Video 4.4: Transmissibility of communicable diseases

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En provenance du cours de The University of Hong Kong

Epidemics

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The University of Hong Kong

Epidemics

29 notes

“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

À partir de la leçon

Theme Two: Spread (Infectious disease epidemiology)

Week 4 Introduction1:10

Video 4.1: The basics8:00

Video 4.2: Epidemic curve7:11

Video 4.3: Incubation period7:29

Video 4.4: Transmissibility of communicable diseases7:58

Video 4.5: Timescale of disease transmission5:51

Video 4.6: Severity of infectious disease7:17

Rencontrer les enseignants

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, we will discuss different measures

for transmissibility of communicable diseases.

One of the most important epidemiologic

characteristics of a communicable disease

is the transmissibility of the pathogen.

Several measures are commonly used to quantify

the transmissibility of a pathogen.

Attack rate is defined as the proportion

of a given exposed population

that has been infected by the pathogen,

which is simply the cumulative number

of infections divided by the population size.

Over the course of an epidemic,

the attack rate increases

as more and more people become infected.

Although attack rate provides a measure

for the level of spread of the pathogen in a population,

it does not directly describe how transmissible

the pathogen is from person to person.

Secondary attack rate and reproductive number

are the two most commonly used measures

for person-to-person transmissibility.

Secondary attack rate is the attack rate

of the exposed susceptible population

in a semi-closed setting,

such as in a household, a school, or an airplane,

after the introduction

of an infected individual into this setting.

For example, during the 2009

influenza H1N1 pandemic in Hong Kong,

a household study of influenza transmission

found that the within-household secondary attack rate

of pandemic H1N1 and seasonal influenza

were similar, which suggested that pandemic H1N1

and seasonal influenza had similar transmissibility.

However, secondary attack rate is not necessarily

an accurate proxy for person-to-person transmissibility.

To see this, consider this example of a household

with 4 members where A is the primary case

with B and C becoming infected

in this household outbreak.

Suppose we can rule out the possibility

that B and C are infected by someone

outside the household, for example,

when disease prevalence in the community

is known to be very low.

The underlying chain of transmission

for this household outbreak has three possibilities.

The first is that B and C are both infected by A.

The second is that A infects B, who then infects C.

The third is that A infects C, who then infects B.

The probability of these possibilities

depend on the person-to-person transmissibility

of the pathogen,

and knowing only the secondary attack rate

is not enough to help us distinguish

among these possibilities.

Person-to-person transmissibility of a pathogen

is most accurately described

by the reproductive number,

which is defined as the expected number

of secondary cases generated by one infected case

and usually denoted by R.

When a pathogen invades a population

that is completely susceptible,

for example, SARS in 2003,

the reproductive number at that stage

is known as the basic reproductive number,

which is universally denoted by R0.

R0 indicates whether the invasion of the pathogen

can give rise to an exponentially growing epidemic.

If R0 is not greater than 1, which means

that on average every infected individual

cannot infect more than one person,

then the chain of transmission will die out

without exponential growth

and the final attack rate will be close to zero.

Otherwise, if R0 is greater than 1,

then the invasion of the pathogen

can lead to an exponentially growing epidemic,

the probability of which increases as R0 increases.

Let us now look at the change

in reproductive number over the course of an epidemic.

Suppose infected individuals become immune

to reinfection after they have recovered

and there are no interventions

to mitigate the epidemic.

As the epidemic unfolds in the exponential growth phase,

the reproductive number and the epidemic growth rate

decrease because of depletion of susceptibles.

When the reproductive number drops to 1,

incidence growth stalls

and the epidemic reaches its peak.

Incidence then begins to drop monotonically

and the epidemic will eventually die out

if replenishment of susceptibles,

for example, via newborns,

is not sufficiently large

to maintain disease transmission.

The final attack rate refers to the proportion

of population that has been infected

by the end of the epidemic.

In general, the final attack rate does not reach 100%,

which means that some proportion

of the population will escape infection.

Instead, the final attack rate

becomes closer and closer to 100% as R0 increases.

This is because if R0 is not extremely large,

the reproductive number becomes smaller than 1

when a substantial proportion

of the population is still susceptible.

As the epidemic subsides after the peak,

only some of these remaining susceptibles

will be infected.

This table shows the estimates

of R0 for some pathogens.

R0 was around 1.5-3 for 1918 pandemic influenza,

2-3 for SARS in Hong Kong and Beijing,

and 12-19 for measles.

The high R0 of measles explains why

measles epidemics occurred every 2 years or so

in England and Wales before

childhood measles vaccination was implemented.

Because R0 for measles is high,

the proportion of population susceptible to measles

was very small after each epidemic

but was continuously replenished by newborns.

It took around 2 years for the susceptible population

to be large enough again for the reproductive number

to rise above 1, hence the biennial cycle

of measles epidemics in the pre-vaccination era.

The One Health model is built upon a fundamental

concept in epidemiology called

the epidemiologic triangle,

which states that epidemic of a communicable disease

is an interplay among the pathogen,

the host, as well as the environment.

As such, transmissibility of a communicable disease

depends not only on the pathogen,

but also on the characteristics of the host population

such as contact patterns and immunity

among individuals, as well as environmental factors

such as climate conditions and animal reservoirs.

For example, this is the epi curve of SARS

in Beijing in 2003 and the corresponding estimates

of the reproductive number

over the course of the epidemic.

The reproductive number dropped sharply

in mid-April 2003, not because of depletion of susceptibles.

Instead, transmissibility was suppressed

because of aggressive public health interventions

that aim to reduce contact between susceptible

and infected people, including case isolation,

contact tracing and quarantine of contacts,

as well as population-wide social distancing.

In summary, in this session, we have discussed

different measures for transmissibility

of communicable diseases.

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