Abstract
This study analyzes the relations between doses administrated of vaccines for Coronavirus disease-2019 (COVID-19) and confirmed cases from March to May 2021 to find out the optimal level of doses administrated per 100 inhabitants, which can lead to a reduction in the diffusion of COVID-19 cases. Findings reveal that a delay of vaccination in population, it moves up the optimal value of doses administrated per 100 inhabitants from 58.5 to more than 86 per 100 people, with consequential damages and long-run deterioration of socioeconomic systems. This study suggests that the optimal policy to pandemic threats is the early, rapid, nationally vaccination rollout for an effective reduction of the spread of infectious disease that reduces negative effects in society.
Keywords. Pandemics; Vaccines; Vaccinations; Infection control; Health Planning; Crisis management; Policy responses.
JEL. C52; L25; M14.References
Abbasi, J. (2020). COVID-19 and mRNA vaccines-first large test for a new approach. JAMA, 324(12), 1125–1127. doi. 10.1001/jama.2020.16866
Ackley, C.A., Lundberg, D.J., Ma, L., (...), Preston, S.H., & Stokes, A.C. (2022). County-level estimates of excess mortality associated with COVID-19 in the United States, SSM - Population Health, 17,101021.
Akamatsu, T., Nagae, T., Osawa, M., Satsukawa, K., Sakai, T., Mizutani, D. (2021). Model-based analysis on social acceptability and feasibility of a focused protection strategy against the COVID-19 pandemic. Scientific Reports, 11(1), 2003. doi. 10.1038/s41598-021-81630-9
Aldila, D., Samiadji, B.M., Simorangkir, G.M., Khosnaw, S.H.A., & Shahzad, M. (2021). Impact of early detection and vaccination strategy in COVID-19 eradication program in Jakarta, Indonesia, BMC Research Notes, 14(1),132-150. doi. 10.1186/s13104-021-05540-9
Anderson, R.M., Vegvari, C., Truscott, J., & Collyer, B.S. (2020). Challenges in creating herd immunity to SARS-CoV-2 infection by mass vaccination. Lancet (London, England), 396(10263), 1614–1616. doi. 10.1016/S0140-6736(20)32318-7
Angelopoulos, A.N., Pathak, R., Varma, R., & Jordan, M.I. (2020). On identifying and mitigating bias in the estimation of the COVID-19 case fatality rate. Harvard Data Science Review. doi. 10.1162/99608f92.f01ee285
Ardito, L., Coccia M., & Messeni, P.A. (2021). Technological exaptation and crisis management: Evidence from COVID-19 outbreaks. R&D Management, 51(4), 381-392. 10.1111/radm.12455
Aschwanden C. (2020). The false promise of herd immunity for COVID-19. Nature. Nov. 587(7832), 26-28. doi. 10.1038/d41586-020-02948-4
Aschwanden C. 2021. Five reasons why COVID herd immunity is probably impossible. Nature, 591(7851), 520–522. doi. 10.1038/d41586-021-00728-2
Barnard, S., Chiavenna, C., Fox, S., Charlett, A., Waller, Z., Andrews, N., Goldblatt, P., (...), De Angelis, D. (2021). Methods for modelling excess mortality across England during the COVID-19 pandemic, Statistical Methods in Medical Research, doi. 10.1177/09622802211046384
Bontempi, E., & Coccia, M. (2021). International trade as critical parameter of COVID-19 spread that outclasses demographic, economic, environmental, and pollution factors, Environmental Research, vol.201, Article number 111514, 10.1016/j.envres.2021.111514
Bontempi, E., Coccia, M., Vergalli, S., & Zanoletti, A. (2021). Can commercial trade represent the main indicator of the COVID-19 diffusion due to human-to-human interactions? A comparative analysis between Italy, France, and Spain, Environmental Research, 201, Article number 111529, 10.1016/j.envres.2021.111529
Coccia, M. (2003). Metrics of R&D performance and management of public research institute, Proceedings of IEEE- IEMC 03, Piscataway, pp. 231-236.
Coccia, M. (2005). A taxonomy of public research bodies: a systemic approach, Prometheus, 23(1), 63-82. doi. 10.1080/0810902042000331322
Coccia, M. (2005a). Countrymetrics: valutazione della performance economica e tecnologica dei paesi e posizionamento dell’Italia, Rivista Internazionale di Scienze Sociali, 113(3), 377-412.
Coccia, M. (2008). Measuring scientific performance of public research units for strategic change. Journal of Informetrics, 2(3), 183-194. doi. 10.1016/j.joi.2008.04.001
Coccia, M. (2013). Population and technological innovation: the optimal interaction across modern countries, Working Paper Ceris del Consiglio Nazionale delle Ricerche, vol.15, n.7.
Coccia, M. (2014). Steel market and global trends of leading geo-economic players. International Journal of Trade and Global Markets, 7(1), 36-52. doi. 10.1504/IJTGM.2014.058714
Coccia, M. (2015). Spatial relation between geo-climate zones and technological outputs to explain the evolution of technology. Int. J. Transitions and Innovation Systems, 4(1), 5-21. doi. 10.1504/IJTIS.2015.074642
Coccia, M. (2016). Problem-driven innovations in drug discovery: co-evolution of the patterns of radical innovation with the evolution of problems, Health Policy and Technology, 5(2), 143-155. doi. 10.1016/j.hlpt.2016.02.003
Coccia, M. (2017). Varieties of capitalism’s theory of innovation and a conceptual integration with leadership-oriented executives: the relation between typologies of executive, technological and socioeconomic performances. Int. J. Public Sector Performance Management, 3(2), 148–168. doi. 10.1504/IJPSPM.2017.084672
Coccia, M. (2017a). Disruptive firms and industrial change, Journal of Economic and Social Thought, 4(4), 437-450. doi. 10.1453/jest.v4i4.1511
Coccia, M. (2017b). New directions in measurement of economic growth, development and under development, Journal of Economics and Political Economy, 4(4), 382-395. doi. 10.1453/jepe.v4i4.1533
Coccia, M. (2017c). Sources of disruptive technologies for industrial change. L’industria –Rivista di Economia e Politica Industriale, 38(1), 97-120. doi. 10.1430/87140
Coccia, M. (2017d). Sources of technological innovation: Radical and incremental innovation problem-driven to support competitive advantage of firms. Technology Analysis & Strategic Management, 29(9), 1048-1061. doi. 10.1080/09537325.2016.1268682
Coccia, M. (2018). An introduction to the methods of inquiry in social sciences, Journal of Social and Administrative Sciences, 5(2), 116-126. doi. 10.1453/jsas.v5i2.1651
Coccia, M. (2018a). An introduction to the theories of institutional change, Journal of Economics Library, 5(4), 337-344. doi. 10.1453/jel.v5i4.1788
Coccia, M. (2018b). General properties of the evolution of research fields: a scientometric study of human microbiome, evolutionary robotics and astrobiology, Scientometrics, 117(2), 1265-1283. doi. 10.1007/s11192-018-2902-8
Coccia, M. (2018c). The origins of the economics of Innovation, Journal of Economic and Social Thought, 5(1), 9-28. doi. 10.1453/jest.v5i1.1574
Coccia, M. (2018d). The relation between terrorism and high population growth, Journal of Economics and Political Economy, 5(1), 84-104. doi. 10.1453/jepe.v5i1.1575
Coccia, M. (2018e). Classification of innovation considering technological interaction, Journal of Economics Bibliography, 5(2), 76-93. doi. 10.1453/jeb.v5i2.1650
Coccia, M. (2018f). An introduction to the theories of national and regional economic development, Turkish Economic Review, 5(4), 350-358. doi. 10.1453/ter.v5i4.1794
Coccia, M. (2019). Metabolism of public organizations: A case study, Journal of Social and Administrative Sciences, 6(1), 1-9. doi. 10.1453/jsas.v6i1.1793
Coccia, M. (2019a). The theory of technological parasitism for the measurement of the evolution of technology and technological forecasting, Technological Forecasting and Social Change, 141, 289-304. doi. 10.1016/j.techfore.2018.12.012
Coccia, M. (2019b). A Theory of classification and evolution of technologies within a Generalized Darwinism, Technology Analysis & Strategic Management, 31(5), 517-531. doi. 10.1080/09537325.2018.1523385
Coccia, M. (2019l). Theories and the reasons for war: a survey. Journal of Economic and Social Thought, 6(2), 115-124. doi. 10.1453/jest.v6i2.1890
Coccia, M. (2020a). Factors determining the diffusion of COVID-19 and suggested strategy to prevent future accelerated viral infectivity similar to COVID. Science of The Total Environment, 729, n.138474. doi. 10.1016/j.scitotenv.2020.138474
Coccia, M. (2020b). How (Un)sustainable Environments are Related to the Diffusion of COVID-19: The Relation between Coronavirus Disease 2019, Air Pollution, Wind Resource and Energy. Sustainability, 12, 9709. doi. 10.3390/su12229709
Coccia, M. (2020c). How do environmental, demographic, and geographical factors influence the spread of COVID-19. Journal of Social and Administrative Sciences, 7(3), 169-209. doi. 10.1453/jsas.v7i3.2018
Coccia, M. (2020d). Destructive Technologies for Industrial and Corporate Change. In: Farazmand A. (eds), Global Encyclopedia of Public Administration, Public Policy, and Governance. Springer, Cham. doi. 10.1007/978-3-319-31816-5_3972-1
Coccia, M. (2020e). Deep learning technology for improving cancer care in society: New directions in cancer imaging driven by artificial intelligence. Technology in Society, 60, 1-11, art. no.101198. doi. 10.1016/j.techsoc.2019.101198
Coccia, M. (2020f). How does science advance? Theories of the evolution of science. Journal of Economic and Social Thought, 7(3), 153-180. doi. 10.1453/jest.v7i3.2111
Coccia, M. (2020g). The evolution of scientific disciplines in applied sciences: dynamics and empirical properties of experimental physics, Scientometrics, 124, 451-487. doi. 10.1007/s11192-020-03464-y
Coccia, M. (2020h). Multiple working hypotheses for technology analysis, Journal of Economics Bibliography, 7(2), 111-126. doi. 10.1453/jeb.v7i2.2050
Coccia, M. (2020i). Asymmetry of the technological cycle of disruptive innovations. Technology Analysis & Strategic Management, 32(12), 1462-1477. doi. 10.1080/09537325.2020.1785415
Coccia, M., Bellitto, M. (2018). Human progress and its socioeconomic effects in society, Journal of Economic and Social Thought, 5(2), 160-178. doi. 10.1453/jest.v5i2.1649
Coccia, M., Benati, I. (2018). Rewards in public administration: A proposed classification, Journal of Social and Administrative Sciences, 5(2), 68-80. doi. 10.1453/jsas.v5i2.1648
Coccia, M., Benati, I. (2018a). Comparative Models of Inquiry, A. Farazmand (ed.), Global Encyclopedia of Public Administration, Public Policy, and Governance, Springer International Publishing AG, part of Springer Nature. doi. 10.1007/978-3-319-31816-5_1199-1
Coccia, M., Cadario, E. (2014). Organisational (un)learning of public research labs in turbulent context. International Journal of Innovation and Learning, 15(2), 115-129. doi. 10.1504/IJIL.2014.059756
Coccia, M., Finardi, U. (2012). Emerging nanotechnological research for future pathway of biomedicine. International Journal of Biomedical nanoscience and nanotechnology, 2(3-4), 299-317. doi. 10.1504/IJBNN.2012.051223
Coccia, M., Finardi, U. (2013). New technological trajectories of non-thermal plasma technology in medicine. Int. J. Biomedical Engineering and Technology, 11(4), 337-356. doi. 10.1504/IJBET.2013.055665
Coccia, M., Rolfo, S. (2000). Ricerca pubblica e trasferimento tecnologico: il caso della regione Piemonte in Rolfo S. (eds) Innovazione e piccole imprese in Piemonte, Franco Angeli Editore, Milano (Italy).
Coccia, M., Rolfo, S. (2008). Strategic change of public research units in their scientific activity, Technovation, 28(8), 485-494. doi. 10.1016/j.technovation.2008.02.005
Coccia, M., Wang, L. (2015). Path-breaking directions of nanotechnology-based chemotherapy and molecular cancer therapy, Technological Forecasting & Social Change, 94(1), 155–169. doi. 10.1016/j.techfore.2014.09.007
Coccia, M., Wang, L. (2016). Evolution and convergence of the patterns of international scientific collaboration, Proceedings of the National Academy of Sciences of the United States of America, 113(8), 2057-2061. doi. 10.1073/pnas.1510820113
Coccia, M., Watts, J. (2020). A theory of the evolution of technology: technological parasitism and the implications for innovation management, Journal of Engineering and Technology Management, 55(2020), 101552. doi. 10.1016/j.jengtecman.2019.11.003
Cornell, A, Knutsen, C.H., Teorell, J. (2020). Bureaucracy and Growth. Comparative Political Studies. 53(14), 2246-2282. doi. 10.1177/0010414020912262
Caliskan B., Nihan Özengin, S. Sıddık Cindoruk 2020. Air quality level, emission sources and control strategies in Bursa/Turkey. Atmospheric Pollution Research, In press, 10.1016/j.apr.2020.05.016
Copat C., Cristaldi A., Fiore M., (...), Conti G.O., & Ferrante M. (2020). The role of air pollution (PM and NO2) in COVID-19 spread and lethality: A systematic review. Environmental Research, 191,110129. doi. 10.1016/j.envres.2020.110129
Davies, N.G., Jarvis, C.I., van Zandvoort, K., Clifford, S., Sun, F.Y., Funk, S., Medley, G., (...), & Keogh, R.H. (2021). Increased mortality in community-tested cases of SARS-CoV-2 lineage B.1.1.7, Nature, 593(7858), 270-274. doi. 10.1038/s41586-021-03426-1
de Vlas, S. J., Coffeng, L. E. 2021. Achieving herd immunity against COVID-19 at the country level by the exit strategy of a phased lift of control. Scientific reports, 11(1), 4445. 10.1038/s41598-021-83492-7
Fontanet, A., Autran, B., Lina, B., Kieny, M.P., Karim, S.S.A., Sridhar, D. (2021). SARS-CoV-2 variants and ending the COVID-19 pandemic, The Lancet, 397(10278), 952-954. doi. 10.1016/S0140-6736(21)00370-6
Garber, A.M. (2021). Learning from excess pandemic deaths, Journal of the American Medical Association, 325(17), 1729-1730. doi. 10.1001/jama.2021.5120
IMARC, (2022). Mechanical Ventilators Market: Global Industry Trends, Share, Size, Growth, Opportunity and Forecast, 2021-2026.
Islam, N., Shkolnikov, V. M., Acosta, R. J., Klimkin, I., Kawachi, I., Irizarry, R. A., Alicandro, G., Khunti, K., Yates, T., Jdanov, D. A., White, M., Lewington, S., & Lacey, B. (2021). Excess deaths associated with covid-19 pandemic in 2020: age and sex disaggregated time series analysis in 29 high income countries. BMJ, 373, n1137. 10.1136/bmj.n1137
Johns Hopkins Center for System Science and Engineering, (2022). Coronavirus COVID-19 Global Cases, accessed in 14 January 2022. [Retrieved from].
Kapitsinis, N. (2020). The underlying factors of the COVID-19 spatially uneven spread. Initial evidence from regions in nine EU countries. Regional Science Policy and Practice, 12(6), 1027-1045. doi. 10.1111/rsp3.12340
Kiang, M.V., Irizarry, R.A., Buckee, C.O., Balsari, S. (2020). Every body counts: Measuring mortality from the COVID-19 pandemic, Annals of Internal Medicine, 173(12), 1004-1007. doi. 10.7326/M20-3100
Lau, H., Khosrawipour, T., Kocbach, P., Ichii, H., Bania, J., Khosrawipour, V. (2021). Evaluating the massive underreporting and undertesting of COVID-19 cases in multiple global epicenters. Pulmonology, 27(2), 110–115. doi. 10.1016/j.pulmoe.2020.05.015
Liu Z., Magal P., Webb G. (2021). Predicting the number of reported and unreported cases for the COVID-19 epidemics in China, South Korea, Italy, France, Germany and United Kingdom. Journal of Theoretical Biology, 509, 110501. 10.1016/j.jtbi.2020.110501
Mayo, C. (2021). Different types of COVID-19 vaccines: How they work. accessed 6 September 2021. [Retrieved from].
Moore, S., Hill, E.M., Tildesley, M.J., Dyson, L., & Keeling, M.J. (2021). Vaccination and non-pharmaceutical interventions for COVID-19: a mathematical modelling study ((2021) The Lancet Infectious Diseases, 21(6), 793-802. doi. 10.1016/s1473-3099(21)00143-2
Nicastro, F., Sironi, G., Antonello, E., (...), Trabattoni, D., & Clerici, M. (2021). Solar UV-B/A radiation is highly effective in inactivating SARS-CoV-2, Scientific Reports 11(1),14805. doi. 10.1038/s41598-021-94417-9
Our World in Data, (2022). Coronavirus (COVID-19) Vaccinations - Statistics and Research - Our World in Data. Accessed 25 January. [Retrieved from].
Pagliaro, M., Coccia M. (2021). How self-determination of scholars outclasses shrinking public research lab budgets, supporting scientific production: a case study and R&D management implications. Heliyon. 7(1), n.1e05998. doi. 10.1016/j.heliyon.2021.e05998
Papanikolaou, V., Chrysovergis, A., Ragos, V., Tsiambas, E., Katsinis, S., Manoli, A., Papouliakos, S., Roukas, D., Mastronikolis, S., Peschos, D., Batistatou, A., Kyrodimos, E., Mastronikolis, N. (2022). From delta to Omicron: S1-RBD/S2 mutation/deletion equilibrium in SARS-CoV-2 defined variants. Gene, 814, 146134. doi. 10.1016/j.gene.2021.146134
Prieto-Curiel, R., González Ramírez, H. (2021). Vaccination strategies against COVID-19 and the diffusion of anti-vaccination views, Scientific Reports, 11(1), 6626. doi. 10.1038/s41598-021-85555-1
Pronti, A., Coccia, M. (2020). Multicriteria analysis of the sustainability performance between agroecological and conventional coffee farms in the East Region of Minas Gerais (Brazil). Renewable Agriculture and Food Systems, 36(3), 299-306. doi. 10.1017/S1742170520000332
Randolph, H.E., Barreiro, L.B. (2020). Herd immunity: understanding COVID-19. Immunity, 52, 737–741.
Ritchie, H., Ortiz-Ospina, E., Beltekian, D., Mathieu, E., Hasel, J., Macdonald, B., Giattino, C., Roser, M. (2020). Policy Responses to the Coronavirus Pandemic. Our World in Data, Statistics and Research. July 7. [Retrieved from].
Rosario Denes K.A., Mutz Yhan S., Bernardes Patricia C., & Conte-Junior Carlos A., (2020). Relationship between COVID-19 and weather: Case study in a tropical country. International Journal of Hygiene and Environmental Health, 229, 113587. doi. 10.1016%2Fj.ijheh.2020.113587
Saadi, N., Chi, Y.-L., Ghosh, S., (...), Jit, M., & Vassall, A. (2021). Models of COVID-19 vaccine prioritisation: a systematic literature search and narrative review, BMC Medicine, 19(1), 318-340. doi. 10.1186/s12916-021-02190-3
Sanmarchi, F., Golinelli, D., Lenzi, J., Esposito, F., Capodici, A., Reno, C., & Gibertoni, D. (2021). Exploring the gap between excess mortality and COVID-19 deaths in 67 countries, JAMA Network Open, 4(7), no.e2117359. doi. 10.1001/jamanetworkopen.2021.17359
Seligman B, Ferranna M, Bloom D.E. (2021). Social determinants of mortality fromCOVID-19: A simulation study using NHANES. PLoS Med, 18(1), e1003490. doi. 10.1371/journal.pmed.1003490
Shattock, A.J., Le Rutte, E.A., Dünner, R.P., (...), Chitnis, N., & Penny, M.A. (2022). Impact of vaccination and no n-pharmaceutical interventions on SARS-CoV-2 dynamics in Switzerland, Epidemics, 38,100535.
Soo Hoo G.W. (2010). Noninvasive ventilation in adults with acute respiratory distress: a primer for the clinician. Hospital Practice, 38(1), 16–25. doi. 10.3810/hp.2010.02.275
Soo Hoo G.W. (2020). Noninvasive ventilation. Medscape. Accessed January 2021, [Retrieved from].
Stokes, A. C., Lundberg, D.J., Bor, J., & Bibbins-Domingo, K. (2021). Excess Deaths During the COVID-19 Pandemic: Implications for US Death Investigation Systems. American Journal of Public Health, 111(S2), S53–S54. 10.2105/AJPH.2021.306331
Stokes, A.C., Lundberg, D.J., Elo, I.T., Hempstead, K., Bor, J., & Preston, S.H. (2021a). COVID-19 and excess mortality in the United States: A county-level analysis, PLoS Medicine, 18(5), no.e1003571. doi. 10.1371/journal.pmed.1003571
The World Bank (2022a). Data, Population, total. Accessed January 2022. [Retrieved from].
The World Bank, (2022). Current health expenditure (% of GDP), Accessed February 2022. [Retrieved from].
Vinceti, M., Filippini, T., Rothman, K.J., Di Federico, S., & Orsini, N. (2021). SARS-CoV-2 infection incidence during the first and second COVID-19 waves in Italy. Environmental research, 197, 111097. doi. 10.1016/j.envres.2021.111097
Woolf, S.H., Chapman, D.A., Sabo, R.T., & Zimmerman, E.B. (2021). Excess deaths from COVID-19 and other causes in the US, March 1, 2020, to January 2, 2021, Journal of the American Medical Association, 325(17), 1786-1789. doi. 10.1001/jama.2021.5199