Nearly every policy recommendation and the prerequisite for opening up countries again have one thing in common — testing. Mass testing is considered crucial in re-opening society and is imperative to effectively combat the novel coronavirus that has turned our world upside down. In response to this need for testing, countries across the world, including India, have shifted their focus to import as many testing kits as possible and knuckle down on improving the accuracy of such tests. However, we seem to have forgotten one decisive actor in this process — people.
Before I delve into this, some facts are influential in addressing this issue. Studies have shown that people affected by the COVID-19 virus can be asymptomatic as well, which means that even if you show no symptoms that have been associated with the virus, you could be carrying it and hence are contagious. People have been identified as passive carriers which are particularly dangerous without testing of the entire population. A second fact is that there have been recurring patients of the virus. Having overcome the infection once does not guarantee you will not be affected again hence testing is further essential for recovered patients.
With that out of the way, let’s consider one false assumption that has gone majorly unmentioned — everyone wants to get tested. There can be multiple reasons people will be unwilling to get tested, least of which is laziness. I will delve deeper into these reasons but the consequence of this assumption is that countries should not just focus on buying testing kits, but convince people to get tested as well.
The first reason people might be unwilling to go for weekly tests is a lack of awareness. In a country like India with over a billion people, it can be close to impossible to provide adequate discourse to all for a multitude of grounds ranging from lack of literacy to ineffective communication methods. This lack of awareness means that not every person is aware that they must get tested, know the relevant symptoms, and how to react in the case of a positive test.
This is compounded because of the rampant poverty and lack of facilities in rural areas. It can be difficult for testing kits to reach every remote clinic and even if that is achieved, not all people can afford to get tested frequently. While this is easily solved by making testing free for all, it will only tax our economy and budget further, both of which are already hurt by the lack of productivity and labour over the past month. There could be additional costs not accounted for which I will address further on in the article.
Second is the expectation that asymptomatic people will also visit their doctors and get themselves tested regularly. Many avoid clinics and hospitals for the reasonable fear of contracting an infection which has only grown multifold with the recent pandemic. Personal Protective Equipment such as face masks and sanitizers have grown in demand hence driving up the price accordingly. Many pieces of equipment remain out of stock as well, hence it is reasonable not to expect people to visit epicentres of disease regularly without adequate protection.
The third, possibly the most generic and common, is human nature. From laziness to distrust in the system, there is a multitude of reasons that falls under this category because of which we cannot work under the assumption people will get tested if it’s available. As a policy-maker, this human nature is imperative to consider during the implementation stage. To ensure effective enforcement or implementation, the policy must be made while accounting for such factors and overcoming the same, something that has been lacking so far in mass testing policies.
So, how do we go about accounting for this false assumption and effectively implement mass testing? You will often see me quoting that there are two major ways of ensuring fulfilment of policy, incentive and deterrence.
Incentive refers to a policy which acts on positive reinforcement and hence motivates or encourages people to act on the policy. By providing incentives, the expectation is that people get a benefit which they are interested in and in return comply with the policy. This creates a positive impact on society but could be costly for the government in the process of providing such incentives. For example, if I tell you that you will be getting a bonus if you finish your task by the deadline, I am incentivising you to comply with my set deadline or policy.
With respect to our current predicament, how do we incentivise the general population to get tested? There have been multiple models suggested, the simplest of which is to not only make testing free but provide some amount per week when you get tested regularly. Similarly, a wage could be provided for those subjected to quarantine to incentivise people to stay inside and comply with the quarantine measures. A second model suggested, slightly more eccentric, is to set up a lottery system based on testing. For a test every week, an entry is made in the lottery and a winner is drawn who is awarded accordingly.
The dominant problem with the first model, and to some extent the second, is the amount of capital required to fulfil these policies. Is it a justified expenditure considering the state of the economy and the other fields so much capital could be better spent, including but not limited to research, awareness and development? To understand and answer this dilemma, let us approach a popular concept in Economics of ‘negative externality’.
An externality refers to an impact suffered by a third-party as a consequence of an economic transaction and by extension, if this impact is a cost on the third-party, it is a negative externality. In this case, we will not be looking at the impact of an economic transaction but the spread of the disease from person-to-person. For every person affected by the virus and failing to get tested promptly, they impact those around them which in turn spreads the disease, increases the cost of recovery, and taxes hospitals on their resources and availability. Hence when someone is affected, they unknowingly impose a cost on those around them as well as the system. This justifies the additional cost of incentivisation to ensure mass testing is effective and this negative externality can be circumvented.
A second problem that arises is the effectiveness of the incentive being provided. There must be sufficient deliberation and experimentation on the model of incentivisation, intricacies of the given model, and success rates of the policy. Only after this process can one conclude that the incentive is sufficient to ensure implementation of the policy. Even beyond this, effectiveness could remain a blemish as no incentive is perfect and the task is to find the middle ground between economic feasibility and effectiveness.
The other model of policy implementation is deterrence. Deterrence refers to an action which discourages or demotivates a person from violating a policy out of fear of consequences for such actions. Unlike incentivisation, deterrence deals with negative reinforcement where fear is the governing factor over encouragement. For example, if I say you will be docked a week’s salary if you don’t stick to your deadline, I am using deterrence to ensure my policy is followed.
Regarding the issue at hand, the ideal deterrent to ensure enforcement of testing is sufficient punishment for non-compliance. If someone does not get themselves tested regularly, the state will punish them either by issuing a fine or arresting people in severe cases of violating quarantine. This fear of punishment is ordinarily a lot more effective in ensuring obedience to policy.
The most significant drawback in relying on deterrence is enforcing the consequences themselves. Especially in countries with large populations like India, it can be difficult to track every individual who has failed to get tested and hence close to impossible to punish each offender because of the lack of a mechanism to track such cases. This might even increase distrust in the system if it fails to enforce the same and can affect the effectiveness of the policy as well.
Deterrence also has some economic implications in executing said punishments on the state although not to the extent of incentivisation. Hence the trade-off, in this case, will lie between ensuring enforcement of deterrence techniques and the economic cost that the state will incur. The severity of deterrence is important as well since if it is too harsh it can question the system as a whole, while leniency will mean the policy need not be strictly followed.
Only through realising the need for incentives or deterrence in testing can we ensure the success of a policy hoping to achieve the same. By accounting for the human factor in decision-making or policy considerations, we can be more inclusive, increase efficacy, and tackle the novel coronavirus more holistically and comprehensively. Policy-makers, pay attention!
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