This is a slightly dated article from December 2020 when the vaccination drive across the world had just about started but relevant for a country like India which is feeling the desperate need for vaccinating her people as quickly as possible as tha pandemic rages across the country. The article features research about behavioural aspects of vaccinating people, particularly on two specific aspects – vaccine hesitancy and deciding who to vaccinate first.
The first few weeks of India’s vaccination drive saw little turnouts – of the eligible age groups, about half or less turned up in the early days, even highlighting reports of vials opened going unused. The low case count during that period meant that people could weigh in the ‘need’ to vaccinate themselves versus factors of safety and side effects. However, as the case count rose exponentially, even before the vaccination was opened to the broader public, the vaccination centres were mobbed with people desperate to get the jab. The article cites research which predicted this behaviour even before the vaccination drives began in the west using game theory.
“Each individual has choices, but the payoff for each choice depends on choices made by others. This is what’s called a “prisoner’s dilemma game” — players weigh cooperation against betrayal, often producing a less than optimal outcome for the common good.
The perceived benefits and costs of vaccination are often expressed as concerns about safety and side effects. If you are on the fence about vaccination, you might decide — noticing lower infection rates as vaccination campaigns gain speed — that it no longer seems so critical to get the jab.
“Some people might play a ‘wait-and-see game,’” Dr. Bauch said. People who choose not to be vaccinated effectively get a free ride, reaping the benefits of reduced virus transmission generated by the people who do opt for vaccination. But the free rides generate a collective threat.
“That is the prisoner’s dilemma,” Dr. Bauch said. When infection levels are low, people feel less at risk, let down their guard, and then infection levels again rise; the ebb and flow between our behavior and the virus causes the pandemic waves. “We end up in this unhappy medium,” he said.
“Vaccination decisions based purely on self-interest can lead to vaccination coverage that is lower than what is optimal for society overall,” Dr. Galvani said in an email.
The self-interest strategy maximizing individual payoff is called the Nash equilibrium. Dr. Galvani’s later research included psychological data and demonstrated that vaccination decisions can be influenced by altruism, thereby boosting uptake beyond the Nash equilibrium and serving the common good.”
Using game theory, the article also shows why in poorer countries like India which is unable to ramp up vaccination drives adequately for her entire population, it may have been better to prioritise the younger population first whilst those countries which could afford to ramp up vaccination drives quickly could prioritise its elderly.
“Vaccines can work in two ways.
“Direct protection” protects people who get vaccinated — for example, those who are high-risk, such as health care and essential workers, people with underlying medical conditions and older adults. In terms of direct protection, the study focused on people over 60 years old.
“Indirect protection” protects the contacts of people who are vaccinated; the high-risk population is shielded by vaccinating the individuals who are most likely to transmit the virus, such as younger people, even if they are themselves less vulnerable to the disease.
…a game-theory model, factored in human behavior, and drew on Google data that revealed who went where and when in Ontario from March to November. This data was used as a proxy, approximating how stringently people adhered to social distancing and other public health advice over time.
The researchers first did a test run of sorts for their combined model, comparing it to the timeline of the pandemic waves so far, March through November. They found a good fit; the model’s projections accurately mirrored our behavioral reality: As Covid-19 cases increased in the spring, the time that people spent at retail, recreation and workplace destinations decreased; over the summer cases trailed off slowly, not abruptly, indicating that as people saw the peak flattening they relaxed their guard.
…Then the researchers ran their model to see what lies ahead — specifically, to project the effectiveness of the different approaches to prioritizing vaccinations.
The model found that if vaccines are available sufficiently early in the pandemic, say January to March 2021 (with 2.5 percent of the population vaccinated per week), then direct protection would prevent more deaths. But if vaccines are not available until later, say July to September, by which time there is more natural immunity, then indirect protection would be more effective at reducing mortality.”
The first few weeks of India’s vaccination drive saw little turnouts – of the eligible age groups, about half or less turned up in the early days, even highlighting reports of vials opened going unused. The low case count during that period meant that people could weigh in the ‘need’ to vaccinate themselves versus factors of safety and side effects. However, as the case count rose exponentially, even before the vaccination was opened to the broader public, the vaccination centres were mobbed with people desperate to get the jab. The article cites research which predicted this behaviour even before the vaccination drives began in the west using game theory.
“Each individual has choices, but the payoff for each choice depends on choices made by others. This is what’s called a “prisoner’s dilemma game” — players weigh cooperation against betrayal, often producing a less than optimal outcome for the common good.
The perceived benefits and costs of vaccination are often expressed as concerns about safety and side effects. If you are on the fence about vaccination, you might decide — noticing lower infection rates as vaccination campaigns gain speed — that it no longer seems so critical to get the jab.
“Some people might play a ‘wait-and-see game,’” Dr. Bauch said. People who choose not to be vaccinated effectively get a free ride, reaping the benefits of reduced virus transmission generated by the people who do opt for vaccination. But the free rides generate a collective threat.
“That is the prisoner’s dilemma,” Dr. Bauch said. When infection levels are low, people feel less at risk, let down their guard, and then infection levels again rise; the ebb and flow between our behavior and the virus causes the pandemic waves. “We end up in this unhappy medium,” he said.
“Vaccination decisions based purely on self-interest can lead to vaccination coverage that is lower than what is optimal for society overall,” Dr. Galvani said in an email.
The self-interest strategy maximizing individual payoff is called the Nash equilibrium. Dr. Galvani’s later research included psychological data and demonstrated that vaccination decisions can be influenced by altruism, thereby boosting uptake beyond the Nash equilibrium and serving the common good.”
Using game theory, the article also shows why in poorer countries like India which is unable to ramp up vaccination drives adequately for her entire population, it may have been better to prioritise the younger population first whilst those countries which could afford to ramp up vaccination drives quickly could prioritise its elderly.
“Vaccines can work in two ways.
“Direct protection” protects people who get vaccinated — for example, those who are high-risk, such as health care and essential workers, people with underlying medical conditions and older adults. In terms of direct protection, the study focused on people over 60 years old.
“Indirect protection” protects the contacts of people who are vaccinated; the high-risk population is shielded by vaccinating the individuals who are most likely to transmit the virus, such as younger people, even if they are themselves less vulnerable to the disease.
…a game-theory model, factored in human behavior, and drew on Google data that revealed who went where and when in Ontario from March to November. This data was used as a proxy, approximating how stringently people adhered to social distancing and other public health advice over time.
The researchers first did a test run of sorts for their combined model, comparing it to the timeline of the pandemic waves so far, March through November. They found a good fit; the model’s projections accurately mirrored our behavioral reality: As Covid-19 cases increased in the spring, the time that people spent at retail, recreation and workplace destinations decreased; over the summer cases trailed off slowly, not abruptly, indicating that as people saw the peak flattening they relaxed their guard.
…Then the researchers ran their model to see what lies ahead — specifically, to project the effectiveness of the different approaches to prioritizing vaccinations.
The model found that if vaccines are available sufficiently early in the pandemic, say January to March 2021 (with 2.5 percent of the population vaccinated per week), then direct protection would prevent more deaths. But if vaccines are not available until later, say July to September, by which time there is more natural immunity, then indirect protection would be more effective at reducing mortality.”
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