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Human behavior-driven epidemic surveillance in urban landscapes (2404.14009v1)

Published 22 Apr 2024 in physics.soc-ph

Abstract: We introduce a surveillance strategy specifically designed for urban areas to enhance preparedness and response to disease outbreaks by leveraging the unique characteristics of human behavior within urban contexts. By integrating data on individual residences and travel patterns, we construct a Mixing matrix that facilitates the identification of critical pathways that ease pathogen transmission across urban landscapes enabling targeted testing strategies. Our approach not only enhances public health systems' ability to provide early epidemiological alerts but also underscores the variability in strategy effectiveness based on urban layout. We prove the feasibility of our mobility-informed policies by mapping essential mobility flows to major transit stations, showing that few resources focused on specific stations yields a more effective surveillance than non-targeted approaches. This study emphasizes the critical role of integrating human behavioral patterns into epidemic management strategies to improve the preparedness and resilience of major cities against future outbreaks.

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References (60)
  1. F. Snowden, Epidemics and Society: From the Black Death to the Present (Yale University Press, 2019).
  2. W. McNeill, Plagues and Peoples (Anchor, 1976).
  3. J. Domínguez-Andrés et al., “Evolution of cytokine production capacity in ancient and modern european populations,” eLife 10, e64971 (2021).
  4. E. Alirol et al., “Urbanisation and infectious diseases in a globalised world,” The Lancet Infectious Diseases 11, 131–141 (2011).
  5. N. Brizuela, N. García-Chan, H. Gutiérrez-Pulido,  and G. Chowell, “Understanding the role of urban design in disease spreading,” Proceedings of the Royal Society A: Mathematical, Physical and Engineering Sciences 477, 20200524 (2021).
  6. U. Bilal, C. P. de Castro, T. Alfaro, T. Barrientos-Gutierrez, M. L. Barreto, C. M. Leveau, K. Martinez-Folgar, J. J. Miranda, F. Montes, P. Mullachery, M. F. Pina, D. A. Rodriguez, G. F. dos Santos, R. F. S. Andrade,  and A. V. D. Roux, “Scaling of mortality in 742 metropolitan areas of the americas,” Science Advances 7, eabl6325 (2021), https://www.science.org/doi/pdf/10.1126/sciadv.abl6325 .
  7. P. A. Kache, M. Santos-Vega, A. M. Stewart-Ibarra, E. M. Cook, K. C. Seto,  and M. A. Diuk-Wasser, “Bridging landscape ecology and urban science to respond to the rising threat of mosquito-borne diseases,” Nature Ecology & Evolution 6, 1601–1616 (2022).
  8. R. Baker, A. Mahmud, I. Miller, et al., “Infectious disease in an era of global change,” Nat Rev Microbiol 20, 193–205 (2022a).
  9. C. Buckee, A. Noor,  and L. Sattenspiel, “Thinking clearly about social aspects of infectious disease transmission,” Nature 595, 205–213 (2021).
  10. B. M. Althouse, S. V. Scarpino, L. A. Meyers, J. W. Ayers, M. Bargsten, J. Baumbach, J. S. Brownstein, L. Castro, H. Clapham, D. A. Cummings, S. Del Valle, S. Eubank, G. Fairchild, L. Finelli, N. Generous, D. George, D. R. Harper, L. Hébert-Dufresne, M. A. Johansson, K. Konty, M. Lipsitch, G. Milinovich, J. D. Miller, E. O. Nsoesie, D. R. Olson, M. Paul, P. M. Polgreen, R. Priedhorsky, J. M. Read, I. Rodríguez-Barraquer, D. J. Smith, C. Stefansen, D. L. Swerdlow, D. Thompson, A. Vespignani,  and A. Wesolowski, “Enhancing disease surveillance with novel data streams: challenges and opportunities,” EPJ Data Science 4, 17 (2015).
  11. S. V. Scarpino, A. Allard,  and L. Hébert-Dufresne, “The effect of a prudent adaptive behaviour on disease transmission,” Nature Physics 12, 1042–1046 (2016).
  12. P. Manfredi and A. D’Onofrio, Modeling the Interplay Between Human Behavior and the Spread of Infectious Diseases (Springer, Berlin, 2015).
  13. D. Watts, R. Muhamad, D. Medina,  and P. Dodds, “Multiscale, resurgent epidemics in a hierarchical metapopulation model,” Proc. Natl. Acad. Sci. U. S. A. 102, 11157–11162 (2005).
  14. V. Colizza, R. Pastor-Satorras,  and A. Vespignani, “Reaction–diffusion processes and metapopulation models in heterogeneous networks,” Nature Physics 3, 276–282 (2007).
  15. V. Colizza and A. Vespignani, “Multiscale, resurgent epidemics in a hierarchical metapopulation model,” Proceedings of the National Academy of Sciences 104, 12487–12492 (2007).
  16. V. Colizza and A. Vespignani, “Epidemic modeling in metapopulation systems with heterogeneous coupling pattern: theory and simulations,” J Theor Biol 251, 450–467 (2008).
  17. D. Balcan, V. Colizza, B. Gonçalves, H. Hu, J. Ramasco,  and A. Vespignani, “Multiscale mobility networks and the spatial spreading of infectious diseases,” Proceedings of the National Academy of Sciences (USA) 106, 21484–21489 (2009).
  18. V. Belik, T. Geisel,  and D. Brockmann, “Epidemic spreading in metapopulation networks with heterogeneous connectivity patterns,” Chaos, Solitons & Fractals 44, 404–412 (2011a).
  19. S. Meloni, N. Perra, A. Arenas, et al., “Modeling human mobility responses to the large-scale spreading of infectious diseases,” Sci Rep 1, 62 (2011).
  20. D. Soriano-Paños, L. Lotero, A. Arenas,  and J. Gómez-Gardeñes, “Spreading processes in multiplex metapopulations containing different mobility networks,” Phys. Rev. X 8, 031039 (2018).
  21. D. Soriano-Paños, J. H. Arias-Castro, A. Reyna-Lara, H. J. Martínez, S. Meloni,  and J. Gómez-Gardeñes, “Vector-borne epidemics driven by human mobility,” Phys. Rev. Research 2, 013312 (2020).
  22. M. Gatto et al., “Spread and dynamics of the covid-19 epidemic in italy: Effects of emergency containment measures,” Proc. Natl Acad. Sci. USA 117, 10484–10491 (2020).
  23. E. Bertuzzo et al., “The geography of covid-19 spread in italy and implications for the relaxation of confinement measures,” Nat. Commun. 11, 1–11 (2020).
  24. A. Arenas, W. Cota, J. Gómez-Gardeñes, S. Gómez, C. Granell, J. T. Matamalas, D. Soriano-Paños,  and B. Steinegger, “Modeling the spatiotemporal epidemic spreading of covid-19 and the impact of mobility and social distancing interventions,” Phys. Rev. X 10, 041055 (2020).
  25. V. Colizza, A. Barrat, M. Barthélemy,  and A. Vespignani, “The role of the airline transportation network in the prediction and predictability of global epidemics,” Proc. Natl Acad. Sci. 103, 2015–2020 (2006).
  26. D. Brockmann and D. Helbing, “The hidden geometry of complex, network-driven contagion phenomena,” Science 342, 1337–1342 (2013).
  27. Q. Zhang, K. Sun, M. Chinazzi, A. Pastore y Piontti, N. E. Dean, D. P. Rojas, S. Merler, D. Mistry, P. Poletti, L. Rossi, M. Bray, M. E. Halloran, I. M. J. Longini,  and A. Vespignani, “Spread of zika virus in the americas,” Proc. Natl Acad. Sci. U.S.A. 114, E4334–E4343 (2017), edited by Alan Hastings, University of California, Davis, CA, approved March 30, 2017 (received for review December 8, 2016).
  28. P. Bosetti, P. Poletti, M. Stella, B. Lepri, S. Merler,  and M. De Domenico, “Heterogeneity in social and epidemiological factors determines the risk of measles outbreaks,” PNAS 117, 30118–30125 (2020).
  29. X. Zhu, Y. Liu, S. Wang, R. Wang, X. Chen,  and W. Wang, “Allocating resources for epidemic spreading on metapopulation networks,” Applied Mathematics and Computation 411, 126531 (2021).
  30. A. Reyna-Lara, D. Soriano-Paños, J. Arias-Castro, H. Martínez,  and J. Gómez-Gardeñes, “A metapopulation approach to identify targets for wolbachia-based dengue control,” Chaos 32, 041105 (2022).
  31. J. Bedson, L. A. Skrip, D. Pedi, S. Abramowitz, S. Carter, M. F. Jalloh, S. Funk, N. Gobat, T. Giles-Vernick, G. Chowell, et al., “A review and agenda for integrated disease models including social and behavioural factors,” Nature human behaviour 5, 834–846 (2021).
  32. J. Bedford, J. Farrar, C. Ihekweazu, G. Kang, M. Koopmans,  and J. Nkengasong, “A new twenty-first century science for effective epidemic response,” Nature 575, 130–136 (2019).
  33. M. Salathé, “Digital epidemiology: what is it, and where is it going?” Life sciences, society and policy 14, 1 (2018).
  34. M. C. González, C. A. Hidalgo,  and A.-L. Barabási, “Understanding individual human mobility patterns,” Nature 453, 779–782 (2008).
  35. H. Barbosa, M. Barthelemy, G. Ghoshal, C. R. James, M. Lenormand, T. Louail, R. Menezes, J. J. Ramasco, F. Simini,  and M. Tomasini, “Human mobility: Models and applications,” Physics Reports 734, 1–74 (2018).
  36. S. Jiang et al., “The timegeo modeling framework for urban motility without travel surveys,” Proc. Natl. Acad. Sci. USA 113, E5370–E5378 (2016).
  37. E. Bokányi, S. Juhász, M. Karsai,  and B. Lengyel, “Universal patterns of long-distance commuting and social assortativity in cities,” Scientific Reports 11, 20829 (2021).
  38. D. Balcan and A. Vespignani, “Phase transitions in contagion processes mediated by recurrent mobility patterns,” Nature Physics 7, 581–586 (2011).
  39. V. Belik, T. Geisel,  and D. Brockmann, “Natural human mobility patterns and spatial spread of infectious diseases,” Phys. Rev. X 1, 011001 (2011b).
  40. A. Apolloni, C. Poletto, J. J. Ramasco, P. Jensen,  and V. Colizza, “Commuting in metapopulation epidemic modeling,” Scientific Reports 4, 4857 (2014).
  41. S. Charaudeau, K. Pakdaman,  and P.-Y. Boëlle, “Commuter mobility and the spread of infectious diseases: Application to influenza in france,” PLoS One 9, e83002 (2014).
  42. J. Gómez-Gardeñes, D. Soriano-Paños,  and A. Arenas, “Critical regimes driven by recurrent mobility patterns of reaction–diffusion processes in networks,” Nature Physics 14, 391–395 (2018).
  43. B. Rader, S. V. Scarpino, A. Nande, A. L. Hill, B. Adlam, R. C. Reiner, D. M. Pigott, B. Gutierrez, A. E. Zarebski, M. Shrestha, J. S. Brownstein, M. C. Castro, C. Dye, H. Tian, O. G. Pybus,  and M. U. G. Kraemer, “Crowding and the shape of covid-19 epidemics,” Nature Medicine 26, 1829–1834 (2020).
  44. S. Hazarie, D. Soriano-Paños, A. Arenas, J. Gómez-Gardeñes,  and G. Ghoshal, “Interplay between population density and mobility in determining the spread of epidemics in cities,” Communications Physics 4, 191 (2021).
  45. J. Aguilar, A. Bassolas, G. Ghoshal, S. Hazarie, A. Kirkley, M. Mazzoli, S. Meloni, S. Mimar, V. Nicosia, J. J. Ramasco,  and A. Sadilek, “Impact of urban structure on infectious disease spreading,” Scientific Reports 12, 3816 (2022).
  46. P. Valgañón, D. Soriano-Paños, A. Arenas,  and J. Gómez-Gardeñes, “Contagion–diffusion processes with recurrent mobility patterns of distinguishable agents,” Chaos 32, 043102 (2022).
  47. L. Torres, K. S. Chan, H. Tong,  and T. Eliassi-Rad, “Nonbacktracking eigenvalues under node removal: X-centrality and targeted immunization,” SIAM Journal on Mathematics of Data Science 3, 656–675 (2021).
  48. C. Roth, S. Kang, M. Batty,  and M. Barthélemy, “Structure of urban movements: Polycentric activity and entangled hierarchical flows,” PLOS ONE 6, e15923 (2011).
  49. A. Bassolas, H. Barbosa-Filho, B. Dickinson, X. Dotiwalla, P. Eastham, R. Gallotti, G. Ghoshal, B. Gipson, S. A. Hazarie, H. Kautz, O. Kucuktunc, A. Lieber, A. Sadilek,  and J. J. Ramasco, “Hierarchical organization of urban mobility and its connection with city livability,” Nature Communications 10, 4817 (2019).
  50. T. Oraby, M. G. Tyshenko, J. C. Maldonado, K. Vatcheva, S. Elsaadany, W. Q. Alali, J. C. Longenecker,  and M. Al-Zoughool, “Modeling the effect of lockdown timing as a covid-19 control measure in countries with differing social contacts,” Scientific reports 11, 3354 (2021).
  51. B. Steinegger, C. Granell, G. Rapisardi, S. Gómez, J. Matamalas, D. Soriano-Paños, J. Gómez-Gardeñes, A. Arenas, et al., “Joint analysis of the epidemic evolution and human mobility during the first wave of covid-19 in spain: Retrospective study,” JMIR Public Health and Surveillance 9, e40514 (2023).
  52. D. H. Morris, F. W. Rossine, J. B. Plotkin,  and S. A. Levin, “Optimal, near-optimal, and robust epidemic control,” Communications Physics 4, 78 (2021).
  53. “Bogotá cómo vamos: Informe de calidad de vida en bogotá,”   (2022).
  54. K. M. Bubar, K. Reinholt, S. M. Kissler, M. Lipsitch, S. Cobey, Y. H. Grad,  and D. B. Larremore, “Model-informed covid-19 vaccine prioritization strategies by age and serostatus,” Science 371, 916–921 (2021).
  55. R. E. Baker, A. S. Mahmud, I. F. Miller, M. Rajeev, F. Rasambainarivo, B. L. Rice, S. Takahashi, A. J. Tatem, C. E. Wagner, L.-F. Wang, A. Wesolowski,  and C. J. E. Metcalf, “Infectious disease in an era of global change,” Nature Reviews Microbiology 20, 193–205 (2022b).
  56. “Colombia’s 2018 National Census of Population and Housing,” https://www.dane.gov.co/index.php/estadisticas-por-tema/demografia-y-poblacion/censo-nacional-de-poblacion-y-vivenda-2018 (2018a), accessed: 20 September 2023.
  57. “Encuesta de Movilidad de Bogotá 2018,” https://datosabiertos.bogota.gov.co/dataset/encuesta_movilidad_bogota (2018b), accessed: 4 August 2020.
  58. “TIGER/Line Shapefiles and TIGER/Line Files,” https://www2.census.gov/geo/tiger/TIGER2010BLKPOPHU/ (2010), accessed: 30 September 2021.
  59. “United States Longitudinal Employer-Household Dynamics (LEHD) Data,” https://lehd.ces.census.gov/data/ (2021), accessed: 30 September 2021.
  60. United States mobility data sources are available at: https://lehd.ces.census.gov/data/lodes/LODES7/ (Accessed: 2021-09-30).
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