Video 9.3: Herd immunity and other indirect benefit

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Do curso por The University of Hong Kong

Epidemics

23 classificações

The University of Hong Kong

Epidemics

23 classificações

“If history is our guide, we can assume that the battle between the intellect and will of the human species and the extraordinary adaptability of microbes will be never-ending.” (1) Despite all the remarkable technological breakthroughs that we have made over the past few decades, the threat from infectious diseases has significantly accelerated. In this course, we will learn why this is the case by looking at the fundamental scientific principles underlying epidemics and the public health actions behind their prevention and control in the 21st century. This course covers the following four topics: 1. Origins of novel pathogens; 2. Analysis of the spread of infectious diseases; 3. Medical and public health countermeasures to prevent and control epidemics; 4. Panel discussions involving leading public health experts with deep frontline experiences to share their views on risk communication, crisis management, ethics and public trust in the context of infectious disease control. In addition to the original introductory sessions on epidemics, we revamped the course by adding: - new panel discussions with world-leading experts; and - supplementary modules on next generation informatics for combating epidemics. -------------------------------------------------------- (1) Fauci AS, Touchette NA, Folkers GK. Emerging Infectious Diseases: a 10-Year Perspective from the National Institute of Allergy and Infectious Diseases. Emerg Infect Dis 2005 Apr; 11(4):519-25. What you'll learn - Demonstrate knowledge of the origins, spread and control of infectious disease epidemics - Demonstrate understanding of the importance of effective communication about epidemics - Demonstrate understanding of key contemporary issues relating to epidemics from a global perspective

Na lição

Theme Three: Control (Vaccination)

Week9: Introduction1:09

Video 9.1: Brief history and current issues3:39

Video 9.2: How vaccines work4:23

Video 9.3: Herd immunity and other indirect benefit8:27

Video 9.4: How to measure vaccine effect5:30

Video 9.5: Vaccine Trials4:35

Video 9.6: Safety4:27

Video 9.7: Influenza vaccines3:19

Video 9.8: Measuring vaccine impact on populations5:39

Video 9.9: Vaccine economics4:40

Video 9.10: Introducing a new vaccine4:04

Conheça os instrutores

Gabriel M. Leung (HKU)
Dean
Li Ka Shing Faculty of Medicine
Joseph T. Wu (HKU)
Associate Professor
Li Ka Shing Faculty of Medicine
Kwok-Yung Yuen (HKU)
Professor
Li Ka Shing Faculty of Medicine
Tommy Lam (HKU)
Assistant Professor
Li Ka Shing Faculty of Medicine
Maria Huachen Zhu (HKU)
Associate Professor
Li Ka Shing Faculty of Medicine
Guan Yi (HKU)
Chair Professor
Li Ka Shing Faculty of Medicine
Benjamin Cowling (HKU)
Professor
Li Ka Shing Faculty of Medicine
Thomas Abraham (HKU)
Associate Professor
Journalism and Media Studies Centre
Mark Jit (LSHTM)
Professor
Department of Infectious Disease Epidemiology
Malik Peiris (HKU)
Chair Professor
Li Ka Shing Faculty of Medicine
Marc Lipsitch (Harvard)
Professor
Department of Epidemiology

In this session, our learning objectives are to understand how

the use of vaccines may produce indirect effects in non-vaccinees.

And how we can use both epidemiological analyses and

mathematical models to understand these effects.

Vaccines may not only protect vaccinees from disease,

they may also prevent vaccinees from transmitting infection to non-vaccinees.

This effect, called herd immunity,

reduces the risk in non-vaccinees from the same population.

In fact, if vaccine coverage is high enough, then enough people

are protected in the population that the infection cannot spread at all,

and hence will eventually be eliminated.

The level of vaccine coverage for

this to occur is called the herd immunity threshold.

The herd immunity threshold depends on how transmissible an infection is.

The more transmissible an infection is, the higher the herd immunity threshold.

So higher vaccine coverage will need to be achieved to eliminate the infection.

As you can see, the herd immunity threshold for smallpox is relatively low.

Which helped to make it the first disease to be eradicated through a vaccination program.

Some vaccines only have direct effects because the risk of

infection does not depend on person to person transmission.

Examples are vaccines against tetanus and rabies.

However, most vaccines have both direct and

indirect effects because they prevent transmission from the vaccinated person

either to other people or to an intermediate vector like mosquitoes.

If vaccination coverage is not high enough to eliminate the infection,

then the force of infection,

the rate type which susceptible people become infected may still decrease.

As a result people who have not been vaccinated

will be infected at a slower rate than before vaccination.

The average age, at which infection occurs,

in an vaccinated people, may hence increase.

This can be beneficial, if adults experience less severe disease,

than children as is the case for whooping cough or pertussis.

However, sometimes this can actually be a bad thing because the serious

consequences of a disease get worse with increasing age.

For instance, rubella is usually a mild disease but

if a pregnant is infected with rubella, then her fetus may not

be born alive or it may be born with congenital abnormalities.

This is called congenital rubella syndrome.

If rubella vaccination is introduced but coverage is not high enough to reach

the herd immunity threshold, the average age at which people get

rubella may shift from early childhood to the childbearing ages.

This may result in more pregnant women acquiring rubella, and

more cases of congenital rubella syndrome.

In Greece, a rubella vaccine was introduced in 1975 and

became available in the private sector.

However, vaccination was not part of a nationally funded program.

So there was only partial uptake of the vaccine.

As a result, the number of pregnant women who were susceptible to rubella

increased leading to many cases of congenital rubella syndrome

during an epidemic in 1993.

Besides herd immunity,

another potential indirect effect of vaccines is replacement.

Replacement occurs when there is competition between related

types of a pathogen to infect their host.

Hence if a vaccine reduces infection by some types

it can lead to an increase in infection rates by the competing types.

An example is pneumococcal conjugate vaccines which protect against several

serotypes of a type of bacteria called Streptococcus pneumoniae.

Countries such as the United Kingdom that have introduced this vaccine

have seen a decrease in disease due to the pneumococcal serotypes

that are protected against by the vaccine.

But they have sometimes also seen an increase due to

other pneumococcal serotypes not in the vaccine.

This replacement effect has diminished although not eliminated

completely the total disease reduction as a result of vaccination.

So how can we measure the extent of heard immunity and

other ecological indirect effects in vaccinated populations?

One way is by conducting a cluster randomized trial,

a clinical trial in which instead of allocating individuals to be vaccinated or

not, we allocate Trial clusters.

These clusters may be households, villages, communities, regions,

subsections of the population where we may expect disease to be transmitted.

Within a cluster, we may expect the incidence of disease to fall,

not only because we vaccinate some members of the cluster, But

because even non-vaccinated members are protected by herd immunity.

A second way is by making ecological observations.

When human papilloma virus vaccination was introduced in Australia,

declines of genital warts, which are caused by human papilloma virus

was seen in women in the age groups that were vaccinated.

But declines were also seen in heterosexual men in the same age groups

even though most of them had not been vaccinated

likely as a result of herd immunity.

Patterns of infection transmission and interactions between pathogens and

their hosts in a population can be very complex.

Sometimes, mathematical models are fitted to surveillance data and used to predict

how much herd immunity is likely to occur following a vaccination program.

Models that take these indirect effects into account are called

transmission dynamic models.

These models can suggest the level of vaccine coverage needed to control and

to eliminate an infection.

As well as to avoid detrimental effects

such as increases in the rate of adult infection for diseases like rubella.

They can also indicate which are the best groups to target with vaccination.

For instance, Dr Marc Baguelin and

his coworkers recently used transmission dynamic models fitted to

many seasons of influenza surveillance data from the United Kingdom

to suggest that vaccinating children against seasonal influenza would have

a large impact on mortality among people of all ages, even

though influenza mortality in children is lower than in some other age groups.

However, models usually require good data on the rates of infection and

disease in different age groups,

as well as the rate at which different people mix with each other.

Building a mathematical model is not a substitute for adequate data collection.

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