Data-forensic determination of the accuracy of international COVID-19 reporting: using Zipf's law for pandemic investigation

Article

Iorliam, A., Ho, A.T.S., Tirunagari, S., Windridge, D., Adeyelu, A., Otor, S. and Akumba, B.O. 2021. Data-forensic determination of the accuracy of international COVID-19 reporting: using Zipf's law for pandemic investigation. International Journal of Advanced Computer Science and Applications. 12 (1), pp. 42-49. https://doi.org/10.14569/IJACSA.2021.0120106
TypeArticle
TitleData-forensic determination of the accuracy of international COVID-19 reporting: using Zipf's law for pandemic investigation
AuthorsIorliam, A., Ho, A.T.S., Tirunagari, S., Windridge, D., Adeyelu, A., Otor, S. and Akumba, B.O.
Abstract

Severe outbreaks of infectious disease occur throughout the world with some reaching the level of international pandemic: Coronavirus (COVID-19) is the most recent to do so. In this paper, a mechanism is set out using Zipf’s law to establish the accuracy of international reporting of COVID-19 cases via a determination of whether an individual country’s COVID-19 reporting follows a power-law for confirmed, recovered, and death cases of COVID-19. The probability of Zipf’s law (P-values) for COVID-19 confirmed cases show that Uzbekistan has the highest P-value of 0.940, followed by Belize (0.929), and Qatar (0.897). For COVID-19 recovered cases, Iraq had the highest P-value of 0.901, followed by New Zealand (0.888), and Austria (0.884). Furthermore, for COVID-19 death cases, Bosnia and Herzegovina had the highest P-value of 0.874, followed by Lithuania (0.843), and Morocco (0.825). China, where the COVID-19 pandemic began, is a significant outlier in recording P-values lower than 0.1 for the confirmed, recovered, and death cases. This raises important questions, not only for China, but also any country whose data exhibits P-values below this threshold. The main application of this work is to serve as an early warning for World Health Organization (WHO) and other health regulatory bodies to perform more investigations in countries where COVID-19 datasets deviate significantly from Zipf’s law. To this end, this paper provide a tool for illustrating Zipf’s law P-values on a global map in order to convey the geographic distribution of reporting anomalies.

KeywordsCOVID-19; power-law; pandemic; Zipf's Law; WHO
Sustainable Development Goals9 Industry, innovation and infrastructure
Middlesex University ThemeCreativity, Culture & Enterprise
PublisherSAI Organization
JournalInternational Journal of Advanced Computer Science and Applications
ISSN2158-107X
Electronic2156-5570
Publication dates
PrintJan 2021
Publication process dates
Accepted2021
Deposited16 Apr 2026
Output statusPublished
Publisher's version
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File Access Level
Open
Copyright Statement

This is an open access article licensed under a Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, even commercially as long as the original work is properly cited.

Digital Object Identifier (DOI)https://doi.org/10.14569/IJACSA.2021.0120106
Web of Science identifierWOS:000621697400006
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Tirunagari, S., Poh, N., Bober, M. and Windridge, D. 2016. Can DMD obtain a scene background in color? 2016 International Conference on Image, Vision and Computing (ICIVC). Portsmouth, UK 03 - 05 Aug 2016 pp. 46-50 https://doi.org/10.1109/ICIVC.2016.7571272
Classification of fibroglandular tissue distribution in the breast based on radiotherapy planning CT
Juneja, P., Evans, P., Windridge, D. and Harris, E. 2016. Classification of fibroglandular tissue distribution in the breast based on radiotherapy planning CT. BMC Medical Imaging. 16 (1). https://doi.org/10.1186/s12880-016-0107-2
Kernel combination via debiased object correspondence analysis
Windridge, D. and Yan, F. 2016. Kernel combination via debiased object correspondence analysis. Information Fusion. 27, pp. 228-239. https://doi.org/10.1016/j.inffus.2015.02.002
On the intrinsic limits to representationally-adaptive machine-learning
Windridge, D. 2015. On the intrinsic limits to representationally-adaptive machine-learning.
Identifying similar patients using self-organising maps: a case study on type-1 diabetes self-care survey responses
Tirunagari, S., Poh, N., Hu, G. and Windridge, D. 2015. Identifying similar patients using self-organising maps: a case study on type-1 diabetes self-care survey responses. https://doi.org/10.48550/arXiv.1503.06316
Longitudinal MRI assessment: the identification of relevant features in the development of posterior fossa syndrome in children
Spiteri, M., Lewis, E., Windridge, D. and Avula, S. 2015. Longitudinal MRI assessment: the identification of relevant features in the development of posterior fossa syndrome in children. Medical imaging 2015: Computer-Aided Diagnosis. Orlando, Florida, United States 21 Feb 2015 Society of Photo-optical Instrumentation Engineers (SPIE). https://doi.org/10.1117/12.2081591
Windowed DMD as a microtexture descriptor for finger vein counter-spoofing in biometrics
Tirunagari, S., Poh, N., Bober, M. and Windridge, D. 2015. Windowed DMD as a microtexture descriptor for finger vein counter-spoofing in biometrics. 2015 IEEE International Workshop on Information Forensics and Security (WIFS). Rome, Italy 16 - 19 Nov 2015 Institute of Electrical and Electronics Engineers (IEEE). pp. 1-6 https://doi.org/10.1109/WIFS.2015.7368599
Globally optimal 2D-3D registration from points or lines without correspondences
Brown, M., Windridge, D. and Guillemaut, J. 2015. Globally optimal 2D-3D registration from points or lines without correspondences. 2015 IEEE International Conference on Computer Vision (ICCV). Santiago, Chile 07 - 13 Dec 2015 IEEE. pp. 2111-2119 https://doi.org/10.1109/ICCV.2015.244
A generalisable framework for saliency-based line segment detection
Brown, M., Windridge, D. and Guillemaut, J. 2015. A generalisable framework for saliency-based line segment detection. Pattern Recognition. 48 (12), pp. 3993-4011. https://doi.org/10.1016/j.patcog.2015.06.015
Identifying quantitative imaging features of posterior fossa syndrome in longitudinal MRI
Spiteri, M., Windridge, D., Avula, S., Kumar, R. and Lewis, E. 2015. Identifying quantitative imaging features of posterior fossa syndrome in longitudinal MRI. Journal of Medical Imaging. 2 (4). https://doi.org/10.1117/1.JMI.2.4.044502
A novel Markov logic rule induction strategy for characterizing sports video footage
Windridge, D., Kittler, J., De Campos, T., Yan, F., Christmas, W. and Khan, A. 2015. A novel Markov logic rule induction strategy for characterizing sports video footage. IEEE MultiMedia. 22 (2), pp. 24-35. https://doi.org/10.1109/MMUL.2014.36
Artificial co-drivers as a universal enabling technology for future intelligent vehicles and transportation systems
Da Lio, M., Biral, F., Bertolazzi, E., Galvani, M., Bosetti, P., Windridge, D., Saroldi, A. and Tango, F. 2015. Artificial co-drivers as a universal enabling technology for future intelligent vehicles and transportation systems. IEEE Transactions on Intelligent Transportation Systems. 16 (1), pp. 244-263. https://doi.org/10.1109/TITS.2014.2330199
Breast cancer data analytics with missing values: a study on ethnic, age and income groups
Tirunagari, S., Poh, N., Abdulrahman, H., Nemmour, N. and Windridge, D. 2015. Breast cancer data analytics with missing values: a study on ethnic, age and income groups. https://doi.org/10.48550/arXiv.1503.03680
Detection of face spoofing using visual dynamics
Tirunagari, S., Poh, N., Windridge, D., Iorliam, A., Suki, N. and Ho, A. 2015. Detection of face spoofing using visual dynamics. IEEE Transactions on Information Forensics and Security. 10 (4), pp. 762-777. https://doi.org/10.1109/TIFS.2015.2406533
Multilevel Chinese takeaway process and label-based processes for rule induction in the context of automated sports video annotation
Khan, A., Windridge, D. and Kittler, J. 2014. Multilevel Chinese takeaway process and label-based processes for rule induction in the context of automated sports video annotation. IEEE Transactions on Cybernetics. 44 (10), pp. 1910-1923. https://doi.org/10.1109/TCYB.2014.2299955
A saliency-based framework for 2D-3D registration
Brown, M., Guillemaut, J. and Windridge, D. 2014. A saliency-based framework for 2D-3D registration. 9th International Conference on Computer Vision Theory and Applications (VISAPP 2014). Lisbon, Portugal 05 - 08 Jan 2014 SCITEPRESS - Science and Technology Publications. pp. 265-273 https://doi.org/10.5220/0004675402650273
Supervised selective kernel fusion for membrane protein prediction
Tatarchuk, A., Sulimova, V., Torshin, I., Mottl, V. and Windridge, D. 2014. Supervised selective kernel fusion for membrane protein prediction. Comin, M., Käll, L., Marchiori, E., Ngom, A. and Rajapakse, J. (ed.) 9th IAPR International Conference Pattern Recognition in Bioinformatics (PRIB 2014). Stockholm, Sweden 21 - 23 Aug 2014 Springer. pp. 98-109 https://doi.org/10.1007/978-3-319-09192-1_9
Challenges in designing an online healthcare platform for personalised patient analytics
Poh, N., Tirunagari, S. and Windridge, D. 2014. Challenges in designing an online healthcare platform for personalised patient analytics. 2014 IEEE Symposium on Computational Intelligence in Big Data (CIBD). Orlando, FL., USA 09 - 12 Dec 2014 IEEE. pp. 1-6 https://doi.org/10.1109/CIBD.2014.7011526
Patient level analytics using self-organising maps: a case study on type-1 diabetes self-care survey responses
Tirunagari, S., Poh, N., Aliabadi, K., Windridge, D. and Cooke, D. 2014. Patient level analytics using self-organising maps: a case study on type-1 diabetes self-care survey responses. 2014 IEEE Symposium on Computational Intelligence and Data Mining (CIDM). Orlando, FL., USA 09 - 12 Dec 2014 Institute of Electrical and Electronics Engineers (IEEE). pp. 304-309 https://doi.org/10.1109/CIDM.2014.7008682
Non-enumerative cross validation for the determination of structural parameters in feature-selective SVMs
Chernousova, E., Levdik, P., Tatarchuk, A., Mottl, V. and Windridge, D. 2014. Non-enumerative cross validation for the determination of structural parameters in feature-selective SVMs. 22nd International Conference on Pattern Recognition ICPR 2014. Stockholm, Sweden 24 - 28 Aug 2014 Institute of Electrical and Electronics Engineers (IEEE). pp. 3654-3659 https://doi.org/10.1109/ICPR.2014.628
Linear regression via elastic net: non-enumerative leave-one-out verification of feature selection
Chernousova, E., Razin, N., Krasotkina, O., Mottl, V. and Windridge, D. 2014. Linear regression via elastic net: non-enumerative leave-one-out verification of feature selection. in: Aleskerov, F., Goldengorin, B. and Pardalos, P. (ed.) Clusters, Orders, and Trees: Methods and Applications: In Honor of Boris Mirkin's 70th Birthday New York Springer.
Automatic annotation of tennis games: an integration of audio, vision, and learning
Yan, F., Kittler, J., Windridge, D., Christmas, W., Mikolajczyk, K., Cox, S. and Huang, Q. 2014. Automatic annotation of tennis games: an integration of audio, vision, and learning. Image and Vision Computing. 32 (11), pp. 896-903. https://doi.org/10.1016/j.imavis.2014.08.004
A kernel-based framework for medical big-data analytics
Windridge, D. and Bober, M. 2014. A kernel-based framework for medical big-data analytics. in: Interactive Knowledge Discovery and Data Mining in Biomedical Informatics: State-of-the-Art and Future Challenges Springer. pp. 197-208
Domain anomaly detection in machine perception: a system architecture and taxonomy
Kittler, J., Christmas, W., De Campos, T., Windridge, D., Yan, F., Illingworth, J. and Osman, M. 2014. Domain anomaly detection in machine perception: a system architecture and taxonomy. IEEE Transactions on Pattern Analysis and Machine Intelligence. 36 (5), pp. 845-859. https://doi.org/10.1109/TPAMI.2013.209
Characterizing driver intention via hierarchical perception-action modeling
Windridge, D., Shaukat, A. and Hollnagel, E. 2013. Characterizing driver intention via hierarchical perception-action modeling. IEEE Transactions on Human-Machine Systems. 43 (1), pp. 17-31. https://doi.org/10.1109/TSMCA.2012.2216868
A framework for hierarchical perception-action learning utilizing fuzzy reasoning
Windridge, D., Felsberg, M. and Shaukat, A. 2013. A framework for hierarchical perception-action learning utilizing fuzzy reasoning. IEEE Transactions on Cybernetics. 43 (1), pp. 155-169. https://doi.org/10.1109/tsmcb.2012.2202109
Trained eyes: experience promotes adaptive gaze control in dynamic and uncertain visual environments
Taya, S., Windridge, D. and Osman, M. 2013. Trained eyes: experience promotes adaptive gaze control in dynamic and uncertain visual environments. PLoS ONE. 8 (8). https://doi.org/10.1371/journal.pone.0071371
High throughput screening for mammography using a human-computer interface with rapid serial visual presentation (RSVP)
Hope, C., Sterr, A., Elangovan, P., Geades, N., Windridge, D., Young, K. and Wells, K. 2013. High throughput screening for mammography using a human-computer interface with rapid serial visual presentation (RSVP). Abbey, C.K. and Mello-Thoms, C.R. (ed.) Medical Imaging 2013: Image Perception, Observer Performance, and Technology Assessment. Lake Buena Vista, Florida, United States 10 - 11 Feb 2013 Society of Photo-optical Instrumentation Engineers (SPIE). https://doi.org/10.1117/12.2007557
Looking to score: the dissociation of goal influence on eye movement and meta-attentional allocation in a complex dynamic natural scene
Taya, S., Windridge, D. and Osman, M. 2012. Looking to score: the dissociation of goal influence on eye movement and meta-attentional allocation in a complex dynamic natural scene. PLoS ONE. 7 (6). https://doi.org/10.1371/journal.pone.0039060
Experience-based modulation of eye-movement behaviour in dynamic and uncertain visual environments
Taya, S., Windridge, D. and Osman, M. 2012. Experience-based modulation of eye-movement behaviour in dynamic and uncertain visual environments. 34th Annual Meeting of the Cognitive Science Society. Sapporo, Japan 01 - 04 Aug 2012 Cognitive Science Society.
Convex support and relevance vector machines for selective multimodal pattern recognition
Seredin, O., Mottl, V., Tatarchuk, A., Razin, N. and Windridge, D. 2012. Convex support and relevance vector machines for selective multimodal pattern recognition. 21st International Conference on Pattern Recognition. Tsukuba, Japan 11 - 15 Nov 2012 International Association for Pattern Recognition (IAPR).
Automatic annotation of court games with structured output learning
Yan, F., Kittler, J., Mikolajczyk, K. and Windridge, D. 2012. Automatic annotation of court games with structured output learning. 21st International Conference on Pattern Recognition. Tsukuba, Japan 11 - 15 Nov 2012 IEEE. pp. 3577-3580 https://doi.org/https://ieeexplore.ieee.org/document/6460938
Application of the multi-modal relevance vector machine to the problem of protein secondary structure prediction
Razin, N., Sungurov, D., Mottl, V., Torshin, I., Sulimova, V., Seredin, O. and Windridge, D. 2012. Application of the multi-modal relevance vector machine to the problem of protein secondary structure prediction. 7th IAPR International Conference on Pattern Recognition in Bioinformatics. Tokyo, Japan 08 - 10 Nov 2012 Springer. pp. 153-165 https://doi.org/10.1007/978-3-642-34123-6_14
On-line spatio-temporal independent component analysis for motion correction in renal DCE-MRI
Kiani, S., Gordon, I., Windridge, D. and Wells, K. 2012. On-line spatio-temporal independent component analysis for motion correction in renal DCE-MRI. 2012 IEEE Nuclear Science Symposium and Medical Imaging Conference Record (NSS/MIC). Anaheim, CA, USA 27 Oct - 03 Nov 2012 IEEE. https://doi.org/10.1109/nssmic.2012.6551664
Evaluation of face recognition system in heterogeneous environments (visible vs NIR)
Goswami, D., Chan, C.H., Windridge, D. and Kittler, J. 2011. Evaluation of face recognition system in heterogeneous environments (visible vs NIR). 2011 IEEE International Conference on Computer Vision Workshops (ICCV Workshops). Barcelona, Spain 06 - 13 Nov 2011 IEEE. pp. 2160-2167 https://doi.org/10.1109/ICCVW.2011.6130515
Domain adaptation in the context of sport video action recognition
Faraji Davar, N., de Campos, T., Windridge, D., Kittler, J. and Christmas, W. 2011. Domain adaptation in the context of sport video action recognition. NIPS 2011 Domain Adaptation Workshop. Sierra Nevada, Spain 17 - 17 Dec 2011
Anomaly detection and knowledge transfer in automatic sports video annotation
Almajai, I., Yan, F., De Campos, T., Khan, A., Christmas, W., Windridge, D. and Kittler, J. 2011. Anomaly detection and knowledge transfer in automatic sports video annotation. in: Weinshall, D., Anemüller, J. and Gool, L. (ed.) Detection and Identification of Rare Audio-visual Cues Springer. pp. 109-117
An evaluation of bags-of-words and spatio-temporal shapes for action recognition
de Campos, T., Barnard, M., Mikolajczyk, K., Kittler, J., Yan, F., Christmas, W. and Windridge, D. 2011. An evaluation of bags-of-words and spatio-temporal shapes for action recognition. 2011 IEEE Workshop on Applications of Computer Vision (WACV). Kona, HI, USA 05 - 07 Jan 2011 IEEE. https://doi.org/10.1109/WACV.2011.5711524
A modified neutral point method for kernel-based fusion of pattern-recognition modalities with incomplete data sets
Panov, M., Tatarchuk, A., Mottl, V. and Windridge, D. 2011. A modified neutral point method for kernel-based fusion of pattern-recognition modalities with incomplete data sets. 10th International Workshop on Multiple Classifier Systems. Naples, Italy 15 - 17 Jun 2011 Springer. https://doi.org/10.1007/978-3-642-21557-5_15
Ball event recognition using HMM for automatic tennis annotation
Almajai, I., Kittler, J., De Campos, T., Christmas, W., Yan, F., Windridge, D. and Khan, A. 2010. Ball event recognition using HMM for automatic tennis annotation. 2010 IEEE International Conference on Image Processing. Hong Kong, China 26 - 29 Sep 2010 IEEE. https://doi.org/10.1109/ICIP.2010.5652415
Adaptive, perception-action-based cognitive modelling of human driving behaviour using control, gaze and signal inputs
Shaukat, A., Windridge, D., Hollnagel, E., Macchi, L. and Kittler, J. 2010. Adaptive, perception-action-based cognitive modelling of human driving behaviour using control, gaze and signal inputs. Brain Inspired Cognitive Systems - BICS 2010. Madrid, Spain 14 - 16 Jul 2010
A support kernel machine for supervised selective combining of diverse pattern-recognition modalities
Tatarchuk, A., Urlov, E., Mottl, V. and Windridge, D. 2010. A support kernel machine for supervised selective combining of diverse pattern-recognition modalities. 9th International Workshop on Multiple Classifier Systems. Cairo, Egypt 07 - 09 Apr 2010 Springer. https://doi.org/10.1007/978-3-642-12127-2_17
Addressing missing values in kernel-based multimodal biometric fusion using neutral point substitution
Poh, N., Windridge, D., Mottl, V., Tatarchuk, A. and Eliseyev, A. 2010. Addressing missing values in kernel-based multimodal biometric fusion using neutral point substitution. IEEE Transactions on Information Forensics and Security. 5 (3), pp. 461-469. https://doi.org/10.1109/TIFS.2010.2053535
A linear-complexity reparameterisation strategy for the hierarchical bootstrapping of capabilities within perception-action architectures
Shevchenko, M., Windridge, D. and Kittler, J. 2009. A linear-complexity reparameterisation strategy for the hierarchical bootstrapping of capabilities within perception-action architectures. Image and Vision Computing. 27 (11), pp. 1702-1714. https://doi.org/10.1016/j.imavis.2008.12.002
Perception-action learning as an epistemologically-consistent model for self-updating cognitive representation
Windridge, D. 2009. Perception-action learning as an epistemologically-consistent model for self-updating cognitive representation. Hussain, A., Aleksander, I., Smith, L., Barros, A., Chrisley, R. and Cutsuridis, V. (ed.) Brain Inspired Cognitive Systems 2008. São Luís, Brazil 24 - 27 Jul 2008 Springer. pp. 95-134 https://doi.org/10.1007/978-0-387-79100-5_6
Epistemic constraints on autonomous symbolic representation in natural and artificial agents
Windridge, D. and Kittler, J. 2008. Epistemic constraints on autonomous symbolic representation in natural and artificial agents. in: Smolinski, T.G., Milanova, M.G. and Hassanien, A.-E. (ed.) Applications of Computational Intelligence in Biology: Current Trends and Open Problems Springer. pp. 395-422
An entropy-based approach to the hierarchical acquisition of perception-action capabilities
Windridge, D., Shevchenko, M. and Kittler, J. 2008. An entropy-based approach to the hierarchical acquisition of perception-action capabilities. 4th International Workshop on Cognitive Vision. Santorini, Greece 12 May 2008 Springer. https://doi.org/10.1007/978-3-540-92781-5_7
Cognitive learning with automatic goal acquisition
Kittler, J., Shevchenko, M. and Windridge, D. 2006. Cognitive learning with automatic goal acquisition. 3rd European Starting AI Researcher Symposium. Riva del Garda, Italy 28 - 29 Aug 2006 IOS Press. https://doi.org/10.5555/1565192.1565195
A memory architecture and contextual reasoning framework for cognitive vision
Kittler, J., Christmas, W.J., Kostin, A., Yan, F., Kolonias, I. and Windridge, D. 2005. A memory architecture and contextual reasoning framework for cognitive vision. 14th Scandinavian Conference on Image Analysis. Joensuu, Finland 19 - 22 Jun 2005 Springer. https://doi.org/10.1007/11499145_36
A linguistic feature vector for the visual interpretation of sign language
Bowden, R., Windridge, D., Kadir, T., Zisserman, A. and Brady, M. 2004. A linguistic feature vector for the visual interpretation of sign language. 8th European Conference on Computer Vision. Prague, Czech Republic 11 - 14 May 2004 Springer. https://doi.org/10.1007/978-3-540-24670-1_30
A general strategy for hidden markov chain parameterisation in composite feature-spaces
Windridge, D., Bowden, R. and Kittler, J. 2004. A general strategy for hidden markov chain parameterisation in composite feature-spaces. Joint IAPR International Workshops, SSPR 2004 and SPR 2004. Lisbon, Portugal 18 - 20 Aug 2004 Springer. pp. 1069-1077 https://doi.org/10.1007/978-3-540-27868-9_118
A morphologically optimal strategy for classifier combination: Multiple expert fusion as a tomographic process
Windridge, D. and Kittler, J. 2003. A morphologically optimal strategy for classifier combination: Multiple expert fusion as a tomographic process. IEEE Transactions on Pattern Analysis and Machine Intelligence. 25 (3), pp. 343-353. https://doi.org/10.1109/TPAMI.2003.1182097
Classifier combination as a tomographic process
Windridge, D. and Kittler, J. 2001. Classifier combination as a tomographic process. 2nd International Workshop on Multiple Classifier Systems. Cambridge, UK 02 - 04 Jul 2001 Springer. pp. 248-258 https://doi.org/10.1007/3-540-48219-9_25
Boosting multiple experts by joint optimization of decision thresholds
Kittler, J., Yusoff, Y., Christmas, W., Windeatt, T. and Windridge, D. 2001. Boosting multiple experts by joint optimization of decision thresholds. Pattern Recognition and Image Analysis. 11 (3), pp. 529-541.
Combined classifier optimisation via feature selection
Windridge, D. and Kittler, J. 2000. Combined classifier optimisation via feature selection. Joint IAPR International Workshops SSPR 2000 and SPR 2000. Alicante, Spain 30 Aug - 01 Sep 2000 Springer. https://doi.org/10.1007/3-540-44522-6_71
An optimal solution to the problem of multiple expert fusion
Windridge, D. 2000. An optimal solution to the problem of multiple expert fusion. University of Surrey.
A fluctuation analysis for optical cluster galaxies - I. Theory
Windridge, D. and Phillipps, S. 2000. A fluctuation analysis for optical cluster galaxies - I. Theory. Monthly Notices of the Royal Astronomical Society (MNRAS). 319 (2), pp. 591-605. https://doi.org/10.1046/j.1365-8711.2000.03908.x