid-19
Networked Data Lab partners, N. D. L. (2021). Networked Data Lab: Demographic variations across Britain among those advised to shield from Covid-19 [Computer Software]. GitHub: The Health Foundation. Retrieved from https://github.com/HFAnalyticsLab/NDL_Output1_Demographics
2020
The Networked Data Lab: Statistical analysis plan for a descriptive analysis of clinically extremely vulnerable people during COVID-19
Networked Data Lab parteners including, N. D. L., & Piroddi, R. (2020). The Networked Data Lab: Statistical analysis plan for a descriptive analysis of clinically extremely vulnerable people during COVID-19: The Networked Data Lab:Statistical analysis planfor a descriptive analysisof clinically extremelyvulnerable peopleduring COVID-19 (NDL1_01_sap). On-line. Retrieved from https://www.health.org.uk/
Ethnicity and Outcomes from COVID-19: The ISARIC CCP-UK Prospective Observational Cohort Study of Hospitalised Patients
Harrison, E., Docherty, A., Barr, B., Buchan, I., Carson, G., Drake, T., . . . Investigators, I. (2020). Ethnicity and Outcomes from COVID-19: The ISARIC CCP-UK Prospective Observational Cohort Study of Hospitalised Patients. doi:10.2139/ssrn.3618215
Responding to COVID-19 in the Liverpool City Region. COVID-19: How Modelling is Contributing to the Merseyside Response.
Alexiou, A., Ashton, M., Barr, B., Buchan, I., O’Flaherty, M., Jewell, C., . . . Sheard, S. (2020). Responding to COVID-19 in the Liverpool City Region. COVID-19: How Modelling is Contributing to the Merseyside Response. (Policy Briefing 003). Heseltine Institute for Public Policy, Practice and Place.
2019
Using Manifold Embedding for Automatic Threat Detection: An Alternative Machine Learning Approach
Piroddi, R., Griffith, E., Goulermas, J. Y. I., Maskell, S., & Ralph, J. (2019, September 9). Using Manifold Embedding for Automatic Threat Detection: An Alternative Machine Learning Approach. In British Machine Vision Conference. Cardiff.
2018
Comparing interrelationships between features and embedding methods for multiple-view fusion
Piroddi, R., Goulermas, Y., Maskell, S., & Ralph, J. (2018). Comparing interrelationships between features and embedding methods for multiple-view fusion. In 2018 21ST INTERNATIONAL CONFERENCE ON INFORMATION FUSION (FUSION) (pp. 1503-1510). Retrieved from https://www.webofscience.com/
Comparing Interrelationships Between Features and Embedding Methods for Multiple-View Fusion.
Piroddi, R., Goulermas, J. Y., Maskell, S., & Ralph, J. F. (2018). Comparing Interrelationships Between Features and Embedding Methods for Multiple-View Fusion.. In FUSION (pp. 1-5). IEEE. Retrieved from https://ieeexplore.ieee.org/xpl/conhome/8442112/proceeding
2017
METHOD AND APPARATUS FOR ORDERING IMAGE
Knee, M. J., & Piroddi, R. (2017, September 8). 15/699,758, METHOD AND APPARATUS FOR ORDERING IMAGE. US.
Image processing with segmentation using directionally-accumulated difference-image pixel values
Piroddi, R. (2014, May 28). US 9648339, Image processing with segmentation using directionally-accumulated difference-image pixel values. US.
2013
Method and apparatus for modifying a moving image sequence
Piroddi, R., Knee, M., & Brooks, D. (2007, February 13). US 8442318, Method and apparatus for modifying a moving image sequence. U.S.A..
2010
Networks of Concepts and Ideas
Petrou, M., Tabacchi, M. E., & Piroddi, R. (2010). Networks of Concepts and Ideas. COMPUTER JOURNAL, 53(10), 1738-1751. doi:10.1093/comjnl/bxp113
Aspect Ratio Problems in Television Today and Some New Solutions
Knee, M., & Piroddi, R. (2010). Aspect Ratio Problems in Television Today and Some New Solutions. SMPTE MOTION IMAGING JOURNAL, 119(1), 35-41. doi:10.5594/J14873
2008
Gradient-adaptive normalized convolution
Argyriou, V., Vlachos, T., & Piroddi, R. (2008). Gradient-adaptive normalized convolution. IEEE SIGNAL PROCESSING LETTERS, 15, 489-492. doi:10.1109/LSP.2008.919836
2006
A method for single-stimulus quality assessment of segmented video
Piroddi, R., & Vlachos, T. (2006). A method for single-stimulus quality assessment of segmented video. EURASIP JOURNAL ON APPLIED SIGNAL PROCESSING. doi:10.1155/ASP/2006/39482
On the structure of the mind
Petrou, M., & Piroddi, R. (2006). On the structure of the mind. In Proceedings of AISB'06: Adaptation in Artificial and Biological Systems Vol. 2 (pp. 60-63).
A simple framework for spatio-temporal video segmentation and delayering using dense motion fields
Piroddi, R., & Vlachos, T. (2006). A simple framework for spatio-temporal video segmentation and delayering using dense motion fields. IEEE SIGNAL PROCESSING LETTERS, 13(7), 421-424. doi:10.1109/LSP.2006.873143
Texture recognition from sparsely and irregularly sampled data
Petrou, M., Piroddi, R., & Talebpour, A. (2006). Texture recognition from sparsely and irregularly sampled data. COMPUTER VISION AND IMAGE UNDERSTANDING, 102(1), 95-104. doi:10.1016/j.cviu.2005.11.003
2005
Integrating human and machine perception to reverse-engineer the human vision system
Piroddi, R., & Petrou, M. (2005). Integrating human and machine perception to reverse-engineer the human vision system. In HUMAN & MACHINE PERCEPTION: COMMUNICATION, INTERACTION, AND INTEGRATION (pp. 119-129). doi:10.1142/9789812703095_0010
Texture interpolation using ordinary Kriging
Chandra, S., Petrou, M., & Piroddi, R. (2005). Texture interpolation using ordinary Kriging. In PATTERN RECOGNITION AND IMAGE ANALYSIS, PT 2, PROCEEDINGS Vol. 3523 (pp. 183-190). Retrieved from https://www.webofscience.com/
2004
Irregularly sampled scenes
Petrou, M., Piroddi, R., & Chandra, S. (2004). Irregularly sampled scenes. In IMAGE AND SIGNAL PROCESSING FOR REMOTE SENSING X Vol. 5573 (pp. 319-333). doi:10.1117/12.579601
Analysis of irregularly sampled data: A review
Piroddi, R., & Petrou, M. (2004). Analysis of irregularly sampled data: A review. ADVANCES IN IMAGING AND ELECTRON PHYSICS, VOL 132, 132, 109-165. doi:10.1016/S1076-5670(04)32003-3
2002
Multiple-Feature Spatiotemporal Segmentation of Moving Sequences using a Rule-based Approach
Piroddi, R., & Vlachos, T. (2002). Multiple-Feature Spatiotemporal Segmentation of Moving Sequences using a Rule-based Approach. In Procedings of the British Machine Vision Conference 2002 (pp. 33.1-33.10). British Machine Vision Association. doi:10.5244/c.16.33
Multiple-Feature Spatiotemporal Segmentation of Moving Sequences using a Rule-based Approach.
Piroddi, R., & Vlachos, T. (2002). Multiple-Feature Spatiotemporal Segmentation of Moving Sequences using a Rule-based Approach.. In P. L. Rosin, & A. D. Marshall (Eds.), BMVC (pp. 1-10). British Machine Vision Association. Retrieved from http://www.informatik.uni-trier.de/~ley/db/conf/bmvc/bmvc2002.html
Object-based segmentation of moving sequences using multiple features
Piroddi, R., & Vlachos, T. (2002). Object-based segmentation of moving sequences using multiple features. In DSP 2002: 14TH INTERNATIONAL CONFERENCE ON DIGITAL SIGNAL PROCESSING PROCEEDINGS, VOLS 1 AND 2 (pp. 547-550). Retrieved from https://www.webofscience.com/