The costs and benefits of primary prevention of zoonotic pandemics

Abstract

The lives lost and economic costs of viral zoonotic pandemics have steadily increased over the past century. Prominent policymakers have promoted plans that argue the best ways to address future pandemic catastrophes should entail, "detecting and containing emerging zoonotic threats." In other words, we should take actions only after humans get sick. We sharply disagree. Humans have extensive contact with wildlife known to harbor vast numbers of viruses, many of which have not yet spilled into humans. We compute the annualized damages from emerging viral zoonoses. We explore three practical actions to minimize the impact of future pandemics: better surveillance of pathogen spillover and development of global databases of virus genomics and serology, better management of wildlife trade, and substantial reduction of deforestation. We find that these primary pandemic prevention actions cost less than 1/20th the value of lives lost each year to emerging viral zoonoses and have substantial cobenefits.

Fig. 1.

Deaths per year from novel viral zoonotic outbreaks since 1912. Numbers are color-coded by the number of continents over which they spread. The size of the symbol shows economic costs, in addition to those based on loss of life, for just the five cases for which the World Bank provided estimates (8). Studies of economic costs from infectious outbreaks use different methods and their results may not be directly comparable. Our study concentrates on loss-of-life costs using the value of statistical life (VSL). VSL costs from other epidemics could be calculated retrospectively using the methods we have used for COVID-19. We have assigned HIV to 1980, although its mortality was spread over many years. Additional references are in the Supplementary Materials.

Fig. 2.. Phases of pathogen emergence, from local to global.

The World Health Organization identifies five phases to which we have added a sixth: pathogen spillover (in red).

Fig. 3.. Viral accumulation curves illustrating the rate at which novel viral pathogens are identified with increasing numbers of animals sampled.

Viral species richness increases for macaque monkeys (blue) and Pteropid bats (red) with the number of animals sampled. Solid lines are from rarefaction; dotted lines are extrapolations (using double sample size). Dots A (samples 310 and richness 141) and D (samples 325 and richness 26) represent 50% sample of sample coverage, and dots C (samples 2325 and richness 284) and F (samples 2705 and richness 52) represent 99% of sample coverage. Dots B and E are the observed viral species richness. Shaded areas represent 95% confidence intervals. Data are from (21, 24).

Fig. 4.. The national density of veterinarians.

The ratio of veterinarians to civilians plotted against the nation’s area. Countries are color-coded based on World Bank income categories. The text mentions names in bold. Data were absent from the OIE database for several nations, including China and Russia.