The Economics of Depression

Normally when we hear the words economics and depression in the same sentence, we think of the great depression of the 1930s. Actually, I am talking about the economic costs of being depressed and the treatment of the same. I also discuss the concept of DALYs.

Economics of Depression

The attempts to estimate the losses caused due to depression or other mental illnesses have lead to the development of the DALYs. Earlier, the years lost due to early death was the only thing considered to measure the burden of particular diseases. Recently though, it was realized that it is also important to take into account the number of years lived with disability; since living with a disease may also lead to lower productivity and loss of resources. This led to the formulation of the DALY (Disability Adjusted Life Years). This quantity is the sum of years that were not lived due to premature death as well as the years which were lived with a disability or a disease.

India accounts for nearly 15% of the global DALY. These mount up to nearly 31 million DALYs! Out of these 31 million DALYs, 11.5 million were due to depression. That is a total percentage of 37% which means that  depression by itself accounts for more than a third. Mental disorders as a whole are believed to have a share of more than half of the global DALYs.

Costs of Depression

Now I understand that it is hard to understand the real costs of depression if I don’t throw a figure around with a currency. It is hard to grasp the concept of DALYs if there is no reference to compare it to. WHO tried to conduct a study into this and estimated the costs of depression for the period of 2016-2030. By their estimate, the non-treatment of depression causes the world a loss of ONE TRILLION DOLLARS in productivity. That is $1,000,000,000,000. That is 1 followed by 12 zeroes. The last time I saw so many zeroes, I was in 5th grade looking at my results in math.

In the same study they also claimed that every $1 put into treatment of depression leads to a $4 return in higher productivity, longevity and efficiency.

Conclusion

Now I understand that figures as big as this are going to be looked at with scepticism. It is hard to believe that an illness could cost a loss this big but that is what the estimates of WHO say. Since mental illnesses are not very well understood, it is necessary that we continue to try and create more awareness. The government has to play its role in this as well. Last year, India spent a meagre 0.4% of its budget on mental health. Developed countries devote about 5% of their health budget to mental wellbeing which seems like a distant dream in India.

Depression is invisible but the costs that it carries are very much tangible and expensive. Are we willing to affect our future due to our present indifference?

References

https://www.thecrimson.com/column/behavioral-economist/article/2014/7/20/the-economics-of-depression/

Charlson, F. J., Baxter, A. J., Cheng, H. G., Shidhaye, R., & Whiteford, H. A. (2016). The burden of mental, neurological, and substance use disorders in China and India: a systematic analysis of community representative epidemiological studies. The Lancet388(10042), 376-389.

https://en.wikipedia.org/wiki/Disability-adjusted_life_year

Devleesschauwer, B., Havelaar, A. H., De Noordhout, C. M., Haagsma, J. A., Praet, N., Dorny, P., … & Speybroeck, N. (2014). Calculating disability-adjusted life years to quantify burden of disease. International journal of public health59(3), 565-569.

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15 Replies to “The Economics of Depression”

  1. I can honestly say I hadn’t considered the economics of depression quite like you have outlined here (other than that fact that people who need it usually can’t afford it). Pretty information and I’m wondering how other countries stack.

    1. It’s something that doesn’t catch the mind very often but when you think about it the costs are atrociously huge. The problem with looking for data of other countries is that they don’t always have the tools necessary to collect and arrange the data. This is a big barrier for WHO as well.

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