Mortality Associated with Influenza in Tropics, State of São Paulo, Brazil, from 2002 to 2011: The Pre-Pandemic, Pandemic, and Post-Pandemic Periods

Hindawi Publishing CorporationInfluenza Research and TreatmentVolume 2013 Article ID 696274 9 pageshttpdxdoiorg1011552013696274

Research ArticleMortality Associated with Influenza in Tropics State ofSatildeo Paulo Brazil from 2002 to 2011 The Pre-PandemicPandemic and Post-Pandemic Periods

Andreacute Ricardo Ribas Freitas123 Priscila M S Bergamo Francisco1

and Maria Rita Donalisio1

1 Epidemiology Department of Public Health Faculty of Medical Sciences State University of Campinas (UNICAMP)126 Tessalia Vieira de Camargo 13083889 Campinas SP Brazil

2 Sao Leopoldo Mandic Medical College Campinas SP Brazil3 Campinas Department of Public Health Campinas SP Brazil

Correspondence should be addressed to Andre Ricardo Ribas Freitas arrfreitas2010gmailcom

Received 31 December 2012 Revised 15 April 2013 Accepted 21 April 2013

Academic Editor Zichria Zakay-Rones

Copyright copy 2013 Andre Ricardo Ribas Freitas et al This is an open access article distributed under the Creative CommonsAttribution License which permits unrestricted use distribution and reproduction in any medium provided the original work isproperly cited

The impact of the seasonal influenza and 2009 AH1N1 pandemic influenza on mortality is not yet completely understoodparticularly in tropical and subtropical countriesThe trends of influenza related mortality rate in different age groups and differentoutcomes on a area in tropical and subtropical climate with more than 41 million people (State of Sao Paulo Brazil) were studiedfrom 2002 to 2011 were studied Serfling-type regression analysis was performed using weekly mortality registries and virologicaldata obtained from sentinel surveillance The prepandemic years presented a well-defined seasonality during winter and a clearrelationship between activity of AH3N2 and increase of mortality in all ages especially in individuals older than 60 years Themortality due to pneumonia and influenza and respiratory causes associated with 2009 pandemic influenza in the age groups 0ndash4years and older than 60 was lower than the previous years Among people aged 5ndash19 and 20ndash59 years the mortality was 26 and 44times higher than that in previous periods respectively The mortality in all ages was higher than the average of the previous yearsbut was equal mortality in epidemics of AH3N2 The 2009 pandemic influenza mortality showed significant differences comparedto other years especially considering the age groups most affected

1 Introduction

Influenza is a significant cause of mortality in temperatecountries [1ndash3]There are still many questions concerning theimpact of influenza on mortality in the tropics [4ndash6] Thereis also a lot of controversy regarding the quantitative aspectsof mortality associated with the 2009 AH1N1 pandemic Itis observed differing severity of disease in many region asshown by studies conducted in Mexico France USA andother countries using different methodologies [7ndash11]

The direct measurement of influenza-related mortalityis difficult for several reasons [12] It is a disease with verynonspecific early symptoms moreover physicians often donot collect specimens for diagnostic confirmation In addi-tion the time period between onset of symptoms and

hospitalization is often too large and does not allow a con-clusive diagnosis Another reason is that many patients diefrom bacterial complications or from decompensation ofpreexisting conditions leading to confusion in defining theunderlying cause For these reasons the basic cause in thedeath certificate is rarely influenza although it has been theroot cause of the events that led the patient to death [12 13]

Despite facing these difficulties the mortality associatedwith influenza and pneumonia have been analyzed as amarker of viral circulation Some studies employ statisticalmodels to the time series of others outcomes such as respira-tory disease cardiorespiratory and all causes of death [12ndash14]

The impact of influenza on mortality is underestimatedeven during pandemics when there is an effort to in-crease influenza tests and confirm diagnosis The study of

2 Influenza Research and Treatment

pneumonia and influenza mortality by age is key to analyzethe total burden of disease and to compare with otherinfluenza seasons and with other regions Understanding thebehavior of past pandemics and epidemics of influenza iscritical for setting public health priorities for the coming sea-sonal and pandemic influenza

The aim of this study is to evaluate the influenza-associated mortality in the State of Sao Paulo Brazil from2002 to 2011 The choice of this period was due to the avail-ability of systematic virological surveillance data allowingvalidate data on mortality associated with influenza withinformation about the antigenic characteristics and levels ofviral activity

2 Material and Methods

21 Locality Sao Paulo is the most populate state in Brazil(over 41 million inhabitants in 2010 Census) with a GDPof US $1500000 per capita and a Human DevelopmentIndex of 0833 (United Nations Development Programme)also with good health care services and epidemiological sur-veillance [15] It is located between latitudes 19∘4610158404510158401015840S and25∘

181015840

4310158401015840SDespite being in the region of predominantly tro-

pical and subtropical climate the study region has clearlydefined seasons of increased circulation of influenza viruses[16]

22 Mortality and Population Mortality data were obtainedfrom Health Statistics System (DATASUS) Mortality Infor-mation System which covers 100 of the State of Sao Paulosince 1979 [17] Causes of death are classified using theInternational Cause of Death ICD-10 codes for pneumoniaand influenza (ICD J 10 to J189) respiratory causes (ICD J00to J99) and all-cause mortality (excluding external causes ofmortality) The mortality rates were calculated in three agegroups 0 to 4 5 to 19 20 to 59 and more than 60 years

Population data were obtained from the Brazilian Insti-tute of Geography and Statistics (IBGE) using data from the2010 Census [17] The weekly estimates were obtained byinterpolation

23 Virological Data Data on influenza virus activity inSoutheastern Brazil were obtained from the Ministry ofHealth through the Information System of EpidemiologicalSurveillance of Influenza Department of Health Surveillance(SIVEP-Gripe) [18] This system monitors the occurrenceof influenza through sentinel units which investigate theetiology of respiratory viruses causing flu-like syndromesNational Reference Laboratories test the samples by indi-rect immunofluorescence for a panel of respiratory viruses(including influenza A and B parainfluenza 1 2 and 3respiratory syncytial virus and adenovirus) and forwardsamples for culture of virus and real-time RT-PCR As theviral subtypes are not provided by SIVEP data are obtainedfrom various official sources [18ndash22]

24 Deaths due to Laboratory-Confirmed Pandemic InfluenzaIn the beginning of the pandemic the criterion to confirm theinfluenza cases was as follows any patient who had flu-like

illness (defined as fever cough or sore throat) and historyof traveling to countries with occurrence of cases or con-tacting with infected person After the initial phase diffusetransmission was confirmed in epidemiological week 28 Atthis time the registration of cases was as follows patientswith severe acute respiratory infections (SARI) that is thedefinition of SARI included fever cough and dyspnea ordeath All patients reported by theNational Systemof Surveil-lance Reportable Disease (SINAN) had respiratory secretionsamples collected for performing real-time RT-PCR in theNational Reference Laboratories Data on deaths confirminginfluenza pandemic were extracted from SINAN by age

25 Statistical Analysis The estimation of influenza-asso-ciated mortality was obtained through the classic methodSerfling with adaptation to weekly data [23] To fit regressionwe used the total period of 10 years excluding the weeks ofgreater viral circulation by laboratory criteria

We defined the onset of periods of increased activity ofthe influenza virus by virological criteria in the Braziliansoutheast (where State of Sao Paulo is located) when therewas the occurrence of two consecutive weeks in which wasconfirmed by indirect immunofluorescence more than twiceof the annual average of cases We defined that this periodends with the occurrence of two consecutive weeks with viraldiagnostic below the annual average The period of highestviral activity in 2009 began at the time the Brazilian Ministryof Health [15] officially declared epidemiological situation asldquowidespread viral transmissionrdquo until the official end of thepandemic was reported by WHO [24]

A cyclical linear regression was constructed as follow

119884 = 1205730+ 1205731lowast 119905 + 120573

2lowast 1199052

+ 1205733lowast 1199053

+ 1205734lowast sin(2 lowast 120587 lowast 119905

5217)

+ 1205735lowast cos(2 lowast 120587 lowast 119905

5217) + 1198901

(1)

where 119884 is the mortality rate 120573 is the coefficients of regres-sion 119905 is time inweeks and 1199052 and 1199053 are variables for adjustingthe secular trend of the disease

After adjusting stepwise linear regression the baseline ofexpected mortality in the absence of influenza was definedUsing this reference influenza epidemic periods were demar-cated as the periods in which mortality from pneumonia andinfluenza was above 95 confidence interval predicted bythe model for two consecutive weeks these periods endedwhen mortality was less than the upper confidence intervalfor two consecutive weeks Weekly excess mortality rate wasestimated by the difference between the observed and pre-dicted mortality rates by the model during influenza epi-demic periods Season mortality rate was calculated as thesum of weekly excess mortality rate during the year

The data were analyzed using the statistical programSPSS for Windows version 130 graphics and data compi-lation were made using the Microsoft Office Excel 2007 Alldatabases analyzed were not able to do any kind of patientidentification to preserve patientsrsquo privacy

Influenza Research and Treatment 3

002040608

112

Jan-

02

Jul-0

2

Jan-

03

Jul-0

3

Jan-

04

Jul-0

4

Jan-

05

Jul-0

5

Jan-

06

Jul-0

6

Jan-

07

Jul-0

7

Jan-

08

Jul-0

8

Jan-

09

Jul-0

9

Jan-

10

Jul-1

0

Jan-

11

Jul-1

1

Jan-

02

Jul-0

2

Jan-

03

Jul-0

3

Jan-

04

Jul-0

4

Jan-

05

Jul-0

5

Jan-

06

Jul-0

6

Jan-

07

Jul-0

7

Jan-

08

Jul-0

8

Jan-

09

Jul-0

9

Jan-

10

Jul-1

0

Jan-

11

Jul-1

1

Jan-

02

Jul-0

2

Jan-

03

Jul-0

3

Jan-

04

Jul-0

4

Jan-

05

Jul-0

5

Jan-

06

Jul-0

6

Jan-

07

Jul-0

7

Jan-

08

Jul-0

8

Jan-

09

Jul-0

9

Jan-

10

Jul-1

0

Jan-

11

Jul-1

1

Jan-

02

Jul-0

2

Jan-

03

Jul-0

3

Jan-

04

Jul-0

4

Jan-

05

Jul-0

5

Jan-

06

Jul-0

6

Jan-

07

Jul-0

7

Jan-

08

Jul-0

8

Jan-

09

Jul-0

9

Jan-

10

Jul-1

0

Jan-

11

Jul-1

1

Mor

talit

y rat

e per

100

000

0 to 4 years

0

01

Mor

talit

y rat

e per

100

000

5 to 19 years

01

03

05

Mor

talit

y rat

e per

100

000

20 to 59 years

3

5

7

9

Mor

talit

y rat

e per

100

000

More than 60 years

Figure 1 Mortality due to pneumonia and influenza (rate per 100000) Weekly pneumonia and influenza mortality rate per 100000inhabitants by age group Sao Paulo Brazil January 2002 to December 2011 (Dark blue line observed rate light blue line baseline mortalityrate predict by model red line upper limit of confidence interval)

3 Results

31 Viral Activity and Excess Mortality due Pneumonia andInfluenza The weekly mortality due pneumonia and influ-enza respiratory causes and all causes showed a seasonalpattern with increased mortality during winter in the South-ern hemisphere (Figures 1 2 and 3) There was concurrencybetween periods of viral activity increased and excessmortal-ity peaks in 8 of the 10 years under study

In the pre-pandemic period the years of highestmortalityamong individuals over 60 years (2006 and 2007) showedhigh proportion of specimens positive for influenza withpredominance of the AH3N2 virus (Tables 1 and 2)

Still considering the pre-pandemic period the years oflower mortality from pneumonia and influenza in all age

groups presented low viral activity (2005) and prevalence ofAH1N1 virus (2008) known to be less lethal

The first laboratory-confirmed imported cases of influ-enza AH1N1 pdm 2009 were detected in Brazil in early MayOn July 16th epidemiological week (EW) 28th BrazilianHealth Ministry [15] officially recognized the occurrence ofcases due to autochthonous widespread transmission Fromearly July EW 26th there seems to be evidence of excessmortality due to pneumonia and influenza among individualsof 20 to 59 years of ageDuringweeks EW28th to 47th in 2009(late November) we found the vast majority of deaths relatedto the pandemic first wave mainly in age groups 5 to 19 and20 to 59 years

Along the first half of 2010 there was a predominance of2009AH1N1 pdmwhile the secondAH3N2 variantwasmore


002040608

112

Jan-

02

Jan-

03

Jul-0

3

Jan-

04

Jul-0

4

Jan-

05

Jul-0

5

Jan-

06

Jul-0

6

Jan-

07

Jul-0

7

Jan-

08

Jul-0

8

Jan-

09

Jul-0

9

Jan-

10

Jul-1

0

Jan-

11

Jul-1

1

Jan-

02

Jan-

03

Jul-0

3

Jan-

04

Jul-0

4

Jan-

05

Jul-0

5

Jan-

06

Jul-0

6

Jan-

07

Jul-0

7

Jan-

08

Jul-0

8

Jan-

09

Jul-0

9

Jan-

10

Jul-1

0

Jan-

11

Jul-1

1

Jan-

02

Jan-

03

Jul-0

3

Jan-

04

Jul-0

4

Jan-

05

Jul-0

5

Jan-

06

Jul-0

6

Jan-

07

Jul-0

7

Jan-

08

Jul-0

8

Jan-

09

Jul-0

9

Jan-

10

Jul-1

0

Jan-

11

Jul-1

1

Jan-

02

Jul-0

2Ju

l-02

Jul-0

2Ju

l-02

Jan-

03

Jul-0

3

Jan-

04

Jul-0

4

Jan-

05

Jul-0

5

Jan-

06

Jul-0

6

Jan-

07

Jul-0

7

Jan-

08

Jul-0

8

Jan-

09

Jul-0

9

Jan-

10

Jul-1

0

Jan-

11

Jul-1

1

Mor

talit

y rat

e per

100

000

0 to 4 years

0

01

02

Mor

talit

y rat

e per

100

000

5 to 19 years

025

045

085

065

Mor

talit

y rat

e per

100

000

20 to 59 years

5

10

15

20

Mor

talit

y rat

e per

100

000

More than 60 years

Figure 2 Mortality due respiratory causes (rate per 100000) Weekly respiratory mortality rate per 100000 inhabitants by age group SaoPaulo Brazil January 2002 to December 2011 (Dark blue line observed rate light blue line baseline mortality rate predict by model redline upper limit of confidence interval)

prevalent [19] In 2010 the excess mortality from pneumoniaand influenza in the age group 0 to 4 and 5 to 19 years wasrespectively 06 and 02 per 100000 in both cases below theaverage of previous years In the age group 20 to 59 years itwas 11 per 100000 slightly above the average for seasonalinfluenza epidemics (09 per 100000) but well below mor-tality observed in 2009 (28 per 100000) Mortality in over60 years was 170 per 100000 a level slightly below the aver-age of influenza epidemic years

That is in 2010 the overall excess mortality from pneu-monia and influenza presented a pattern more like a year ofseasonal influenza epidemics with higher mortality amongthe elderly and sparing ages between 5 and 59 years some-thing very different from the pandemic periodThis situationmay have been influenced by the wide dissemination ofthe virus in 2009 with naturally induced immunization

extensive vaccination campaign conducted in early 2010against pandemic influenza and atypical intense circulationof the virus AH3N2 in the second half of 2010 This atypicalmovement of AH3N2 remained throughout spring of 2010and early summer of 2011 and may have been a consequenceof disturbances in herd immunity caused by the pandemic

In early 2011 there was a wave of excess mortality due topneumonia and influenza in EW 4th and 6th (January andFebruary) probably related to atypical activity of AH3N2The alternative hypothesis to explain this peak which is theactivity of respiratory syncytial virus activity seems unlikelybecause the higher prevalence of this virus was in EW13th that year (SIVEP GRIPE) The pattern of mortalityfrom pneumonia and influenza in 2011 was similar to yearsof seasonal H3N2 influenza epidemics with high mortalityamong the elderly above normal


Table 1 Annual excess mortality rate per 100000 inhabitants by age group in prepandemic pandemic and postpandemic periods State ofSao Paulo Brazil 2002 to 2011

1ndash4 years(95 CI)



60 and more years(95 CI)

All ages(95 CI)

2002Pneumonia and influenza 20 (15ndash25) 03 (12ndash04) 07 (06ndash09) 168 (126ndash210) 22 (19ndash27)

Respiratory causes 27 (20ndash34) 04 (03ndash05) 13 (99ndash16) 270 (210ndash330) 35 (76ndash43)All causes 55 (38ndash72) 12 (08ndash16) 63 (48ndash77) 891 (611ndash1170) 122 (87ndash157)



















Average of epidemicsH3N2 (2006-2007) years(a)

Pneumonia and influenza 15 02 09 222 28Respiratory causes 23 04 15 307 40

All causes 78 16 55 994 136

Average 2002 to 2008years (b)


All causes 72 10 46 751 104

Rate ratio (2009a)Pneumonia and influenza 06 26 32 06 12

Respiratory causes 09 23 26 07 12All causes 13 08 15 06 09

Rate ratio (2009b)Pneumonia and influenza 05 26 44 09 17



4

5

6

7

8

Jan-

02

Jan-

03

Jul-0

3

Jan-

04

Jul-0

4

Jan-

05

Jul-0

5

Jan-

06

Jul-0

6

Jan-

07

Jul-0

7

Jan-

08

Jul-0

8

Jan-

09

Jul-0

9

Jan-

10

Jul-1

0

Jan-

11

Jul-1

1

Jan-

02

Jan-

03

Jul-0

3

Jan-

04

Jul-0

4

Jan-

05

Jul-0

5

Jan-

06

Jul-0

6

Jan-

07

Jul-0

7

Jan-

08

Jul-0

8

Jan-

09

Jul-0

9

Jan-

10

Jul-1

0

Jan-

11

Jul-1

1

Jan-

02

Jan-

03

Jul-0

3

Jan-

04

Jul-0

4

Jan-

05

Jul-0

5

Jan-

06

Jul-0

6

Jan-

07

Jul-0

7

Jan-

08

Jul-0

8

Jan-

09

Jul-0

9

Jan-

10

Jul-1

0

Jan-

11

Jul-1

1

Jan-

02

Jul-0

2Ju

l-02

Jul-0

2Ju

l-02

Jan-

03

Jul-0

3

Jan-

04

Jul-0

4

Jan-

05

Jul-0

5

Jan-

06

Jul-0

6

Jan-

07

Jul-0

7

Jan-

08

Jul-0

8

Jan-

09

Jul-0

9

Jan-

10

Jul-1

0

Jan-

11

Jul-1

1

Mor

talit

y rat

e per

100

000

0 to 4 years

03

02

07

06

05

04

Mor

talit

y rat

e per

100

000

5 to 19 years

42

62

52

Mor

talit

y rat

e per

100

000

20 to 59 years

50

70

90

110

Mor

talit

y rat

e per

100

000

More than 60 years

Figure 3 Mortality due to all causes (rate per 100000) Weekly all causes mortality rate per 100000 inhabitants by age group Sao PauloBrazil January 2002 to December 2011 (Dark blue line observed rate light blue line baseline mortality rate predict by model red lineupper limit of confidence interval)

In 2011 the seasonality seems to have returned to normalsince 86 of positive samples for influenza were obtained inEW 20th to 32th in the Southeast similar to the standardpattern before the pandemic

Data from official surveillance for SARI confirmed anexcess of mortality like more than half of the estimated casesof deaths in 2009 (54)The sensitivity for diagnosis appearsto have been greater in younger age groups (Table 3) On theother hand the age group with the highest underreportingwas the over 60 years (3) This may be due to the higherincidence of severe pneumonia in the elderly as a complica-tion of chronic diseases confusing the diagnosis Moreoverin young patients viral pneumonia were more severe andclinically distinct from bacterial pneumonia which is oftenthe cause of complications in patients older than 60 years

4 Discussion

In the study period we identified pneumonia and influenzaexcess mortality simultaneously with the increase in viral cir-culationThere was a clear relationship between the intensityof the circulation of influenza virus known to be pathogenic(AH3N2) and occurrence of mortality from pneumonia andinfluenza particularly in over 60 years group

The excessmortality due to pneumonia and influenza andother outcomes in 2009 was below the average of previousinfluenza seasons (2002 to 2008) in the age groups 0 to 4and over 60 years In the groups 5 to 19 and 20 to 59 yearsduring 2009 the pneumonia and influenza excess mortalitywas respectively 26 and 44 times the average of the previousperiods In all age groups mortality was higher than thosethe average of the previous period (2002 to 2008) and equal


Table 2 Influenza virus identified by year positivity of specimens by season State of Sao Paulo 2002ndash2011

Year Virus probably predominant Positive specimens average in season6 Total number of specimens20021 B (58) AH3N2 e AH1N1 (20 each) 99 89220031 AH3N2 (606) H1N1 (27) 118 136520042 AH3N2 (67) influenza B (20) 90 215920051 H3N2 (656) B (24) e H1N1 (114) 49 161220063 AH3N2 104 213520073 AH3N2 85 484020084 AH1N1 e B 66 630320094 AH1N1 e AH1N1 pdm 2009 78 1703lowast

20105 AH1N1 pdm2009 = 1st mid AH3N2 = 2nd mid 48 2205lowast

20115 AH3N2 e AH1N1 pdm2009 35 27951FluNet (WHO data referring to South America) [22]2Guia de vigilancia epidemiologica Ministerio da Saude Secretaria de Vigilancia em Saude 6 ed Brasılia 2005 [28]3Boletim da Saude 2009 (State Board of Health Rio Grande do Sul) [29]4Boletim Epidemiologico 2011 (State Board of Health Rio Grande do Sul) [30]5Site httpaispahoorgphipvized fluasp [19]6SIVEP GRIPE-(Brazilian Ministry of Health) [31]lowastDuring the pandemic there was a commitment in the collection of samples for surveillance of flu-like syndromes

Table 3 Deaths by laboratoryndashconfirmed 2009 pandemics and estimates from statics models State of Sao Paulo 2002ndash2011

Laboratory-confirmed Laboratory-confirmedestimate

deaths due torespiratory causes ()

2009 Pandemics excess mortalityrate100000 (95 CI)

H3N2 epidemics excess mortalityrate100000 (2006-2007) (95 CI)

Mortality(rate100000) Deaths Deaths (P amp I) Respiratory causes Deaths (P amp I) Respiratory causes

0ndash4 years 14 40 73 25 (15ndash35) 55 (36ndash75) 44 (33ndash55) 65 (48ndash82)5ndash19 years 06 57 70 58 (49ndash67) 81 (66ndash96) 22 (18ndash27) 35 (28ndash42)20ndash59 years 18 418 46 659 (577ndash741) 907 (792ndash1023) 207 (165ndash249) 343 (280ndash407)60+ 07 33 3 425 (318ndash532) 976 (678ndash1274) 962 (814ndash1111) 1351 (1151ndash1550)All ages 14 1098 54 1172 (962ndash1382) 2032 (1581ndash2483) 1117 (927ndash1307) 1627 (1362ndash1892)Proportion ofexcess deathamong gt60years

6 36 48 86 83

mortality in epidemics of AH3N2 (2006 to 2007) althoughthe age groupsmost affectedwere different (Table 3)The totalnumber of influenza-related deaths in 2009 was higher thanthe average of previous years but was lower than in yearsof seasonal H3N2 influenza epidemics During epidemicsof AH3N2 86 of deaths from pneumonia and influenzaoccurred among those over 60 years while in 2009 pandemiconly 36 of the deaths occurred in this age group confirmingthe expected shift in age characteristic of pandemics Theseresults are consistent with others from study performed inBrazil [25]

Research conducted in other countries shows slightlydifferent results InTheNetherlands increasedmortality con-centrated in the age group 0 to 4 [26] The most affected inFrance were children under 4 and 35 to 44 years (consideringthe outcome pneumonia and influenza) [8] In Austria of allage groups below 44 years had highermortality than the aver-age of previous years but the most affected group was child-ren under 14 years [27] In Mexico the age groups mostaffected were 5 to 19 and 20 to 59 years with increases of9 and 145 times from the average of the previous periods

respectivelyThe same groupswere themost affected inBrazilalthoughwith higher incidence andmortality rates inMexico[7] In that country children under 5 years and elderly olderthan 60 years were less affected than in previous years butthe influenza pneumonia excess mortality in all ages was26 times higher than that observed in previous years Studycarried out in Hong Kong [9] showed a different tendency asthe most affected by influenza A H1N1 was the elderly Theseresults should be viewed with caution because it is a uniquecity

Unlike what happened in England where the secondwave seems to have been more intense than the first in Brazilthere was not a second wave of the 2009 pandemic [11]

In Mexico Charu and colleagues [7] observed increasedmortality among people over 60 already in the year 2010as noted in Sao Paulo in 2011 In that country this phe-nomenon occurred in a period slightly different from thenormal influenza seasonal probably due to an increase inthe circulation of the virus AH3N2 which could not beidentified by sentinel surveillance due to be concentrated insome region or in certain age groups [7]


This study has some limitations mentioned below As itis an ecological study of mortality rates certainly there arevariables not controlled as vaccination climatic changingand circulation of others virus Other limitation is the smallnumber of specimens collected weekly (average of 500 perweek) which may have hampered the identification of smallpeaks of viral activity contributing to the lack of perfectsynchronization between the excess mortality and increasedviral activity Analysis of subtypes circulating in influenzaseasons was compromised by having used aggregate dataobtained from the entire South America 2002 2003 20052010 and 2011 and may not accurately reflect the local realityof the state of Sao Paulo (PAHO WHO)

This study concludes that the method Serfling adaptedto weekly information with validation through viral activitydata using the influenza and pneumonia excess mortalitymay be appropriate in this geographic climatic and epidem-iological context In the state of Sao Paulo mortality from2009 pandemic influenza affected most age groups 5ndash50years and spared those younger than 5 and older than 60years The 2009 influenza H1N1 pandemic had almost all itseffect in 2009 without a second significant wave Others stud-ies are needed with standardized methodology for evaluatingthe appropriate charge of the 2009 pandemic in differentregions considering climatic and social context health sys-tems and measures taken This can be useful to health auth-orities in developing appropriate contingency plans for newpandemics

Conflict of Interests

All authors declare that they have no conflict of interests inthe research

Acknowledgments

The authors are grateful to Roberto Men Fernandes andWalquiria Aparecida Ferreira de Almeida from BrazilianMinistry of Health for providing the mortality and virologi-cal surveillance data respectively and Luana Hughes FreitasBruno Marcela and Nicole Montenegro de Medeiros forhelpful comments on themanuscript and general discussionsmany aspects of influenza

References

[1] R E Serfling ldquoMethods for current statistical analysis of excesspneumonia-influenza deathsrdquo Public Health Reports pp 494ndash506 1963

[2] S D Collins and J Lehmann ldquoTrends and epidemics of influ-enza and pneumonia 1918ndash1951rdquo Public Health Reports vol 66no 46 pp 1487ndash1516 1951

[3] B Nunes C Viboud A Machado et al ldquoExcess mortality asso-ciated with influenza epidemics in Portugal 1980 to 2004rdquo PloSOne vol 6 no 6 Article ID e20661 2011

[4] J Tamerius M I Nelson S Z Zhou C Viboud M A MillerandW J Alonso ldquoGlobal influenza seasonality reconciling pat-terns across temperate and tropical regionsrdquo EnvironmentalHealth Perspectives vol 119 no 4 pp 439ndash445 2011

[5] A Chow S Ma E L Ai and K C Suok ldquoInfluenza-associateddeaths in tropical Singaporerdquo Emerging Infectious Diseases vol12 no 1 pp 114ndash121 2006

[6] F E A Moura ldquoInfluenza in the tropicsrdquo Current Opinion inInfectious Diseases vol 23 no 5 pp 415ndash420 2010

[7] V Charu G Chowell L S Palacio Mejia S Echevarrıa-ZunoV H Borja-Aburto L Simonsen et al ldquoMortality burden of theAH1N1 pandemic inMexico a comparison of deaths and yearsof life lost to seasonal influenzardquo Clinical Infectious Diseasesvol 53 no 10 pp 985ndash993 2011

[8] M Lemaitre F Carrat G Rey M Miller L Simonsen and CViboud ldquoMortality Burden of the 2009 AH1N1 influenza pan-demic in France comparison to seasonal influenza and theAH3N2 pandemicrdquo PloS One vol 7 no 9 Article ID e450512012

[9] L Yang K P Chan B J Cowling S S Chiu K H Chan J SM Peiris et al ldquoExcess mortality associated with the 2009 pan-demic of influenza A(H1N1) in Hong Kongrdquo Epidemiology andInfection vol 140 no 9 pp 1542ndash1550

[10] S S Shrestha D L Swerdlow R H Borse et al ldquoEstimatingthe burden of 2009 pandemic influenza a (H1N1) in the UnitedStates (April 2009-April 2010)rdquo Clinical Infectious Diseases vol52 no 1 pp S75ndashS82 2011

[11] O T Mytton P D Rutter and L J Donaldson ldquoInfluenzaA (H1N1) pdm09 in England 2009 to 2011 a greater burdenof severe illness in the year after the pandemic than in thepandemic yearrdquo Eurosurveillance vol 17 14 article 3 2012

[12] W W Thompson L Comanor and D K Shay ldquoEpidemiologyof seasonal influenza use of surveillance data and statisticalmodels to estimate the burden of diseaserdquo Journal of InfectiousDiseases vol 194 supplement 2 pp S82ndashS91 2006

[13] A Nicoll B C Ciancio V L Chavarrias K Moslashlbak RPebody B Pedzinski et al ldquoInfluenza-related deathsmdashavailablemethods for estimating numbers and detecting patterns forseasonal and pandemic influenza in Europerdquo Eurosurveillancevol 17 no 18 pp 1ndash13 2012

[14] M Madjid M Naghavi S Litovsky and S W CasscellsldquoInfluenza and cardiovascular disease a new opportunity forprevention and the need for further studiesrdquo Circulation vol108 no 22 pp 2730ndash2736 2003

[15] W Oliveira E Carmo G Penna et al ldquoPandemic H1N1 influ-enza in Brazil analysis of the first 34506 notified cases of influ-enza-like illness with severe acute respiratory infection (SARI)rdquoEurosurveillance vol 14 no 42 pp 1ndash6 2009

[16] N Beilei E Carraro A Perosa AWatanabe E Arruda and CGranato ldquoAcute respiratory infection and influenza-like illnessviral etiologies in Brazilian adultsrdquo Journal of Medical Virologyvol 80 no 10 pp 1824ndash1827 2008

[17] Ministerio da Saude Indicadores e Dados Basicos Brasil 2011httptabnetdatasusgovbrcgiidb2011matrizhtmmort

[18] Ministerio da Saude Guia De Vigilancia EpidemiologicaBrasılia Brazil 5th edition 2005

[19] PAHO ldquoPAHO Regional Health Observatory-PHIP-Epidemicdiseases-Flurdquo 2012 httpaispahoorgphipvized fluasp

[20] S M Straliotto T S Gregianini T G Baccin F C Mottaand M Siqueira ldquoVirus influenza detectados no estado do riogrande do sul durante 2006 E 2007rdquo Boletim Da Saude vol 23no 1 pp 57ndash62 2009

[21] M Bercini T Ranieri M Aparecida D P Muller and RMohrdieck ldquoEspecial Influenzardquo Boletim Epidemiologico RioGrande do Sul pp 1ndash16 2011


[22] WHO ldquoFluNetrdquo httpwwwwhointinfluenzagisrs labora-toryfluneten

[23] L Simonsen M J Clarke G D Williamson D F Stroup NH Arden and L B Schonberger ldquoThe impact of influenzaepidemics onmortality introducing a severity indexrdquoAmericanJournal of Public Health vol 87 no 12 pp 1944ndash1950 1997

[24] World Health Organization ldquoChronology of Influenza A(H1N1)rdquo April 2009 httpwwwsearowhointenSection10Section2562 14942htmApril27

[25] C Schuck-Paim C Viboud L Simonsen M Miller F EMoura R M Fernandes et al ldquoWere equatorial regions lessaffected by the 2009 influenza pandemic The Brazilian expe-riencerdquo PloS One vol 7 no 8 Article ID e41918 2012

[26] C CWijngaard Van Den L Asten Van M P G KoopmansWPelt Van N J D Nagelkerke C C HWielders et al ldquoCompar-ing pandemic to seasonal influenza mortality moderate impactoverall but high mortality in young childrenrdquo PloS One vol 7no 2 Article ID e31197 2012

[27] M Redlberger-Fritz J H Aberle T Popow-Kraupp and MKundi ldquoAttributable deaths due to influenza a comparativestudy of seasonal and pandemic influenzardquo European Journal ofEpidemiology vol 27 no 7 pp 567ndash575 2012

[28] Ministerio da Saude Guia de Vigilancia Epidemiologica Secre-taria de Vigilancia em Saude Brasılia Brazil 6th edition 2005

[29] Boletim da Saude State Board of Health Rio Grande do SulBrazil 2009

[30] Boletim Epidemiologico State Board of Health Rio Grande doSul Brazil 2011

[31] SIVEP GRIPE Brazilian Ministery of Health

Submit your manuscripts athttpwwwhindawicom

Evidence-Based Complementary and Alternative Medicine

Volume 2013Hindawi Publishing Corporationhttpwwwhindawicom

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2013

MediatorsinflaMMation

of

Diabetes ResearchJournal of


ISRN AIDS



Computational and Mathematical Methods in Medicine

Hindawi Publishing Corporationhttpwwwhindawicom

Volume 2013Issue 1

GastroenterologyResearch and Practice

Clinical ampDevelopmentalImmunology


Volume 2013


ISRN Biomarkers

Hindawi Publishing Corporation httpwwwhindawicom Volume 2013Hindawi Publishing Corporation httpwwwhindawicom Volume 2013

The Scientific World Journal


Oxidative Medicine and Cellular Longevity

ISRN Addiction


International Journal of

EndocrinologyHindawi Publishing Corporationhttpwwwhindawicom

Volume 2013

ISRN Anesthesiology


BioMed Research International



OncologyJournal of

Volume 2013

OphthalmologyHindawi Publishing Corporationhttpwwwhindawicom Volume 2013

Journal of


ObesityJournal of

ISRN Allergy


PPARRe sea rch



pneumonia and influenza mortality by age is key to analyzethe total burden of disease and to compare with otherinfluenza seasons and with other regions Understanding thebehavior of past pandemics and epidemics of influenza iscritical for setting public health priorities for the coming sea-sonal and pandemic influenza

The aim of this study is to evaluate the influenza-associated mortality in the State of Sao Paulo Brazil from2002 to 2011 The choice of this period was due to the avail-ability of systematic virological surveillance data allowingvalidate data on mortality associated with influenza withinformation about the antigenic characteristics and levels ofviral activity

2 Material and Methods

21 Locality Sao Paulo is the most populate state in Brazil(over 41 million inhabitants in 2010 Census) with a GDPof US $1500000 per capita and a Human DevelopmentIndex of 0833 (United Nations Development Programme)also with good health care services and epidemiological sur-veillance [15] It is located between latitudes 19∘4610158404510158401015840S and25∘

181015840

4310158401015840SDespite being in the region of predominantly tro-

pical and subtropical climate the study region has clearlydefined seasons of increased circulation of influenza viruses[16]

22 Mortality and Population Mortality data were obtainedfrom Health Statistics System (DATASUS) Mortality Infor-mation System which covers 100 of the State of Sao Paulosince 1979 [17] Causes of death are classified using theInternational Cause of Death ICD-10 codes for pneumoniaand influenza (ICD J 10 to J189) respiratory causes (ICD J00to J99) and all-cause mortality (excluding external causes ofmortality) The mortality rates were calculated in three agegroups 0 to 4 5 to 19 20 to 59 and more than 60 years

Population data were obtained from the Brazilian Insti-tute of Geography and Statistics (IBGE) using data from the2010 Census [17] The weekly estimates were obtained byinterpolation

23 Virological Data Data on influenza virus activity inSoutheastern Brazil were obtained from the Ministry ofHealth through the Information System of EpidemiologicalSurveillance of Influenza Department of Health Surveillance(SIVEP-Gripe) [18] This system monitors the occurrenceof influenza through sentinel units which investigate theetiology of respiratory viruses causing flu-like syndromesNational Reference Laboratories test the samples by indi-rect immunofluorescence for a panel of respiratory viruses(including influenza A and B parainfluenza 1 2 and 3respiratory syncytial virus and adenovirus) and forwardsamples for culture of virus and real-time RT-PCR As theviral subtypes are not provided by SIVEP data are obtainedfrom various official sources [18ndash22]

24 Deaths due to Laboratory-Confirmed Pandemic InfluenzaIn the beginning of the pandemic the criterion to confirm theinfluenza cases was as follows any patient who had flu-like

illness (defined as fever cough or sore throat) and historyof traveling to countries with occurrence of cases or con-tacting with infected person After the initial phase diffusetransmission was confirmed in epidemiological week 28 Atthis time the registration of cases was as follows patientswith severe acute respiratory infections (SARI) that is thedefinition of SARI included fever cough and dyspnea ordeath All patients reported by theNational Systemof Surveil-lance Reportable Disease (SINAN) had respiratory secretionsamples collected for performing real-time RT-PCR in theNational Reference Laboratories Data on deaths confirminginfluenza pandemic were extracted from SINAN by age

25 Statistical Analysis The estimation of influenza-asso-ciated mortality was obtained through the classic methodSerfling with adaptation to weekly data [23] To fit regressionwe used the total period of 10 years excluding the weeks ofgreater viral circulation by laboratory criteria

We defined the onset of periods of increased activity ofthe influenza virus by virological criteria in the Braziliansoutheast (where State of Sao Paulo is located) when therewas the occurrence of two consecutive weeks in which wasconfirmed by indirect immunofluorescence more than twiceof the annual average of cases We defined that this periodends with the occurrence of two consecutive weeks with viraldiagnostic below the annual average The period of highestviral activity in 2009 began at the time the Brazilian Ministryof Health [15] officially declared epidemiological situation asldquowidespread viral transmissionrdquo until the official end of thepandemic was reported by WHO [24]

A cyclical linear regression was constructed as follow

119884 = 1205730+ 1205731lowast 119905 + 120573

2lowast 1199052

+ 1205733lowast 1199053

+ 1205734lowast sin(2 lowast 120587 lowast 119905

5217)

+ 1205735lowast cos(2 lowast 120587 lowast 119905

5217) + 1198901

(1)

where 119884 is the mortality rate 120573 is the coefficients of regres-sion 119905 is time inweeks and 1199052 and 1199053 are variables for adjustingthe secular trend of the disease

After adjusting stepwise linear regression the baseline ofexpected mortality in the absence of influenza was definedUsing this reference influenza epidemic periods were demar-cated as the periods in which mortality from pneumonia andinfluenza was above 95 confidence interval predicted bythe model for two consecutive weeks these periods endedwhen mortality was less than the upper confidence intervalfor two consecutive weeks Weekly excess mortality rate wasestimated by the difference between the observed and pre-dicted mortality rates by the model during influenza epi-demic periods Season mortality rate was calculated as thesum of weekly excess mortality rate during the year

The data were analyzed using the statistical programSPSS for Windows version 130 graphics and data compi-lation were made using the Microsoft Office Excel 2007 Alldatabases analyzed were not able to do any kind of patientidentification to preserve patientsrsquo privacy


002040608

112

Jan-

02

Jul-0

2

Jan-

03

Jul-0

3

Jan-

04

Jul-0

4

Jan-

05

Jul-0

5

Jan-

06

Jul-0

6

Jan-

07

Jul-0

7

Jan-

08

Jul-0

8

Jan-

09

Jul-0

9

Jan-

10

Jul-1

0

Jan-

11

Jul-1

1

Jan-

02

Jul-0

2

Jan-

03

Jul-0

3

Jan-

04

Jul-0

4

Jan-

05

Jul-0

5

Jan-

06

Jul-0

6

Jan-

07

Jul-0

7

Jan-

08

Jul-0

8

Jan-

09

Jul-0

9

Jan-

10

Jul-1

0

Jan-

11

Jul-1

1

Jan-

02

Jul-0

2

Jan-

03

Jul-0

3

Jan-

04

Jul-0

4

Jan-

05

Jul-0

5

Jan-

06

Jul-0

6

Jan-

07

Jul-0

7

Jan-

08

Jul-0

8

Jan-

09

Jul-0

9

Jan-

10

Jul-1

0

Jan-

11

Jul-1

1

Jan-

02

Jul-0

2

Jan-

03

Jul-0

3

Jan-

04

Jul-0

4

Jan-

05

Jul-0

5

Jan-

06

Jul-0

6

Jan-

07

Jul-0

7

Jan-

08

Jul-0

8

Jan-

09

Jul-0

9

Jan-

10

Jul-1

0

Jan-

11

Jul-1

1

Mor

talit

y rat

e per

100

000

0 to 4 years

0

01

Mor

talit

y rat

e per

100

000

5 to 19 years

01

03

05

Mor

talit

y rat

e per

100

000

20 to 59 years

3

5

7

9

Mor

talit

y rat

e per

100

000

More than 60 years


3 Results








002040608

112

Jan-

02

Jan-

03

Jul-0

3

Jan-

04

Jul-0

4

Jan-

05

Jul-0

5

Jan-

06

Jul-0

6

Jan-

07

Jul-0

7

Jan-

08

Jul-0

8

Jan-

09

Jul-0

9

Jan-

10

Jul-1

0

Jan-

11

Jul-1

1

Jan-

02

Jan-

03

Jul-0

3

Jan-

04

Jul-0

4

Jan-

05

Jul-0

5

Jan-

06

Jul-0

6

Jan-

07

Jul-0

7

Jan-

08

Jul-0

8

Jan-

09

Jul-0

9

Jan-

10

Jul-1

0

Jan-

11

Jul-1

1

Jan-

02

Jan-

03

Jul-0

3

Jan-

04

Jul-0

4

Jan-

05

Jul-0

5

Jan-

06

Jul-0

6

Jan-

07

Jul-0

7

Jan-

08

Jul-0

8

Jan-

09

Jul-0

9

Jan-

10

Jul-1

0

Jan-

11

Jul-1

1

Jan-

02

Jul-0

2Ju

l-02

Jul-0

2Ju

l-02

Jan-

03

Jul-0

3

Jan-

04

Jul-0

4

Jan-

05

Jul-0

5

Jan-

06

Jul-0

6

Jan-

07

Jul-0

7

Jan-

08

Jul-0

8

Jan-

09

Jul-0

9

Jan-

10

Jul-1

0

Jan-

11

Jul-1

1

Mor

talit

y rat

e per

100

000

0 to 4 years

0

01

02

Mor

talit

y rat

e per

100

000

5 to 19 years

025

045

085

065

Mor

talit

y rat

e per

100

000

20 to 59 years

5

10

15

20

Mor

talit

y rat

e per

100

000

More than 60 years












All ages(95 CI)























All causes 78 16 55 994 136



All causes 72 10 46 751 104






4

5

6

7

8

Jan-

02

Jan-

03

Jul-0

3

Jan-

04

Jul-0

4

Jan-

05

Jul-0

5

Jan-

06

Jul-0

6

Jan-

07

Jul-0

7

Jan-

08

Jul-0

8

Jan-

09

Jul-0

9

Jan-

10

Jul-1

0

Jan-

11

Jul-1

1

Jan-

02

Jan-

03

Jul-0

3

Jan-

04

Jul-0

4

Jan-

05

Jul-0

5

Jan-

06

Jul-0

6

Jan-

07

Jul-0

7

Jan-

08

Jul-0

8

Jan-

09

Jul-0

9

Jan-

10

Jul-1

0

Jan-

11

Jul-1

1

Jan-

02

Jan-

03

Jul-0

3

Jan-

04

Jul-0

4

Jan-

05

Jul-0

5

Jan-

06

Jul-0

6

Jan-

07

Jul-0

7

Jan-

08

Jul-0

8

Jan-

09

Jul-0

9

Jan-

10

Jul-1

0

Jan-

11

Jul-1

1

Jan-

02

Jul-0

2Ju

l-02

Jul-0

2Ju

l-02

Jan-

03

Jul-0

3

Jan-

04

Jul-0

4

Jan-

05

Jul-0

5

Jan-

06

Jul-0

6

Jan-

07

Jul-0

7

Jan-

08

Jul-0

8

Jan-

09

Jul-0

9

Jan-

10

Jul-1

0

Jan-

11

Jul-1

1

Mor

talit

y rat

e per

100

000

0 to 4 years

03

02

07

06

05

04

Mor

talit

y rat

e per

100

000

5 to 19 years

42

62

52

Mor

talit

y rat

e per

100

000

20 to 59 years

50

70

90

110

Mor

talit

y rat

e per

100

000

More than 60 years




4 Discussion















6 36 48 86 83











Acknowledgments


References






































of



ISRN AIDS





Volume 2013Issue 1




Volume 2013


ISRN Biomarkers





ISRN Addiction




Volume 2013

ISRN Anesthesiology





OncologyJournal of

Volume 2013


Journal of


ObesityJournal of

ISRN Allergy


PPARRe sea rch



002040608

112

Jan-

02

Jul-0

2

Jan-

03

Jul-0

3

Jan-

04

Jul-0

4

Jan-

05

Jul-0

5

Jan-

06

Jul-0

6

Jan-

07

Jul-0

7

Jan-

08

Jul-0

8

Jan-

09

Jul-0

9

Jan-

10

Jul-1

0

Jan-

11

Jul-1

1

Jan-

02

Jul-0

2

Jan-

03

Jul-0

3

Jan-

04

Jul-0

4

Jan-

05

Jul-0

5

Jan-

06

Jul-0

6

Jan-

07

Jul-0

7

Jan-

08

Jul-0

8

Jan-

09

Jul-0

9

Jan-

10

Jul-1

0

Jan-

11

Jul-1

1

Jan-

02

Jul-0

2

Jan-

03

Jul-0

3

Jan-

04

Jul-0

4

Jan-

05

Jul-0

5

Jan-

06

Jul-0

6

Jan-

07

Jul-0

7

Jan-

08

Jul-0

8

Jan-

09

Jul-0

9

Jan-

10

Jul-1

0

Jan-

11

Jul-1

1

Jan-

02

Jul-0

2

Jan-

03

Jul-0

3

Jan-

04

Jul-0

4

Jan-

05

Jul-0

5

Jan-

06

Jul-0

6

Jan-

07

Jul-0

7

Jan-

08

Jul-0

8

Jan-

09

Jul-0

9

Jan-

10

Jul-1

0

Jan-

11

Jul-1

1

Mor

talit

y rat

e per

100

000

0 to 4 years

0

01

Mor

talit

y rat

e per

100

000

5 to 19 years

01

03

05

Mor

talit

y rat

e per

100

000

20 to 59 years

3

5

7

9

Mor

talit

y rat

e per

100

000

More than 60 years


3 Results








002040608

112

Jan-

02

Jan-

03

Jul-0

3

Jan-

04

Jul-0

4

Jan-

05

Jul-0

5

Jan-

06

Jul-0

6

Jan-

07

Jul-0

7

Jan-

08

Jul-0

8

Jan-

09

Jul-0

9

Jan-

10

Jul-1

0

Jan-

11

Jul-1

1

Jan-

02

Jan-

03

Jul-0

3

Jan-

04

Jul-0

4

Jan-

05

Jul-0

5

Jan-

06

Jul-0

6

Jan-

07

Jul-0

7

Jan-

08

Jul-0

8

Jan-

09

Jul-0

9

Jan-

10

Jul-1

0

Jan-

11

Jul-1

1

Jan-

02

Jan-

03

Jul-0

3

Jan-

04

Jul-0

4

Jan-

05

Jul-0

5

Jan-

06

Jul-0

6

Jan-

07

Jul-0

7

Jan-

08

Jul-0

8

Jan-

09

Jul-0

9

Jan-

10

Jul-1

0

Jan-

11

Jul-1

1

Jan-

02

Jul-0

2Ju

l-02

Jul-0

2Ju

l-02

Jan-

03

Jul-0

3

Jan-

04

Jul-0

4

Jan-

05

Jul-0

5

Jan-

06

Jul-0

6

Jan-

07

Jul-0

7

Jan-

08

Jul-0

8

Jan-

09

Jul-0

9

Jan-

10

Jul-1

0

Jan-

11

Jul-1

1

Mor

talit

y rat

e per

100

000

0 to 4 years

0

01

02

Mor

talit

y rat

e per

100

000

5 to 19 years

025

045

085

065

Mor

talit

y rat

e per

100

000

20 to 59 years

5

10

15

20

Mor

talit

y rat

e per

100

000

More than 60 years












All ages(95 CI)























All causes 78 16 55 994 136



All causes 72 10 46 751 104






4

5

6

7

8

Jan-

02

Jan-

03

Jul-0

3

Jan-

04

Jul-0

4

Jan-

05

Jul-0

5

Jan-

06

Jul-0

6

Jan-

07

Jul-0

7

Jan-

08

Jul-0

8

Jan-

09

Jul-0

9

Jan-

10

Jul-1

0

Jan-

11

Jul-1

1

Jan-

02

Jan-

03

Jul-0

3

Jan-

04

Jul-0

4

Jan-

05

Jul-0

5

Jan-

06

Jul-0

6

Jan-

07

Jul-0

7

Jan-

08

Jul-0

8

Jan-

09

Jul-0

9

Jan-

10

Jul-1

0

Jan-

11

Jul-1

1

Jan-

02

Jan-

03

Jul-0

3

Jan-

04

Jul-0

4

Jan-

05

Jul-0

5

Jan-

06

Jul-0

6

Jan-

07

Jul-0

7

Jan-

08

Jul-0

8

Jan-

09

Jul-0

9

Jan-

10

Jul-1

0

Jan-

11

Jul-1

1

Jan-

02

Jul-0

2Ju

l-02

Jul-0

2Ju

l-02

Jan-

03

Jul-0

3

Jan-

04

Jul-0

4

Jan-

05

Jul-0

5

Jan-

06

Jul-0

6

Jan-

07

Jul-0

7

Jan-

08

Jul-0

8

Jan-

09

Jul-0

9

Jan-

10

Jul-1

0

Jan-

11

Jul-1

1

Mor

talit

y rat

e per

100

000

0 to 4 years

03

02

07

06

05

04

Mor

talit

y rat

e per

100

000

5 to 19 years

42

62

52

Mor

talit

y rat

e per

100

000

20 to 59 years

50

70

90

110

Mor

talit

y rat

e per

100

000

More than 60 years




4 Discussion















6 36 48 86 83











Acknowledgments


References






































of



ISRN AIDS





Volume 2013Issue 1




Volume 2013


ISRN Biomarkers





ISRN Addiction




Volume 2013

ISRN Anesthesiology





OncologyJournal of

Volume 2013


Journal of


ObesityJournal of

ISRN Allergy


PPARRe sea rch



002040608

112

Jan-

02

Jan-

03

Jul-0

3

Jan-

04

Jul-0

4

Jan-

05

Jul-0

5

Jan-

06

Jul-0

6

Jan-

07

Jul-0

7

Jan-

08

Jul-0

8

Jan-

09

Jul-0

9

Jan-

10

Jul-1

0

Jan-

11

Jul-1

1

Jan-

02

Jan-

03

Jul-0

3

Jan-

04

Jul-0

4

Jan-

05

Jul-0

5

Jan-

06

Jul-0

6

Jan-

07

Jul-0

7

Jan-

08

Jul-0

8

Jan-

09

Jul-0

9

Jan-

10

Jul-1

0

Jan-

11

Jul-1

1

Jan-

02

Jan-

03

Jul-0

3

Jan-

04

Jul-0

4

Jan-

05

Jul-0

5

Jan-

06

Jul-0

6

Jan-

07

Jul-0

7

Jan-

08

Jul-0

8

Jan-

09

Jul-0

9

Jan-

10

Jul-1

0

Jan-

11

Jul-1

1

Jan-

02

Jul-0

2Ju

l-02

Jul-0

2Ju

l-02

Jan-

03

Jul-0

3

Jan-

04

Jul-0

4

Jan-

05

Jul-0

5

Jan-

06

Jul-0

6

Jan-

07

Jul-0

7

Jan-

08

Jul-0

8

Jan-

09

Jul-0

9

Jan-

10

Jul-1

0

Jan-

11

Jul-1

1

Mor

talit

y rat

e per

100

000

0 to 4 years

0

01

02

Mor

talit

y rat

e per

100

000

5 to 19 years

025

045

085

065

Mor

talit

y rat

e per

100

000

20 to 59 years

5

10

15

20

Mor

talit

y rat

e per

100

000

More than 60 years












All ages(95 CI)























All causes 78 16 55 994 136



All causes 72 10 46 751 104






4

5

6

7

8

Jan-

02

Jan-

03

Jul-0

3

Jan-

04

Jul-0

4

Jan-

05

Jul-0

5

Jan-

06

Jul-0

6

Jan-

07

Jul-0

7

Jan-

08

Jul-0

8

Jan-

09

Jul-0

9

Jan-

10

Jul-1

0

Jan-

11

Jul-1

1

Jan-

02

Jan-

03

Jul-0

3

Jan-

04

Jul-0

4

Jan-

05

Jul-0

5

Jan-

06

Jul-0

6

Jan-

07

Jul-0

7

Jan-

08

Jul-0

8

Jan-

09

Jul-0

9

Jan-

10

Jul-1

0

Jan-

11

Jul-1

1

Jan-

02

Jan-

03

Jul-0

3

Jan-

04

Jul-0

4

Jan-

05

Jul-0

5

Jan-

06

Jul-0

6

Jan-

07

Jul-0

7

Jan-

08

Jul-0

8

Jan-

09

Jul-0

9

Jan-

10

Jul-1

0

Jan-

11

Jul-1

1

Jan-

02

Jul-0

2Ju

l-02

Jul-0

2Ju

l-02

Jan-

03

Jul-0

3

Jan-

04

Jul-0

4

Jan-

05

Jul-0

5

Jan-

06

Jul-0

6

Jan-

07

Jul-0

7

Jan-

08

Jul-0

8

Jan-

09

Jul-0

9

Jan-

10

Jul-1

0

Jan-

11

Jul-1

1

Mor

talit

y rat

e per

100

000

0 to 4 years

03

02

07

06

05

04

Mor

talit

y rat

e per

100

000

5 to 19 years

42

62

52

Mor

talit

y rat

e per

100

000

20 to 59 years

50

70

90

110

Mor

talit

y rat

e per

100

000

More than 60 years




4 Discussion















6 36 48 86 83











Acknowledgments


References






































of



ISRN AIDS





Volume 2013Issue 1




Volume 2013


ISRN Biomarkers





ISRN Addiction




Volume 2013

ISRN Anesthesiology





OncologyJournal of

Volume 2013


Journal of


ObesityJournal of

ISRN Allergy


PPARRe sea rch








All ages(95 CI)























All causes 78 16 55 994 136



All causes 72 10 46 751 104






4

5

6

7

8

Jan-

02

Jan-

03

Jul-0

3

Jan-

04

Jul-0

4

Jan-

05

Jul-0

5

Jan-

06

Jul-0

6

Jan-

07

Jul-0

7

Jan-

08

Jul-0

8

Jan-

09

Jul-0

9

Jan-

10

Jul-1

0

Jan-

11

Jul-1

1

Jan-

02

Jan-

03

Jul-0

3

Jan-

04

Jul-0

4

Jan-

05

Jul-0

5

Jan-

06

Jul-0

6

Jan-

07

Jul-0

7

Jan-

08

Jul-0

8

Jan-

09

Jul-0

9

Jan-

10

Jul-1

0

Jan-

11

Jul-1

1

Jan-

02

Jan-

03

Jul-0

3

Jan-

04

Jul-0

4

Jan-

05

Jul-0

5

Jan-

06

Jul-0

6

Jan-

07

Jul-0

7

Jan-

08

Jul-0

8

Jan-

09

Jul-0

9

Jan-

10

Jul-1

0

Jan-

11

Jul-1

1

Jan-

02

Jul-0

2Ju

l-02

Jul-0

2Ju

l-02

Jan-

03

Jul-0

3

Jan-

04

Jul-0

4

Jan-

05

Jul-0

5

Jan-

06

Jul-0

6

Jan-

07

Jul-0

7

Jan-

08

Jul-0

8

Jan-

09

Jul-0

9

Jan-

10

Jul-1

0

Jan-

11

Jul-1

1

Mor

talit

y rat

e per

100

000

0 to 4 years

03

02

07

06

05

04

Mor

talit

y rat

e per

100

000

5 to 19 years

42

62

52

Mor

talit

y rat

e per

100

000

20 to 59 years

50

70

90

110

Mor

talit

y rat

e per

100

000

More than 60 years




4 Discussion















6 36 48 86 83











Acknowledgments


References






































of



ISRN AIDS





Volume 2013Issue 1




Volume 2013


ISRN Biomarkers





ISRN Addiction




Volume 2013

ISRN Anesthesiology





OncologyJournal of

Volume 2013


Journal of


ObesityJournal of

ISRN Allergy


PPARRe sea rch



4

5

6

7

8

Jan-

02

Jan-

03

Jul-0

3

Jan-

04

Jul-0

4

Jan-

05

Jul-0

5

Jan-

06

Jul-0

6

Jan-

07

Jul-0

7

Jan-

08

Jul-0

8

Jan-

09

Jul-0

9

Jan-

10

Jul-1

0

Jan-

11

Jul-1

1

Jan-

02

Jan-

03

Jul-0

3

Jan-

04

Jul-0

4

Jan-

05

Jul-0

5

Jan-

06

Jul-0

6

Jan-

07

Jul-0

7

Jan-

08

Jul-0

8

Jan-

09

Jul-0

9

Jan-

10

Jul-1

0

Jan-

11

Jul-1

1

Jan-

02

Jan-

03

Jul-0

3

Jan-

04

Jul-0

4

Jan-

05

Jul-0

5

Jan-

06

Jul-0

6

Jan-

07

Jul-0

7

Jan-

08

Jul-0

8

Jan-

09

Jul-0

9

Jan-

10

Jul-1

0

Jan-

11

Jul-1

1

Jan-

02

Jul-0

2Ju

l-02

Jul-0

2Ju

l-02

Jan-

03

Jul-0

3

Jan-

04

Jul-0

4

Jan-

05

Jul-0

5

Jan-

06

Jul-0

6

Jan-

07

Jul-0

7

Jan-

08

Jul-0

8

Jan-

09

Jul-0

9

Jan-

10

Jul-1

0

Jan-

11

Jul-1

1

Mor

talit

y rat

e per

100

000

0 to 4 years

03

02

07

06

05

04

Mor

talit

y rat

e per

100

000

5 to 19 years

42

62

52

Mor

talit

y rat

e per

100

000

20 to 59 years

50

70

90

110

Mor

talit

y rat

e per

100

000

More than 60 years




4 Discussion















6 36 48 86 83











Acknowledgments


References






































of



ISRN AIDS





Volume 2013Issue 1




Volume 2013


ISRN Biomarkers





ISRN Addiction




Volume 2013

ISRN Anesthesiology





OncologyJournal of

Volume 2013


Journal of


ObesityJournal of

ISRN Allergy


PPARRe sea rch














6 36 48 86 83











Acknowledgments


References






































of



ISRN AIDS





Volume 2013Issue 1




Volume 2013


ISRN Biomarkers





ISRN Addiction




Volume 2013

ISRN Anesthesiology





OncologyJournal of

Volume 2013


Journal of


ObesityJournal of

ISRN Allergy


PPARRe sea rch







Acknowledgments


References






































of



ISRN AIDS





Volume 2013Issue 1




Volume 2013


ISRN Biomarkers





ISRN Addiction




Volume 2013

ISRN Anesthesiology





OncologyJournal of

Volume 2013


Journal of


ObesityJournal of

ISRN Allergy


PPARRe sea rch


















of



ISRN AIDS





Volume 2013Issue 1




Volume 2013


ISRN Biomarkers





ISRN Addiction




Volume 2013

ISRN Anesthesiology





OncologyJournal of

Volume 2013


Journal of


ObesityJournal of

ISRN Allergy


PPARRe sea rch







of



ISRN AIDS





Volume 2013Issue 1




Volume 2013


ISRN Biomarkers





ISRN Addiction




Volume 2013

ISRN Anesthesiology





OncologyJournal of

Volume 2013


Journal of


ObesityJournal of

ISRN Allergy


PPARRe sea rch


Health & Medicine

Mortality Associated with Influenza in Tropics, State of São Paulo, Brazil, from 2002 to 2011: The Pre-Pandemic, Pandemic, and Post-Pandemic Periods