Long-term strategy Corona policy

The government is thinking about long-term corona policy. The recent period has shown that the Omikron variant is contagious, but that the number of hospital admissions remains limited. The cabinet has therefore decided to phase out the corona measures. However, there is a chance that hospital admissions will increase in the future. For example, when autumn starts or when a new variety spreads. The government takes various possible scenarios into account.

Should the government introduce corona measures in these scenarios? What goals should the government actually pursue with its corona policy? And which indicator should be controlled on? The answers to these questions are important to arrive at good policy.

 

The research

Populytics carried out two preference surveys in February 2022 on behalf of the Behavioral Unit of the RIVM to answer the following questions:

  1. Which social goals do citizens consider important in corona policy?
  2. Which measures do citizens find desirable and/or acceptable in four different scenarios?
  3. At what point do citizens think that the government should decide to introduce measures?
  4. What preferences do citizens have with regard to the policy decision-making process?

Populytics is a TU Delft start-up that specializes in measuring preferences of individuals using the Participation Value Evaluation (PVE) method. The essence of a PVE is that citizens can give advice on a government choice issue. Citizens are, as it were, put in the seat of a policy maker. The choice issue of a government is simulated in an online environment. Citizens are then asked what they would advise if they were in the shoes of the policymaker. This study is a successor to an earlier preference study in which 36,000 Dutch people contributed ideas about how the corona measures should be scaled up in the event of a revival of the virus (Mouter et al., 2021a).

We performed two PVE experiments. In the first experiment, we presented four scenarios for how the pandemic could develop. Citizens gave advice on the implementation of measures for each scenario. Participants were given information about the extent to which the chance that hospitals will become (too) crowded if the measure is introduced. We then asked what they would advise their governmentand why they would advise this. It concerns the following four scenarios:

  1. A situation where the virus is under control. Few people with corona are in hospital. Hospitals don't have to postpone surgeries. There is also no dangerous new variant of the virus that causes problems.
  2. A situation in which the virus spreads more quickly in the autumn, whereby especially vulnerable people and people who have not been vaccinated end up in hospital. In this scenario, the pressure on healthcare increases.
  3. A situation in which a new, more contagious variant of the virus has been found in another country. It is not yet clear how sickening this variant is. It can be better than expected and then nothing will happen with the pressure on care, but it can also be disappointing and then the pressure on care will increase sharply.
  4. A situation in which a new, more contagious variant of the virus has been found in another country that is also more pathogenic. In this situation, it is certain that the pressure on healthcare will increase enormously if the government does not take additional measures quickly.

In the second PVE experiment, we investigated the preferences of the Dutch for the goals of the corona policy. We asked the participants to award points to various goals that the government can pursue. When they supported a cause, they could award a lot of points to it. We first asked them to prioritize social goals of the corona policy. We then asked them to prioritize goals related to sharing the burden of corona policy. Finally, we asked them to prioritize goals for decision making. Some of the participants also received information about which measures would fit these goals. In this way we could measure whether people give different advice when they receive more extensive information. It follows from the study that providing extra information in none of the choice tasks led to substantially different advice from participants. After participants had divided their points, we asked them why they had divided their points in this way. The answers to the in-depth questions provide insight into the motives, values ​​and fairness considerations underlying the participants' choices. We also analyze whether different groups in society share or think differently about certain preferences, goals and values.

A representative group of Dutch people was approached to participate in both studies. The first experiment ran from February 3 to February 10, 2022 and a total of 2,011 participants completed the PVE. The second experiment ran from February 18 to March 1, 2022 and a total of 2,958 participants completed the PVE.

Key results and findings

Comparing different forms of support

In the two experiments we conducted in this study, participants were asked in two different ways about support for corona measures. In the first experiment, we asked them what they would choose for themselves if they were sitting in the driver's seat (active support); in the second experiment, we asked a different group of participants per measure to what extent they would find it acceptable if the government decided to do so (passive support).

In the first three scenarios, we see that the percentage of participants that would actively opt for a measure is lower than the percentage that would accept the measure if the government decides to do so. We conclude from this that a substantial group of citizens prefer to accept a bit more risk themselves (they choose fewer measures) if they have to make decisions from the role of a policymaker (also for others), but nevertheless support certain measures if they are introduced by the government and therefore imposed from above. In the fourth scenario, we see that the percentage of participants who recommend or find radical measures such as closing schools, catering and sports facilities acceptable is very low. It is striking that participants in experiment 1 and experiment 2 rank the measures in almost the same way. Thus, measures most often advised by participants in Experiment 1 are also seen as the most acceptable measures by participants in Experiment 2.

Citizens increasingly feel that their preferences should be taken into account

 

The results of the study form a piece of the puzzle that the government must complete. Of course, other studies are also being conducted and the government is also taking other elements into consideration. 23% of the participants believe that the advice of citizens should weigh more heavily than the advice of scientists or that only citizens should be listened to. In a study into the relaxation of corona measures in May 2020, this was only 5%. Citizens therefore increasingly believe that their preferences should be taken into account in policy. On the other hand, about 40% of the participants think that advice from scientists should be more important than advice from citizens. In May 2020 this was still 70%. The vast majority of participants believe that both advice from citizens and advice from scientists should be taken into account by politicians in decision-making about corona measures.

More than 70% of the participants found the Participative Value Evaluation to be a good method for involving citizens in choices that the government has to make regarding corona policy. 5% of the participants thought this was not a good method. More than 60% of the participants say that the final decision will be more acceptable to them because the government involves citizens on a large scale in corona policy through this research, while 9% indicate that the fact that the government has this research carried out has no effect on their acceptance of decisions about corona policy.

FAQs

 

Photo by Andrea Rapuzzi on Unsplash.

 

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