PERTANIKA JOURNAL OF SCIENCE AND TECHNOLOGY

The COVID-19 pandemic due to the SARS-CoV-2 coronavirus has vastly impacted our national health and economic industries. Hence, the utilisation of big data simulation of the outbreak is essential to guide policymakers, government, and health authorities in better understanding the dynamics of the infectious disease. This paper integrates the Agent-Based-Model (ABM) and Susceptible, Exposed, Infectious and Recovered (SEIR) framework to understand the dynamic transmission of COVID-19 in Sabah, Malaysia. This study employed NetLogo software, which includes parameters such as geographical distribution, population density, variant type, lockdown measures, and vaccination rates across 27 districts, to run the simulation and assess the potential impact of public health interventions. The methodology involves different scenario simulations using varying variant types, vaccination coverage, lockdown, and social distancing measures to determine the virus transmission level. The results indicate that higher vaccination coverage and strict adherence to preventive measures can reduce the spread of the virus, especially in highly densely populated areas. Our simulation resulted in a 2.54% variance with the true data following the parameters and settings mentioned above. Additionally, this study also found that geographical structure and uneven distribution of healthcare across the Sabah district notably affect disease and disaster management and intervention policy and efficacy. These insights are crucial for Malaysian policymakers and health authorities, which need to tailor the public health responses considering geographical and demographic settings. Future recommendations include data of higher geographical resolution, immunisation records, and real-time mobility data to portray a more realistic simulation.

• Ahasan, R., Alam, M. S., Chakraborty, T., & Hossain, M. M. (2022). Applications of GIS and geospatial analyses in COVID-19 research: A systematic review. F1000Research, 9, 1–18. https://doi.org/10.12688/f1000research.27544.2
  
  Almeshal, A. M., Almazrouee, A. I., Alenizi, M. R., & Alhajeri, S. N. (2020). Forecasting the spread of COVID-19 in Kuwait using compartmental and logistic regression models. Applied Sciences, 10(10), Article 3402. https://doi.org/10.3390/app10103402
  
  Avinash, N., Xavier, G. B. A., Alsinai, A., Ahmed, H., Sherine, V. R., & Chellamani, P. (2022). Dynamics of COVID-19 using SEIQR epidemic model. Journal of Mathematics, 2022(1), Article 2138165. https://doi.org/10.1155/2022/2138165
  
  Azhary, J. M. K., Leng, L. K., Razali, N., Sulaiman, S., Wahab, A. V. A., Adlan, A. S. A., & Hassan, J. (2022). The prevalence of menstrual disorders and premenstrual syndrome among adolescent girls living in North Borneo, Malaysia: a questionnaire-based study. BMC Women’s Health, 22(1), 1–9. https://doi.org/10.1186/s12905-022-01929-1
  
  Azzeri, A., Goh, H. C., Jaafar, H., Mohd Noor, M. I., Razi, N. A., Then, A. Y., Suhaimi, J., Kari, F., & Dahlui, M. (2020). A review of published literature regarding health issues of coastal communities in Sabah, Malaysia. International Journal of Environmental Research and Public Health, 17(5), Article 1533. https://doi.org/10.3390/ijerph17051533
  
  Badr, H. S., Du, H., Marshall, M., Dong, E., Squire, M. M., & Gardner, L. M. (2020). Association between mobility patterns and COVID-19 transmission in the USA: A mathematical modelling study. The Lancet Infectious Diseases, 20(11), 1247–1254. https://doi.org/10.1016/S1473-3099(20)30553-3
  
  Balakrishnan, K. N., Yew, C. W., Chong, E. T. J., Daim, S., Mohamad, N. E., Rodrigues, K., & Lee, P. C. (2023). Timeline of SARS-CoV-2 transmission in Sabah, Malaysia: Tracking the molecular evolution. Pathogens, 12(8), 1–17. https://doi.org/10.3390/pathogens12081047
  
  Chen, X., Huang, H., Ju, J., Sun, R., & Zhang, J. (2022). Impact of vaccination on the COVID-19 pandemic in U.S. states. Scientific Reports, 12(1), 1–10. https://doi.org/10.1038/s41598-022-05498-z
  
  Chenchula, S., Karunakaran, P., Sharma, S., & Chavan, M. (2022). Current evidence on efficacy of COVID-19 booster dose vaccination against the Omicron variant: A systematic review. Journal of Medical Virology, 94(7), 2969–2976. https://doi.org/10.1002/jmv.27697
  
  Cheng, X., Han, Z., Abba, B., & Wang, H. (2020). Regional infectious risk prediction of COVID-19 based on geo-spatial data. PeerJ, 8, 1–24. https://doi.org/10.7717/peerj.10139
  
  Dollah, R., Jafar, A., Joko, E. P., Sakke, N., Mapa, M. T., Atang, C., Hung, C. V., & George, F. (2022). Perception of youth in East Malaysia (Sabah) towards the Malaysia national COVID-19 immunisation programme (PICK). Journal of Public Health and Development, 20(1), 203–217. https://doi.org/10.55131/jphd/2022/200116
  
  Dong, T., Dong, W., & Xu, Q. (2022). Agent simulation model of COVID-19 epidemic agent-based on GIS: A case study of Huangpu District, Shanghai. International Journal of Environmental Research and Public Health, 19(16), Article 10242. https://doi.org/10.3390/ijerph191610242
  
  Farheen, F., Shamil, M. S., Rahman Jony, S. S., Ahmad, Z., Sojib, K. H., Chowdhury, A., Niaz Arifin, S. M., Sania, A., & Rahman, M. S. (2022). An agent-based model for COVID-19 in Bangladesh. MedRxiv. https://doi.org/10.1101/2022.07.24.22277974
  
  Gill, B. S., Jayaraj, V. J., Singh, S., Ghazali, S. M., Cheong, Y. L., Iderus, N. H. M., Sundram, B. M., Aris, T., Ibrahim, H. M., Hong, B. H., & Labadin, J. (2020). Modelling the effectiveness of epidemic control measures in preventing the transmis. International Journal of Environmental Research and Public Health, 17(15), 1–13. https://doi.org/10.3390/ijerph17155509
  
  Goroh, M. M. D., Rajahram, G. S., Avoi, R., Van Den Boogaard, C. H., William, T., Ralph, A. P., & Lowbridge, C. (2020). Epidemiology of tuberculosis in Sabah, Malaysia, 2012–2018. Infectious Diseases of Poverty, 9, 1-11. https://doi.org/10.1186/s40249-020-00739-7
  
  Goroh, M., Rajahram, G., Avoi, R., Cvd, B., William, T., Ralph, A. P., & Lowbridge, C. (2020). An Epidemiological Review of Tuberculosis in Sabah, Malaysia, 2012-2018. Research Square. https://doi.org/10.21203/rs.3.rs-28071/v1
  
  Godio, A., Pace, F., & Vergnano, A. (2020). SEIR Modeling of the Italian Epidemic of SARS-CoV-2 Using Computational Swarm Intelligence. International Journal of Environmental Research and Public Health, 17(10), Article 3535. https://doi.org/10.3390/ijerph17103535
  
  Gharakhanlou, N. M., & Hooshangi, N. (2020). Spatio-temporal simulation of the novel coronavirus (COVID-19) outbreak using the agent-based modeling approach (case study: Urmia, Iran). Informatics in Medicine Unlocked, 20, Article 100403. https://doi.org/10.1016/j.imu.2020.100403
  
  Harizah, K. (2021, August 27). Highest records to date at 24,599 cases, 393 deaths. The Malaysian Reserve. https://themalaysianreserve.com/2021/08/27/highest-records-to-date-at-24599-cases-393-deaths/
  
  Hashim, J. H., Adman, M. A., Hashim, Z., Radi, M. F. M., & Kwan, S. C. (2021). COVID-19 epidemic in Malaysia: Epidemic progression, challenges, and response. Frontiers in Public Health, 9, 1–19. https://doi.org/10.3389/fpubh.2021.560592
  
  Hassan, A. M., Ramos, H., & Moaaz, O. (2023). Second-order dynamic equations with noncanonical operator: Oscillatory behavior. Fractal and Fractional, 7(2), 1–17. https://doi.org/10.3390/fractalfract7020134
  
  He, S., Peng, Y., & Sun, K. (2020). SEIR modeling of the COVID-19 and its dynamics. Nonlinear Dynamics, 101(3), 1667–1680. https://doi.org/10.1007/s11071-020-05743-y
  
  Hinch, R., Probert, W. J. M., Nurtay, A., Kendall, M., Wymant, C., Hall, M., Lythgoe, K., Bulas Cruz, A., Zhao, L., Stewart, A., Ferretti, L., Montero, D., Warren, J., Mather, N., Abueg, M., Wu, N., Legat, O., Bentley, K., Mead, T., … & Fraser, C. (2021). OpenABM-Covid19-An agent-based model for non-pharmaceutical interventions against COVID-19 including contact tracing. PLoS Computational Biology, 17(7), 1–26. https://doi.org/10.1371/journal.pcbi.1009146
  
  Hunter, E., & Kelleher, J. D. (2022). Validating and testing an agent-based model for the spread of COVID-19 in Ireland. Algorithms, 15(08), Article 0270. https://doi.org/10.3390/a15080270
  
  Iderus, N. H., Singh, S., Singh, L., Ghazali, S. M., Ling, C. Y., Vei, T. C., Syahmi, A., Zamri, S., Jaafar, N. A., Ruslan, Q., Huda, N., Jaghfar, A., & Gill, B. S. (2022). Correlation between population density and COVID-19 cases during the third wave in Malaysia: Effect of the Delta Variant. International Journal of Environmental Research and Public Health, 19(12), Article 7439. https://doi.org/10.3390/ijerph19127439
  
  Jafar, A., Dollah, R., Sakke, N., Mapa, M. T., Atang, C., Joko, E. P., Sarjono, F., Zakaria, N. S., George, F., & Hung, C. V. (2024). Public perception toward the Malaysian National COVID-19 Immunisation Programme (PICK) in the state of Sabah, Malaysia: A cross-sectional survey. Disaster Medicine and Public Health Preparedness, 18, Article e43. https://doi.org/10.1017/dmp.2024.31
  
  Jiee, S. F., Jantim, A., Mohamed, A. F., & Emiral, M. E. (2021). COVID-19 Pandemic: determinants of workplace preventive practice among primary healthcare workers in Sabah, Malaysia. Journal of Preventive Medicine and Hygiene, 62(3), Article E605. https://doi.org/10.15167/2421-4248/jpmh2021.62.3.2031
  
  Kim, Y., & Cho, N. (2022). A Simulation study on spread of disease and control measures in closed population using ABM. Computation, 10(01), Article 0002. https://doi.org/10.3390/computation10010002
  
  Kong, L., Duan, M., Shi, J., Hong, J., Chang, Z., & Zhang, Z. (2022). Compartmental structures used in modeling COVID-19: A scoping review. Infectious Diseases of Poverty, 11(1), 1–9. https://doi.org/10.1186/s40249-022-01001-y
  
  Kucharski, A. J., Klepac, P., Conlan, A. J. K., Kissler, S. M., Tang, M. L., Fry, H., Gog, J. R., Edmunds, W. J., Emery, J. C., Medley, G., Munday, J. D., Russell, T. W., Leclerc, Q. J., Diamond, C., Procter, S. R., Gimma, A., Sun, F. Y., Gibbs, H. P., Rosello, A., … & Simons, D. (2020). Effectiveness of isolation, testing, contact tracing, and physical distancing on reducing transmission of SARS-CoV-2 in different settings: A mathematical modelling study. The Lancet Infectious Diseases, 20(10), 1151–1160. https://doi.org/10.1016/S1473-3099(20)30457-6
  
  López, L., & Rodó, X. (2021). A modified SEIR model to predict the COVID-19 outbreak in Spain and Italy: Simulating control scenarios and multi-scale epidemics. Results in Physics, 21, Article 103746. https://doi.org/10.1016/j.rinp.2020.103746
  
  Motzev, M. (2019). Prediction accuracy - A measure of simulation reality. Vanguard Scientific Instruments in Management, 15(1), 1–18. https://doi.org/10.13140/RG.2.2.18743.75687
  
  Mwalili, S., Kimathi, M., Ojiambo, V., Gathungu, D., & Mbogo, R. (2020). SEIR model for COVID-19 dynamics incorporating the environment and social distancing. BMC Research Notes, 13(1), 1–5. https://doi.org/10.1186/s13104-020-05192-1
  
  Nagori, A., Awasthi, R., Joshi, V., Vyalla, S. R., Jarodia, A., Gupta, C., Gulati, A., Bandhey, H., Guliani, K. K., Gill, M. S., Kumaraguru, P., & Sethi, T. (2020). Less wrong COVID-19 projections with interactive assumptions. medRxiv. https://doi.org/10.1101/2020.06.06.20124495
  
  Onyechege, D. C., Nor, N. M., & Omer, A. S. F. (2022). The indirect effect of coronavirus disease (COVID-19) pandemic on economic growth in Malaysia: Evidence from the ARDL approach. International Journal of Economics and Management, 16(S1), 99-115. https://doi.org/10.47836/ijeamsi.16.1.007
  
  Pandey, G., Chaudhary, P., Gupta, R., & Pal, S. (2019). SEIR and Regression Model based COVID-19 outbreak predictions in India. arXiv Preprint.
  
  Patrick, E. M. (2022, January 05). Sabah kesan Omicron pertama [Sabah the first Omicron effect]. Astro Awani. https://www.astroawani.com/berita-malaysia/sabah-kesan-kes-omicron-pertama-340088
  
  Paul, S., Mahata, A., Ghosh, U., & Roy, B. (2020). Since January 2020 Elsevier has created a COVID-19 resource centre with free information in English and Mandarin on the novel coronavirus COVID- 19. Elsevier.
  
  Qiu, Z., Sun, Y., He, X., Wei, J., Zhou, R., Bai, J., & Du, S. (2022). Application of genetic algorithm combined with improved SEIR model in predicting the epidemic trend of COVID-19, China. Scientific Reports, 12(1), 1–9. https://doi.org/10.1038/s41598-022-12958-z
  
  Qureshi, S., Akanbi, M. A., Shaikh, A. A., Wusu, A. S., Ogunlaran, O. M., Mahmoud, W., & Osman, M. S. (2023). A new adaptive nonlinear numerical method for singular and stiff differential problems. Alexandria Engineering Journal, 74, 585–597. https://doi.org/10.1016/j.aej.2023.05.055
  
  Reeves, K. D., Polk, C. M., Cox, L. A., Fairman, R. T., Hawkins, G. A., Passaretti, C. L., & Sampson, M. M. (2022). Severe acute respiratory coronavirus virus 2 (SARS-CoV-2) infections occurring in healthcare workers after booster vaccination: A comparison of delta versus omicron variants. Antimicrobial Stewardship and Healthcare Epidemiology, 2(1), 1–7. https://doi.org/10.1017/ash.2022.239
  
  Roslan, M. N. F., Ismail, W. I., Zamzuri, A. S., Ismail, N. F., & Abdul, N. A. N. (2022). Comorbidity status of deceased of Covid-19 patients in Malaysia. International Journal of Academic Research in Business and Social Sciences, 12(10), 2262-2268. https://doi.org/10.6007/ijarbss/v12-i10/15465
  
  Shah, A. U. M., Safri, S. N. A., Thevadas, R., Noordin, N. K., Rahman, A. A., Sekawi, Z., Ideris, A., & Sultan, M. T. H. (2020). COVID-19 outbreak in Malaysia: Actions taken by the Malaysian government. International Journal of Infectious Diseases, 97, 108–116. https://doi.org/10.1016/j.ijid.2020.05.093
  
  Shamil, S., Farheen, F., Ibtehaz, N., Mahmud, I., & Sohel, K. M. (2021). An agent-based modeling of COVID-19: Validation, analysis, and recommendations. In Cognitive Computation (pp. 1723–1734). Springer. https://doi.org/10.1007/s12559-020-09801-w
  
  Silva, P. C. L., Batista, P. V. C., Lima, H. S., Alves, M. A., Guimarães, F. G., & Silva, R. C. P. (2020). COVID-ABS: An agent-based model of COVID-19 epidemic to simulate health and economic effects of social distancing interventions. Chaos, Solitons and Fractals, 139, Article 110088. https://doi.org/10.1016/j.chaos.2020.110088
  
  Tan, C. S., Saim, L., Rao, Y., Kok, S. H., & Ming, L. C. (2021). Public and private sectors collective response to combat COVID-19 in Malaysia. Journal of Pharmaceutical Policy and Practice, 14(1), Article 40. https://doi.org/10.1186/s40545-021-00322-x
  
  Tang, X., Zhao, S., Chiu, A. P. Y., Ma, H., Xie, X., Mei, S., Kong, D., Qin, Y., Chen, Z., Wang, X., & He, D. (2017). Modelling the transmission and control strategies of varicella among school children in Shenzhen, China. PLoS ONE, 12(5), 1–17. https://doi.org/10.1371/journal.pone.0177514
  
  Tha, N. O., Shoesmith, W. D., Tan, B. Y., Ibrahim, M. Y., & Hussein, S. S. (2020). Geographic accessibility of healthcare services and health seeking behaviours of rural communities in Kudat and Pitas areas of Sabah. Borneo Epidemiology Journal, 1(1), 46-54. https://doi.org/10.51200/bej.v1i1.2436
  
  Thompson, J., & Wattam, S. (2021). Estimating the impact of interventions against COVID-19: From lockdown to vaccination. PLoS ONE, 16, 1–54. https://doi.org/10.1371/journal.pone.0261330
  
  Umair, I. (2022, January 31). The science behind the omicron wave’s sharp peak and rapid decline. The Vox. https://www.vox.com/22905020/omicron-wave-surge-covid-19-cases-vaccines
  
  World Health Organization. (2023a). Covid-19. World Health Organization. https://www.who.int/emergencies/diseases/novel-coronavirus-2019/covid-19-policy-briefs
  
  World Health Organization. (2023b). WHO Coronavirus (COVID-19) Dashboard. World Health Organization. https://covid19.who.int/
  
  Yang, Z., Zeng, Z., Wang, K., Wong, S. S., Liang, W., Zanin, M., Liu, P., Cao, X., Gao, Z., Mai, Z., Liang, J., Liu, X., Li, S., Li, Y., Ye, F., Guan, W., Yang, Y., Li, F., Luo, S., … & He, J. (2020). Modified SEIR and AI prediction of the epidemics trend of COVID-19 in China under public health interventions. Journal of Thoracic Disease, 12(3), 165–174. https://doi.org/10.21037/jtd.2020.02.64
  
  Yeo, A. (2020, October 31). Sabah perlu infrastruktur, sistem kesihatan lebih baik [Sabah needs better infrastructure and healthcare systems]. Berita Harian. https://www.bharian.com.my/rencana/komentar/2020/10/748301/sabah-perlu-infrastruktur-sistem-kesihatan-lebih-baik
  
  Zhao, W., Sun, Y., Li, Y., & Guan, W. (2022). Prediction of COVID-19 data using hybrid modeling approaches. Frontiers in Public Health, 10, 1–13. https://doi.org/10.3389/fpubh.2022.923978