Keywords
Spatiotemporal Visualization
Standalone Dashboard
Phylogenomic Analysis
Public Health Informatics
How to Cite
Abstract
In the scope of public health, the rapid identification and control of infectious disease outbreaks are a paramount concern. Traditional surveillance methods often face challenges in effectively combining genetic, geographical, and temporal data, which is crucial for a comprehensive understanding of disease transmission dynamics. Addressing this critical need, the Spatiotemporal Phylogenomic Research and Epidemiological Analysis Dashboard (SPREAD) emerges as an innovative standalone web-based application. SPREAD integrates several modules for detailed genomic relationships, pinpointing genetically close pathogens, and spatial mapping, providing in-depth views of how diseases spread across populations and territories, with significant advantage to manage both bacteria and viruses based on allele and variant calling, respectively. Designed for broad accessibility, SPREAD operates seamlessly within web browsers, eliminating the need for sophisticated IT infrastructure and facilitating its use across various public health contexts. Its intuitive interface ensures that users can effortlessly navigate complex datasets, facilitating widespread access to advanced surveillance capabilities. Through its initial deployments, SPREAD has proven instrumental in quickly identifying transmission clusters, significantly aiding in the formulation of prompt and targeted public health responses. Through the integration of state-of-the-art technology with a focus on user-centered design, SPREAD offers a promising solution that highlights the potential of digital health innovations.
References
Akther, S., Bezrucenkovas, E., Sulkow, B., Panlasigui, C., Li, L., Qiu, W., & Di, L. (2020). CoV Genome Tracker: tracing genomic footprints of Covid-19 pandemic. Cold Spring Harbor Laboratory. https://doi.org/10.1101/2020.04.10.036343
Arshad, S., Arshad, J., Khan, M. M., & Parkinson, S. (2021). Analysis of security and privacy challenges for DNA-genomics applications and databases. In Journal of Biomedical Informatics (Vol. 119, p. 103815). Elsevier BV. https://doi.org/10.1016/j.jbi.2021.103815
Baker, K. S., Jauneikaite, E., Hopkins, K. L., Lo, S. W., Sánchez-Busó, L., Getino, M., Howden, B. P., Holt, K. E., Musila, L. A., Hendriksen, R. S., Amoako, D. G., Aanensen, D. M., Okeke, I. N., Egyir, B., Nunn, J. G., Midega, J. T., Feasey, N. A., & Peacock, S. J. (2023). Genomics for public health and international surveillance of antimicrobial resistance. In The Lancet Microbe (Vol. 4, Issue 12, pp. e1047–e1055). Elsevier BV. https://doi.org/10.1016/s2666-5247(23)00283-5
Bhatia, S., Lassmann, B., Cohn, E., Desai, A. N., Carrion, M., Kraemer, M. U. G., Herringer, M., Brownstein, J., Madoff, L., Cori, A., & Nouvellet, P. (2021). Using digital surveillance tools for near real-time mapping of the risk of infectious disease spread. In npj Digital Medicine (Vol. 4, Issue 1). Springer Science and Business Media LLC. https://doi.org/10.1038/s41746-021-00442-3
Brady, K., Moon, S., Nguyen, T., & Coffman, J. (2020). Docker Container Security in Cloud Computing. In 2020 10th Annual Computing and Communication Workshop and Conference (CCWC). 2020 10th Annual Computing and Communication Workshop and Conference (CCWC). IEEE. https://doi.org/10.1109/ccwc47524.2020.9031195
Carriço, J. A., Rossi, M., Moran-Gilad, J., Van Domselaar, G., & Ramirez, M. (2018). A primer on microbial bioinformatics for nonbioinformaticians. In Clinical Microbiology and Infection (Vol. 24, Issue 4, pp. 342–349). Elsevier BV. https://doi.org/10.1016/j.cmi.2017.12.015
Castelli, P., De Ruvo, A., Bucciacchio, A., D’Alterio, N., Cammà, C., Di Pasquale, A., & Radomski, N. (2023). Harmonization of supervised machine learning practices for efficient source attribution of Listeria monocytogenes based on genomic data. In BMC Genomics (Vol. 24, Issue 1). Springer Science and Business Media LLC. https://doi.org/10.1186/s12864-023-09667-w
Chen, S. (2023). Ultrafast one‐pass FASTQ data preprocessing, quality control, and deduplication using fastp. In iMeta (Vol. 2, Issue 2). Wiley. https://doi.org/10.1002/imt2.107
Di Lorenzo, A., Mangone, I., Colangeli, P., Cioci, D., Curini, V., Vincifori, G., Mercante, M. T., Di Pasquale, A., Radomski, N., & Iannetti, S. (2023). One health system supporting surveillance during COVID-19 epidemic in Abruzzo region, southern Italy. In One Health (Vol. 16, p. 100471). Elsevier BV. https://doi.org/10.1016/j.onehlt.2022.100471
Di Pasquale, A., Radomski, N., Mangone, I., Calistri, P., Lorusso, A., & Cammà, C. (2021). SARS-CoV-2 surveillance in Italy through phylogenomic inferences based on Hamming distances derived from pan-SNPs, -MNPs and -InDels. In BMC Genomics (Vol. 22, Issue 1). Springer Science and Business Media LLC. https://doi.org/10.1186/s12864-021-08112-0
Edler, D., & Vetter, M. (2019). The Simplicity of Modern Audiovisual Web Cartography: An Example with the Open-Source JavaScript Library leaflet.js. In KN - Journal of Cartography and Geographic Information (Vol. 69, Issue 1, pp. 51–62). Springer Science and Business Media LLC. https://doi.org/10.1007/s42489-019-00006-2
Gmeiner, A., Ivanova, M., Kamau Njage, P. M., Hansen, L. T., Chindelevitch, L., & Leekitcharoenphon, P. (2023). Quantitative prediction of disinfectant tolerance inListeria monocytogenesusing whole genome sequencing and machine learning. Cold Spring Harbor Laboratory. https://doi.org/10.1101/2023.11.05.565740
Grubaugh, N. D., Ladner, J. T., Lemey, P., Pybus, O. G., Rambaut, A., Holmes, E. C., & Andersen, K. G. (2018). Tracking virus outbreaks in the twenty-first century. In Nature Microbiology (Vol. 4, Issue 1, pp. 10–19). Springer Science and Business Media LLC. https://doi.org/10.1038/s41564-018-0296-2
Hayes, D., Cappa, F., & Le-Khac, N. A. (2020). An effective approach to mobile device management: Security and privacy issues associated with mobile applications. In Digital Business (Vol. 1, Issue 1, p. 100001). Elsevier BV. https://doi.org/10.1016/j.digbus.2020.100001
Hayman, D. T. S., Adisasmito, W. B., Almuhairi, S., Behravesh, C. B., Bilivogui, P., Bukachi, S. A., Casas, N., Becerra, N. C., Charron, D. F., Chaudhary, A., Ciacci Zanella, J. R., Cunningham, A. A., Dar, O., Debnath, N., Dungu, B., Farag, E., Gao, G. F., Khaitsa, M., Machalaba, C., … Koopmans, M. (2023). Developing One Health surveillance systems. In One Health (Vol. 17, p. 100617). Elsevier BV. https://doi.org/10.1016/j.onehlt.2023.100617
Herfort, B., Lautenbach, S., Porto de Albuquerque, J., Anderson, J., & Zipf, A. (2021). The evolution of humanitarian mapping within the OpenStreetMap community. In Scientific Reports (Vol. 11, Issue 1). Springer Science and Business Media LLC. https://doi.org/10.1038/s41598-021-82404-z
Heron, M. J., Hanson, V. L., & Ricketts, I. (2013). Open Source and Accessibility: Advantages and Limitations. In Journal of Interaction Science (Vol. 1, Issue 1, p. 2). Springer Science and Business Media LLC. https://doi.org/10.1186/2194-0827-1-2
Kędzior, M. (2020). The right to data protection and the COVID-19 pandemic: the European approach. In ERA Forum (Vol. 21, Issue 4, pp. 533–543). Springer Science and Business Media LLC. https://doi.org/10.1007/s12027-020-00644-4
Kostkova, P. (2018). Disease surveillance data sharing for public health: the next ethical frontiers. In Life Sciences, Society and Policy (Vol. 14, Issue 1). Springer Science and Business Media LLC. https://doi.org/10.1186/s40504-018-0078-x
Letunic, I., & Bork, P. (2021). Interactive Tree Of Life (iTOL) v5: an online tool for phylogenetic tree display and annotation. In Nucleic Acids Research (Vol. 49, Issue W1, pp. W293–W296). Oxford University Press (OUP). https://doi.org/10.1093/nar/gkab301
Liu, Y.-Y., Chen, C.-C., Yang, C.-H., Hsieh, H.-Y., He, J.-X., Lin, H.-H., & Lee, C.-C. (2022). LmTraceMap: A Listeria monocytogenes fast-tracing platform for global surveillance. In Z. Ruan (Ed.), PLOS ONE (Vol. 17, Issue 5, p. e0267972). Public Library of Science (PLoS). https://doi.org/10.1371/journal.pone.0267972
Mangone, I., Radomski, N., Di Pasquale, A., Santurbano, A., Calistri, P., Cammà, C., & Maassen, K. (2021). Refinement of the COHESIVE Information System towards a unified ontology of food terms for the public health organizations (COHESIVE). https://doi.org/10.5281/ZENODO.5482422
Mixão, V., Pinto, M., Sobral, D., Di Pasquale, A., Gomes, J. P., & Borges, V. (2023). ReporTree: a surveillance-oriented tool to strengthen the linkage between pathogen genetic clusters and epidemiological data. In Genome Medicine (Vol. 15, Issue 1). Springer Science and Business Media LLC. https://doi.org/10.1186/s13073-023-01196-1
Nasri, F., Kongkitimanon, K., Wittig, A., Cortés, J. S., Brinkmann, A., Nitsche, A., Schmachtenberg, A.-J., Renard, B. Y., & Fuchs, S. (2023). MpoxRadar: a worldwide MPXV genomic surveillance dashboard. In Nucleic Acids Research (Vol. 51, Issue W1, pp. W331–W337). Oxford University Press (OUP). https://doi.org/10.1093/nar/gkad325
Neher, R. A., & Bedford, T. (2018). Real-Time Analysis and Visualization of Pathogen Sequence Data. In C. S. Kraft (Ed.), Journal of Clinical Microbiology (Vol. 56, Issue 11). American Society for Microbiology. https://doi.org/10.1128/jcm.00480-18
Nsoesie, E. O., Kluberg, S. A., Mekaru, S. R., Majumder, M. S., Khan, K., Hay, S. I., & Brownstein, J. S. (2015). New digital technologies for the surveillance of infectious diseases at mass gathering events. In Clinical Microbiology and Infection (Vol. 21, Issue 2, pp. 134–140). Elsevier BV. https://doi.org/10.1016/j.cmi.2014.12.017
Overbeek, R., Disz, T., & Stevens, R. (2004). The SEED. In Communications of the ACM (Vol. 47, Issue 11, pp. 46–51). Association for Computing Machinery (ACM). https://doi.org/10.1145/1029496.1029525
Payne, M., Hu, D., Wang, Q., Sullivan, G., Graham, R. M., Rathnayake, I. U., Jennison, A. V., Sintchenko, V., & Lan, R. (2024). DODGE: Automated point source bacterial outbreak detection using cumulative long term genomic surveillance. Cold Spring Harbor Laboratory. https://doi.org/10.1101/2024.01.21.24301506
Perry, H. N., McDonnell, S. M., Alemu, W., Nsubuga, P., Chungong, S., Otten, M. W., Jr, Lusamba-dikassa, P. S., & Thacker, S. B. (2007). Planning an integrated disease surveillance and response system: a matrix of skills and activities. In BMC Medicine (Vol. 5, Issue 1). Springer Science and Business Media LLC. https://doi.org/10.1186/1741-7015-5-24
Potdar, A. M., D G, N., Kengond, S., & Mulla, M. M. (2020). Performance Evaluation of Docker Container and Virtual Machine. In Procedia Computer Science (Vol. 171, pp. 1419–1428). Elsevier BV. https://doi.org/10.1016/j.procs.2020.04.152
Pronyk, P. M., de Alwis, R., Rockett, R., Basile, K., Boucher, Y. F., Pang, V., Sessions, O., Getchell, M., Golubchik, T., Lam, C., Lin, R., Mak, T.-M., Marais, B., Twee-Hee Ong, R., Clapham, H. E., Wang, L., Cahyorini, Y., Polotan, F. G. M., Rukminiati, Y., … Sintchenko, V. (2023). Advancing pathogen genomics in resource-limited settings. In Cell Genomics (Vol. 3, Issue 12, p. 100443). Elsevier BV. https://doi.org/10.1016/j.xgen.2023.100443
Salem, B., Alves Lino, J., & Simons, J. (2017). A Framework for Responsive Environments. In Lecture Notes in Computer Science (pp. 263–277). Springer International Publishing. https://doi.org/10.1007/978-3-319-56997-0_21
Sattari, M., Jahanbakhsh, M., Ashrafi-Rizi, H., & Jangi, M. (2020). Big data in COVID-19 surveillance system: A commentary. In Journal of Education and Health Promotion (Vol. 9, Issue 1, p. 329). Medknow. https://doi.org/10.4103/jehp.jehp_303_20
Schwind, A., Midoglu, C., Alay, Ö., Griwodz, C., & Wamser, F. (2019). Dissecting the performance of YouTube video streaming in mobile networks. In International Journal of Network Management (Vol. 30, Issue 3). Wiley. https://doi.org/10.1002/nem.205
Silva, M., Machado, M. P., Silva, D. N., Rossi, M., Moran-Gilad, J., Santos, S., Ramirez, M., & Carriço, J. A. (2018). chewBBACA: A complete suite for gene-by-gene schema creation and strain identification. In Microbial Genomics (Vol. 4, Issue 3). Microbiology Society. https://doi.org/10.1099/mgen.0.000166
Ștefan, I. A., Ștefan, A., Tsalapatas, H., Heidmann, O., & Gheorghe, A. F. (2022). Collaborative decision-making in software research projects: the innovation challenge. In Procedia Computer Science (Vol. 199, pp. 1318–1326). Elsevier BV. https://doi.org/10.1016/j.procs.2022.01.167
Stockdale, J. E., Liu, P., & Colijn, C. (2022). The potential of genomics for infectious disease forecasting. In Nature Microbiology (Vol. 7, Issue 11, pp. 1736–1743). Springer Science and Business Media LLC. https://doi.org/10.1038/s41564-022-01233-6
Tweed, S., Stewart, D., Hornsey, E., & Graham, W. (2022). Increasing role of Public Health Rapid Response Teams in infectious disease outbreaks. In European Journal of Public Health (Vol. 32, Issue Supplement_3). Oxford University Press (OUP). https://doi.org/10.1093/eurpub/ckac130.022
Volkov, V. (2022). System analysis of the fast global coronavirus disease 2019 (COVID-19) spread. Can we avoid future pandemics under global climate change? In Communicative & Integrative Biology (Vol. 15, Issue 1, pp. 150–157). Informa UK Limited. https://doi.org/10.1080/19420889.2022.2082735
Xu, X., Xu, A., Jiang, Y., Wang, Z., Wang, Q., Zhang, Y., & Wen, H. (2020). Research on Security Issues of Docker and Container Monitoring System in Edge Computing System. In Journal of Physics: Conference Series (Vol. 1673, Issue 1, p. 012067). IOP Publishing. https://doi.org/10.1088/1742-6596/1673/1/012067
Young, S. F., & McCauley, C. D. (2019). User-Driven Feedback Tools for Leader Development. In Feedback at Work (pp. 265–285). Springer International Publishing. https://doi.org/10.1007/978-3-030-30915-2_14
Zhou, Z., Alikhan, N.-F., Sergeant, M. J., Luhmann, N., Vaz, C., Francisco, A. P., Carriço, J. A., & Achtman, M. (2018). GrapeTree: visualization of core genomic relationships among 100,000 bacterial pathogens. In Genome Research (Vol. 28, Issue 9, pp. 1395–1404). Cold Spring Harbor Laboratory. https://doi.org/10.1101/gr.232397.117
Zhou, Z., Alikhan, N.-F., Mohamed, K., Fan, Y., & Achtman, M. (2019). The EnteroBase user’s guide, with case studies on Salmonella transmissions, Yersinia pestis phylogeny, and Escherichia core genomic diversity. In Genome Research (Vol. 30, Issue 1, pp. 138–152). Cold Spring Harbor Laboratory. https://doi.org/10.1101/gr.251678.119