Estimates of the reproduction number for seasonal, pandemic, and zoonotic influenza: A systematic review of the literature

Abstract

Background:
The potential impact of an influenza pandemic can be assessed by calculating a set of transmissibility parameters, the most important being the reproduction number (R), which is defined as the average number of secondary cases generated per typical infectious case.

Methods:
We conducted a systematic review to summarize published estimates of R for pandemic or seasonal influenza and for novel influenza viruses (e.g. H5N1). We retained and summarized papers that estimated R for pandemic or seasonal influenza or for human infections with novel influenza viruses.

Results:
The search yielded 567 papers. Ninety-one papers were retained, and an additional twenty papers were identified from the references of the retained papers. Twenty-four studies reported 51 R values for the 1918 pandemic. The median R value for 1918 was 1.80 (interquartile range [IQR]: 1.47-2.27). Six studies reported seven 1957 pandemic R values. The median R value for 1957 was 1.65 (IQR: 1.53-1.70). Four studies reported seven 1968 pandemic R values. The median R value for 1968 was 1.80 (IQR: 1.56-1.85). Fifty-seven studies reported 78 2009 pandemic R values. The median R value for 2009 was 1.46 (IQR: 1.30-1.70) and was similar across the two waves of illness: 1.46 for the first wave and 1.48 for the second wave. Twenty-four studies reported 47 seasonal epidemic R values. The median R value for seasonal influenza was 1.28 (IQR: 1.19-1.37). Four studies reported six novel influenza R values. Four out of six R values were <1.

Conclusions:
These R values represent the difference between epidemics that are controllable and cause moderate illness and those causing a significant number of illnesses and requiring intensive mitigation strategies to control. Continued monitoring of R during seasonal and novel influenza outbreaks is needed to document its variation before the next pandemic.

Full text

Estimates of the reproduction number for seasonal,
pandemic, and zoonotic influenza: a systematic
review of the literature
Matthew Biggerstaff1*
* Corresponding author
Email: mbiggerstaff@cdc.gov
Simon Cauchemez2
Email: simon.cauchemez@pasteur.fr
Carrie Reed1
Email: creed1@cdc.gov
Manoj Gambhir3
Email: manoj.gambhir@monash.edu
Lyn Finelli1
Email: lfinelli@cdc.gov
1 Epidemiology and Prevention Branch, Influenza Division, National Center for
Immunization and Respiratory Diseases, Centers for Disease Control and
Prevention, 1600 Clifton Road NE MS A-32, Atlanta 30333, Georgia
2 Mathematical Modelling of Infectious Diseases Unit, Institut Pasteur, Paris,
France
3 National Center for Immunization and Respiratory Diseases, CDC, Atlanta,
Georgia
Abstract
Background
The potential impact of an influenza pandemic can be assessed by calculating a set of
transmissibility parameters, the most important being the reproduction number (R), which is
defined as the average number of secondary cases generated per typical infectious case.
Methods
We conducted a systematic review to summarize published estimates of R for pandemic or
seasonal influenza and for novel influenza viruses (e.g. H5N1). We retained and summarized
papers that estimated R for pandemic or seasonal influenza or for human infections with
novel influenza viruses.

Results
The search yielded 567 papers. Ninety-one papers were retained, and an additional twenty
papers were identified from the references of the retained papers. Twenty-four studies
reported 51 R values for the 1918 pandemic. The median R value for 1918 was 1.80
(interquartile range [IQR]: 1.47–2.27). Six studies reported seven 1957 pandemic R values.
The median R value for 1957 was 1.65 (IQR: 1.53–1.70). Four studies reported seven 1968
pandemic R values. The median R value for 1968 was 1.80 (IQR: 1.56–1.85). Fifty-seven
studies reported 78 2009 pandemic R values. The median R value for 2009 was 1.46 (IQR:
1.30–1.70) and was similar across the two waves of illness: 1.46 for the first wave and 1.48
for the second wave. Twenty-four studies reported 47 seasonal epidemic R values. The
median R value for seasonal influenza was 1.28 (IQR: 1.19–1.37). Four studies reported six
novel influenza R values. Four out of six R values were <1.
Conclusions
These R values represent the difference between epidemics that are controllable and cause
moderate illness and those causing a significant number of illnesses and requiring intensive
mitigation strategies to control. Continued monitoring of R during seasonal and novel
influenza outbreaks is needed to document its variation before the next pandemic.
Keywords
Reproductive number, Influenza, Pandemics, Zoonotic influenza
Background
Annual influenza epidemics occur worldwide and cause substantial morbidity and mortality
[1]. In the United States between 5% and 20% of the population are infected with influenza
every year [2], resulting in between 3,000 and 49,000 influenza-associated deaths [3].
Influenza viruses are constantly changing either through the collection of minor point
mutations or through major antigenic shifts. These major shifts can result in the introduction
of novel influenza viruses into the human population to which humans have little or no
immunity, causing pandemics [1]. Four influenza pandemics have occurred since the
beginning of the 20th century and have ranged widely in transmissibility and clinical severity
[1,4].
Recognizing that the characteristics of future pandemics will be difficult to predict given the
mutability of the influenza virus and the range of morbidity and mortality experienced in
previous pandemics, an approach to the early assessment of influenza pandemics has been
developed relying on standardized measures of transmissibility and clinical severity [5]. An
important transmissibility parameter identified is the reproduction number (R), which is
defined as the average number of secondary cases generated per typical infectious case [6,7].
R describes on average how many persons a case will infect, and a value of R greater than 1
indicates that the infection may grow or persist in the population while a value of R less than
1 indicates that the infection will decline in the population, although exceptions exist[7,8].
Many methods to calculate R have been described that allow for the use of epidemiologic
data from different epidemic time points [7]. Some examples include estimating R using the

growth rate of the epidemic, the epidemic curve’s size and shape, the final attack rate, or by
direct observation of disease transmission from one generation to the next [7]. The population
susceptibility to the infection also affects the interpretation of R. If R is calculated in a
population entirely susceptible to infection (or where an assumption about population
susceptibility to infection is made), then R is known as the basic reproduction number (R0).
In contrast, the effective reproduction number (RE) is calculated in a population with
underlying immunity and accounts for a population’s reduced susceptibility to infection [9].
The value of R characterizes the final number infected in the absence of an intervention in
homogeneously mixed populations, the herd immunity threshold, and, when coupled with the
generation time, defined as the interval between infections in two consecutive generations, or
the serial interval, defined as the interval between the onset of symptoms in two consecutive
generations), the speed with which the disease spreads in the population [10-12]. Therefore,
the magnitude of R plays an important role in the selection and aggressiveness of
countermeasures (e.g. social distancing, treating ill individuals, or vaccination) required to
slow transmission of the disease [10,13].
Because R is used as a measure of transmissibility and informs the selection of different
mitigation strategies, it is important to understand the range and uncertainty of published R
values. In this paper, we investigate whether published estimates of R differ between
pandemic, seasonal, and novel influenza, we compare values of R calculated in differing
geographic regions and settings, and we explore the assumptions and limitations of the
estimation methods of R.
Methods
We performed a literature search using the PubMed database from 1950 to January 16, 2013.
The following key terms were searched: “reproduction number and influenza”, “reproductive
number and influenza”, “R0 and influenza”, “reproduction rate and influenza”, and
“reproductive rate and influenza”. We limited our search to articles in English. We retained
articles that estimated R for pandemic or seasonal influenza or for human infections with
non-human influenza viruses (e.g. H5N1). For all studies retained, we abstracted the date of
publication, the year, the geographic location where the data were collected, the influenza
subtype, the study population, whether it was a confined setting, the wave of the observation
(if during a pandemic), the estimated value of R, the method to identify influenza cases, and
whether it was a R0 or RE. If multiple R values were provided, we provide the median and
range. Since methods to estimate the reproduction number often require a value for the
generation time or the serial interval, we also report those values [14]. We classified the
method used to determine influenza-associated cases into two categories: laboratory
confirmed, which required the use of confirmatory testing of respiratory or blood specimens,
or unconfirmed, which relied on syndromic case definitions to identify cases and required no
laboratory confirmation of illnesses.
Median R values and interquartile ranges (IQR) were reported for each pandemic and for the
group of inter-pandemic seasonal epidemics. If a range of values was given for an individual
study instead of a point estimate, the middle value of the range was used in the pandemic or
epidemic median calculations.

Results
The search strategy initially identified 567 papers (Figure 1). Ninety-one papers were
retained that estimated R for pandemic or seasonal influenza or for human infections with
non-human influenza viruses (e.g. H5N1). Twenty additional papers were contributed by the
references of the papers identified through the original search. In all, 111 articles were
retained that presented original estimates of the reproduction number (summarized in Tables
1, 2, 3, 4, 5 and 6). Data provided in the tables are also available as .csv files in Additional
files 1, 2, 3, 4, 5 and 6.
Figure 1 PRISMA flowchart of the article selection for the reproductive number and
influenza literature review.

Table 1 Reproduction Numbers from the 1918 Influenza A/H1N1 Pandemic
Location Wave
a
Study
Population
Mean
GT/SIb Reproduction Number
(R)
95% CI
c
Basic or
Effective
Case definition Reference
Year
Published
Australia 1st community 2.6 1.80 1.6–2.0 basic unconfirmed
hospitalizations/deaths [115] 2008
Brazil 1st community 4 2.68 basic unconfirmed illness [116] 2007
Canada 1st community 3 1.50 1.5–1.5 basic unconfirmed deaths [117] 2011
Canada 1st community 6 2.1 2.1–2.1 basic unconfirmed deaths [117] 2011
Colombia 1st community 3 1.4–1.5 effective unconfirmed deaths [118] 2012
Colombia 1st community 4 1.5–1.7 effective unconfirmed deaths [118] 2012
Denmark 1st community 2.6 2.2–2.4 effective unconfirmed illness [119] 2008
Denmark 1st community 4 2.8–3.0 effective unconfirmed illness [119] 2008
Denmark 1st community 2.6 2.8–4.0 effective unconfirmed hospitalizations [119] 2008
Denmark 1st community 4 3.6–5.4 effective unconfirmed hospitalizations [119] 2008
Italy 1st community 3 1.03 1.00–
1.08 basic unconfirmed hospitalizations [120] 2011
Mexico 1st community 3 1.30 effective unconfirmed deaths [121] 2010
Peru 1st community 3 1.38 1.37–
1.40 effective unconfirmed deaths [122] 2011
Switzerland 1st community 3.11 1.49 1.45–
1.53 basic unconfirmed hospitalizations [123] 2006
Switzerland 1st community 3.4 1.50 basic unconfirmed deaths [124] 2009
United
Kingdom 1st community 2.6 1.7 basic unconfirmed deaths [10] 2006
United
Kingdom 1st community 4.1 2.10 effective unconfirmed illness [36] 2006
United
Kingdom 1st community 6 2.00 basic unconfirmed illness [37] 2005
United
Kingdom 1st community NR 1.16–2.94 effective unconfirmed illness [125] 2010
United
Kingdom 1st students NR 1.43–5.36 effective unconfirmed illness [125] 2010
USA 1st community 4 1.34–3.21 effective unconfirmed illness [126] 2008
Various 1st community 4 1.2–3.0 effective unconfirmed illness [127] 2007

Various 1st community 4 2.1–7.5 effective unconfirmed illness [127] 2007
1st sailors 4 4.97 effective unconfirmed illness [126] 2008
Canada 2nd community 3.6 2.26 1.95–
2.63 basic unconfirmed illness [128] 2010
Canada 2nd community 3.6 1.49 1.42–
1.55 basic unconfirmed illness [128] 2010
Canada 2nd community 3 2.40 2.4–2.5 basic unconfirmed deaths [117] 2011
Canada 2nd community 6 4.3 4.2–4.4 basic unconfirmed deaths [117] 2011
Denmark 2nd community 2.6 1.22–1.24 effective unconfirmed illness [119] 2008
Denmark 2nd community 4 1.29–1.33 effective unconfirmed illness [119] 2008
Denmark 2nd community 2.6 1.2–1.3 effective unconfirmed hospitalizations [119] 2008
Denmark 2nd community 4 1.3–1.4 effective unconfirmed hospitalizations [119] 2008
Germany 2nd community 1 1.58 0.03–
10.3 basic unconfirmed deaths [129] 2007
Germany 2nd community 3 2.52 0.75–
5.85 basic unconfirmed deaths [129] 2007
Germany 2nd community 5 3.41 1.91–
5.57 basic unconfirmed deaths [129] 2007
Italy 2nd community 3 1.38 1.3–1.5 basic unconfirmed hospitalizations [120] 2011
Mexico 2nd community 3 1.30 effective unconfirmed deaths [121] 2010
New Zealand 2nd military >1.5 1.3–3.1 basic unconfirmed hospitalizations [130] 2006
Switzerland 2nd community 2.28 3.75 3.6–3.9 effective unconfirmed hospitalizations [123] 2006
Switzerland 2nd community 3.4 2.40 basic unconfirmed deaths [124] 2009
United
Kingdom 2nd community 3 1.39 1.36–
1.43 effective unconfirmed deaths [131] 2008
United
Kingdom 2nd community 6 1.84 1.75–
1.92 effective unconfirmed deaths [131] 2008
United
Kingdom 2nd community 6 1.55 basic unconfirmed illness [37] 2005
United
Kingdom 2nd community 2.6 1.50 basic unconfirmed deaths [10] 2006
USA 2nd community 2.5 2.14 basic unconfirmed deaths [132] 2009
USA 2nd community NR 2.20 1.55–
2.84 effective unconfirmed illness [30] 2007
USA 2nd community 4 2.00 1.7–2.3 effective unconfirmed deaths [133] 2004

USA 2nd community 2.85 1.73 effective unconfirmed deaths [14] 2007
United
Kingdom 3rd community 3 1.39 1.29–
1.49 effective unconfirmed deaths [131] 2008
United
Kingdom 3rd community 6 1.82 1.61–
2.05 effective unconfirmed deaths [131] 2008
United
Kingdom 3rd community 6 1.70 basic unconfirmed illness [37] 2005
Median reproduction number for the 1918 pandemic: 1.80; Interquartile range 1.47–2.27
a The first wave of illnesses began in the Northern Hemisphere in the spring 1918 [1]. A second wave of more intense transmission occurred
concurrently in North America, Europe, and Africa in the Fall of 1918 while a third and final wave of activity occurred in some areas of the
world during the winter of 1919 [15].
b The generation time (GT) or serial interval (SI) assumed in the reproduction number estimation.
c Confidence interval.
NR = Not reported.
This table is also available as a .csv file as Additional file 1.

Table 2 Reproduction Numbers from the 1957 Influenza A/H2N2 Pandemic
Location Wave
a
Study
Population
Mean GT/SI
b
Reproduction Number (R) 95% CI
c
Basic or Effective
Case definition Reference
Year Published
Netherlands 2nd community 3 1.39 basic unconfirmed deaths [34] 2010
United Kingdom 2nd community 2.6 1.70 basic unconfirmed deaths [10] 2006
United Kingdom 2nd community 3 1.5–1.6 basic unconfirmed illness [35] 2008
United Kingdom 2nd community 4 1.7–1.8 basic unconfirmed illness [35] 2008
United Kingdom 2nd community 4.1 1.50 effective unconfirmed illness [36] 2006
United Kingdom 2nd community NR 1.65 basic serology confirmed infection [37] 2005
USA 2nd community 4 1.70 basic unconfirmed illness [38] 2004
Median reproduction number for the 1957 pandemic: 1.65; Interquartile range 1.53–1.70
a The 1957 influenza A/H2N2 pandemic began in February 1957 in southern China and spread to Singapore and Hong Kong in April [1]. The
virus was first isolated in the United States in June 1957 and was associated with a mild first wave of illnesses [1,17]. The peak of the pandemic
occurred during the second wave in the Northern Hemisphere in October 1957 and was followed by a third wave in January 1958.
b The generation time (GT) or serial interval (SI) assumed in the reproduction number estimation.
c Confidence interval.
NR = Not reported.
This table is also available as a .csv file as Additional file 2.

Table 3 Reproduction Numbers from the 1968 Influenza A/H3N2 Pandemic.
Location Wave
a
Study Population
Mean GT/SI
b
Reproduction Number (R)
95% CI
c
Basic or Effective
Case definition Reference
Year Published
Hong Kong 1st community 2.95 1.89 basic unconfirmed illness [39] 1986
various 1st community 4 1.06–2.06 basic serology; laboratory confirmed illness; unconfirmed illness [18] 2010
various 1st confined settings 4 1.08–1.62 basic serology; laboratory confirmed illness; unconfirmed illness [18] 2010
United Kingdom
1st community 4.1 1.80 effective unconfirmed illness [36] 2006
United Kingdom
2nd community NR 1.85 effective serology confirmed infection [37] 2005
various 2nd community 4 1.08–2.02 effective serology; laboratory confirmed illness; unconfirmed illness [18] 2010
various 2nd confined settings 4 1.43 1.23–1.63
effective serology; laboratory confirmed illness; unconfirmed illness [18] 2010
Median reproduction number for the 1968 pandemic: 1.80; Interquartile range 1.56–1.85.
a The 1968 influenza A/H3N2 pandemic began in Hong Kong in July 1968. Large single waves of illness were reported in the Northern
Hemisphere between September 1968 and April 1969 (with peaks occurring in December 1968–January 1969). Large single waves of illnesses
were reported in the Southern Hemisphere between June and September 1969. Some countries in the Northern Hemisphere, such as the United
Kingdom, did not have an outbreak of H3N2 until the winter of 1969–70.
b The generation time (GT) or serial interval (SI) assumed in the reproduction number estimation.
c Confidence interval.
NR = Not reported.
This table is also available as a .csv file as Additional file 3.

Table 4 Reproduction Numbers from the 2009 Influenza A/H1N1 Pandemic
Location Wave
a
Study Population
Mean GT/SI
b
Reproduction Number (R) 95% CI
c
Basic or Effective
Case definition Reference
Year Published
Mexico 0 community 1.91 1.25 0.76–1.74
basic laboratory confirmed illness [19] 2011
Australia 1st community 2.8 1.50 1.50–2.70
effective laboratory confirmed illness [40] 2010
Australia 1st community 2.8 1.20 1.0–1.4 effective laboratory confirmed illness [40] 2010
Australia 1st community 2.9 2.40 2.3–2.4 effective laboratory confirmed illness [41] 2009
Australia, rural 1st community 2.9 1.28 1.26–1.30
effective laboratory confirmed illness [42] 2011
Australia, urban 1st community 2.9 1.26 1.22–1.30
effective laboratory confirmed illness [42] 2011
Canada 1st community 1.91 1.30 1.12–1.47
basic laboratory confirmed illness [43] 2010
Canada 1st community 2.78 2.21 1.98–2.50
basic laboratory confirmed illness [44] 2012
Canada 1st community 3.6 1.63 1.31–1.96
basic laboratory confirmed illness [43] 2010
Canada 1st community 4.31 1.31 1.25–1.38
basic laboratory confirmed illness [45] 2010
Chile 1st community 2.5 1.80 1.6–2.0 effective unconfirmed emergency room visits [46] 2010
Chile, central 1st community 3 1.32 1.27–1.37
effective unconfirmed hospitalizations [47] 2012
Chile, northern 1st community 3 1.19 1.13–1.24
effective unconfirmed hospitalizations [47] 2012
Chile, southern 1st community 3 1.58 1.45–1.72
effective unconfirmed hospitalizations [47] 2012
China 1st community 2.6 1.25 1.22–1.28
effective laboratory confirmed illness [48] 2012
China 1st community 4.31 1.53 1.45–1.60
basic laboratory confirmed illness [49] 2012
China 1st community NR 1.68 basic laboratory confirmed illness [50] 2011
Hong Kong 1st community 3 1.70 1.6–1.8 effective laboratory confirmed illness [51] 2010
Hong Kong 1st community 3.2 1.45 1.4–1.5 effective laboratory confirmed illness [52] 2010
Israel 1st community 2.92 1.06 0.97–1.16
effective laboratory confirmed illness [53] 2011
Italy 1st community 2.6 1.30 1.23–1.32
effective unconfirmed illness [54] 2012
Japan 1st school 1.9 2.30 2.0–2.6 effective laboratory confirmed illness [55] 2009
Japan 1st community 2.7 1.28 1.23–1.33
effective laboratory confirmed illness [55] 2009
Mexico 1st community 1.91 1.58 1.34–2.04
basic unconfirmed illness [56] 2009
Mexico 1st community 1.96 1.42 basic unconfirmed illness [57] 2010
Mexico 1st community 2.6 1.40 1.2–1.9 basic laboratory confirmed illness [56] 2009
Mexico 1st community 2.6 1.22 1.05–1.60
basic laboratory confirmed illness [56] 2009
Mexico 1st community 3 1.80 1.78–1.81
effective unconfirmed illness [58] 2011
Mexico 1st community 3 1.43 1.29–1.57
effective laboratory confirmed illness [59] 2009
Mexico 1st community 3.1 2.20 2.1–2.4 effective laboratory confirmed illness [60] 2009
Mexico 1st community 3.5 2.30 2.1–2.5 basic laboratory confirmed illness [11] 2009
Mexico 1st community 3.6 1.75 1.6–1.9 basic seeding from Mexico [61] 2009
Mexico 1st community 4.1 3.10 2.9–3.5 effective laboratory confirmed illness [60] 2009
Mexico City 1st community 3 1.72 basic laboratory confirmed illness [62] 2009
Morocco 1st community 2.3 1.44 1.32–1.56
basic laboratory confirmed illness [63] 2012
Morocco 1st community 2.7 1.40 1.34–1.48
basic laboratory confirmed illness [63] 2012
Netherlands 1st community 3 0.50 effective laboratory confirmed illness [64] 2009
New Zealand 1st community 2.7 1.25 1.07–1.47
effective laboratory confirmed illness [65] 2011
New Zealand 1st community 2.8 1.96 1.80–2.15
effective laboratory confirmed illness [66] 2009
New Zealand 1st community 2.8 1.55 1.16–1.86
effective laboratory confirmed illness; unconfirmed illness [67] 2010
North America 1st community 2.7 1.3–2.1 basic laboratory confirmed illness [68] 2010
Peru 1st community 2.8 1.37 1.33–1.41
effective laboratory confirmed illness [69] 2009
Peru 1st community 3 1.30 1.3–1.3 effective unconfirmed illness [70] 2011
Peru, Lima 1st community 3 1.70 1.6–1.7 effective unconfirmed illness [70] 2011
Singapore 1
st
dance club 1.91 1.9–2.1 basic laboratory confirmed illness [71] 2010
Singapore 1st military NR 1.91 1.50–2.36
effective laboratory confirmed and unconfirmed illness [72] 2010

South Africa 1st community 2.3 1.43 1.38–1.49
effective laboratory confirmed illness [73] 2012
South Africa 1st community 2.78 1.47 1.30–1.72
effective laboratory confirmed illness [73] 2012
South Africa 1st community 2.78 1.42 1.20–1.71
effective laboratory confirmed illness [73] 2012
Southern Hemisphere 1st community 1.9 1.16–1.53 effective laboratory confirmed illness [74] 2010
Southern Hemisphere 1st community 2.60 1.33 1.28–1.45
basic laboratory confirmed and unconfirmed illness [75] 2011
Taiwan 1st community 1.91 1.14 1.04–1.25
effective laboratory confirmed illness [76] 2011
Taiwan 1st community NR 1.16 0.98–1.34
effective serology confirmed infection [77] 2011
Thailand 1st community 1.9 1.78 1.67–1.89
basic laboratory confirmed illness [78] 2009
Thailand 1st community 2.6 2.07 1.92–2.22
basic laboratory confirmed illness [78] 2009
United Kingdom 1st school 2.2 1.33 1.11–1.56
effective laboratory confirmed illness [79] 2012
United Kingdom 1st community 2.5 1.44 1.27–1.63
effective laboratory confirmed illness [80] 2009
USA 1st community 2.2 1.70 1.4–2.1 basic laboratory confirmed illness [29] 2009
USA 1st community 2.6 2.20 1.4–2.5 basic laboratory confirmed illness [29] 2009
USA 1st school 2.7 3.30 3.0–3.6 effective unconfirmed illness [31] 2009
USA 1st community 3.5 1.3–2.0 1.0–2.2 basic laboratory confirmed illness [11] 2009
USA 1st camp attendees 7 2.20 1.4–3.3 effective unconfirmed illness [81] 2011
Vietnam 1st community 1.9 1.50 1.5–1.6 basic laboratory confirmed illness [82] 2010
Vietnam 1st community 3.6 2.00 1.9–2.2 basic laboratory confirmed illness [82] 2010
worldwide 1st community 2.67 1–2 effective laboratory confirmed illness [83] 2011
China 2nd community 4 1.66 1.27–2.05
effective confirmed hospitalizations [84] 2012
China 2nd community 4.3 1.70 1.4–1.9 effective laboratory confirmed illness [85] 2010
France 2nd military 2.9 1.5–1.6 effective unconfirmed illness [86] 2012
Iran 2nd school NR 1.28 1.05–1.54
basic unconfirmed illness [87] 2012
Italy 2nd community 2.5 1.33 effective unconfirmed illness [88] 2011
Japan 2nd community 3 1.48 1.41–1.56
effective unconfirmed illness [89] 2012
Mexico 2nd community 3 1.62 1.61–1.63
effective unconfirmed illness [58] 2011
Reunion Island 2nd community 2.8 1.26 1.08–1.49
effective unconfirmed illness [90] 2010
Taiwan 2nd community 1.91 1.02 1.01–1.02
effective laboratory confirmed illness [76] 2011
Taiwan 2nd community NR 1.87 1.68–2.06
effective serology confirmed infection [77] 2011
United Kingdom 2nd community 2.5 1.30 1.2–1.5 effective laboratory confirmed illness [91] 2010
Mexico 3rd community 3 1.24 1.23–1.24
effective unconfirmed illness [58] 2011
various community NR 1.30 1.1–1.4 effective serology confirmed infection [92] 2012
Median reproduction number for the 2009 pandemic: 1.46; Interquartile range 1.30–1.70
a The 2009 influenza A/H1N1 pandemic began in Mexico in the late winter or early spring of 2009 [19]. The United States and the United Kingdom experienced a first wave of illnesses in the Spring of 2009 followed
by a second wave during the Fall of 2009 [4]. However, unlike these three countries, a number of countries, especially in the Southern Hemisphere, only experienced a single wave of illnesses [20].
b The generation time (GT) or serial interval (SI) assumed in the reproduction number estimation.
c Confidence interval.
NR = Not reported.
This table is also available as a .csv file as Additional file 4.

Table 5 Reproduction Numbers from Seasonal Influenza Epidemics
Year(s) Type/Subtype Study Population
Mean GT/SI
a
Reproduction Number (R) 95% CI
b
Basic or Effective Case definition Reference Year Published
1889–1890 H3N8? USA & Europe 2.6 2.10 1.9–2.4 basic unconfirmed deaths [93] 2010
1948–1949 H1N1 Canada 4.1 1.30 effective unconfirmed illness [36] 2006
1949–1950 H1N1 Canada 4.1 1.50 effective unconfirmed illness [36] 2006
1950–1951 H1N1 Canada & UK 4.1 2.00 1.9–2.5 effective unconfirmed deaths [36] 2006
1958–1973 H2N2; H3N2; B United Kingdom 4.48 3.9–7.1 effective unconfirmed illness [94] 1979
1972–2002 H1N1/H3N2/B Australia 5.5 1.30 effective unconfirmed deaths [95] 2008
1972–2002 H1N1/H3N2/B France 5.5 1.30 effective unconfirmed deaths [95] 2008
1972–2002 H1N1/H3N2/B USA 5.5 1.30 effective unconfirmed deaths [95] 2008
1972–2002 H1N1/H3N2/B USA; France; Australia 5.5 1.30 1.2–1.4 effective unconfirmed deaths [95] 2008
1975–2004 H1N1/H3N2/B Norway 6 1.06–1.69 effective unconfirmed deaths [96] 2010
1976–1981 H1N1/H3N2/B USA 2.6 1.70 basic serology confirmed infection [10] 2006
1976–1981 H1N1/H3N2/B USA 4.1 1.16 basic serology confirmed infection [97] 2000
1977–1978 H1N1 United Kingdom 2.2 4.38 basic unconfirmed illness [33] 2005
1977–1978 H1N1 United Kingdom 3 21.00 basic unconfirmed illness [13] 2004
1977–1978 H1N1 United Kingdom 4.70 16.90 basic unconfirmed illness [33] 2005
1984–1985 H1N1/H3N2 France 2.49 1.37 effective unconfirmed illness [98] 1988
1985–2005 H1N1/H3N2/B United Kingdom 2.2 1.6–2.1 basic unconfirmed illness [99] 2010
1985–2005 H1N1/H3N2/B United Kingdom 2.7 1.6–2.5 basic unconfirmed illness [100] 2012
1985–2006 H1N1/H3N2/B France 2.4 1.4–1.7 1.3–1.8 basic unconfirmed illness [101] 2008
1996–2006 H1N1/H3N2/B Brazil 3 1.03 1.02–1.04 effective unconfirmed deaths [102] 2010
1998–1999 H3N2 Israel 3 1.14 effective unconfirmed illness [103] 2011
1998–1999 H3N2 Israel 3 1.16 effective unconfirmed illness [103] 2011
1998–1999 H3N2 USA 3 1.18 1.05–1.25 effective laboratory confirmed illness [104] 2009
1998–2009 H1N1/H3N2/B Israel 2.5 1.17–1.62 effective unconfirmed illness [105] 2012
1999–2000 H3N2 Israel 3 1.16 effective unconfirmed illness [103] 2011
1999–2000 H3N2 Israel 3 1.18 effective unconfirmed illness [103] 2011
1999–2006 seasonal H1N1 Taiwan 2 1.19 0.76–1.86 basic confirmed and unconfirmed illness [106] 2010
1999–2006 H3N2 Taiwan 3 1.41 0.92–2.19 basic confirmed and unconfirmed illness [106] 2010
1999–2006 B Taiwan 3 1.07 0.69–1.69 basic confirmed and unconfirmed illness [106] 2010
2000–2001 H1N1 Israel 3 1.12 effective unconfirmed illness [103] 2011
2000–2009 H1N1/H3N2/B Italy 4 1.17–1.36 effective unconfirmed illness [107] 2012
2001–2002 H3N2 Israel 3 1.25 effective unconfirmed illness [103] 2011
2001–2002 H3N2 Israel 3 1.27 effective unconfirmed illness [103] 2011
2003–2004 H3N2 Israel 3 1.19 effective unconfirmed illness [103] 2011
2003–2004 H3N2 Israel 3 1.21 effective unconfirmed illness [103] 2011
2003–2004 H3N2 Switzerland 2.6 1.2–1.3 effective unconfirmed illness [108] 2011

2004–2005 H3N2 Israel 3 1.25 effective unconfirmed illness [103] 2011
2004–2005 H3N2 Israel 3 1.25 effective unconfirmed illness [103] 2011
2004–2005 unspecified Taiwan 4.1 1.00 effective unconfirmed deaths [109] 2010
2004–2005 H3N2 USA 7 1.20 1.1–1.3 effective laboratory confirmed illness [110] 2008
2006–2007 H3N2 Israel 3 1.28 effective unconfirmed illness [103] 2011
2006–2007 H3N2 Israel 3 1.33 effective unconfirmed illness [103] 2011
2007–2008 H3N2 Israel 3 1.25 effective unconfirmed illness [103] 2011
2007–2008 H3N2 Israel 3 1.29 effective unconfirmed illness [103] 2011
2011/12 H1N1 Mexico 3 1.20 effective laboratory confirmed hospitalizations [111] 2012
2011/12 H1N1 Mexico 3 1.20 effective laboratory confirmed hospitalizations [112] 2012
2011/12 H1N1 Mexico 4 1.30 effective laboratory confirmed hospitalizations [112] 2012
Median reproduction number for seasonal influenza: 1.28; Interquartile range 1.19–1.37
a The generation time (GT) or serial interval (SI) assumed in the reproduction number estimation
b Confidence interval
NR = Not reported
This table is also available as a .csv file as Additional file 5.

Table 6 Reproduction Numbers from Novel Influenza Outbreaks
Year(s) Subtype
Study Population
Mean GT/SI
a
Reproduction Number (R)
95% CI
b
Basic or Effective
Case definition
Reference
Year Published
1976 H1N1 New Jersey 1.9 1.20 1.1–1.4 basic serologically confirmed illness
[23] 2007
2004–2006
H5N1 Vietnam 7 0.00 0–0.42 effective laboratory confirmed illness [110] 2008
2004–2006
H5N1 Indonesia 7 0.00 0–0 effective laboratory confirmed illness [110] 2008
2005 H5N1 Turkey 9.5 <1 basic laboratory confirmed illness [113] 2007
2005–2009
H5N1 Indonesia 6 0.1–0.25 0–0.4 effective laboratory confirmed illness [114] 2012
2006 H5N1 Indonesia 9.5 1.14 0.61–2.14
basic laboratory confirmed illness [113] 2007
Median reproduction number for novel influenza outbreaks: 0.34; Interquartile range 0.05–0.98
a The generation time (GT) or serial interval (SI) assumed in the reproduction number estimation.
NR = Not reported.
b Confidence interval.
This table is also available as a .csv file as Additional file 6.

1918 influenza pandemic
The origins of the 1918 influenza A/H1N1 pandemic are unknown, and illnesses are thought
to have occurred in three waves [1,15]. The first wave began in the Northern Hemisphere in
the spring 1918 [1]. A second wave of more intense transmission occurred concurrently in
North America, Europe, and Africa in fall 1918, and a third and final wave occurred in some
areas of the world during winter 1919 [15,16]. The 1918 pandemic was the most deadly
pandemic ever recorded, and an estimated 675,000 deaths occurred in the United States
during the pandemic period. In contrast to seasonal influenza, which disproportionately
affects the very young and old, those aged 20–40 years were especially affected [15].
Twenty-four studies reported 51 separate 1918 pandemic values of R (Table 1; Figure 2). The
median point estimate of R in the community setting for all waves of illness was 1.80 (IQR:
1.47–2.27) (Table 1). A higher median R value (R = 3.82; IQR: 2.68–4.84) was reported in
confined settings, such as ships, military camps, and schools. The median values of R were
similar between the first and subsequent waves of illness: the median value of R was 1.81
(IQR: 1.50–2.28) for the 1st wave, 1.73 (IQR: 1.39–2.33) for the second wave, and 1.70 (IQR:
1.55–1.76) for the third wave (Table 1).
Figure 2 Estimates of the reproduction number for the 1918 influenza A/H1N1
pandemic according to location, wave of illness, setting, and the serial interval or
generation time assumed in the estimation method. For individual studies, the single
estimate or median of multiple estimates is shown as a circle for basic reproduction numbers
or a square for effective reproduction numbers, and the range or confidence interval is
denoted by brackets. Estimates of the reproduction number are color coded based on the
generation time or serial interval used in calculations: red (<3 days), blue (≥3 days), or black
(not reported or not used).
The majority of 1918 pandemic values for R were calculated for populations in Europe,
which accounted for 58% of the R estimates included in this analysis. The mean generation
time or serial interval used in the calculations to estimate R had a median value of 3.3 days,
and the mean ranged from 1.5–6 days. Because the influenza virus was not discovered until
1931[1], all studies included in this review relied on reports of unconfirmed illness to identify
those ill. A majority (65%) used pneumonia-and-influenza-related hospitalizations and deaths
as the case ascertainment source (Table 1).
1957 influenza pandemic
The 1957 influenza A/H2N2 pandemic began in February 1957 in southern China and spread
to Singapore and Hong Kong in April[1]. The virus was first isolated in the United States in
June 1957 and was associated with a first wave [1,17]. The peak of the pandemic occurred
during the second wave in the Northern Hemisphere in October 1957 and was followed by a
third wave in January 1958. An estimated 115,000 deaths occurred in the United States
during the pandemic period [15].
Six studies reported seven separate 1957 pandemic values of R (Table 2; Figure 3). The
median point estimate of R in the community setting for the second wave of illnesses was
1.65 (IQR: 1.53–1.70). No R values were reported for confined settings or for the 1st or 3rd
waves of illness.

Figure 3 Estimates of the reproduction number for the 1957 influenza A/H2N2 and the
1968 influenza A/H3N2 pandemics according to location, wave of illness, setting, and the
serial interval or generation time assumed in the estimation method. For individual
studies, the single estimate or median of multiple estimates is shown as a circle for basic
reproduction numbers or a square for effective reproduction numbers, and the range or
confidence interval is denoted by brackets. Estimates of the reproduction number are color
coded based on the generation time or serial interval used in calculations: red (<3 days), blue
(≥3 days), or black (not reported or not used).
A majority (86%) of 1957 pandemic R values were calculated for populations in Europe. The
mean generation time or serial interval used in the calculations to determine R had a median
value of 3.5 days, and the mean ranged from 2.6–4.1 days. All studies but one included in this
review relied on an unconfirmed illnesses to identify those ill. The other study relied on the
final attack rate as determined by serological methods (Table 2).
1968 influenza pandemic
The 1968 influenza A/H3N2 pandemic began in Hong Kong in July 1968. Large single
waves were reported in the Northern Hemisphere between September 1968 and April 1969
(with peaks occurring in December and January) and in the Southern Hemisphere between
June and September 1969. Some countries in the Northern Hemisphere, such as the United
Kingdom, did not have an outbreak of H3N2 until the winter of 1969–70. In all, an estimated
110,000 deaths occurred in the United States during the pandemic period [15].
Four studies reported seven separate 1968 pandemic values of R (Table 3; Figure 3). The
median point estimate of R in the community setting for all waves of illness was 1.80 (IQR:
1.56–1.85) (Table 3). Only two values for R in confined settings were reported, and the
median value was 1.39. Two values of R were reported in a community setting during the
first wave and three during the second wave. The median value of R during the 1st wave was
1.56 and 1.68 during the 2nd wave (Table 3).
The 1968 pandemic values for R were calculated among populations in diverse geographic
locations, mainly because of one study that calculated separate values for over 25 locations,
such as Africa, Asia, and South America (the overall estimate for R is included in Table 3)
[18]. The mean generation time or serial interval used in the calculations to determine R had
a median value of 4 days with little variation. The studies for the 1968 pandemic included in
this review relied on a mix of laboratory-confirmed, unconfirmed illnesses, or serologically-
confirmed infections to identify those ill (Table 3).
The 2009 influenza pandemic
The 2009 influenza A/H1N1 pandemic began in Mexico in the late winter or early spring
2009 [19]. The United States and the United Kingdom experienced a first wave of illnesses in
the spring followed by a second wave during the fall [4]. However, a number of other
countries, especially in the Southern Hemisphere, only experienced a single wave of illnesses
[20]. In all, an estimated 12,000 deaths occurred in the United States during the first year of
pandemic circulation [21].
Fifty-seven studies reported 78 separate 2009 pandemic values of R (Table 4; Figure 4). The
median point estimate of R in the community setting for all waves of illness was 1.46 (IQR:

1.30–1.70) while a higher median R value (R = 1.96; IQR: 1.50–2.23) was reported in
confined settings, such as military or summer camps, schools, and night clubs. The value of R
was similar across the two distinct waves of illness: the median value of R was 1.47 (IQR:
1.31–1.71) for the first wave and 1.48 (IQR: 1.30–1.66) for the second wave (Table 4).
Figure 4 Estimates of the reproduction number for the 2009 Influenza A/H1N1
pandemic according to location, wave of illness, setting, and the serial interval or
generation time assumed in the estimation method. For individual studies, the single
estimate or median of multiple estimates is shown as a circle for basic reproduction numbers
or a square for effective reproduction numbers, and the range or confidence interval is
denoted by brackets. Estimates of the reproduction number are color coded based on the
generation time or serial interval used in calculations: red (<3 days), blue (≥3 days), or black
(not reported or not used).
A majority of 2009 pandemic values for R were calculated for populations in North America
(30%) and Asia (26%). The mean generation time or serial interval used in the calculations to
determine R had a median value of 2.8 days, and the mean ranged from 1.9–7 days (Table 4).
A majority of the studies included for the 2009 pandemic relied on either laboratory-
confirmed illnesses (71%) or unconfirmed illnesses (24%) to identify those ill (Table 4).
Seasonal influenza
Seasonal influenza causes sustained epidemics in the non-tropical areas of the Northern
Hemisphere and Southern Hemisphere during their respective late fall to early spring months.
Epidemics in the tropical regions occur sporadically but can be associated with the rainy
season [1]. The mortality burden from influenza varies by season, and from 1976–2007,
estimates of annual influenza-associated deaths in the United States from respiratory and
circulatory causes ranged from 3,000 to 49,000 [3].
Twenty-four studies reported 47 separate seasonal epidemic values of R (Table 5; Figure 5).
The median point estimate of R in the community setting for seasonal influenza was 1.27
(IQR: 1.19–1.37) while a higher median R value (R = 16.9) was reported in a British
boarding school during the 1977–78 influenza season (Table 5). R values for seasons where
H3N2 (R = 1.25; IQR: 1.18–1.27) or H1N1 (R = 1.25; IQR: 1.18–1.35) predominated were
equivalent (Table 5).
Figure 5 Estimates of the reproduction number in the community for seasonal influenza
epidemics according to location, wave of illness, and the serial interval or generation
time assumed in the estimation method. For individual studies, the single estimate or
median of multiple estimates is shown as a circle for basic reproduction numbers or a square
for effective reproduction numbers, and the range or confidence interval is denoted by
brackets. Estimates of the reproduction number are color coded based on the generation time
or serial interval used in calculations: red (<3 days), blue (≥3 days), or black (not reported or
not used).
A majority of seasonal influenza values for R were calculated for populations in Israel (35%),
Europe (25%), and North America (21%). The mean generation time or serial interval used in
the calculations to determine R had a median value of 3.0 days, and the mean ranged from
2.0–7.0 days (Table 5). A majority of the studies included for seasonal influenza relied on

unconfirmed illnesses or deaths (79%); the reminder relied on either laboratory-confirmed
illnesses or hospitalizations or serologically-confirmed infections (Table 5).
Human infections with non-human influenza viruses
Human infections with novel or non-human influenza viruses (also known as zoonotic
influenza viruses) are rare but can result in a pandemic if sustained person-to-person
transmission occurs and the population has little or no pre-existing population immunity to
the virus. Therefore, instances of infection with non-human influenza viruses are investigated
thoroughly to assess the transmissibility of the virus. The largest number of novel influenza
cases at the time of this review was from the ongoing influenza A/H5N1 outbreak centered in
Southeast Asia and the Middle East. From January, 1, 2003 to February 15, 2013, 620
laboratory-confirmed cases have been reported to the WHO, of which 367 have died [22].
Another large outbreak of novel influenza occurred in 1976 in Fort Dix, New Jersey, which
was caused by an influenza A/H1N1 virus similar to those found circulating in swine [23].
Four studies estimated the values of R for the A/H5N1 and A/H1N1 outbreaks (Table 6).
Four out of six estimates (67%) of R were less than one, and the highest R estimate (R = 1.2)
was for the 1976 A/H1N1 outbreak in a New Jersey military camp (a confined setting) (Table
6).
A majority of novel A virus R values were calculated for populations in Southeast Asia
(67%), indicative of where the bulk of A/H5N1 bird-to-human transmission occurs. The
mean generation time or serial interval used in the calculations to determine R had a median
value of 7.0 days, and the mean ranged from 1.9–9.5 days (Table 6). All studies relied on
either laboratory-confirmed illness or serological-confirmed infection (Table 6).
Discussion
In this review, the median R values reported for the four pandemics and seasonal influenza
varied between 1.27–1.8 while R values for novel influenza were generally below 1. We
found the highest median reproduction number associated with the 1918 and the 1968
influenza pandemics (both 1.8), followed by the 1957 pandemic (1.65), the 2009 pandemic
(1.46), seasonal influenza epidemics (1.27), and novel influenza outbreaks. A majority of R
values published were for either the 1918 pandemic or the 2009 pandemic; the 1957 and 1968
pandemics had the fewest published studies. Researchers calculated values for R for a variety
of locations and utilized many different case definitions, ascertainment methods, and
assumptions about the generation time or serial interval.
The approximate basic reproductive numbers for some common infectious diseases range
from 12–18 for measles, 12–17 for pertussis, and 4–7 for mumps, polio, rubella, and
smallpox [12]. These values are much higher than what has been reported for influenza, and
most R values reported in this review ranged from 1.0–2.0. However, the overall clinical
attack rate and peak daily incidence of an outbreak, which measures the potential burden on
healthcare services and school and workplace absenteeism, are very sensitive to changes in
the value of R within this range. Past research utilizing a number of assumptions on the
symptomatic ratio, contact patterns, and seeding has estimated that the cumulative clinical
attack rates for a pandemic when R = 1.3 ranged from 15%–21% and increased to 34%–42%
for R = 2.0 [10,11]. Similarly, the peak daily attack rate is 0.5% for R = 1.3 and 2.2% for R =

2.0 [10]. Therefore, with only an absolute difference in R of 0.7, the clinical attack rates in
these studies more than doubled and the peak daily incidence more than quadrupled.
Differences in the value of R within this range also affect the evaluation of potential
mitigation strategies (e.g., school closures, vaccination, household isolation) for influenza
pandemics. Analysis of strategies to mitigate an influenza pandemic have found that the
effectiveness of non-travel-related control policies, such as school closures, household
quarantine, and vaccination, would decrease as the value of R increases from 1.0 to 2.0 [10].
The success of various vaccination strategies would also be more likely for values of R < 1.7
[10,11]. Therefore, the small variations in pandemic R estimates found in this analysis can
have important implications for the overall impact and success of mitigation efforts for an
influenza pandemic. This finding highlights the importance of making precise estimates of R
early in a pandemic. Further research should focus on refining methods that allow for early,
robust estimates of R.
The results of this analysis reinforce the idea that R is a measure that captures the
transmissibility of an influenza virus in the population under study and is not an intrinsic
value. The inputs for its calculation can include the population contact rate, the probability of
infection per contact, the duration of illness, and the percentage of the population that is
susceptible which is affected by the characteristics of the population under study. Therefore,
the variations in the value for R for the same pandemic or seasonal outbreak are expected and
may be due to the underlying social and socio-demographic factors of the population studied,
public health interventions, and geographical or climatic factors of the location. These
variations include the percentage of the source’s population under 18 years old; differences in
contact patterns between age groups, which vary by country [24,25]; and differences in
population susceptibility profiles, which varied by age group for the 2009 pandemic [26].
Another important factor that may contribute to the variation is the season from which data
used to estimate R is collected. While the effect of weather on the transmissibility of
influenza has not been fully explored, some studies have shown that the level of absolute
humidity is inversely correlated with influenza transmissibility [27,28]. Therefore, estimates
of R should be interpreted in the context of the population under study and the season in
which data was collected and direct comparisons of R between populations should be
undertaken with caution.
Variations in the estimated values of R may also be driven by changes in surveillance
intensity in the same country over time. If a country suddenly improves its surveillance
system in response to a pandemic and is better able to identify cases, then the number of
cases being reported will increase, even though the actual number of cases occurring will not
have changed. This increase in the reported number of cases may increase the estimated R as
the growth rate of the outbreak will increase [29]. Conversely, the value of R could be
artificially lowered if countries implement changes in surveillance practices that result in a
lower number of identified cases, such as reducing screening recommendations, or have their
surveillance systems overwhelmed. This effect was seen in the United States during the 2009
pandemic, when influenza testing for every case became unfeasible and testing
recommendations were changed [4].
One of the more important methodological assumptions that can have a large impact on the
estimated value of R is the length of the serial interval or generation time used during the
estimation of R. Longer serial intervals have previously been associated with higher estimates
of R when compared to estimates from the same dataset using shorter serial intervals [9]. In

this analysis, estimates of R from the 1918, 1957, and 1968 pandemics utilized higher serial
interval values than were used for the 2009 pandemic or for seasonal influenza. Additionally,
higher values of R from the 2009 pandemic often were estimated using a generation time or
serial interval of 3 days or more (Figure 4). Therefore, the estimates of R included in this
analysis should be interpreted in the context of the serial intervals or generation times used in
the estimation method. Like R, the values for the generation time or the serial interval can
vary by the source population. Therefore, researchers estimating the values of R should strive
to use standard estimates of the serial interval or generation time for influenza or at least
include common values in a sensitivity analysis. This will help with the comparability of R
values across studies and may aid in the correct interpretation of R estimates. An additional
way in which estimates of R may be biased up or down lies in the choice of estimation
procedure itself. Chowell et al. showed that estimates of R obtained using simple epidemic
mathematical models varied considerably as the model increased in complexity (e.g. the
addition of a period of infection latency or an age-structured population) [30].
Although we found no difference in the value of R for studies using confirmed cases versus
unconfirmed cases in the estimation method, the trade-off between the accuracy of the less
specific but more efficient and cost effective syndromic data compared to laboratory-
confirmed influenza infections is unknown. The incubation periods of non-influenza
respiratory pathogens that co-circulate with influenza (e.g. respiratory syncytial virus or
rhinovirus) range from a median of 1.9–5.6 days; estimates of R for influenza could either be
overestimated or underestimated during periods of co-circulation, depending on the intensity
and identity of the co-circulating respiratory pathogen [31]. Future research should focus on
estimation of R using laboratory-confirmed cases and hospitalizations and should provide
estimates from syndromic data for comparison.
Most studies included in this analysis focused on 1918 or the 2009 pandemic. Only a small
number of estimates of the reproduction number have been reported for the two other
pandemics of the 20th century (1957 and 1968). As a consequence, there is still insufficient
information to fully clarify the transmission dynamics of the 1957 and 1968 pandemics.
Because historical data are available for these pandemics, future research should focus on
estimations of R for the 1957 and 1968 pandemics to better understand the characteristics of
these pandemics.
This study generally found higher reproduction numbers for confined settings, such as
schools, military bases, or night clubs, except for estimates from the 1968 pandemic. Because
confined settings increase the intensity of transmission by increasing contact rates among
those ill and well, the values of R presented for outbreaks in confined settings are likely to be
much higher than values of R estimated for the community and should be interpreted
accordingly. While the estimation of R in confined settings may be useful for the assessment
of the upper bounds of transmissibility, its value is not directly comparable to estimates of R
made in the community setting.
This review found, with one exception, a high degree of consistency in the estimated values
of R for seasonal influenza epidemics. The only notable exception was the extremely high R
values estimated for an outbreak of influenza A (H1N1) in 1978 at a small British boarding
school with 763 male students aged 10–18 who were mostly full boarders [32]. The results of
this analysis suggest that the extreme R values reported for this outbreak are not typical of
seasonal or pandemic influenza and instead may be the result of the lack of pre-existing
immunity among the students to the strain of influenza A (H1N1) that caused the outbreak,

the extremely high contact rates likely among a group of boarded students, or a study artifact
related to the small number of students in the study population [13,32,33]. Additionally, the
median R value of seasonal influenza (R = 1.27) is well below the median values seen during
the four pandemics examined in this report. The consistency of seasonal R values is even
more remarkable given the wide variety of estimation methods, data sources, and
assumptions used in the studies included here. However, the majorities of seasonal influenza
estimates were from a small number of countries. Estimates of R from countries in Africa,
Asia, and South America are also needed to determine if values of R for seasonal influenza
epidemics are affected by geographic and social factors.
This systematic review is subject to at least three limitations. First, we combined estimates
for the basic and effective reproductive numbers when presenting the median estimates in this
study. Even though these values measure transmission in populations with differing levels of
underlying population immunity, some papers included in this review did not clearly
differentiate between basic and effective reproductive numbers or state the required
population immunity assumptions when reporting basic reproductive numbers. Therefore, we
choose to present summary values for the basic and effective reproductive numbers together
to simplify the results. The tables include whether the reproductive number estimate was
reported as basic or effective for each study. Second, we did not assess included studies for
the type or quality of their methodology or the risk of study bias. Finally, we only included
published estimates of the reproductive number, which may not be representative of
unpublished reproductive number values.
Conclusions
In this review, we explored the ranges and uncertainty of the values of R estimated for
seasonal, pandemic, and novel influenza. We found that values of R changed over the course
of a pandemic but the effect of the waves varied. The value of R is not constant and may be
affected by mitigation strategies, the season, and the population under study. The values of R
found in this analysis represent the difference between a pandemic that is controllable with
less intensive mitigation strategies and would cause moderate amounts of illness to a
pandemic that would require very intensive mitigation strategies and would cause greater
amounts of illness. Continued monitoring of R during outbreaks of human infections with
non-human influenza viruses and in various settings throughout future pandemics will be
required to fully understand the effects of mitigation, geography, and season.
Competing interest
The authors declare that they have no financial or non-financial competing interests with the
publication of this manuscript.
Authors’ contributions
MB led the data collection, analysis, and the writing of the article. SC led the editing of the
article and assisted with data interpretation. CR and MG contributed significantly to data
interpretation and reviewed multiple drafts of the article. LF contributed to the design of the
study, data interpretation, and reviewed multiple drafts of the article. All authors read and
approved the final manuscript.

Acknowledgements
We are particularly grateful for the assistance in the preparation and editing of the manuscript
given by Alejandro Perez and Dr. Claudia Campbell.
Disclaimer
The findings and conclusions in this report are those of the authors and do not necessarily
represent the official position of the Centers for Disease Control and Prevention.
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Additional files
Additional_file_1 as CSV
Additional file 1 Reproduction Numbers from the 1918 Influenza A/H1N1 Pandemic.
Additional_file_2 as CSV
Additional file 2 Reproduction Numbers from the 1957 Influenza A/H2N2 Pandemic.
Additional_file_3 as CSV
Additional file 3 Reproduction Numbers from the 1968 Influenza A/H3N2 Pandemic.
Additional_file_4 as CSV
Additional file 4 Reproduction Numbers from the 2009 Influenza A/H1N1 Pandemic.
Additional_file_5 as CSV
Additional file 5 Reproduction Numbers from Seasonal Influenza Epidemics.

Additional_file_6 as CSV
Additional file 6 Reproduction Numbers from Novel Influenza Outbreaks.

Figure 1

Figure 2

Figure 3

Figure 4

Figure 5

Additional files provided with this submission:
Additional file 1: 1087449605126674_add1.csv, 5K
http://www.biomedcentral.com/imedia/1178226896141653/supp1.csv
Additional file 2: 1087449605126674_add2.csv, 1K
http://www.biomedcentral.com/imedia/6171285401416534/supp2.csv
Additional file 3: 1087449605126674_add3.csv, 1K
http://www.biomedcentral.com/imedia/2078462722141653/supp3.csv
Additional file 4: 1087449605126674_add4.csv, 9K
http://www.biomedcentral.com/imedia/1181872864141653/supp4.csv
Additional file 5: 1087449605126674_add5.csv, 5K
http://www.biomedcentral.com/imedia/1503447023141653/supp5.csv
Additional file 6: 1087449605126674_add6.csv, 1K
http://www.biomedcentral.com/imedia/1526934972141653/supp6.csv