A Game Theoretic Analysis of Competition Between Vaccine and Drug Companies During Disease Contraction and Recovery

Overview

Journal Med Decis Making

Publisher Sage Publications

Date 2021 Nov 5

PMID 34738510

Citations 1

Authors

Kjell Hausken

Mthuli Ncube

Affiliations

Soon will be listed here.

Abstract

Background: Infectious diseases such as COVID-19 and HIV/AIDS are behaviorally challenging for persons, vaccine and drug companies, and donors.

Methods: In 3 linked games in which a disease may or may not be contracted, persons choose risky or safe behavior (game 1). Two vaccine companies (game 2) and 2 drug companies (game 3) choose whether to develop vaccines and drugs. Each person chooses whether to buy 1 vaccine (if no disease contraction) or 1 drug (if disease contraction). A donor subsidizes vaccine and drug developments and purchases. Nature probabilistically chooses disease contraction, recovery versus death with and without each drug, and whether vaccines and drugs are developed successfully. COVID-19 data are used for parameter estimation.

Results: Each person chooses risky behavior if its utility outweighs safe behavior, accounting for nature's probability of disease contraction which depends on how many are vaccinated. Each person buys a vaccine or drug if the companies produce them and if their utilities (accounting for side effects and virus mutation) outweigh the costs, which may be subsidized by a sponsor.

Discussion: Drug purchases depend on nature's recovery probability exceeding the probability in the absence of a drug. Each company develops and produces a vaccine or drug if nature's probability of successful development is high, if sufficiently many persons buy the vaccine or drug at a sales price that sufficiently exceeds the production price, and if the donor sponsors.

Conclusion: Accounting for all players' interlinked decisions allowing 14 outcomes, which is challenging without a game theoretic analysis, the donor maximizes all persons' expected utilities at the societal level to adjust how persons' purchases and the companies' development and production are subsidized.

Highlights: A game theoretic approach can help explain the production decisions of vaccine and drug companies, and the decisions of persons and a donor, impacted by Nature.In 3 linked games, persons choose risky behavior if its utility outweighs safe behavior.Vaccine and drug companies develop vaccines and drugs sponsored by a donor if profitable, allowing 14 outcomes.

Citing Articles

Game-theoretic analysis of governance and corruption in China's pharmaceutical industry.

Wang X, Zhang T, Gong H, Li J, Wu B, Chen B Front Med (Lausanne). 2024; 11:1439864.

PMID: 39206179 PMC: 11349649. DOI: 10.3389/fmed.2024.1439864.

References

Coates T, Richter L, Caceres C . Behavioural strategies to reduce HIV transmission: how to make them work better. Lancet. 2008; 372(9639):669-84. PMC: 2702246. DOI: 10.1016/S0140-6736(08)60886-7. View

Forsythe S, McGreevey W, Whiteside A, Shah M, Cohen J, Hecht R . Twenty Years Of Antiretroviral Therapy For People Living With HIV: Global Costs, Health Achievements, Economic Benefits. Health Aff (Millwood). 2019; 38(7):1163-1172. DOI: 10.1377/hlthaff.2018.05391. View

Creese A, Floyd K, Alban A, Guinness L . Cost-effectiveness of HIV/AIDS interventions in Africa: a systematic review of the evidence. Lancet. 2002; 359(9318):1635-43. DOI: 10.1016/S0140-6736(02)08595-1. View

Crossley T, Fisher P, Low H . The heterogeneous and regressive consequences of COVID-19: Evidence from high quality panel data. J Public Econ. 2020; 193:104334. PMC: 7666552. DOI: 10.1016/j.jpubeco.2020.104334. View

Hecht R, Stover J, Bollinger L, Muhib F, Case K, de Ferranti D . Financing of HIV/AIDS programme scale-up in low-income and middle-income countries, 2009-31. Lancet. 2010; 376(9748):1254-60. DOI: 10.1016/S0140-6736(10)61255-X. View

Granich R, Kahn J, Bennett R, Holmes C, Garg N, Serenata C . Expanding ART for treatment and prevention of HIV in South Africa: estimated cost and cost-effectiveness 2011-2050. PLoS One. 2012; 7(2):e30216. PMC: 3278413. DOI: 10.1371/journal.pone.0030216. View

Galarraga O, Colchero M, Wamai R, Bertozzi S . HIV prevention cost-effectiveness: a systematic review. BMC Public Health. 2009; 9 Suppl 1:S5. PMC: 2779507. DOI: 10.1186/1471-2458-9-S1-S5. View

Izazola-Licea J, Wiegelmann J, Aran C, Guthrie T, De Lay P, Avila-Figueroa C . Financing the response to HIV in low-income and middle-income countries. J Acquir Immune Defic Syndr. 2009; 52 Suppl 2:S119-26. DOI: 10.1097/QAI.0b013e3181baeeda. View

Canning D . The economics of HIV/AIDS in low-income countries: the case for prevention. J Econ Perspect. 2006; 20(3):121-42. DOI: 10.1257/jep.20.3.121. View

10.

Garre-Olmo J, Turro-Garriga O, Marti-Lluch R, Zacarias-Pons L, Alves-Cabratosa L, Serrano-Sarbosa D . Changes in lifestyle resulting from confinement due to COVID-19 and depressive symptomatology: A cross-sectional a population-based study. Compr Psychiatry. 2020; 104:152214. PMC: 7574785. DOI: 10.1016/j.comppsych.2020.152214. View

11.

Hogan D, Baltussen R, Hayashi C, Lauer J, Salomon J . Cost effectiveness analysis of strategies to combat HIV/AIDS in developing countries. BMJ. 2005; 331(7530):1431-7. PMC: 1315644. DOI: 10.1136/bmj.38643.368692.68. View

12.

Boily M, Masse B, Alsallaq R, Padian N, Eaton J, Vesga J . HIV treatment as prevention: considerations in the design, conduct, and analysis of cluster randomized controlled trials of combination HIV prevention. PLoS Med. 2012; 9(7):e1001250. PMC: 3393676. DOI: 10.1371/journal.pmed.1001250. View

13.

Walker D . Cost and cost-effectiveness of HIV/AIDS prevention strategies in developing countries: is there an evidence base?. Health Policy Plan. 2003; 18(1):4-17. DOI: 10.1093/heapol/18.1.4. View

14.

Gonsalves G . HIV/AIDS prevention and treatment. Lancet. 2002; 360(9326):87; author reply 87-8. DOI: 10.1016/S0140-6736(02)09344-3. View

15.

Sun J, He W, Wang L, Lai A, Ji X, Zhai X . COVID-19: Epidemiology, Evolution, and Cross-Disciplinary Perspectives. Trends Mol Med. 2020; 26(5):483-495. PMC: 7118693. DOI: 10.1016/j.molmed.2020.02.008. View

16.

DiMasi J, Grabowski H, Hansen R . Innovation in the pharmaceutical industry: New estimates of R&D costs. J Health Econ. 2016; 47:20-33. DOI: 10.1016/j.jhealeco.2016.01.012. View

17.

Belot M, Choi S, Tripodi E, van den Broek-Altenburg E, Jamison J, Papageorge N . Unequal consequences of Covid 19: representative evidence from six countries. Rev Econ Househ. 2021; 19(3):769-783. PMC: 8025452. DOI: 10.1007/s11150-021-09560-z. View

18.

Alistar S, Brandeau M . Decision making for HIV prevention and treatment scale up: bridging the gap between theory and practice. Med Decis Making. 2010; 32(1):105-17. PMC: 3271126. DOI: 10.1177/0272989X10391808. View

19.

. HIV treatment as prevention: models, data, and questions--towards evidence-based decision-making. PLoS Med. 2012; 9(7):e1001259. PMC: 3393655. DOI: 10.1371/journal.pmed.1001259. View

20.

Hausken K, Ncube M . Policy makers, the international community and the population in the prevention and treatment of diseases: case study on HIV/AIDS. Health Econ Rev. 2017; 7(1):5. PMC: 5267592. DOI: 10.1186/s13561-016-0139-x. View