Prevention and mitigation of epidemics: biodiversity conservation and confinement policies
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Emmanuelle Augeraud-Véron, Giorgio Fabbri and Katheline Schubert*
The hopes of the post-war period that infectious diseases were behind us thanks to control and treatment improvements have proved to be false: the number of emerging infectious diseases (EID) has continued to rise since the 1950s (1). 60% of these EID are caused by zoonotic pathogens, mainly (72%) of wildlife origin (2). Examples include AIDS, SARS, MERS, Nipah Virus, Avian influenza, Ebola, Influenza A virus subtype H1N1, as well as COVID-19.
While all the underlying mechanisms are not fully understood, a growing scientific literature documents the complex links between the loss of biodiversity and the emergence of zoonotic infectious diseases (3). At least two mechanisms are at play: encroachment in ecosystems and habitat destruction increase the contact between wildlife and humans and their livestock (4); the dilution effect, such that pathogens tend to be “diluted” in complex, undisturbed, ecosystems (5), applies in reverse. However, to the best of the authors’ knowledge, this question is totally overlooked in the economic literature.
In this article, Emmanuelle Augeraud-Véron, Giorgio Fabbri and Katheline Schubert build a long-term macrodynamic model embedding into a simple economic framework biodiversity on the one hand, and epidemics, through a standard model called SIR that divides the population in different categories, on the other hand.
Society makes decisions about the amount of the land it devotes to biodiversity conservation and the amount it converts to economic activities: agricultural production, infrastructures, human settlements etc. The more biodiversity is conserved, the smaller the probability of occurrence of epidemic outbreaks, but the smaller the amount of land available in the production process, besides efficient labor. Conserving biodiversity thus acts as a prevention policy against epidemics, but it has a cost. Once an epidemic occurs, society also has to decide the intensity of the mitigation policy put in place to reduce mortality at the cost of a reduction of productivity, that is the severity of the mandatory lockdown reducing social interactions.
To represent the population ethics of society, social welfare depends on the utility derived from consumption per capita but also on the size of the population, with a relative weight representing the social preference for life over economic performance.
The optimal allocation of land to biodiversity conservation and the optimal lockdown policy are computed. More patient societies and societies with a higher preference for life over economic performance conserve more biodiversity. Societies with high risk aversion accept a large welfare loss to mitigate the pandemics and also do more prevention, not to have to incur the loss too often.
The model is calibrated to Covid-19 data, using Gollier (6) who evaluates the death toll and the economic cost of the Covid-19 pandemic for different scenarios: laissez-faire, “flatten-the-curve” strategy, consisting in confining 30% of the population for 5 months, and suppression strategy, consisting in confining 90% of the population for 4 months to eradicate the virus. The authors exhibit the terms of the trade-off between the loss of lives and the loss of GDP for the whole set of mitigation strategies, from laissez-faire to suppression, and compute the optimal lockdown policy as a function of the relative value society assigns to life over the economy. They compute the threshold of this relative value under which laisser-faire is optimal, and the threshold above which suppression is optimal. Their framework allows for the revelation of the value of life implicit in the actual government mitigation choices.
(1) Smith, K. F., Goldberg, M., Rosenthal, S., Carlson, L., Chen, J., Chen, C. and Ramachandran, S. (2014). Global rise in human infectious disease outbreaks. Journal of the Royal Society Interface, 11(101)
(2) Jones, K.E. Patel, N.G., Levy, M.A., Storeygard, A., Balk, D., Gittleman, J.L. and Daszak, P. (2008). Global Trends in Emerging Infectious Diseases. Nature, 452, 990-994
(3) Morand, S., Jittapalapong, S., Suputtamongkol, Y., Abdullah, M. T. and Huan, T. B. (2014). Infectious diseases and their outbreaks in Asia-Pacific: biodiversity and its regulation loss matter. PLoS One, 9(2) — Morand, S. (2018). Biodiversity and disease transmission. In The Connections Between Ecology and Infectious Disease (pp. 39-56). Springer
(4) Nathan D. Wolfe, Claire Panosian Dunavan and Jared Diamond. Origins of major human infectious diseases. Nature. 2007; 447(7142): 279–283
(5) Keesing, F., Belden, L. K., Daszak, P., Dobson, A., Harvell, C. D., Holt, R. D. and Myers, S. S. (2010). Impacts of biodiversity on the emergence and transmission of infectious diseases. Nature, 468(7324), 647-652
(6) Gollier, C. (2020). Cost-benefit analysis of age-specific deconfinement strategies. Covid Economics, 24, 1—29
Original title of the article: Prevention and mitigation of epidemics: biodiversity conservation and confinement policies
Published in : Mimeo – PSE covid special issue
* PSE Member
Credits : Shutterstock - Kevin Wells Photography