Impact of outbreaks caused by respiratory viruses on healthcare and economic systems: A systematic review
A pandemic’s socioeconomic disruption can result in deaths due to deprivation, suicide, violence, and trauma, in addition to virus-related consequences. This study seeks to map the scientific literature on the effects of mitigation measures for respiratory virus outbreaks on healthcare and economic systems across countries, as well as the models used to predict those effects. The primary objectives were to identify the main contributions in this field and delineate the major research pathways that can inform a future research agenda. The study uses bibliometric analysis, keyword co-occurrence analysis, and cluster analysis. Keyword linkages were examined to identify possible trends across the retrieved papers. Hierarchical cluster analysis was also applied to categorize related papers into distinct groups. The results facilitated the identification and classification of multiple theoretical perspectives derived from primary research across seven major approaches: (i) economic parameters affected by the COVID-19 crisis; (ii) healthcare crisis management; (iii) predictions of government interventions’ impact on the healthcare system; (iv) impacts of influenza virus in a global economic scenario; (v) general impacts of outbreaks in European and Asia Pacific countries; (vi) operating statistical stability in data analysis; and (vii) statistical trends regarding healthcare in a global economy over a pandemic crisis. Overall, the review synthesizes the main themes in the literature and highlights priority areas related to economic systems, healthcare systems, and predictive modeling. The findings highlight the strong interconnections among economic stability, healthcare system resilience, and public policy, while identifying key health and economic parameters that may inform predictive models assessing the effects of mitigation measures.
Adil, M.T., Rahman, R., Whitelaw, D., Jain, V., Al-Taan, O., Rashid, F., Munasinghe, A., & Jambulingam, P. (2021). SARS-CoV-2 and the pandemic of COVID-19. Postgraduate Medical Journal, 97(1144), 110–116. https://doi.org/10.1136/postgradmedj-2020-138386
Akram, S., Alam, M.S., & Shah, S. (2024). Significant impact exerted on global economy by implementing pandemi-creactive global-scale public health measures. Global Health Economics and Sustainability, 3(3), 92–100. https://doi.org/10.36922/ghes.4531
Aleta, A., Martin-Corral, D., Pastore y Piontti, A., Ajelli, M., Litvinova, M., Chinazzi, M., Dean, N. E., Halloran, M. E., Longini Jr, I. M., Merler, S., Pentland, A., Vespignani, A., Moro, E., & Moreno, Y. (2020). Modelling the impact of testing, contact tracing and household quarantine on second waves of COVID-19. Nature Human Behaviour, 4(9), 964–971. https://doi.org/10.1038/s41562-020-0931-9
Ali, A. (2024). Sustainability of specialized healthcare in upper-middle- income economies: Innovations despite constraints. Global Health Economics and Sustainability, 2(3), 2717. https://doi.org/10.36922/ghes.2717
Almehmadi, A. (2021). COVID-19 Pandemic Data Predict the Stock Market. Computer Systems Science and Engineering, 36(3), 451–460. https://doi.org/10.32604/CSSE.2021.015309
Amiri, A., & Solankallio-Vahteri, T. (2020). Analyzing economic feasibility for investing in nursing care: Evidence from panel data analysis in 35 OECD countries. International Journal of
Nursing Sciences, 7(1), 13–20. https://doi.org/10.1016/j.ijnss.2019.06.009
Arabi, Y.M., Azoulay, E., Al-Dorzi, H.M., Phua, J., Salluh, J., Binnie, A., et al. (2021). How the COVID-19 pandemic will change the future of critical care. Intensive care medicine, 47(3), 282–291. https://doi.org/10.1007/s00134-021-06352-y
Ardabili, S., Mosavi, A., Ghamisi, P., Ferdinand, F., Varkonyi-Koczy, A., Reuter, U., Rabczuk, T., & Atkinson, P. (2020). COVID-19 Outbreak Prediction with Machine Learning. Algorithms, 13(10). https://doi.org/10.3390/a13100249
Aydın, H., Doğan, H., & Erdoğan, M.O. (2023). Comparison of COVID-GRAM, 4C Mortality, qSOFA, SIRS, NEWS, and MEWS in Predicting Mortality in COVID-19. Medical Journal of Bakirkoy, 19(1), 111–118. https://doi.org/10.4274/BMJ.galenos.2023.2022.7-10
Beutels, P., Jia, N., Zhou, Q.Y., Smith, R., Cao, W.C., & De Vlas, S.J. (2009). The economic impact of SARS in Beijing, China. Tropical Medicine and International Health, 14(SUPPL. 1), 85–91. https://doi.org/10.1111/j.1365-3156.2008.02210.x
Bizuneh, M., & Geremew, M. (2021). Assessing the Impact of Covid-19 Pandemic on Emerging Market Economies’ (EMEs) Sovereign Bond Risk Premium and Fiscal Solvency. Eastern Economic Journal, 47(4), 519–545. https://doi.org/10.1057/s41302-021-00201-y
Blakely, T., Thompson, J., Bablani, L., Andersen, P., Ait Ouakrim, D., Carvalho, N., Abraham, P., Boujaoude, M.-A., Katar, A., Akpan, E., Wilson, N., & Stevenson, M. (2021). Association of Simulated COVID-19 Policy Responses for Social Restrictions and Lockdowns with Health-Adjusted Life-Years and Costs in Victoria, Australia. JAMA Health Forum, 2(7), E211749. https://doi.org/10.1001/jamahealthforum.2021.1749
Boncristiani, H.F. (2009). Respiratory Viruses. Encyclopedia of Microbiology, January, 500–518. https://doi.org/10.1016/B978-012373944-5.00314-X
Bonfiglio, A., Coderoni, S., & Esposti, R. (2022). Policy responses to COVID-19 pandemic waves: Cross-region and cross-sector economic impact. Journal of Policy Modeling, 44(2), 252–279. https://doi.org/10.1016/j.jpolmod.2022.03.009
Borghi, P.H., Zakordonets, O., & Teixeira, J.P. (2021). A COVID-19 time series forecasting model based on MLP ANN. Procedia Computer Science, 181(2019), 940–947. https://doi.org/10.1016/j.procs.2021.01.250
Browne, C.J., Gulbudak, H., & Macdonald, J.C. (2022). Differential impacts of contact tracing and lockdowns on outbreak size in COVID-19 model applied to China. Journal of Theoretical Biology, 532(Xx). https://doi.org/10.1016/j.jtbi.2021.110919
Buyukbaşaran, T., Karasoy-Can, G., & Kucuk, H. (2022). Macroeconomic effects of bank lending in an emerging economy: Evidence from Turkey. Economic Modelling, 115, 105946. https://doi.org/10.1016/j.econmod.2022.105946
Carvalho, K., Vicente, J.P., Jakovljevic, M., & Teixeira, J.P.R. (2021). Analysis and forecasting incidence, intensive care unit admissions, and projected mortality attributable to covid-19 in Portugal, the UK, Germany, Italy, and France: Predictions for 4 weeks ahead. Bioengineering, 8(6). https://doi.org/10.3390/bioengineering8060084
Cheteni, P., & Mazenda, A. (2023). Economic impact of government intervention in response to covid-19 in selected sub-Saharan African countries. Development Southern Africa, 40(2), 406–420. https://doi.org/10.1080/0376835X.2022.2046550
de Oliveira, L.S., Gruetzmacher, S.B., & Teixeira, J.P. (2021). Covid-19 time series prediction. Procedia Computer Science, 181(2019), 973–980. https://doi.org/10.1016/j.procs.2021.01.254
Do, T.T., & Pham, V.H. (2023). Influence of the Covid-19 Pandemic on Reducing the Income of Workers. Corporate Governance and Organizational Behavior Review, 7(2), 138–146. https://doi.org/10.22495/cgobrv7i2p12
Farah, Z., El Naja, H. A., Tempia, S., Saleh, N., Abubakar, A., Maison, P., & Ghosn, N. (2023). Estimation of the influenza-associated respiratory hospitalization burden using sentinel surveillance data, Lebanon, 2015–2020. Influenza and Other Respiratory Viruses, 17(4), 1–8. https://doi.org/10.1111/irv.13138
Fineberg, H.V. (2014). Pandemic Preparedness and Response—Lessons from the H1N1 Influenza of 2009. New England Journal of Medicine, 370(14), 1335–1342. https://doi.org/10.1056/nejmra1208802
Gormsen, N.J., & Koijen, R.S.J. (2020). Coronavirus: Impact on stock prices and growth expectations. Review of Asset Pricing Studies, 10(4), 574–597. https://doi.org/10.1093/rapstu/raaa013
Grey, S., & MacAskill, A. (2020). Special Report: Johnson listened to his scientists about coronavirus - but they were slow to sound the alarm. Reunters. https://www.reuters. com/article/us-health-coronavirus-britain-path-speciidUSKBN21P1VF
Hashim, M.J., Alsuwaidi, A.R., & Khan, G. (2020). Population risk factors for COVID-19 mortality in 93 countries. Journal of Epidemiology and Global Health, 10(3), 204–208. https://doi.org/10.2991/jegh.k.200721.001
Huseynova, A., Mazanova, O., Mammadova, S., Majidova, S., Aslanova, A., & Rustamova, S. (2022). Analysis of the Relationship between the Economic Confidence Index and Gross Domestic Product Growth in Azerbaijan. WSEAS Transactions on Business and Economics, 19(March), 867–875. https://doi.org/10.37394/23207.2022.19.75
Hysa, E., Imeraj, E., Feruni, N., Panait, M., & Vasile, V. (2022). COVID-19—A Black Swan for Foreign Direct Investment: Evidence from European Countries. Journal of Risk and Financial Management, 15(4). https://doi.org/10.3390/jrfm15040156
Inoue, H., & Todo, Y. (2020). The propagation of economic impacts through supply chains: The case of a mega-city lockdown to prevent the spread of COVID-19. PLoS one, 15(9 September), 1–10. https://doi.org/10.1371/journal.pone.0239251
Jakovljevic, M., Chang, H., Pan, J., Guo, C., Hui, J., Hu, H., Grujic, D., Li, Z., & Shi, L. (2023). Successes and challenges of China’s health care reform: a four-decade perspective spanning 1985—2023. Cost Effectiveness and Resource Allocation, 21(1), 59. https://doi.org/10.1186/s12962-023-00461-9
Jakovljevic, M., Groot, W., & Souliotis, K. (2016). Health care financing and affordability in the emerging global markets. Frontiers in Public Health, 4. https://doi.org/10.3389/fpubh.2016.00002
Jakovljevic, M., Liu, Y., Cerda, A., Simonyan, M., Correia, T., Mariita, R.M., et al. (2021). The Global South political economy of health financing and spending landscape history and presence. Journal of Medical Economics, 24(Sup1), 25–33. https://doi.org/10.1080/13696998.2021.2007691
Jakovljevic, M.M. (2016). Comparison of historical medical spending patterns among the BRICS and G7. Journal of Medical Economics, 19(1), 70–76. https://doi.org/10.3111/13696998.2015.1093493
Jin, H., Li, B., & Jakovljevic, M. (2022). How China controls the Covid-19 epidemic through public health expenditure and policy? Journal of Medical Economics, 25, 437–449. https://doi.org/10.1080/13696998.2022.2054202
Jin, H., Xue, J., Yang, H., Zhu, Z., & Jakovljevic, M. (2024). How long has it taken China’s economy to recover from the COVID-19 epidemic. Global Health Economics and Sustainability. https://doi.org/10.36922/ghes.1842
Katris, C. (2021). Unemployment and COVID-19 Impact in Greece: A Vector Autoregression (VAR) Data Analysis †. Engineering Proceedings, 5(1). https://doi.org/10.3390/engproc2021005041
Kim, K.H., Tandi, T.E., Choi, J.W., Moon, J.M., & Kim, M.S. (2016). Middle East respiratory syndrome coronavirus (MERS-CoV) outbreak in South Korea, 2015: epidemiology, characteristics and public health implications. Journal of Hospital Infection, 95(2), 207–213. https://doi.org/10.1016/j.jhin.2016.10.008
Klement, R.J., & Walach, H. (2022). Identifying factors associated with COVID-19 related deaths during the first wave of the pandemic in Europe. Frontiers in Public Health, 10. https://doi.org/10.3389/fpubh.2022.922230
Krumel, T.P., Goodrich, C., & Fiala, N. (2023). Labour demand in the time of post-COVID-19. Applied Economics Letters, 30(3), 343–348. https://doi.org/10.1080/13504851.2021.1985067
Lai, D.-H., Le, T.-H., & Tran-Nam, B. (2024). Effectiveness of the lockdown policy in Vi-etnam during the COVID-19 pandemic. Global Health Economics and Sustainability, 2(4), 3423. https://doi.org/10.36922/ghes.3423
Lau, K., Dorigatti, I., Miraldo, M., & Hauck, K. (2021). SARIMA-modelled greater severity and mortality during the 2010/11 post-pandemic influenza season compared to the 2009 H1N1 pandemic in English hospitals. International Journal of Infectious Diseases, 105, 161–171. https://doi.org/10.1016/j.ijid.2021.01.070
Leung, V. K. Y., Wong, J. Y., Barnes, R., Kelso, J., Milne, G. J., Blyth, C. C., Cowling, B. J., Moore, H. C., & Sullivan, S. G. (2021). Excess respiratory mortality and hospitalizations associated with influenza in Australia, 2007-2015. International Journal of Epidemiology, 51(2), 458–467. https://doi.org/10.1093/ije/dyab138
Lilleri, D., Zavaglio, F., Gabanti, E., Gerna, G., & Arbustini, E. (2020). Analysis of the SARS-CoV-2 epidemic in Italy: The role of local and interventional factors in the control of the epidemic. PLoS ONE, 15(11), 1–12. https://doi.org/10.1371/journal.pone.0242305
Mashud, A.H. M., Hasan, M.R., Daryanto, Y., & Wee, H.M. (2021). A resilient hybrid payment supply chain inventory model for post Covid-19 recovery. Computers and Industrial Engineering, 157, 107249. https://doi.org/10.1016/j.cie.2021.107249
McCombs, A., & Kadelka, C. (2020). A model-based evaluation of the efficacy of COVID-19 social distancing, testing and hospital triage policies. PLoS Computational Biology, 16(10), 1–18. https://doi.org/10.1371/journal.pcbi.1008388
Mitze, T., & Makkonen, T. (2020). Can large-scale RDI funding stimulate post-crisis recovery growth? Evidence for Finland during COVID-19. Technological Forecasting and Social Change. 2023;186:122073. https://doi.org/10.1016/j.techfore.2022.122073
Mustafa, H., Ahmed, F., Zainol, W.W., & Enh, A.M. (2021). Forecasting the impact of gross domestic product (Gdp) on international tourist arrivals to langkawi, malaysia: A postcovid‐19 future. Sustainability (Switzerland), 13(23). https://doi.org/10.3390/su132313372
Navarro Romero, E. del C., Gelves Alarcon, O.M., & Garcia Corrales, N. (2021). Correlational analysis between the economics, socio-demographic indices and statistics of contagion due to Covid-19, applying the Clustering methodology in countries of America. Inge CuC, 17(1), 285–302. https://doi.org/10.17981/ingecuc.17.1.2021.21
Nguyen, P.-H., Tsai, J.-F., Kayral, I.E., & Lin, M.-H. (2021). Unemployment Rates Forecasting with Grey-Based Models in the Post-COVID-19 Period: A Case Study from Vietnam. Sustainability, 13(14), 7879. https://doi.org/10.3390/su13147879
Nguyen, L.Q., Fernandes, P.O., & Teixeira, J.P. (2022). Analyzing and Forecasting Tourism Demand in Vietnam with Artificial Neural Networks. 36–50. https://doi.org/10.3390/forecast4010003
Pang, X., Zhu, Z., Guo, F.X.J., Gong, X., Liu, D., Liu, Z., Chin, D.P., Feikin, D.R. (2003). Evaluation of control measures implemented in the severe acute respiratory syndrome outbreak in Beijing, 2003. Infectious Diseases in Clinical Practice, 290(24), 3215-3221. https://doi.org/10.1001/jama.290.24.3215
Petrou, S., & Jakovljevic, M. (2024). Reimagining the relationship between economics and health–WHO ‘Health for all’provisions. Cost Effectiveness and Resource Allocation, 22(1), 5. https://doi.org/10.1186/s12962-024-00512-9
Pollitzer, R. (1951). Plague studies. 1. A summary of the history and survey of the present distribution of the disease. Bulletin of the World Health Organization, 4(4), 475–533. Rahmani, A.M., & Hosseini Mirmahaleh, S.Y. (2022). An Intelligent Algorithm to Predict GDP Rate and Find a Relationship Between COVID-19 Outbreak and Economic Downturn. Computational Economics, 63(3), 1001–1020. https://doi.org/10.1007/s10614-022-10332-9
Reissl, S., Caiani, A., Lamperti, F., Guerini, M., Vanni, F., Fagiolo, G., Ferraresi, T., Ghezzi, L., Napoletano, M., & Roventini, A. (2022). Assessing the Economic Impact of Lockdowns in Italy: A Computational Input–Output Approach. Industrial and Corporate Change, 31(2), 358–409. https://doi.org/10.1093/icc/dtac003
Rostan, P., & Rostan, A. (2022). Assessing the Resilience of Uk’S Economy After the Covid-19 Pandemic and Brexit. Online Journal Modelling the New Europe, 40, 47–77. https://doi.org/10.24193/OJMNE.2022.40.03
Sadovnichiy, V.A., Akaev, A.A., Zvyagintsev, A.I., & Sarygulov, A.I. (2022). Mathematical Modeling of Overcoming the COVID-19 Pandemic and Restoring Economic Growth. Doklady Mathematics, 106(1), 230–235. https://doi.org/10.1134/S1064562422040160
Sahin, U., Muik, A., Derhovanessian, E., Vogler, I., Kranz, L. M., Vormehr, M., Baum, A., Pascal, K., Quandt, J., Maurus, D., Brachtendorf, S., Lorks, V., Sikorski, J., Hilker, R., Becker, D., Eller, A.-K., Grutzner, J., Boesler, C., Rosenbaum, C., … Tureci, O. (2021). Publisher Correction: COVID 19 vaccine BNT162b1 elicits human antibody and TH1 T cell responses. Nature, 590(7844), E17–E17. https://doi.org/10.1038/s41586-020-03102-w
Santosa, P.B., Pangestuti, I.R. D., Wahyudi, S., & Muharam, H. (2023). Dividend policy in Indonesian banking sector during COVID-19 pandemic period. Cogent Social Sciences, 9(2). https://doi.org/10.1080/23311886.2023.2272657
Sharma, S., Bansal, M., & Saxena, A.K. (2022). Forecasting of GDP (Gross Domestic Product) per Capita Using (ARIMA) Data-Driven Intelligent Time Series Predicting Approach. 2022 International Conference on Sustainable Islamic Business and Finance, SIBF 2022, 85–90. https://doi.org/10.1109/SIBF56821.2022.9939928
Shi, L., Khan, Y.A., & Tian, M.W. (2022). COVID-19 pandemic and unemployment rate prediction for developing countries of Asia: A hybrid approach. PLoS ONE, 17(12 December), 1–17. https://doi.org/10.1371/journal.pone.0275422
Shu, Y., & McCauley, J. (2017). GISAID: Global initiative on sharing all influenza data – from vision to reality. Eurosurveillance, 22(13), 2–4. https://doi.org/10.2807/1560-7917.ES.2017.22.13.30494
Simonsen, L., Spreeuwenberg, P., Lustig, R., Taylor, R. J., Fleming, D. M., Kroneman, M., Van Kerkhove, M. D., Mounts, A. W., & Paget, W. J. (2013). Global Mortality Estimates for the 2009 Influenza Pandemic from the GLaMOR Project: A Modeling Study. PLoS Medicine, 10(11). https://doi.org/10.1371/journal.pmed.1001558
Singh, K., Chander Pushap, A., Kaur, G., Bharti, S., Jhon, A., Sudershan, S., Ahmed Dar, F., Ahmad Sheikh, B., Bashir, M., Ahmad Najar, S., & Sudershan, A. (2024). COVID-19 changed our world: A systematic review. Global Health Economics and Sustainability, 3(1), 38–63. https://doi.org/10.36922/ghes.3992
Smith, R.D., & Keogh-Brown, M.R. (2013). Macroeconomic impact of pandemic influenza and associated policies in Thailand, South Africa and Uganda. Influenza and Other Respiratory Viruses, 7(SUPPL.2), 64–71. https://doi.org/10.1111/irv.12083
Szanyi, J., Wilson, T., Howe, S., Zeng, J., Andrabi, H., Rossiter, S., & Blakely, T. (2023). Epidemiologic and economic modelling of optimal COVID-19 policy: public health and social measures, masks and vaccines in Victoria, Australia. The Lancet Regional Health - Western Pacific, 32, 100675. https://doi.org/10.1016/j.lanwpc.2022.100675
Tamesberger, D., & Bacher, J. (2020). COVID-19 Crisis: How to Avoid a ‘Lost Generation.’ Intereconomics, 55(4), 232–238. https://doi.org/10.1007/s10272-020-0908-y
Towers, S., & Chowell, G. (2012). Impact of weekday social contact patterns on the modeling of influenza transmission, and determination of the influenza latent period. Journal of Theoretical Biology, 312, 87–95. https://doi.org/10.1016/j.jtbi.2012.07.023
van der Schans, S., Schottler, M.H., van der Schans, J., Connolly, M.P., Postma, M.J., & Boersma, C. (2023). Investing in the Prevention of Communicable Disease Outbreaks: Fiscal Health Modelling—The Tool of Choice for Assessing Public Finance Sustainability. Vaccines, 11(4), 823. https://doi.org/10.3390/vaccines11040823
Vaya, E., Garcia, J.R., Surinach, J., & Pons, E. (2023). Effects of the COVID-19 tourism crisis on the Spanish economy. Tourism Economics, 0(0), 1–18. https://doi.org/10.1177/13548166231185899
Verma, M., & Naveen, B.R. (2021). COVID-19 Impact on Buying Behaviour. Vikalpa, 46(1), 27–40. https://doi.org/10.1177/02560909211018885
Verma, P., Dumka, A., Bhardwaj, A., Ashok, A., Kestwal, M.C., & Kumar, P. (2021). A Statistical Analysis of Impact of COVID19 on the Global Economy and Stock Index Returns. SN Computer Science, 2(1), 1–13. https://doi.org/10.1007/s42979-020-00410-w
Wahyono, H., Narmaditya, B.S., Wibowo, A., & Kustiandi, J. (2021). Irrationality and economic morality of SMEs’ behavior during the Covid-19 pandemic: lesson from Indonesia. Heliyon, 7(7), e07400. https://doi.org/10.1016/j.heliyon.2021.e07400
Wang, Y. (2024). Income-related inequality in health outcomes among older individuals in China: A measurement and decomposition analysis. Global Health Economics and Sus-Tainability, 2(1), 2243. https://doi.org/10.36922/ghes.2243
Wichitaksorn, N. (2022). Analyzing and forecasting Thai macroeconomic data using mixed-frequency approach. Journal of Asian Economics, 78, 101421. https://doi.org/10.1016/j.asieco.2021.101421
Wu, W., Zhang, P., Zhu, D., Jiang, X., & Jakovljevic, M. (2022). Environmental Pollution Liability Insurance of Health Risk and Corporate Environmental Performance: Evidence From China. Frontiers in Public Health, 10, 1–13. https://doi.org/10.3389/fpubh.2022.897386
Yang, J.D.X. (2023). Cross-sector co-movements and policy impact in the COVID-19 stock market: A dynamic factor approach. Global Finance Journal, 56, 100772. https://doi.org/10.1016/j.gfj.2022.100772
Yen, M.-Y., Chiu, A. W.-H., Schwartz, J., King, C.-C., Lin, Y. E., Chang, S.-C., Armstrong, D., & Hsueh, P.-R. (2014). From SARS in 2003 to H1N1 in 2009: lessons learned from Taiwan in preparation for the next pandemic. Journal of Hospital Infection, 87(4), 185–193. https://doi.org/10.1016/j.jhin.2014.05.005
Yamacli, D.S., & Yamacli, S. (2023). Estimation of the unemployment rate in Turkey: A comparison of the ARIMA and machine learning models including Covid-19 pandemic periods. Heliyon, 9(1), e12796. https://doi.org/10.1016/j.heliyon.2023.e12796
Zhuang, X. (2020). Financial Modeling Analysis of the Impact of Consumer Coupons on Economic Recovery after the Pandemic. 2020 Management Science Informatization and Economic Innovation Development Conference (MSIEID), 601–607. https://doi.org/10.1109/msieid52046.2020.00119