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Delineating Zones of Disease Diffusion from the Amenity-Sharing Network in Peninsular Malaysia

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Earth Data Analytics for Planetary Health

Part of the book series: Atmosphere, Earth, Ocean & Space ((AEONS))

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Abstract

Disease diffusion happens when infected and susceptible individuals move around and closely interact with each other. The boundary of human movement can be found by analysing the locations of amenities and people. The human movement boundaries can be considered as the zones of disease diffusion, which is essential for the establishment of disease control measures. During the COVID-19 pandemic, Malaysia had gone through a series of nationwide Movement Control Orders (MCO)—multiple phases of country/city lockdown measures—starting from March 2020. One key order during MCO was to restrict the travel distance to a 10 km radius from household locations. However, this movement restriction can only eliminate/reduce the long-range disease spreading (relocation) but not the disease diffusion within a local area (expansion). The disease can still be transmitted within a neighbourhood and between closely located or densely interacted neighbourhoods. In other words, people who visited the same region of an outbreak cluster would still expose to the disease. This study analyses the boundaries of densely connected neighbourhoods based on the amenity-sharing relationships, i.e., the disease diffusion zones, and identify the vulnerable locations in terms of spreading and contracting diseases, i.e., the centre(s) of zones. Using Peninsular Malaysia as a case study, a four-step framework was established, which utilised the open-data materials and open-source software. The analysis results from the case study showed that while some of the zones resembled the administrative boundaries, a considerable proportion of the zones extended the city area to the neighbouring urbanised area while some zones split a city into separated zones. These identified zones function as a reference for future policymaking on disease control issues.

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Notes

  1. 1.

    Geofabrik’s free download server: https://download.geofabrik.de/asia.html.

  2. 2.

    All spatial data were projected to EPSG:3375 projection from EPSG:4326.

  3. 3.

    GADM database, version 3.4: https://gadm.org/download_country.html.

  4. 4.

    Infomap, version 1.7.0: https://www.mapequation.org/infomap/.

References

  1. Bernama (2020) MCO: travel now restricted to 10-km radius. Bernama. Accessed 2022 Jan 03

    Google Scholar 

  2. Boeing G, Higgs C, Liu S, Giles-Corti B, Sallis JF, Cerin E, Lowe M, Adlakha D, Hinckson E, Moudon AV, Salvo D, Adams MA, Barrozo LV, Bozovic T, Delclòs-Alió X, Dygrýn J, Ferguson S, Gebel K, Ho TP, Lai P-C, Martori JC, Nitvimol K, Queralt A, Roberts JD, Sambo GH, Schipperijn J, Vale D, Van de Weghe N, Vich G, Arundel J (2022) Using open data and opensource software to develop spatial indicators of urban design and transport features for achieving healthy and sustainable cities. Lancet Glob Health 10(6):e907–e918

    Article  Google Scholar 

  3. Bunyan J (2020) PM: Malaysia under movement control order from Wed until March 31, all shops closed except for essential services. Malay Mail. Accessed 2022 Jan 03

    Google Scholar 

  4. Chin WCB (2021) Daily life pattern of a city: delineating activity space and time using social media data. SSRN, p 3961269

    Google Scholar 

  5. Chin WCB, Bouffanais R (2020) Spatial super-spreaders and super-susceptibles in human movement networks. Sci Rep 10:18642

    Article  Google Scholar 

  6. Chin WCB, Huang C-Y (2020) Comments on “EpiRank: modeling bidirectional disease spread in asymmetric commuting networks” for analyzing emerging coronavirus epidemic patterns. MedRxiv

    Google Scholar 

  7. Chin WCB, Wen T-H (2015) Geographically modified PageRank algorithms: identifying the spatial concentration of human movement in a geospatial network. PLoS One 10(10):e0139509

    Article  Google Scholar 

  8. Chin WCB, Wen T-H, Sabel CE, Wang I-H et al (2017) A geo-computational algorithm for exploring the structure of diffusion progression in time and space. Sci Rep 7(1):1–13

    Article  Google Scholar 

  9. Cliff AD, Haggett P, Smallman-Raynor M, Smallman-Raynor MR (2000) Island epidemics. Oxford University Press on Demand

    Google Scholar 

  10. Department of Statistics, Malaysia (2011) Population distribution and basic demographic characteristics 2010. http://www.statistics.gov.my/portal/download_Population/files/census2010/Taburan_Penduduk_dan_Ciri-ciri_Asas_Demografi.pdf. Accessed 2021 Nov 16

  11. Di Domenico L, Pullano G, Sabbatini CE, Boëlle P-Y, Colizza V (2020) Impact of lockdown on COVID-19 epidemic in Île-de-France and possible exit strategies. BMC Med 18(1):1–13

    Article  Google Scholar 

  12. Geofabrik (2021) Download OpenStreetMap data for this region: Malaysia, Singapore, and Brunei. https://download.geofabrik.de/asia/malaysia-singapore-brunei.html. Accessed 2021 Jul 26

  13. Golledge RG (1997) Spatial behavior: a geographic perspective. Guilford Press

    Google Scholar 

  14. Haggett P (1966) Locational analysis in human geography. St. Martin’s

    Google Scholar 

  15. Huang C-Y, Chin WCB, Wen T-H, Fu Y-H, Tsai Y-S (2019) Epirank: modeling bidirectional disease spread in asymmetric commuting networks. Sci Rep 9(1):1–15

    Google Scholar 

  16. Huang C-Y, Wen T-H, Tsai Y-S (2014) FLUed: a novel four-layer model for simulating epidemic dynamics and assessing intervention policies. J Appl Math 2013:325816

    Google Scholar 

  17. Huang J, Kwan M-P, Kan Z (2021) The superspreading places of COVID-19 and the associated built-environment and socio-demographic features: a study using a spatial network framework and individual-level activity data. Health Place 72:102694

    Article  Google Scholar 

  18. Kan Z, Kwan M-P, Huang J, Wong MS, Liu D (2021) Comparing the space-time patterns of high-risk areas in different waves of COVID-19 in Hong Kong. Trans GIS 25(6):2982–3001

    Article  Google Scholar 

  19. Klapka P, Halas M (2016) Conceptualising patterns of spatial flows: five decades of advances in the definition and use of functional regions. Morav Geogr Rep 24(2):2–11

    Google Scholar 

  20. Kuo F-Y, Wen T-H (2021) A mathematical model for evaluating the medical resource availability of COVID-19 in time and space. In: Shaw S-L, Sui D (eds) Mapping COVID-19 in space and time: understanding the spatial and temporal dynamics of a global pandemic, Chapter 15. Springer International Publishing, Cham, pp 295–308

    Chapter  Google Scholar 

  21. Kuo F-Y, Wen T-H (2021) Regionalization for infection control: an algorithm for delineating containment zones considering the regularity of human mobility. Appl Geogr 126:102375

    Article  Google Scholar 

  22. Kuo F-Y, Wen T-H, Sabel CE (2018) Characterizing diffusion dynamics of disease clustering: a modified space-time DBSCAN (MST-DBSCAN) algorithm. Ann Am Assoc Geogr 108(4):1168–1186

    Google Scholar 

  23. Lau H, Khosrawipour V, Kocbach P, Mikolajczyk A, Schubert J, Bania J, Khosrawipour T (2020) The positive impact of lockdown in Wuhan on containing the COVID-19 outbreak in China. J Travel Med 27(3):1–7

    Article  Google Scholar 

  24. Lee J, Lay J-G, Chin WCB, Chi Y-L, Hsueh Y-H (2014) An experiment to model spatial diffusion process with nearest neighbor analysis and regression estimation. Int J Appl Geosp Res 5(1):1–15

    Article  Google Scholar 

  25. Lee JH, Davis AW, Yoon SY, Goulias KG (2016) Activity space estimation with longitudinal observations of social media data. Transportation 43(6):955–977

    Article  Google Scholar 

  26. Leong C-H, Chin WCB, Feng C-C, Wang Y-C (2021) A socio-ecological perspective on COVID19 spatiotemporal integrated vulnerability in Singapore. In: Shaw S-L, Sui D (eds) Mapping COVID-19 in space and time: understanding the spatial and temporal dynamics of a global pandemic, Chapter 6. Springer International Publishing, Cham, pp 81–111

    Chapter  Google Scholar 

  27. Mat NFC, Edinur HA, Razab MKAA, Safuan S (2020) A single mass gathering resulted in massive transmission of COVID-19 infections in Malaysia with further international spread. J Travel Med 27(3):1–4

    Google Scholar 

  28. Meade MS, Emch M (2010) Medical geography. Guilford Press

    Google Scholar 

  29. Moovit (2020) Kuala Lumpur public transit statistics. https://moovitapp.com/insights/en/Moovit_Insights_Public_Transit_Index_Malaysia_Kuala_Lumpur-1082. Accessed 2022 Jan 03

  30. Numbeo (2020) Traffic in Kuala Lumpur, Malaysia. https://www.numbeo.com/traffic/in/Kuala-Lumpur. Accessed 2022 Jan 03

  31. Pfefferbaum B, North CS (2020) Mental health and the Covid-19 pandemic. N Engl J Med 383(6):510–512

    Article  Google Scholar 

  32. Philbrick AK (1957) Principles of areal functional organization in regional human geography. Econ Geogr 33(4):299–336

    Article  Google Scholar 

  33. Pung R, Chiew CJ, Young BE, Chin S, Chen MI, Clapham HE, Cook AR, Maurer-Stroh S, Toh MP, Poh C et al (2020) Investigation of three clusters of COVID-19 in Singapore: implications for surveillance and response measures. The Lancet 395(10229):1039–1046

    Article  Google Scholar 

  34. Rosvall M, Axelsson D, Bergstrom CT (2009) The map equation. Eur Phys J Spec Top 178(1):13–23

    Article  Google Scholar 

  35. Sabel CE, Pringle D, Schærström A (2010) Infectious disease diffusion. In: Brown T, McLafferty S, Moon G (eds) Companion to health and medical geography, Chapter 7. WileyBlackwell, Wiley-Blackwell Malden, MA, pp 111–132

    Google Scholar 

  36. Salim N, Chan WH, Mansor S, Bazin NEN, Amaran S, Faudzi AAM, Zainal A, Huspi SH, Khoo EJH, Shithil SM (2020) COVID-19 epidemic in Malaysia: impact of lock-down on infection dynamics. MedRxiv

    Google Scholar 

  37. Schönfelder S, Axhausen KW (2003) Activity spaces: measures of social exclusion? Transp Policy 10(4):273–286

    Article  Google Scholar 

  38. Srikanth ADS, Chin WCB, Bouffanais R, Schröpfer T (2022) Complexity science-based spatial performance analyses of UNStudio/DP Architects’ SUTD Campus and WOHA’s Kampung Admiralty. In: As I, Basu P, Talwar P (eds) Artificial intelligence in urban planning and design: technologies, implementation, and impacts, Chapter 12. Elsevier, pp 217–244

    Chapter  Google Scholar 

  39. Srikanth ADS, Chin WCB, Bouffanais R, Schröpfer T (2022) Complexity science for urban solutions. In: As I, Basu P, Talwar P (eds) Artificial intelligence in urban planning and design: technologies, implementation, and impacts, Chapter 3. Elsevier, pp 39–58

    Chapter  Google Scholar 

  40. Tang KHD (2020) Movement control as an effective measure against Covid-19 spread in Malaysia: an overview. J Public Health 30:583–586

    Article  Google Scholar 

  41. Tang KHD (2021) From movement control to National Recovery Plan: Malaysia’s strategy to live with COVID-19. Int J Sci Healthc Res 6(4):286–292

    Article  Google Scholar 

  42. Tang KHD, Chin BLF (2021) Correlations between control of COVID-19 transmission and influenza occurrences in Malaysia. Public Health 198:96–101

    Article  Google Scholar 

  43. The Star (2022) Covid-19: high possibility of Omicron wave hitting Malaysia, says Khairy. The Star. Accessed: 2022 Jan 04

    Google Scholar 

  44. The Star (2022) Covid-19: two Omicron sub-variants detected in Malaysia, says Khairy. The Star. Accessed 2022 Jun 10

    Google Scholar 

  45. Wen T-H, Chin WCB (2015) Incorporation of spatial interactions in location networks to identify critical geo-referenced routes for assessing disease control measures on a large-scale campus. Int J Environ Res Public Health 12(4):4170–4184

    Article  Google Scholar 

  46. Wen T-H, Tsai C-T, Chin WCB (2016) Evaluating the role of disease importation in the spatiotemporal transmission of indigenous dengue outbreak. Appl Geogr

    Google Scholar 

  47. Yan Y, Chin WCB, Leong C-H, Wang Y-C, Feng C-C (2021) Emotional responses through COVID-19 in Singapore. In: Shaw S-L, Sui D (eds) Mapping COVID-19 in space and time: understanding the spatial and temporal dynamics of a global pandemic, Chapter 5. Springer International Publishing, Cham, pp 61–79

    Chapter  Google Scholar 

  48. Yao XA, Huang H, Jiang B, Krisp JM (2019) Representation and analytical models for location-based big data. Int J Geogr Inf Sci 33(4):707–713

    Article  Google Scholar 

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Correspondence to Wei Chien Benny Chin .

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Chin, W.C.B. (2023). Delineating Zones of Disease Diffusion from the Amenity-Sharing Network in Peninsular Malaysia. In: Wen, TH., Chuang, TW., Tipayamongkholgul, M. (eds) Earth Data Analytics for Planetary Health. Atmosphere, Earth, Ocean & Space. Springer, Singapore. https://doi.org/10.1007/978-981-19-8765-6_8

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