COVID-19 RISK MAPPING AND LIFE INSURANCE ESTIMATION: MARKOV CHAIN MODEL FOR PREMIUMS AND BENEFITS IN BANDUNG CITY
Abstract
The COVID-19 pandemic, first identified in China, rapidly spread worldwide and significantly impacted various sectors, including health and insurance. In Indonesia, regional disparities in case trends have highlighted the need for localized risk assessment. This study applies a Markov Chain model to estimate life insurance premiums and benefits by forecasting long-term COVID-19 transmission probabilities across 30 sub-districts in Bandung City. The analysis uses daily confirmed case data collected between September 18, 2020, and April 17, 2022, a period marked by multiple infection waves and heightened transmission risk. COVID-19 trends were categorized into discrete states—decrease, no change, and increase—and modeled to construct transition probability matrices and stationary distributions. These long-term probabilities were then used to generate a regional risk map and inform actuarial pricing of insurance products. The results reveal spatial heterogeneity in case increase probabilities, with Coblong, Arcamanik, and Antapani exhibiting the highest long-term risk. A strong correlation (R² = 0.9473) was found between case increase probabilities and projected insurance benefits and premiums. The practical implication of this study lies in its provision of a data-driven framework that enables insurance companies to align policy pricing with region-specific and evolving pandemic risks, including long-term health consequences such as post-COVID-19 conditions. This approach enhances both the fairness of premium structures and the financial resilience of insurers in managing future public health crises.
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Y. Assefa, C. F. Gilks, S. Reid, R. van de Pas, D. G. Gete, and W. Van Damme, “ANALYSIS OF THE COVID-19 PANDEMIC: LESSONS TOWARDS A MORE EFFECTIVE RESPONSE TO PUBLIC HEALTH EMERGENCIES,” Global. Health, vol. 18, no. 1, pp. 1–13, 2022, doi: https://doi.org/10.1186/s12992-022-00805-9.
F. Ricci et al., “RECOMMENDATIONS FOR PHYSICAL INACTIVITY AND SEDENTARY BEHAVIOR DURING THE CORONAVIRUS DISEASE (COVID-19) PANDEMIC,” Front. Public Heal., vol. 8, no. May, pp. 8–11, 2020, doi: https://doi.org/10.3389/fpubh.2020.00199.
K. A. Riggan, J. Reckhow, M. A. Allyse, M. Long, V. Torbenson, and E. Y. Rivera-Chiauzzi, “IMPACT OF THE COVID-19 PANDEMIC ON OBSTETRICIANS/GYNECOLOGISTS,” Mayo Clin. Proc. Innov. Qual. Outcomes, vol. 5, no. 6, pp. 1128–1137, 2021, doi: https://doi.org/10.1016/j.mayocpiqo.2021.11.002.
S. Sun, Z. Xie, K. Yu, B. Jiang, S. Zheng, and X. Pan, “COVID-19 AND HEALTHCARE SYSTEM IN CHINA: CHALLENGES AND PROGRESSION FOR A SUSTAINABLE FUTURE,” Global. Health, vol. 17, no. 1, pp. 1–8, 2021, doi: https://doi.org/10.1186/s12992-021-00665-9.
A. D. Kaye et al., “ECONOMIC IMPACT OF COVID-19 PANDEMIC ON HEALTHCARE FACILITIES AND SYSTEMS: INTERNATIONAL PERSPECTIVES,” Best Pract. Res. Clin. Anaesthesiol., vol. 35, no. 3, pp. 293–306, 2021, doi: https://doi.org/10.1016/j.bpa.2020.11.009.
R. Filip, R. Gheorghita Puscaselu, L. Anchidin-Norocel, M. Dimian, and W. K. Savage, “GLOBAL CHALLENGES TO PUBLIC HEALTH CARE SYSTEMS DURING THE COVID-19 PANDEMIC: A REVIEW OF PANDEMIC MEASURES AND PROBLEMS,” J. Pers. Med., vol. 12, no. 8, 2022, doi: https://doi.org/10.3390/jpm12081295.
T. Bhatt, V. Kumar, S. Pande, R. Malik, A. Khamparia, and D. Gupta, “A REVIEW ON COVID-19,” Stud. Comput. Intell., vol. 924, no. April, pp. 25–42, 2021, doi: https://doi.org/10.1007/978-3-030-60188-1_2.
C. Sohrabi et al., “WORLD HEALTH ORGANIZATION DECLARES GLOBAL EMERGENCY: A REVIEW OF THE 2019 NOVEL CORONAVIRUS (COVID-19),” Int. J. Surg., vol. 76, no. February, pp. 71–76, 2020, doi: https://doi.org/10.1016/j.ijsu.2020.02.034.
M. Khan et al., “COVID-19: A GLOBAL CHALLENGE WITH OLD HISTORY, EPIDEMIOLOGY AND PROGRESS SO FAR,” Molecules, vol. 26, no. 1, pp. 1–25, 2021, doi: https://doi.org/10.3390/molecules26010039.
M. Guo, X. Liu, X. Chen, and Q. Li, “INSIGHTS INTO NEW-ONSET AUTOIMMUNE DISEASES AFTER COVID-19 VACCINATION,” Autoimmun. Rev., vol. 22, no. 7, p. 103340, 2023, doi: https://doi.org/10.1016/j.autrev.2023.103340.
R. K. Sinuraya, A. A. Suwantika, and M. J. Postma, “CONTROLLING THE COVID-19 PANDEMIC THROUGH VACCINATION: A PERSPECTIVE FROM INDONESIA,” Expert Rev. Vaccines, vol. 24, no. 1, pp. 91–95, 2025, doi: https://doi.org/10.1080/14760584.2025.2451883.
M. Malahayati, T. Masui, and L. Anggraeni, “AN ASSESSMENT OF THE SHORT-TERM IMPACT OF COVID-19 ON ECONOMICS AND THE ENVIRONMENT: A CASE STUDY OF INDONESIA,” EconomiA, vol. 22, no. 3, pp. 291–313, 2021, doi: https://doi.org/10.1016/j.econ.2021.12.003.
R. Djalante et al., “REVIEW AND ANALYSIS OF CURRENT RESPONSES TO COVID-19 IN INDONESIA: PERIOD OF JANUARY TO MARCH 2020,” Prog. Disaster Sci., vol. 6, 2020, doi: https://doi.org/10.1016/j.pdisas.2020.100091.
F. Sudari, I. Priskilla, M. Febiola, and R. K. Sinuraya, “STRATEGIES TO IMPROVE THE VACCINE DISTRIBUTION AND COMMUNITY AWARENESS OF TAKING COVID-19 VACCINE IN RURAL AREAS IN INDONESIA,” Pharmacia, vol. 69, no. 2. pp. 543–553, 2022, doi: https://doi.org/10.3897/pharmacia.69.e81525.
S. M.Ross, “STOCHASTIC PROCESSES SM.” John Wiley & Sons, New York, p. 510, 1996.
S. Banerjee, S. Khajanchi, and S. Chaudhuri, “A MATHEMATICAL MODEL TO ELUCIDATE BRAIN TUMOR ABROGATION BY IMMUNOTHERAPY WITH T11 TARGET STRUCTURE,” PLoS One, vol. 10, no. 5, pp. 1–21, 2015, doi: https://doi.org/10.1371/journal.pone.0123611.
H. W. Hethcote, “THE MATHEMATICS OF INFECTIOUS DISEASES (SIAM REVIEW),” SIAM Rev., vol. 42, no. 4, pp. 599–653, 2000. doi: https://doi.org/10.1137/S0036144500371907
A. W. Roddam, “MATHEMATICAL EPIDEMIOLOGY OF INFECTIOUS DISEASES: MODEL BUILDING, ANALYSIS AND INTERPRETATION,” Int. J. Epidemiol., vol. 30, no. 1, pp. 186–186, 2001, doi: https://doi.org/10.1093/ije/30.1.186.
H. E. Tillett, “INFECTIOUS DISEASES OF HUMANS: DYNAMICS AND CONTROL”. R. M. Anderson, R. M. May, Pp. 757. Oxford University Press; 1991 (£50.00)., Epidemiol. Infect., vol. 108, no. 1, pp. 211–211, 1992, doi: https://doi.org/10.1017/S0950268800059896.
S. Tabera Tsilefa and A. Raherinirina, “SPATIAL MARKOV MATRICES FOR MEASURING THE SPATIAL DEPENDENCIES OF AN EPIDEMIOLOGICAL SPREAD : CASE COVID’19 MADAGASCAR,” BMC Public Health, vol. 24, no. 1, 2024, doi: https://doi.org/10.1186/s12889-024-19654-9 .
J. Odhiambo, P. Weke, and P. Ngare, “MODELING KENYAN ECONOMIC IMPACT OF CORONA VIRUS IN KENYA USING DISCRETE-TIME MARKOV CHAINS,” J. Financ. Econ., vol. 8, no. 2, pp. 80–85, 2020, doi: 10.12691/jfe-8-2-5.
Z. Dehghan Shabani and R. Shahnazi, “SPATIAL DISTRIBUTION DYNAMICS AND PREDICTION OF COVID-19 IN ASIAN COUNTRIES: SPATIAL MARKOV CHAIN APPROACH,” Reg. Sci. Policy Pract., vol. 12, no. 6, pp. 1005–1025, 2020, doi: https://doi.org/10.1111/rsp3.12372.
W. Zhang et al., “ANALYSIS OF COVID-19 EPIDEMIC AND CLINICAL RISK FACTORS OF PATIENTS UNDER EPIDEMIOLOGICAL MARKOV MODEL,” Results Phys., vol. 22, p. 103881, 2021, doi: https://doi.org/10.1016/j.rinp.2021.103881.
D. Haryanto, “THE APPLICATION OF MARKOV CHAIN MODEL TO CALCULATE PREMIUM AND RESERVE OF ENDOWMENT INSURANCE,” BAREKENG J. Ilmu Mat. dan Terap., vol. 16, no. 1, pp. 015–022, 2022, doi: https://doi.org/10.30598/barekengvol16iss1pp015-022.
Z. Xu, H. Zhang, and Z. Huang, “A CONTINUOUS MARKOV-CHAIN MODEL FOR THE SIMULATION OF COVID-19 EPIDEMIC DYNAMICS,” Biology (Basel)., vol. 11, no. 2, 2022, doi: https://doi.org/10.3390/biology11020190.
R. C. van Wijk, L. Mockeliunas, C. M. Upton, J. Peter, A. H. Diacon, and U. S. H. Simonsson, “SEASONAL INFLUENCE ON RESPIRATORY TRACT INFECTION SEVERITY INCLUDING COVID-19 QUANTIFIED THROUGH MARKOV CHAIN MODELING,” CPT Pharmacometrics Syst. Pharmacol., vol. 12, no. 9, pp. 1250–1261, 2023, doi: https://doi.org/10.1002/psp4.13006.
R. Ma, X. Zheng, P. Wang, H. Liu, and C. Zhang, “THE PREDICTION AND ANALYSIS OF COVID-19 EPIDEMIC TREND BY COMBINING LSTM AND MARKOV METHOD,” Sci. Rep., vol. 11, no. 1, pp. 1–14, 2021, doi: https://doi.org/10.1038/s41598-021-97037-5.
S. Zhou et al., “APPLICATION OF HIDDEN MARKOV MODELS TO ANALYZE, GROUP AND VISUALIZE SPATIO-TEMPORAL COVID-19 DATA,” IEEE Access, vol. 9, pp. 134384–134401, 2021, doi: https://doi.org/10.1109/ACCESS.2021.3114364.
P. Babuna, X. Yang, A. Gyilbag, D. A. Awudi, D. Ngmenbelle, and D. Bian, “THE IMPACT OF COVID-19 ON THE INSURANCE INDUSTRY,” Int. J. Environ. Res. Public Health, vol. 17, no. 16, pp. 1–14, 2020, doi: https://doi.org/10.3390/ijerph17165766
C. O. Gunawan and N. Trihadmini, “INSURANCE COMPANY PERFORMANCE ANALYSIS BEFORE AND DURING THE COVID-19 PANDEMIC (STUDY OF GENERAL INSURANCE COMPANIES LISTED ON THE IDX IN 2018-2022),” 2nd Int. Conf. Econ. Business, Manag. Res., 2023, [Online]. Available: https://e-conf.usd.ac.id/index.php/icebmr/.
P. M. Liedtke, “VULNERABILITIES AND RESILIENCE IN INSURANCE INVESTING: STUDYING THE COVID-19 PANDEMIC,” Geneva Pap. Risk Insur. Issues Pract., vol. 46, no. 2, pp. 266–280, 2021, doi: https://doi.org/10.1057/s41288-021-00219-5.
A. G. Macovei, O. Popelo, A. Zhavoronok, R. Dankiewicz, C. G. Cosmulese, and L. Popova, “‘PRE- AND POST-EFFECT OF COVID-19 ON THE INSURANCE INDUSTRY: A STUDY BASED ON ROMANIAN COMPANIES,’” Insur. Mark. Co., vol. 15, no. 2, pp. 74–84, 2024, doi: https://doi.org/10.21511/ins.15(2).2024.07.
K. Puławska, “FINANCIAL STABILITY OF EUROPEAN INSURANCE COMPANIES DURING THE COVID-19 PANDEMIC,” J. Risk Financ. Manag., vol. 14, no. 6, 2021, doi: https://doi.org/10.3390/jrfm14060266.
R. Rajnikanth and S. Doss, “IMPACT OF COVID-19 PANDEMIC ON THE LIFE INSURANCE INDUSTRY INTRODUCTION,” BimaQuest-The J. Insur. Pension Manag., vol. 21, no. 2, pp. 65–85, 2021.
A. M. Farhan et al., “MEASURING THE IMPACT OF THE CORONA PANDEMIC ON THE EFFICIENCY OF INSURANCE ACTIVITY IN THE KINGDOM OF SAUDI ARABIA,” vol. 7, no. 7, pp. 263–278, 2023.
A. Raju, “A MARKOV MODEL FOR PREDICTION OF CORONA VIRUS COVID-19 IN INDIA- A STATISTICAL STUDY,” J. Xidian Univ., vol. 14, no. 4, 2020, doi: https://doi.org/10.37896/jxu14.4/164
A. Din, A. Khan, and D. Baleanu, “STATIONARY DISTRIBUTION AND EXTINCTION OF STOCHASTIC CORONAVIRUS (COVID-19) EPIDEMIC MODEL,” Chaos, Solitons and Fractals, vol. 139, p. 110036, 2020, doi: https://doi.org/10.1016/j.chaos.2020.110036
W. L. Winston and J. B. Goldberg, Operations research, Fourth., vol. 73, no. C. 1971.
Gavin J. Gibson, “MARKOV CHAIN MONTE CARLO METHODS FOR FITTING SPATIOTEMPORAL STOCHASTIC MODELS IN PLANT EPIDEMIOLOGY,” J. R. Stat. Soc. Ser. C (Applied Stat., vol. 46, no. 2, pp. 215–233, 1997, doi: https://doi.org/10.1111/1467-9876.00061.
P. Lemey, M. Suchard, and A. Rambaut, “RECONSTRUCTING THE INITIAL GLOBAL SPREAD OF A HUMAN INFLUENZA PANDEMIC,” PLoS Curr., no. SEP, pp. 1–7, 2009, doi: https://doi.org/10.1371/currents.RRN1031.
S. Merler et al., “SPATIOTEMPORAL SPREAD OF THE 2014 OUTBREAK OF EBOLA VIRUS DISEASE IN LIBERIA AND THE EFFECTIVENESS OF NON-PHARMACEUTICAL INTERVENTIONS: A COMPUTATIONAL MODELLING ANALYSIS,” Lancet Infect. Dis., vol. 15, no. 2, pp. 204–211, 2015, doi: https://doi.org/10.1016/S1473-3099(14)71074-6.
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