Introduction
Acute lower respiratory tract infections are the leading cause of death in children
in low-income regions [1,2]. Pneumonia is the main clinical presentation of such infections,
being of high incidence and severity among children and elderly [3,4]. Community-acquired
pneumonia is a common cause of hospitalizations among infants throughout the world.
It has been estimated that each year, 120 million new episodes of pneumonia, and 11.9
million hospitalizations due to pneumonia occur in children living in low and middle-income
regions [5,6].
The economic burden of pneumonia is significant. In recent years, significant economic
burden due to pneumonia in children has been demonstrated, in particular in those
under two years of age living in low-income countries [7]. Streptococcus pneumoniae
is responsible for 60% to 75% of all bacterial pneumonia episodes in this age-group
[8]. The inclusion of pneumococcal protein polysaccharide conjugate vaccines (PCVs)
in National Immunization Programs (NIPs) is recommended as the primary strategy for
prevention of pneumococcal disease in low-income countries, because of their substantial
effect and cost-effectiveness [9].
Studies assessing the effect of 7-valent PCV (PCV7) introduction on pneumonia epidemiologic
and economic burden have demonstrated significant impact shortly after vaccine introduction
as a result of averted costs of illness and associated productivity losses [7]. In
2010, PCV7 was replaced by 13-valent (PCV13). The incorporation of these two vaccines
in different countries was accompanied by a decrease in the incidence of pneumonia
hospitalizations in children soon after vaccine introduction, both in age-groups targeted
(direct effect) [10], and non-targeted (indirect effect) by vaccination [11]. Long-term
direct and indirect PCV7 impact on pneumonia hospitalizations have also been demonstrated
in developed countries [12,13]. The indirect effect of vaccination is attributed to
the reduction of nasopharyngeal colonization by vaccine serotypes in vaccinated children,
thus contributing to decrease the risk of pneumococcus transmission in the community.
In Brazil, pneumonia hospitalization rates are high throughout all age-groups, with
greater burden in children in their first year of life. In March 2010, the Brazilian
Ministry of Health introduced 10-valent PCV (PCV10) into its NIP, targeting infants
[14]. PCV10 differs from PCV7 and PCV13 not only in numbers of serotypes but also
in concentration of the capsular polysaccharides, immunogenicity, carrier proteins,
and conjugation process [15]. Shortly after PCV10 introduction, high vaccine coverage
rates were observed, reaching 81.7% in 2011, and 94.2% in 2015 [16]. A significant
reduction in invasive pneumococcal disease (IPD) was readily observed in 2012 in children
under two years of age in most regions of the country [17]. Two recent studies demonstrated
the direct impact of PCV10 on the reduction of pneumonia hospitalizations in children
in Brazil. The first one demonstrated, by 2011, a significant reduction in pneumonia
hospitalizations in children aged 2–23 months in 3 out of 5 large municipalities which
are state capitals located in various regions of the country [18]. Another study conducted
in 2012, showed nationwide reduction of pneumonia hospitalizations in children younger
than one year of age [19]. Despite this evidence, there is still uncertainty regarding
the indirect effect of PCV10 on pneumonia hospitalization. In particular, to date,
no such study has been conducted in developing countries. Furthermore, the impact
of PCV10 on the reduction of the economic burden of pneumonia hospitalizations, which
is the main component of such burden, has not yet been demonstrated in developing
settings.
In Brazil, most population uses the Unified Health System (SUS), which is provided
free of charge. Vaccines are also offered by the NIP through SUS. All hospitalizations
occurring nationwide in SUS are recorded in a National Hospitalization Information
System (SIH), which includes information on hospital admissions and discharges since
1975 [20,21].
In this investigation, using population-based data from the SIH, we measured both
direct and indirect effect on pneumonia hospitalizations in Brazil, after the introduction
of PCV10 for infants in 2010. The PCV10 impact on the economic burden of pneumonia
hospitalizations in all age-groups was also estimated.
Methods
Study design
We conducted an interrupted time-series analysis comparing monthly rates of pneumonia
hospitalizations with those of a comparison group of disease. We also conducted an
economic burden analysis, modeling the averted costs of pneumonia hospitalizations.
Study site and population
Brazil is a middle-income country with continental dimensions and with significant
social and economic inequalities. Its overall population was estimated at approximately
190 million people in 2010 [22]. The study population considered hospitalization data
for all age groups, including children, adults, and elderly, from January 2005 to
December 2015. A total of 126,998,568 hospitalizations due to any cause occurred in
the SUS during this 11-year period.
Ethics approval
The Ethics Committee of Federal University of Goiás in Goiania, Brazil, (# 162,532)
granted ethical approval for this investigation. Considering we used national bigdata
without personal identifiers, the Institutional Research Board (IRB) waived the written
individual consent.
Intervention
PCV10 was introduced in the Brazilian Immunization Program for infants in all municipalities
from March to September 2010, being offered as a free of charge universal childhood
vaccination [14]. PCV10 includes serotypes 1, 5, and 7F, in addition to serotypes
4, 6B, 9V, 14, 18C, 19F, and 23F, contained in the formulation of PCV7. The adopted
vaccination schedule was three primary doses at 2, 4, and 6 months plus a booster
at 12 to 15 months of age. During the vaccine introduction period, a catch-up schedule
was recommended for children between 7–11 months of age (two doses plus booster),
and for those between 12–23 months of age (single catch-up dose). The vaccine was
not recommended for children aged 24 months of age and older. Vaccination coverage
for the three primary doses reached 81.7%, 88.4%, 93.6%, 92.9% and 94.2% for 2011–2015
respectively [16]. Although PCV7 had been licensed in Brazil in 2001, it was only
available to a small portion of the population, through private clinics or through
the NIP to high-risk individuals in selected NIP units responsible for providing special
vaccines to special target groups.
Study periods
For the time-series analysis, we defined the pre-intervention period from January
2005 to December 2009, and the post-intervention period from January 2011 to December
2015. The year 2010 was excluded from the analysis, as it was the transition period
when coverage of PCV10 increased progressively to over 80%. For the assessment of
PCV10 impact on economic burden, we estimated the costs of averted pneumonia cases
in the post- intervention period.
Hospitalization data source
We used data from the SIH of the SUS without personal identification information,
which are publicly available online [23]. All hospitalizations funded by SUS, which
represents 65.7% of all hospitalizations in the country [24], are recorded into the
SIH. International statistical classification and related health problems, 10th revision
(ICD10) codes [25] assigned for discharge diagnoses of all hospitalized patients are
recorded in SIH. The databases were extracted in April 2017, and the following variables
were considered: state of residence, city of residence, date of birth, date of admission,
discharge diagnosis, and cost of hospitalization.
Age-groups and outcomes
For this investigation, the following age-groups were considered: <12 months, 12–23
months, 2–4 years, 5–9 years, 10–17 years, 18–39 years, 40–49 years, 50–64 years,
and ≥65 years.
The main outcome of interest was all-cause pneumonia hospitalizations defined by ICD10
codes J12-J18. The comparison groups were a combination of multiple sets of diseases,
having as a basis the ICD-10 codes groups proposed by Bruhn et al. [26], but performing
a manual selection of which ones should be excluded from each age-groups. Excluded
disease groups were those potentially influenced by the introduction of PCV-10 vaccine,
those whose trend in the pre-vaccination period differed much from the observed trend
for pneumonia, those that could have suffered the concurrent effect of another national
public health intervention and those that were related to very short-stay or very
long-stay hospitalizations. For each age group, a different combination of groups
was selected (S1 File).
Data analysis
Descriptive analysis
Rates per 100,000 and numbers of pneumonia and comparison group hospitalizations,
and populations were described by year and age-group. Annual average rates of pneumonia
and comparison group hospitalizations were examined by period (pre-vaccination and
post-vaccination) and age-group.
Time-series analysis
Observed hospitalizations rates per 100,000 population were calculated considering
in the numerator monthly counts of hospitalization due to specific ICD10 codes listed
on the primary diagnosis field, which represents the main or primary discharge diagnosis.
Denominators were monthly population estimated by linear regression based of the 2000
and 2010 census data for each of the age-specific populations (the dataset generated
is available in S1 Dataset).
The additive Holt-Winters model was used for the interrupted time-series analysis
[27–29]. This method provides an exponentially weighted moving average of the observed
values in the pre-vaccination. The rationale for using this model is that the most
recent observations in the pre-vaccination period will provide the most valuable data
to forecast the future. The time series is represented by the model:
y
t
=
L
t
+
S
t
+
T
t
+
ξ
t
where:
L
t
represents the Level adjustment component,
S
t
represents the Seasonal adjustment component, with S
t
= S
t+s
= S
t+2s
= ⋯, for t = 1, 2, …, (s-1) and s is the length of the seasonal period.
T
t
is the Trend component adjustment,
ξ
t
are the residuals.
This model can be forecasted by:
S
^
t
=
γ
(
y
t
−
L
^
t
)
+
(
1
−
γ
)
(
S
^
t
−
s
)
,
with
0
<
γ
<
1
L
^
t
=
α
(
y
t
−
S
^
t
−
s
)
+
(
1
−
α
)
(
L
^
t
−
1
+
T
^
t
−
1
)
,
with
0
<
α
<
1
T
^
t
=
β
(
L
^
t
−
L
^
t
−
1
)
+
(
1
−
β
)
(
T
^
t
−
1
)
,
with
0
<
β
<
1
where α, β and γ are arbitrary constants of initialization: α is the level constant,
β is the trend constant and γ is the seasonal constant.
We calculated the initial values of the recurrence equation by:
S
^
j
=
y
j
1
s
∑
k
=
1
s
y
k
,
j
=
1
,
2
,
…
,
s
.
y
^
s
=
1
s
∑
k
=
1
s
y
k
,
and
T
^
s
=
0.
And the forecast for new values by:
y
^
t
+
1
(
h
−
1
)
=
L
^
t
+
1
+
(
h
−
1
)
T
^
t
+
1
+
S
^
t
+
1
+
h
−
s
,
with h
=
1
,
…
,
s
+
1
.
For each of the Holt-Winters models, the trend component was assessed by linear regression
and Cox-Stuart tests and the seasonal component by Kruskal-Wallis tests. These indicator
variables were only retained in the final models if they were found to be statistically
significant.
The error component was obtained by:
ξ
^
t
=
y
t
−
y
^
t
i.e. the difference between predicted and observed values. As a measure of prediction
accuracy, we present the mean absolute percentage error (MPE) of each model of the
pre-vaccination period.[29]
M
P
E
=
1
n
∑
t
=
1
n
(
y
t
−
y
^
t
y
t
)
*
100
We first fitted Holt-Winters models to the pre-vaccination period, using monthly rates
from 2005 to 2009, but excluding the data points from April to October 2009, which
corresponded to the period of the pandemic influenza virus A (H1N1) in Brazil. Next,
we used Holt-Winters models based on pre-vaccination data to predict the monthly hospitalization
rates “expected” to occur in the post-vaccination period (2011–2015), i.e. in the
absence of PCV10 vaccination. All models were run separately for the all cause-pneumonia
and for the comparison group hospitalizations, for each of the age-groups considered.
The post-vaccination predicted rates were then compared to the post-vaccination observed
rates, i.e. in the presence of PCV10 vaccination. In order to do that, we calculated
the percentage of change between the mean of the observed and the mean of the predicted
monthly rates using the following formulae:
Percentage Change
=
PC
=
MMRobs
−
MMRpred
SMRpred
*
100
Mean of the observed monthly rates
=
MMRobs
=
1
n
∑
t
=
1
n
M
R
o
b
s
t
Mean of the predicted monthly rates
=
MMRpred
=
1
n
∑
t
=
1
n
M
R
p
r
e
d
t
We tested the hypothesis that the mean of the observed monthly rates differed from
the mean of the predicted monthly rates and calculated a 95% confidence interval for
the difference of means, using standard tests for two independent normal populations
with unequal and unknown variances.[30]
Finally, we calculated the difference between the percentage changes obtained for
the pneumonia and comparison groups, using the formula:
Relative Percentage Change
=
R
P
C
=
P
C
p
n
e
u
m
o
n
i
a
−
P
C
c
o
m
p
a
r
i
s
o
n
g
r
o
u
p
This is our measure of vaccination impact, which we refer to as the “relative percentage
change”. Relative percentage changes were calculated considering cumulative years
in the post vaccination period (i.e. for 2011, 2011–2012, 2011–2013, 2011–2014 and
for the whole post-vaccination period 2011–2015). Respective 95% confidence intervals
(95%CI) and p-values were similarly estimated.[30]
For the economic burden, after estimating the predicted annual numbers of pneumonia
hospitalization cases in the post-vaccination period, by the age-groups, we calculated
the number of all-cause pneumonia hospitalizations averted by vaccination as the difference
between the predicted and observed cumulative number of pneumonia hospitalizations
in the PCV10 post-vaccination period.
Data management was performed in STATA v. 13.0. We used R software (packages base
and stats) for all data analysis and graphics. The modeling scripts are available
as supporting information (S2 File).
Cost and averted economic burden of hospitalized pneumonia cases
Economic burden analysis considered the SUS perspective. Costs of hospitalized pneumonia
cases in all age-groups were obtained by the gross-costing methodology [31], which
considers the reimbursement paid by SUS to the hospital in which the individual had
been hospitalized. Reimbursement values include both medical and non-medical costs.
Medical costs include hospital stay, healthcare professional services and physical
therapy, while non-medical costs include hospital stay of a parent or caregiver accompanying
the hospitalized individual.
Reimbursed values by cost items are standardized nationwide based on SUS own price
list [32]. Hospital stay is valued based on the ICD10 diagnostic code for the main
or primary discharge diagnosis. Pneumonia reimbursement value is BRL 504.00 for hospital
stay of up to 9 days, after which an additional BRL 20.00 per day is paid. Standard
reimbursement values for healthcare professional services for pneumonia are BRL 78.35,
which may increase depending on the need for additional specialty professionals. For
each physical therapy session, an additional BRL 6.35 is paid. Each day of hospital
stay of an accompanying parent or caregiver is reimbursed at BRL 8.00 [32,33].
The average and standard deviations of cost of pneumonia hospitalizations were estimated
by age-group, based on reimbursement values by patient reported in the SUS hospitalization
database. We assumed that the cost of observed hospitalized cases each year in the
period of 2011–2015 was equivalent to the cost of cases averted, should they have
occurred.
For the assessment of PCV10 impact on economic burden, we then multiplied the cost
per hospitalized pneumonia by the number of all-cause pneumonia hospitalizations averted
by PCV10 vaccination, as estimated by the time-series analysis. Costs in BRL were
converted to US Dollars (USD) considering the official exchange rate in December 2011
(1 BRL = 0.53 USD), December 2012 (1 BRL = 0.50 USD), December 2013 (1 BRL = 0.43
USD), December 2014 (1 BRL = 0.39), and December 2015 (1BRL = 0.26) [34] Official
purchasing power parity exchange rates for 2011 (1 Int$ = 1.47 BRL), 2012 (1 Int$
= 1.56 BRL), 2013 (1 Int$ = 1.65 BRL), 2014 (1 Int$ = 1.73 BRL), and 2015 (1Int$ =
1.87BRL) were used to convert Brazilian Reais into and International dollars (Int$)
[35]. We present costs for each year individually and therefore opted not to adjust
these amounts to inflation rate [36].
Results
Descriptive analysis
From 2005 to 2015, a total of 126,998,568 SUS hospitalizations were recorded. After
exclusion of records of hospitalizations due to selected groups of discharge diagnoses
(S1 File) and records with missing date of birth (n = 26,716), a total of 78,727,692
records were available for analysis. Among these, pneumonia was recorded as the main
discharge diagnosis in 7,829,895 (9.9%) hospitalizations, of which 2,053,419 (26.2%)
occurred in children <24 months of age, and 1,902,819 (24.3%) in elderly ≥65 years.
Pneumococcal pneumonia was coded as the discharge diagnosis in 0.5% (n = 42,146) of
all pneumonia hospitalizations. Considering all age-groups, the total and the average
annual number of pneumonia hospitalizations were 3,689,416 and 737,883 in the pre-vaccination
period, and 3,378,795 and 675,957 in the post-vaccination periods, respectively (S1
Table).
Annual rates of pneumonia hospitalization were highest at the extreme age-groups,
in both vaccination periods, with rates of approximately 3,500 hospitalizations per
100,000 individuals for both children 2–4 years and elderly (≥65 years). While hospitalization
rates declined for children and for adults of less than 50 years of age when comparing
the pre- and post-PCV10 periods, there was an increase in hospitalization rates for
individuals of 65 years or older (Fig 1). Annual rates of pneumonia and comparison
group hospitalizations by age-group are showed in Table 1.
10.1371/journal.pone.0184204.g001
Fig 1
Average annual pneumonia rates (per 100,000 population) of pneumonia hospitalizations
in the pre- and post-PCV10 vaccination periods, by age-groups. Brazil, 2005–2015.
10.1371/journal.pone.0184204.t001
Table 1
Annual rates (per 100,000 population) of pneumonia and comparison group hospitalizations,
by age-group. Brazil, 2005–2015.
Age-group
2005
2006
2007
2008
2009
2010
2011
2012
2013
2014
2015
Annual rates for pneumonia hospitalization
<12 months
4,335.5
4,489.8
4,378.4
4,260.6
4,741.2
4,170.8
4,067.9
3,864.2
3,879.8
3,589.7
3,433.0
12–23 months
3,043.4
3,151.4
3,098.6
2,933.3
3,159.4
2,959.5
2,568.5
2,435.2
2,389.1
2,284.2
2,175.1
2–4 years
1,120.1
1,168.8
1,182.8
1,106.1
1,219.1
1,161.6
1,066.00
973.7
955.5
904.0
834.5
5–9 years
346.7
370.3
347.4
339.2
389.3
348.5
302.8
281.4
291.3
263.7
231.7
10–17 years
119.5
127.2
119.2
110.0
146.6
122.4
109.5
99.6
100.1
86.5
71.8
18–39 years
122.2
118.7
111.8
105.8
134.9
113.8
101.9
93.3
93.6
82.9
69.3
40–49 years
176.3
174.3
162.3
160.2
189.0
171.9
157.4
147.5
145.3
128.5
114.5
50–64 years
289.2
287.4
277.6
281.1
322.5
315.4
306.1
290.1
294.6
270.7
256.0
≥ 65 years
1,065.8
1,087.0
1,094.9
1,099.7
1,252.2
1,299.2
1,350.6
1,255.8
1,312.2
1,294.2
1,323.5
Annual rates for comparison group hospitalization
<12 months
3,692.70
3,572.24
3,374.46
3,754.10
3,544.69
3,589.19
3,676.66
3,861.75
4,006.76
4,256.58
4,445.58
12–23 months
3,346.47
3,409.78
3,193.84
2,889.16
2,844.65
3,012.17
2,858.62
2,911.11
2,903.42
2,973.37
3,021.94
2–4 years
2,128.40
2,114.45
2,089.03
2,065.32
2,096.00
2,205.25
2,175.76
2,158.80
2,157.00
2,189.48
2,181.04
5–9 years
1,721.63
1,738.47
1,702.33
1,668.77
1,634.86
1,687.35
1,660.92
1,586.38
1,581.47
1,590.94
1,578.99
10–17 years
1,322.61
1,329.06
1,329.18
1,298.41
1,336.50
1,393.71
1,414.56
1,389.27
1,397.54
1,410.59
1,387.92
18–39 years
2,480.91
2,479.97
2,448.47
2,351.05
2,339.60
2,389.49
2,346.15
2,313.43
2,273.34
2,311.41
2,261.11
40–49 years
3,929.34
3,864.94
3,810.36
3,632.64
3,642.10
3,714.82
3,644.20
3,548.95
3,498.91
3,500.17
3,391.60
50–64 years
5,653.54
5,561.73
5,501.90
5,303.96
5,382.94
5,552.73
5,566.27
5,480.72
5,508.29
5,572.26
5,501.74
≥ 65 years
11,231.77
11,077.30
10,819.70
10,287.79
10,543.25
10,815.17
10,779.77
10,615.69
10,732.52
10,867.32
10,926.65
Time-series analyses
For the purpose of the time-series analysis, after excluding hospitalizations occurring
during the H1N1 influenza pandemic in Brazil (n = 4,229,226), a total of 74,498,466
hospitalizations were considered. Trends of observed (black lines) and predicted (red
lines) rates of pneumonia hospitalization, by age-group, for the entire study period
are presented in Fig 2. For almost all age-groups, but particularly for those aged
10 to 64 years, it is possible to visualize a peak of hospital admissions in 2009,
overlapping with the influenza pandemic months in Brazil (gray vertical bands). Fig
2 shows that in the post-vaccination period, observed rates of pneumonia hospitalizations
were lower than predicted rates for all age-groups which are shown with their 95%
confidence intervals, except for elderly (≥ 65 years). The differences between observed
and predicted rates increases significantly over time in all age groups, except for
those aged 65 years and older. The mean percentage error of each model of the pre-vaccination
period, which is a measure of model fitness, is presented in S2 Table.
10.1371/journal.pone.0184204.g002
Fig 2
Trends in observed (black lines), fit curve (red lines in the pre-vaccination period),
and predicted (red lines in the post-vaccination period) pneumonia hospitalization
monthly rates per 100,000 population by age-groups in Brazil.
Pre-vaccination period: 2005–2009; Transition period: 2010 (year of PCV10 introduction);
Post-vaccination period: 2011–2015. Routine infant PCV10 vaccination was introduced
through March to September 2010 by the National Immunization Program. The yellow bar
represents the transition period which was excluded from the time-series analysis.
Gray bar highlights the months excluded of the flu pandemic months (April-October
2009) from the model.
Trends of observed and predicted rates of comparison group hospitalizations are displayed
in S1 Fig. Of note, for the youngest age-group, rates are increasing in the post-vaccination
period.
Considering the whole post-vaccination period, a significant decrease in the estimated
percent of change in pneumonia hospitalization rates following PCV10 introduction
is demonstrated in all age groups up to 49 years of age, varying from 13.9% to 17.6%
in age-groups targeted by vaccination, and 16.8% to 20.9% in the 10–49 year age-group,
not targeted by vaccination (Table 2). A non-significant reduction was found for individuals
aged 50–64 years. PCV10 vaccination was not shown to decrease pneumonia hospitalization
rates in individuals aged 65 years and more; on the contrary, a significant increase
(16.6%, p<0.001) in rates was observed in the post-vaccination period compared to
the pneumonia predicted rates. After taking into consideration the percentage of change
in hospitalizations of the comparison group, the impact of vaccination, expressed
as a relative percentage difference, for the target population ranged from 17.4% to
26.5%. In individuals 10–49 years of age, not target for immunization, a significant
decrease in pneumonia hospitalizations was observed with impact ranging from 11.1%
to 27.1% (Table 2).
10.1371/journal.pone.0184204.t002
Table 2
Percentage change in rates for pneumonia hospitalization and comparison groups, and
relative percentage change (PCV10 impact) with respective confidence intervals, by
age-group.
Brazil, 2011–2015.
Age-group
% of change
95% CI
P-value
Pneumonia
<12 months
-13.9
-22.9; -4.9
0.017
12–23 months
-22.2
-30.7; -13.8
0.000
2–4 years
-17.6
-26.0; -9.3
0.000
5–9 years
-21.8
-30.2; -13.5
0.000
10–17 years
-20.9
-27.9; -14.0
0.000
18–39 years
-21.4
-27.0; -15.9
0.000
40–49 years
-16.8
-21.9; -11.7
0.000
50–64 years
-1.1
-5.5; 3.3
0.696
≥65 years
16.6
12.4; 20.8
0.000
Comparison group
<12 months
12.6
10.9; 14.2
0.000
12–23 months
-4.9
-7.4; -2.4
0.000
2–4 years
3.9
2.3; 5.4
0.000
5–9 years
-5.1
-6.8; -3.4
0.000
10–17 years
6.2
4.7; 7.7
0.000
18–39 years
-4.2
-5.8; -2.6
0.000
40–49 years
-5.7
-7.6; -3.8
0.000
50–64 years
1.8
0.2; 3.5
0.043
≥65 years
1.4
-0.3; 3.0
0.143
Relative percentage change
<12 months
-26.5
-35.5; -17.5
0.001
12–23 months
-17.4
-25.8; -8.9
0.006
2–4 years
-21.5
-29.8; -13.2
0.002
5–9 years
-16.8
-25.1; -8.4
0.006
10–17 years
-27.1
-34.1; -20.2
0.009
18–39 years
-17.3
-22.8; -11.7
0.006
40–49 years
-11.1
-16.2; -6.0
0.004
50–64 years
-3.0
-7.4; 1.5
0.730
≥65 years
15.2
11.0; 19.4
0.005
All analysis excluded data from influenza pandemic months (April-October 2009).
Vaccination impact, as measured by the relative percentage change, increased with
the accumulating number of years in the post-vaccination period (Fig 3). For those
under 40 years of age, vaccination impact was statistically significant from the very
first years of the post-vaccination period. For those aged 40–49, it was statistically
significant only from 2013.
10.1371/journal.pone.0184204.g003
Fig 3
Annual relative percentage change on pneumonia hospitalizations by age-group in the
post-vaccination period.
Brazil, 2011–2015.
Averted pneumonia hospitalization costs
Considering the predicted number of 3,700,325 pneumonia hospitalizations for the post
vaccination period, we estimated that a total of 462,940 pneumonia hospitalizations
were averted in Brazil for individuals aged less than 65 years (Table 3). The average
cost of pneumonia hospitalization varied by age-group and year, being lower in the
2-4y age-group and higher in adults and the elderly followed by children <12 months
of age. Average cost per case in all age-groups was BRL 812 (USD 430.5; $Int 552.6)
in 2011, BRL 854 (USD 427; $Int 553.9) in 2012, BRL 880 (USD 378; $Int 533.4) in 2013,
BRL 913 (USD 356.3; $Int 528) in 2014, and BRL 936 (USD 243.3; $Int 300.3) in 2015.
10.1371/journal.pone.0184204.t003
Table 3
Number of predicted, observed and averted cases, cost per case, and estimated averted
costs of hospitalized pneumonia following PCV10 introduction, by age-group.
Brazil, 2011–2015.
Year and age-group
Predicted number of cases
Predicted number of cases lower 95% CI
Predicted number of cases upper 95% CI
Observed number of cases
Averted number of cases
Cost per hospitalized pneumonia cases (Reais R$)
Total estimated averted costs of hospitalized pneumonia
R$
a
$Int
b
USD
c
2011
<12 months
116,396
107,676
125,117
108,405
7,991
881
7,042,468
4,790,795
3,732,508
12–23 months
80,641
75,524
85,758
67,987
12,654
724
9,156,434
6,228,867
4,852,910
2–4 years
94,759
88,508
101,010
87,784
6,975
695
4,845,533
3,296,281
2,568,132
5–9 years
51,803
48,478
55,128
44,873
6,930
702
4,867,632
3,311,314
2,579,845
10–17 years
32,383
30,602
34,165
30,089
2,294
758
1,738,852
1,182,893
921,592
18–39 years
79,827
76,268
83,386
72,780
7,047
796
5,610,821
3,816,885
2,973,735
40–49 years
42,058
40,181
43,936
39,939
2,119
880
1,864,932
1,268,661
988,414
50–64 years
73,280
69,865
76,696
78,606
-5,326
949
-67,649,950
-46,020,374
-35,854,473
≥ 65 years
161,803
154,571
169,035
195,594
-33,791
925
-31,256,675
-21,263,044
-16,566,038
Sub-total
732,950
691,672
774,229
726,057
6,893
-63,779,952
-43,387,723
-33,803,375
2012
<12 months
114,144
105,423
122,864
101,030
13,114
915
12,001,933
7,693,547
6,000,966
12–23 months
78,852
73,735
83,969
63,238
15,614
740
11,551,237
7,404,639
5,775,619
2–4 years
92,411
86,160
98,662
78,628
13,783
716
9,868,628
6,326,044
4,934,314
5–9 years
51,318
47,993
54,643
41,248
10,070
724
7,294,708
4,676,095
3,647,354
10–17 years
32,253
30,471
34,034
27,302
4,951
801
3,965,256
2,541,831
1,982,628
18–39 years
80,748
77,189
84,307
67,402
13,346
837
11,170,602
7,160,642
5,585,301
40–49 years
43,170
41,293
45,047
38,264
4,906
939
4,608,696
2,954,293
2,304,348
50–64 years
75,941
72,525
79,357
76,789
-848
1,008
-854,784
-547,938
-427,392
≥ 65 years
167,139
159,907
174,371
187,117
-19,978
1,005
-20,077,890
-12,870,442
-10,038,945
Sub-total
735,975
694,697
777,254
681,018
54,957
39,528,386
25,338,709
19,764,193
2013
<12 months
112,477
103,756
121,197
99,481
12,996
929
12,070,685
7,315,567
5,190,394
12–23 months
77,853
72,737
82,970
60,847
17,006
749
12,735,793
7,718,663
5,476,391
2–4 years
91,187
84,936
97,437
75,638
15,549
718
11,167,292
6,768,056
4,801,935
5–9 years
51,074
47,749
54,399
42,238
8,836
732
6,464,418
3,917,829
2,779,700
10–17 years
32,605
30,823
34,386
27,402
5,203
812
4,224,836
2,560,507
1,816,679
18–39 years
82,531
78,972
86,090
68,322
14,209
892
12,671,586
7,679,749
5,448,782
40–49 years
44,430
42,553
46,307
38,523
5,907
966
5,704,981
3,457,564
2,453,142
50–64 years
78,514
75,099
81,930
80,302
-1,788
1,069
-1,911,372
-1,158,407
-821,890
≥ 65 years
172,492
165,260
179,724
201,004
-28,512
1,055
-30,080,160
-18,230,400
-12,934,469
Sub-total
743,162
701,883
784,440
693,757
49,405
33,048,058
20,029,126
14,210,665
2014
<12 months
110,022
101,302
118,743
90,233
19,789
945
18,700,605
10,809,598
7,293,236
12–23 months
76,167
71,050
81,284
57,030
19,137
766
14,666,597
8,477,802
5,719,973
2–4 years
89,200
82,949
95,451
70,111
19,089
736
14,041,868
8,116,687
5,476,329
5–9 years
50,370
47,045
53,695
37,823
12,547
744
9,338,732
5,398,111
3,642,106
10–17 years
32,367
30,586
34,149
23,624
8,743
863
7,545,209
4,361,392
2,942,632
18–39 years
83,002
79,443
86,561
61,202
21,800
917
19,990,600
11,555,260
7,796,334
40–49 years
45,132
43,255
47,009
34,775
10,357
1,013
10,491,641
6,064,532
4,091,740
50–64 years
80,375
76,960
83,791
75,911
4,464
1,131
5,048,784
2,918,372
1,969,026
≥ 65 years
176,215
168,983
183,447
203,667
-27,452
1,106
-30,361,912
-17,550,238
-11,841,146
Sub-total
742,851
701,572
784,130
654,376
88,475
69,462,124
40,151,517
27,090,228
2015
<12 months
107,763
99,042
116,483
84,563
23,200
948
21,993,600
11,761,283
5,718,336
12–23 months
74,575
69,458
79,692
53,218
21,357
773
16,508,961
8,828,321
4,292,330
2–4 years
87,309
81,058
93,559
63,390
23,919
743
17,771,817
9,503,645
4,620,672
5–9 years
49,762
46,437
53,088
32,858
16,904
778
13,151,312
7,032,787
3,419,341
10–17 years
32,255
30,474
34,037
19,585
12,670
902
11,428,340
6,111,412
2,971,368
18–39 years
83,839
80,280
87,398
51,707
32,132
983
31,585,756
16,890,779
8,212,297
40–49 years
46,049
44,172
47,926
31,629
14,420
1,065
15,357,300
8,212,460
3,992,898
50–64 years
82,689
79,273
86,105
73,815
8,874
1,139
10,107,486
5,405,073
2,627,946
≥ 65 years
181,146
173,914
188,378
213,812
-32,666
1,089
-35,573,274
-19,023,141
-9,249,051
Sub-total
745,387
704,109
786,666
624,577
120,810
102,331,298
54,722,619
26,606,137
a Brazilian Reais.
b International dollars.
c USD dollar.
When these values were multiplied by the total number of pneumonia hospitalizations
averted by age-group, the total averted costs of hospitalized pneumonia cases in children
targeted by vaccination (<5 years) was approximately BRL 194.1 million (USD 91.9 million,
Int$ 115 million) for the 5 years period after PCV10 introduction (2011–2015). Among
age-groups in which PCV10 resulted in decreased pneumonia hospitalizations (0–49 years),
the total averted costs of hospitalized pneumonia was BRL 383.2 million (USD 147 million,
Int$ 225.2 million) for the period. Roughly half of these averted costs (50.1%) incurred
in children targeted by vaccination (<5 years). Interestingly, we observed averted
costs hospitalized pneumonia in all age-groups till 49 years of age in all the years
analyzed, but only in 2014 and 2015 a significant number of pneumonia cases averted
were observed in the 50–64 age-group. In all the study period, the costs of hospitalized
pneumonia cases increased in the ≥65 year age-group, as a result of an increase in
number of observed cases (Table 3). The overall averted costs for individuals less
than 50 years of age considering the 2011–2015 period was BRL 383,199,661 (USD 147,004,281;
$Int 225,194,791) (S3 Table).
Discussion
In this study, we report relevant direct and indirect impact of PCV10 vaccination
on pneumonia hospitalization in Brazil. Both impacts were observed since the first
year of the post-vaccination period and increased over time. The indirect impact is
reported up to the 40–49 years of age-group. Reductions on hospitalizations were also
found to translate into significant reductions of the economic burden due to the disease.
We observed a significant burden of pneumonia hospitalizations in all age-groups in
Brazil througout the study period, comparable to the rates reported in the US prior
to PCV7 introduction [11]. Differently from the US, where the greatest pneumonia burden
is represented by the age-group of elderly individuals aged 65 years and over, we
found the greatest burden in children aged <12 months, with rates almost four times
higher than those observed in children of 2–4 years. This finding underscores the
importance of preventive interventions against pneumonia in the first years of life.
The range of the direct impact of PCV10 in hospitalization rates for pneumonia in
the cohort of children under two years of age (17.4–26.5%) is similar, albeit slightly
lower, to that previously reported in 3 large urban centers in Brazil (23–29%) in
the first year after PCV10 introduction [18]. This may be due to a combination of
various issues. This previous study had probably better quality of data, as the three
urban centers were chosen for this very purpose, and there were also methodological
variations, such as the exclusion of duplicate records, among others. Our direct impact
estimates are similar to those presented by an active population-based surveillance
on pneumonia hospitalization conducted in one city of the Mid-Western region in Brazil,
which reports reductions of 12.6% and 14.2% in pneumonia hospitalizations for children
aged 2–11 months and 12–23 months, respectively, 3 years after vaccine introduction
[37].
In addition to direct effects, our study demonstrates significant indirect effects
in the population up to 40–49 years of age group. Bruhn et al. [26], which applied
a different time-series methodology to Brazilian hospitalization data up to 2013,
also report indirect effects of slightly lower magnitude when compared to ours, up
to the age group of 18–39 years of age. In another study in the US, indirect impact
was also observed in individuals aged 18–39 years old, but only four years after PCV7
introduction [38]. We believe that the fact that in Brazil the indirect effects were
observed from the first years of the post-vaccination period and had an increasing
magnitude over the study years may be due to the high PCV10 vaccination coverage attained
very quickly throughout the country after vaccination start in Brazil. This contrasts
to the relatively low coverage of the first years since PCV7 vaccination started in
the US [39].
Differently from what was observed by Griffin et al in US [12], where the indirect
effect of PCV7 was found to extend to individuals in the older age groups, we observed
increasing trends of pneumonia hospitalizations in elderly individuals aged 65 years
and older (15.2%). These increasing rates may represent true increase in disease burden
in this age group or may be an artifact due to unmeasured changes in diagnostic and/or
coding practices or due to other sources of bias that we were unable to prevent with
our methodology.
Similar increases in pneumonia hospitalization rates of elderly individuals were also
observed in Scotland as reported by Nair and colleagues six year after PCV7 and PCV13
introduction (2+1 schedule) [40]. In this Scottish study, hospitalizations due to
all-cause pneumonia increased from 46%-63% in individuals aged ≥75 years. In Australia,
Menzies et al also described no significant changes in hospitalizations in adults
above 65 years, six years following the introduction of PCV 7 and PCV13 [41]. In our
study, the observed increase in pneumonia hospitalizations in this age-group started
long before PCV10 introduction, and vaccine introduction was not able to alter this
trend. These findings align with those from previous studies conducted in US which,
after 4 years of PCV7 introduction, found no trend reduction in all-cause pneumonia
hospitalization rates of individuals 65 years or more [42].
Most studies on the indirect impact of PCV on pneumonia are from countries in which
a 3+1 schedule was used. This is also the schedule adopted in Brazil [14]. Evidence
of the indirect impact of PCV on pneumonia in countries where 2+1 and 3+0 schedules
are used is still lacking. In Uruguay, a study evaluating children under 15 years
of age failed to demonstrate the presence of any indirect effect in this age-group,
five years after PCV7/PCV13 introduction [43].
The observed economic impact of PCV10 on averted direct costs associated to hospitalized
pneumonia is a very important finding. The economic impact following vaccine introduction
is perceived by various stakeholders to be of great value in aiding decision-making
[44]. Most economic evaluation studies of vaccine introduction are done prior to vaccine
introduction. By aggregating an assessment of economic burden to a time-series modeling
of vaccine impact, we have estimated the averted costs of all hospitalizations occurring
in SUS in Brazil. As innovative analyses of historical observational datasets have
been recently recommended as a means to assess the economic impact of vaccination
[45], we believe our methods are valuable to assess the post-introduction impact using
observed data, and as such provide more robust evidence than models whose assumptions
are not driven by data.
Significant costs were averted as a result of PCV introduction in Brazil. In the age
groups targeted by the vaccine (0–5 years) a total of BRL 194.1 million (USD 91.9
million, Int$ 115 million) was averted in the post-vaccination period. A similar amount
was averted in the age groups of those non-targeted by the vaccine (5–49 years), of
BRL 189.1 million (USD 70.5 million, Int$ 110.2 million).
Even without having shown indirect impact in the older age groups, which do represent
a significant proportion of the burden of pneumonia in the country, we identified
a reduction in costs of hospitalized pneumonia in the 50–64 year age-group, which
seems to be more important in 2014. However, for the older age group of individuals
65 years and older, the increase in pneumonia hospitalizations led to an increase
in costs of approximatelly BRL 147.4 million (USD 60.6 million; Int$ 88.9 million)
in the 5 year period after PCV10 introduction.
There is strong evidence of temporal association between respiratory infections caused
by many viral agents and episodes of bacterial pneumonia in the elderly. Studies show
that pneumonia is caused by many viral and bacterial infections other than pneumococci
serotypes included in PCV10 [46]. It is important to mention that, the population
>60 years of age in Brazil has been the target of annual vaccination campaigns against
influenza virus for about two decades, with stable vaccination coverage of 85% [16].
This implies that pneumonia hospitalizations in the elderly seem to have increased
in recent years in Brazil, despite the high rates of PCV10 vaccination in infants
and of the influenza vaccination, which target this population. Little is known about
the distribution of viral and bacterial aetiologies causing community acquired pneumonia
in the elderly in Brazil. There is also scarce data on which serotypes are responsible
for the pneumococcal pneumonias. However, there seems to be an indication that, differently
from children, in which the majority of serotypes causing IPD are covered by PCV10,
there is a greater diversity in serotypes causing IPD in adults with 50 years and
more [47]. As a result, PCV10 vaccination of children may not be affecting at least
a proportion of the serotypes causing pneumonia in the elderly. It could be that there
is one or more combining reasons for the increase of pneumonia in the elderly, or
even just aging of the population.
Our study has some limitations, which should be addressed. Since we used a secondary
source of data, which has been originally developed for administrative purposes, the
possibility of misdiagnosis of the cause of hospitalization recorded cannot be ruled
out. However, a recent study found good agreement between the diagnoses of pneumonia
as registered in SIH and those detected by primary data collected though active hospital
surveillance [48]. As we used the SIH database without personal identifier, the identification
and exclusion of duplicate records could not be performed. Thus, it is possible that
the number of hospitalizations may be overestimated as some hospitalization records
may represent the same episode of disease in the same patient, registered more than
one time. However, we do not believe that this would impact our analyses, as previous
studies have demonstrated that the distribution of duplicate records in SIH is randomly
distributed in both the pre- and post-vaccination periods [18]. Also, as SIH is the
information system for hospitalizations in SUS only, hospitalizations occurring in
the supplementary and private healthcare systems were not considered. We do not think
that the exclusive use of SIH data reduces the validity of the study, since this database
covers all publicly funded hospitalizations in Brazil, and its coverage remained stable
throughout the study period [20]. Regarding the averted pneumonia costs, our estimates
are conservative as we consider SUS reimbursement costs in the base case, which are
significantly lower than costs of pneumonia hospitalization for children in Brazil
as reported in the literature [7,49,50]. Studies from the private healthcare sector
in Brazil have estimated the costs of pneumonia hospitalization to be 10 times higher
than the costs considered in our analysis [51].
Conclusions
Vaccination with PCV10 five year after its introduction in Brazil was associated with
a relevant reduction in all-cause pneumonia hospitalizations and related costs in
the target age-groups for vaccination and in unvaccinated individuals aged up to the
age-group of 40–49 years, indicating the indirect impact provided by vaccination.
Further studies are needed to identify factors associated with the increase in trends
of pneumonia hospitalizations in the elderly, considered a matter of concern for public
health decision-makers given the rapid aging of the Brazilian population.
Supporting information
S1 Dataset
The dataset generated / analyzed during the current study.
(XLSX)
Click here for additional data file.
S1 File
ICD10 codes for comparison groups according to age-groups.
(DOCX)
Click here for additional data file.
S2 File
R modeling scripts.
(DOCX)
Click here for additional data file.
S1 Fig
Trends in observed (black lines), fit curve (red lines in the pre-vaccination period),
and predicted (red lines in the post-vaccination period) hospitalization monthly rates
per 100,000 population for the comparison group by age-groups in Brazil.
Pre-vaccination period: 2005–2009; Transition period (year of PCV10 introduction):
2010; Post-vaccination period: 2011–2015. Routine infant PCV10 vaccination was introduced
through March to September 2010 by the National Immunization Program. The yellow bar
represents the transition period which was excluded from the analysis. Gray bar highlights
the months excluded of the flu pandemic months (April-October 2009) from the model.
(TIF)
Click here for additional data file.
S1 Table
Annual number for pneumonia and comparison group hospitalization, and mid-year population
estimates by age-group.
Brazil, 2005–2015.
(DOCX)
Click here for additional data file.
S2 Table
Mean percentage error of fitting models of time-series analyses for pneumonia and
comparison group hospitalizations rates by age-group.
(DOCX)
Click here for additional data file.
S3 Table
Number of predicted, observed and averted cases, cost per case, and estimated averted
costs of hospitalized pneumonia following PCV10 introduction, by age-group.
Brazil, 2011–2015.
(DOCX)
Click here for additional data file.