Abstract:

Due to the importance of annual flu vaccination in the elderly, the study aimed to analyze the impact of influenza vaccination on morbidity and mortality from influenza in the elderly from 2010 to 2019 in the major geographic regions of Brazil. This is an ecological epidemiological study with data from the Information System of the National Immunization Program, Hospital Information System, and Mortality Information System, available from the Brazilian Ministry of Health. Data referred to Brazil and its five major regions and included influenza vaccination coverage rates in the elderly and morbidity and mortality from causes related to influenza and pneumonia in the elderly. Simple linear regression models were used to study the relationship between morbidity and mortality and vaccination coverage rates. There was an increase in vaccination coverage during the period, and the target of 80% coverage was reached in all the regions since 2011. A directly proportional statistical association was identified between the study variables, and the increase in vaccination coverage was associated with an increase in morbidity and mortality from the target causes. These data may be related to reports in the literature showing that the vaccine’s effect is modest in the elderly. However, the rates’ calculation does not take the population’s aging into account, using data from outdated census estimates. Besides, the hospitalization and mortality data may include other circulating viruses and bacteria besides influenza. The maintenance of high vaccination coverage may prevent the impact of influenza from being even higher on morbidity and mortality in the elderly.

Keywords:
Influenza Vaccines; Aged; Vaccination Coverage; Morbidity; Mortality Registries

Introduction

Brazil is experiencing the phenomenon of population aging, characterized by an increase in the number of elderly Brazilians, due mainly to the reduction in the fertility and mortality rates ¹1. Miranda GMD, Mendes ACG, Silva ALA. Desafios das políticas públicas no cenário de transição demográfica e mudanças sociais no Brasil. Interface (Botucatu) 2017; 21:309-22..

The elderly population experiences specific physiological and pathological changes. According to data from the Hospital Information System of the Unified Health System (SIH/SUS; http://tabnet.datasus.gov.br/cgi/tabcgi.exe?sih/cnv/niuf.def, accessed on 15/May/2020) for the year 2019, the leading cause of hospitalization in the elderly population was the group of diseases of the digestive system (n = 1,208,223), followed by diseases of the respiratory system (n = 1,186,828), and of the circulatory system (n = 1,177,590). This context includes acute infectious diseases, among which influenza, commonly known as the flu ²2. Kline KA, Bowdish DME. Infection in an aging population. Curr Opin Microbiol 2016; 29:63-7..

Influenza is an acute viral infection, the etiological agent of which is Myxovirus influenzae, or influenza virus. It is highly transmissible and affects an individual’s respiratory system several times over the course of life, with either mild or more serious presentations ³3. Fundação Nacional de Saúde. Informe técnico: 21ª Campanha Nacional de Vacinação contra a Influenza 2019. http://www.cosemssp.org.br/wp-content/uploads/2019/04/Informe-21%C2%AA-Campanha-Nacional-de-Vacina%C3%A7%C3%A3o-contra-a-Influenza-1.pdf (acessado em 30/Out/2019).
http://www.cosemssp.org.br/wp-content/up... . Transmission of the virus between humans occurs by the respiratory route, through secretions in the form of aerosols, droplets, or direct contact with the mucosa. The symptoms are similar to those of other viruses that affect the respiratory tract, such as fever (lasting approximately three days), cough, headache, muscle pain, coryza, and malaise ³3. Fundação Nacional de Saúde. Informe técnico: 21ª Campanha Nacional de Vacinação contra a Influenza 2019. http://www.cosemssp.org.br/wp-content/uploads/2019/04/Informe-21%C2%AA-Campanha-Nacional-de-Vacina%C3%A7%C3%A3o-contra-a-Influenza-1.pdf (acessado em 30/Out/2019).
http://www.cosemssp.org.br/wp-content/up... ^,44. Departamento de Vigilância das Doenças Transmissíveis, Secretaria de Vigilância em Saúde, Ministério da Saúde. Protocolo de tratamento de influenza 2017. http://bvsms.saude.gov.br/publicacoes/protocolo_tratamento_influenza_2017 (acessado em 16/Jan/2020).
http://bvsms.saude.gov.br/publicacoes/pr... ^,55. World Health Organization. Influenza (seasonal). https://www.who.int/news-room/fact-sheets/detail/influenza-(seasonal) (acessado em 16/Jan/2020).
https://www.who.int/news-room/fact-sheet... .

These symptoms normally resolve spontaneously in a week, but the disease can evolve with complications, more frequent in individuals with cardiac and respiratory com diseases, elderly, and immunocompromised individuals ⁴4. Departamento de Vigilância das Doenças Transmissíveis, Secretaria de Vigilância em Saúde, Ministério da Saúde. Protocolo de tratamento de influenza 2017. http://bvsms.saude.gov.br/publicacoes/protocolo_tratamento_influenza_2017 (acessado em 16/Jan/2020).
http://bvsms.saude.gov.br/publicacoes/pr... ^,66. Zambon M. Influenza and other emerging respiratory viruses. Medicine 2014; 42:45-51.. The most common complications are bacterial pneumonia, sinusitis, otitis, dehydration, exacerbation of preexisting chronic diseases such as heart failure, asthma, and diabetes mellitus, and primary pneumonia from influenza ⁴4. Departamento de Vigilância das Doenças Transmissíveis, Secretaria de Vigilância em Saúde, Ministério da Saúde. Protocolo de tratamento de influenza 2017. http://bvsms.saude.gov.br/publicacoes/protocolo_tratamento_influenza_2017 (acessado em 16/Jan/2020).
http://bvsms.saude.gov.br/publicacoes/pr... . These complications can lead to hospitalization and death ³3. Fundação Nacional de Saúde. Informe técnico: 21ª Campanha Nacional de Vacinação contra a Influenza 2019. http://www.cosemssp.org.br/wp-content/uploads/2019/04/Informe-21%C2%AA-Campanha-Nacional-de-Vacina%C3%A7%C3%A3o-contra-a-Influenza-1.pdf (acessado em 30/Out/2019).
http://www.cosemssp.org.br/wp-content/up... .

Flu epidemics affect large numbers of people, and it is not possible to predict them, since they depend mainly on prevention and control measures. The World Health Organization (WHO) estimates 3 to 5 million serious influenza cases per year in the world, with 290,000 to 650,000 deaths ⁵5. World Health Organization. Influenza (seasonal). https://www.who.int/news-room/fact-sheets/detail/influenza-(seasonal) (acessado em 16/Jan/2020).
https://www.who.int/news-room/fact-sheet... .

Influenza vaccination emerged in this context as an effective national strategy to reduce morbidity and mortality from respiratory diseases in the elderly population. The WHO states that the vaccine provides protection in healthy adults. Meanwhile, among the elderly, influenza vaccination may be less effective in the prevention of diseases, but it helps reduce the severity of incidence of complications and death, directly decreasing hospitalizations and expenditures on drugs for the treatment of secondary infections ⁵5. World Health Organization. Influenza (seasonal). https://www.who.int/news-room/fact-sheets/detail/influenza-(seasonal) (acessado em 16/Jan/2020).
https://www.who.int/news-room/fact-sheet... .

In analysis of the trend in mortality and hospital morbidity rates from causes related to influenza in the elderly population from 1992 to 2006 and assessment of the impact of implementing influenza vaccination campaigns in Brazil, vaccination campaigns were found to decrease hospitalizations and deaths from influenza in that period ⁷7. Daufenbac LZ, Duarte EC, Carmo EH, Campagna AS. Impacto da vacinação contra a influenza na morbidade hospitalar por causas relacionadas à influenza em idosos no Brasil. Epidemiol Serv Saúde 2014; 23:9-20..

Brazil’s national public influenza vaccination policy, which is part of the National Immunization Program (PNI), began in 1999, with annual campaigns aimed at coverage of at least 70% of the target population, consisting of elderly 65 years and older (this age bracket was extended downward to 60 years in 2000). In 2010, the risk groups were expanded and reached the maximum amplitude, due to the vaccination campaign against pandemic influenza A (H1N1) during the 2009 pandemic. More than 89 million Brazilians were vaccinated at the time, corresponding to vaccination coverage of 47% of the country’s total population ⁸8. Domingues CMAS, Oliveira WK. Uptake of pandemic influenza (H1N1)-2009 vaccines in Brazil 2010. Vaccine 2012; 30:4744-51..

According to Technical Report 2019 ³3. Fundação Nacional de Saúde. Informe técnico: 21ª Campanha Nacional de Vacinação contra a Influenza 2019. http://www.cosemssp.org.br/wp-content/uploads/2019/04/Informe-21%C2%AA-Campanha-Nacional-de-Vacina%C3%A7%C3%A3o-contra-a-Influenza-1.pdf (acessado em 30/Out/2019).
http://www.cosemssp.org.br/wp-content/up... on the 21st National Influenza Vaccination Campaign, the goal of 70% coverage was maintained until 2006, increasing to 80% in 2008 and 90% of the target population since 2017. This change was due to the population’s intense demand for the vaccine, resulting from the high death rates from influenza, as well as the vaccination’s good performance.

Various studies explain that non-adherence to annual influenza vaccination campaigns is associated with various factors, such as not considering it important to take the vaccine every year, believing that the vaccine causes reactions, fear, lack of orientation from healthcare professionals, difficult access, low schooling, age, presence of chronic diseases, life habits, and doubts as to the vaccine’s efficacy, among others ⁹9. Francisco PMSB, Barros MBA, Cordeiro MRD. Vacinação contra influenza em idosos: prevalência, fatores associados e motivos da não-adesão em Campinas, São Paulo, Brasil. Cad Saúde Pública 2011; 27:417-26.^,1010. Moura RF, Andrade FB, Duarte YAO, Lebrão ML, Antunes JLF. Fatores associados à adesão à vacinação anti-influenza em idosos não institucionalizados, São Paulo, Brasil. Cad Saúde Pública 2015; 31:2157-68.^,1111. Neves RG, Duro SMS, Tomasi E. Vacinação contra influenza em idosos de Pelotas-RS, 2014: um estudo transversal de base populacional. Epidemiol Serv Saúde 2016; 25:755-66.^,1212. Victor JF, Gomes GD, Sarmento LR, Soares AMG, Silva MJ. Fatores associados à vacinação contra influenza A (H1N1) em idosos. Rev Esc Enferm USP 2014; 48:58-65.. A systematic review concluded that seasonal influenza vaccination is influenced by social, structural, intermediate, and health-related determinants ¹³13. Nagata JM, Ramos IH, Kurup AS, Albrecht D, Torrealba CV, Paredes CF. Social determinants of health and seasonal influenza vaccination in adults = 65 years: a systematic review of qualitative and quantitative data. BMC Public Health 2013; 13:388..

A brief search of the Brazilian literature showed that although the influenza vaccine was implemented in 1999, publications on the vaccination’s impact in reducing morbidity and mortality in the elderly are rare, especially since the H1N1 pandemic in 2009 ⁷7. Daufenbac LZ, Duarte EC, Carmo EH, Campagna AS. Impacto da vacinação contra a influenza na morbidade hospitalar por causas relacionadas à influenza em idosos no Brasil. Epidemiol Serv Saúde 2014; 23:9-20.^,1414. Daufenbach LZ, Duarte EC, Carmo EH, Campagna AS, Santos CAST. Impacto da vacinação contra a influenza na morbidade hospitalar por causas relacionadas à influenza em idosos no Brasil. Epidemiol Serv Saúde 2014; 23:9-20.^,1515. Donalisio MR, Francisco PMSB, Latorre MRO. Tendência da mortalidade por doenças respiratórias em idosos antes e depois das campanhas de vacinação contra influenza no Estado de São Paulo - 1980 a 2004. Rev Bras Epidemiol 2006; 9:32-4.^,1616. Francisco PMS, Donalisio MRC, Latorre MRDO. Impacto da vacinação contra influenza na mortalidade por doenças respiratórias em idosos. Rev Saúde Pública 2005; 39:75-81.. In addition, there are various prevalence studies ⁹9. Francisco PMSB, Barros MBA, Cordeiro MRD. Vacinação contra influenza em idosos: prevalência, fatores associados e motivos da não-adesão em Campinas, São Paulo, Brasil. Cad Saúde Pública 2011; 27:417-26.^,1010. Moura RF, Andrade FB, Duarte YAO, Lebrão ML, Antunes JLF. Fatores associados à adesão à vacinação anti-influenza em idosos não institucionalizados, São Paulo, Brasil. Cad Saúde Pública 2015; 31:2157-68.^,1111. Neves RG, Duro SMS, Tomasi E. Vacinação contra influenza em idosos de Pelotas-RS, 2014: um estudo transversal de base populacional. Epidemiol Serv Saúde 2016; 25:755-66.^,1212. Victor JF, Gomes GD, Sarmento LR, Soares AMG, Silva MJ. Fatores associados à vacinação contra influenza A (H1N1) em idosos. Rev Esc Enferm USP 2014; 48:58-65., but few are recent or use the Ministry of Health databases. Such analysis is relevant, since the data can evidence the benefits of annual campaigns. An increase in vaccination coverage is expected to lead to fewer hospitalizations and deaths from influenza in the elderly population. The current study aimed to analyze the impact of influenza vaccination on morbidity and mortality from influenza in the elderly from 2010 to 2019 in the major geographic regions of Brazil.

Method

Study design

This is an ecological epidemiological study ¹⁷17. Gordis L. Epidemiology. 3rd Ed. Amsterdam/Philadelphia: Elsevier; 2004. with a time series component analyzing the trends in mortality and morbidity rates from respiratory tract diseases, as well as influenza vaccination coverage from 2010 to 2019. Data on vaccination coverage came from the Information System of the National Immunization Program (SI-PNI), morbidity data from the SIH/SUS (http://tabnet.datasus.gov.br/cgi/tabcgi.exe?sih/cnv/niuf.def, accessed on 15/May/2020), and mortality data from the Mortality Information System (SIM; http://tabnet.datasus.gov.br/cgi/deftohtm.exe?sim/cnv/obt10uf.def, accessed on 15/Jun/2020), all available on public access official websites.

Location and population

The data refer to Brazil’s five major geographic regions (North, Northeast, Southeast, South, and Central).

Variables

The study focused on the 10-year period from 2010 to 2019, due to the H1N1 pandemic in 2009, aiming to identify the post-pandemic profile of vaccination coverage and morbidity and mortality.

Data on vaccination coverage were obtained directly from the SI-PNI database, which contains information in which the numerator is the annul number of influenza vaccine doses administered to the elderly, and the denominator is the estimated elderly population (≥ 60 years), multiplied by 100, i.e., presented as percentages per year and by region of the country. Data with more than one decimal place after the period were rounded off to the nearest whole place.

Morbidity was analyzed according to the data collected from the SIH database, considering hospitalizations in Brazil’s five major regions, per year. The study considers the diseases listed in the International Classification of Diseases - 10th revision (ICD-10) under influenza (flu) and pneumonia (codes ICD-10 J09, J10, J11, J12, J13, J14, J15, J16, J17, and J18) and the age brackets 60-69, 70-79, and 80 years or older. The crude data were collected and transported to Excel spreadsheets, version 2013 (https://products.office.com/), and morbidity rates were calculated per thousand inhabitants. For the rates, the numerator was the annual number of hospitalizations and the denominator was the estimated elderly population (≥ 60 years), multiplied by 1,000. The estimated elderly population was the same as in the SI-PNI for calculating vaccination coverage.

Mortality was analyzed with data from the SIM database. Data on deaths were collected for the five regions of Brazil, per year. The analysis considered ICD-10 codes J09, J10, J11, J12, J13, J14, J15, J16, J17, and J18 and the age brackets 60-69, 70-79, and 80 years or older. The crude data were collected and transported to Excel spreadsheets, version 2013, where the mortality rates per thousand inhabitants were calculated. For the rates, the numerator was the annual number of deaths and the denominator was the estimated elderly population (≥ 60 years), multiplied by 1,000. The estimated elderly population was the same as in the SI-PNI for calculating vaccination coverage. Mortality in the SIM database is only available up to the year 2018.

Data analysis

The Excel software, version 2013, was used to calculate the rates. Time trend graphs were constructed for Brazil and the five regions to explain the evolution in the indicators during the study period ¹⁸18. Pagano M, Gauvreau K. Princípios de bioestatística. São Paulo: Thomson; 2004., and scatterplots with regression lines were estimated by regression equations, according to the hypothesis that vaccination coverage may affect morbidity and mortality. Simple linear regression models were used for this to study the relationship between a single dependent variable (morbidity/mortality) and the independent variable (vaccination coverage). A model was generated for each region of Brazil, plus a model for Brazil as a whole. The assumption for these models is that their residuals have a normal distribution with mean zero and constant variance, and all the assumptions were checked and verified ¹⁹19. Montgomery DC. Design and analysis of experiments. 5th Ed. New York: John Wiley & Sons; 2000.^,2020. Selvin S. Statistical analysis of epidemiologic data. v. 35. Oxford: Oxford University Press; 2004.. We also calculated Pearson’s correlation coefficient, which quantifies the association between two quantitative variables and varies between -1 and 1. Value 0 (zero) means that there is no linear relationship, a value of 1 indicates a perfect linear relationship, and value -1 also indicates a perfect linear relationship, but inverse. This value was inserted in the scatterplot with the regression equation ¹⁸18. Pagano M, Gauvreau K. Princípios de bioestatística. São Paulo: Thomson; 2004..

All the analyses set significance at 5%, and the fits were obtained with the R software, version 3.5 (http://www.r-project.org).

Ethical aspects

The study uses secondary data, analyzed in aggregate form, without identification of individuals. Since these are open-access data, no authorization was necessary for their use.

Results

Figures 1 and 2 present the data on vaccination coverage, morbidity, and mortality in elderly individuals from 2010 to 2019 in Brazil and by major regions, respectively.

In the time series, 2010 was the only year in which the 80% target for vaccination coverage, set by the Ministry of Health, was not reached in the Central (79.2%), Northeast (78.9%), Southeast (76.3%), South (77.1%), and in Brazil as a whole (79.1%). In the rest of the period, all regions reached or exceeded the target.

The results showed an increase in vaccination coverage in the year 2016 (compared to 2015) in Brazil and all five regions except for the Central.

We note the vaccination coverage rates greater than 100% in the Central in 2015 (109.3%), 2016 (101.6%), 2018 (109%), and 2019 (107%), and in the North in 2019 (103%).

In relation to morbidity, the South and Central regions showed the highest rates in the time series. The lowest rates until the year 2017 were in the Northeast region; and in 2018 and 2019 in the Southeast. The lowest rate was observed in the Northeast region 2012 (8.18‰) and the highest in the South in 2018 (18.78‰).

The mortality data show that the highest rates in the study period were in the Southeast. The North and Northeast regions had the lowest mortality rates until the year 2016, when the South and Central regions showed a drop in the rates. In 2017, the mortality rates in these regions were similar (North - 2.53‰, Northeast - 2.64‰, South and Central - 2.92‰) and lower than in the Southeast region (3.9‰).

Table 1 shows the results of the linear regression analysis for morbidity and mortality rates and vaccination coverage in the elderly.

Figure 3 shows the regression lines from the regression model for morbidity rates from respiratory diseases with ICD codes J09-J18 (‰ inhabitants) and vaccination coverage (%) for the study years in the regions and Brazil.

Figure 4 shows the estimated lines from the regression model for mortality rates from respiratory diseases with IDC codes J09-J18 (‰ inhabitants) and vaccination coverage (%) for the study years in the regions and Brazil.

According to the analyses, there is a directly proportional association between influenza vaccination coverage and morbidity, and between vaccination coverage and mortality. The results are statistically significant for morbidity in the Northeast, Southeast, and South regions and in Brazil. For mortality, the Northeast was the only region that did not present significant results.

We can infer statistically that the increase in vaccination coverage resulted in an increase in morbidity and mortality from diseases with ICD codes J09-J18 during the 10-year period. Therefore, the study’s hypothesis was not confirmed.

Discussion

The current study’s results show that influenza vaccination coverage in the elderly has increased in recent years, reaching or exceeding 100% in 2019. Note that the flu vaccine has not reached elderly Brazilians universally, since there is a variation in coverage over the years according to regions of the country.

Vaccination coverage rates greater than 100% are worthy of note, and we believe that they may be explained by the population’s aging. According to the national census by the Brazilian Institute of Geography and Statistics (IBGE) in 2010, the country’s population was 190,755,199, with 20,590,599 elderly (10.8%) ²¹21. Instituto Brasileiro de Geografia e Estatística. Sinopse do Censo Demográfico de 2010. Rio de Janeiro: Instituto Brasileiro de Geografia e Estatística; 2011.. The available calculations on vaccination coverage in the SI-PNI in the years 2010 and 2011 considered a total of 19,428,086 elderly. In the year 2012, the figure used was 20,590,599 (corresponding to the 2010 census). From 2013 to 2019, the number of elderly individuals for calculating the vaccination coverage rates was 20,889,849, corresponding to a population estimate published by IBGE in the year 2012, according to the SI-PNI. The number of elderly individuals has not been updated again since then.

According to the projection of the Brazilian population by sex and age published by IBGE, the proportion of elderly in the year 2019 was 13.85% of the total population (https://www.ibge.gov.br/estatisticas/sociais/populacao/9109-projecao-da-populacao.html?=&t=resultados, accessed on 01/Nov/2019), corresponding to approximately 29.105.377 persons 60 years or older, thus higher than the number used to calculate vaccination coverage that same year. Considering the number of doses applied from 2013 to 2019, if the population indicators by IBGE were used, vaccination coverage in Brazil would be the following: 2013 - 79%; 2014 - 74.5%; 2015 - 74.3%; 2016 - 78%; 2017 - 73.2%; 2018 - 72.4%; and 2019 - 71.3%, and the 90% target was not reached in any of the years.

We thus believe that the high vaccination coverage rates reached by the country’s regions in recent years may be due to the fact that the total population used for the calculation has been underestimated. This fact had already been discussed previously in relation to vaccination in children under one year, also indicating that besides flaws in the denominator for calculating coverage rates, there may also have been flaws in the production of data on doses applied ²²22. Moraes JC, Ribeiro MCSA, Simões O, Castro PC, Barata RB. Qual é a cobertura vacinal real? Epidemiol Serv Saúde 2003; 12:147-53.. With publication of the data from the 2020 census, we hope to know the real impact of influenza vaccination campaigns in Brazil. We highlight the importance of periodically conducting population surveys, especially in years with more time elapsed since the last estimate or census. Such periodic surveys would generate more valid and reliable information ²²22. Moraes JC, Ribeiro MCSA, Simões O, Castro PC, Barata RB. Qual é a cobertura vacinal real? Epidemiol Serv Saúde 2003; 12:147-53..

We chose to adopt the same denominator used to calculate vaccination coverage when calculating morbidity and mortality rates, aimed at standardizing them. There may be a mismatch in these rates as well, since they also showed increases.

The data showed a directly proportional relationship between vaccination coverage and morbidity and mortality.

Importantly, life expectancy in Brazil has increased in recent years, from 69.8 years in 2000 to 73.9 in 2010 and 76.3 in 2018 ²³23. Instituto Brasileiro de Geografia e Estatística. Tábua completa de mortalidade para o Brasil - 2018: breve análise da evolução da mortalidade no Brasil. https://biblioteca.ibge.gov.br/visualizacao/periodicos/3097/tcmb_2018.pdf (acessado em 16/Mai/2020).
https://biblioteca.ibge.gov.br/visualiza... . Studies show that the oldest seniors present a lower immune response to the influenza vaccine when compared to younger groups ²⁴24. Andrew MK, Bowles SK, Pawelec G, Haynes L, Kuchel GA, MsNeil AS, et al. Influenza vaccination in older adults: recent innovations and practical applications. Drugs Aging 2019; 36:29-37.^,2525. Ciabattinia A, Nardini C, Santoroa F, Garagnani P, Franceschig S, Medaglin D. Vaccination in the elderly: the challenge of immune changes with aging. Semin Immunol 2018; 40:83-94., making them more susceptible to more severe forms of influenza, which can lead to hospitalization and death. In addition, each individual’s history (immunological biography) is an important component of individual variation in the capacity of elderly individuals to respond to vaccines ²⁵25. Ciabattinia A, Nardini C, Santoroa F, Garagnani P, Franceschig S, Medaglin D. Vaccination in the elderly: the challenge of immune changes with aging. Semin Immunol 2018; 40:83-94..

The influenza vaccine supplied free of cost to seniors in Brazil’s public health system is the trivalent vaccine, while the quadrivalent vaccine is offered in the private system. The vaccine’s composition is updated yearly according to the prevalence of circulating strains in the world and is recommended by the WHO ³3. Fundação Nacional de Saúde. Informe técnico: 21ª Campanha Nacional de Vacinação contra a Influenza 2019. http://www.cosemssp.org.br/wp-content/uploads/2019/04/Informe-21%C2%AA-Campanha-Nacional-de-Vacina%C3%A7%C3%A3o-contra-a-Influenza-1.pdf (acessado em 30/Out/2019).
http://www.cosemssp.org.br/wp-content/up... . In Brazil, Sentinel Influenza Surveillance is responsible for identifying the circulation of the influenza virus and other respiratory viruses and sending the information to WHO to adjust the influenza vaccine strains ²⁶26. Ministério da Saúde. Portaria de Consolidação nº 5, de 28 de setembro de 2017. Consolidação das normas sobre as ações e os serviços de saúde do Sistema Único de Saúde. Diário Oficial da União 2017; 3 out.. Recommendation of the vaccine strains is based on a resolution by the Brazilian Health Regulatory Agency (Anvisa) in the second semester each year, containing the vaccine’s composition to be applied in the Southern Hemisphere in the winter of the following year ³3. Fundação Nacional de Saúde. Informe técnico: 21ª Campanha Nacional de Vacinação contra a Influenza 2019. http://www.cosemssp.org.br/wp-content/uploads/2019/04/Informe-21%C2%AA-Campanha-Nacional-de-Vacina%C3%A7%C3%A3o-contra-a-Influenza-1.pdf (acessado em 30/Out/2019).
http://www.cosemssp.org.br/wp-content/up... . The decision on the type of vaccine (trivalent or quadrivalent) to be supplied by the country takes into consideration both the circulating strains and the cost-benefit relationship for the general population. Despite the effort to update the information and the improvement in the surveillance program, a mismatch may occur, that it, incompatibility between the recommended vaccine strain and the circulating influenza strains ²⁷27. Barros ENCB, Cintra O, Rossetto E, Freitas L, Colindres R. Patterns of influenza B circulation in Brazil and its relevance to seasonal vaccine composition. Braz J Infect Dis 2016; 20:81-90., which may have contributed to the current study’s results.

A systematic review and meta-analysis that aimed to assess the efficacy and effectiveness of the different types of influenza vaccine found that the currently available vaccines may offer moderate overall protection against the disease, but there is no evidence of high-level protection, especially in individuals at risk of medical complications or 65 years of age or older ²⁸28. Osterholm MT, Kelley NS, Sommer A, Belongia EA. Efficacy and effectiveness of influenza vaccines: a systematic review and meta-analysis. Lancet Infect Dis 2012; 12:36-44.. Another review also found that the vaccine’s effect against influenza is only modest in the elderly ²⁹29. Jefferson T, Rivetti D, Rivetti A, Rudin M, Pietrantonj CD, Demicheli V. Efficacy and effectiveness of influenza vaccines in elderly people: a systematic review. Lancet 2005; 366:1165-74..

Nevertheless, vaccination with any type of recommended vaccine is still an important tool in the prevention of influenza and its complications. With time, a better understanding of the changes resulting from the aging process may result in adaptation of the available vaccines in order to generate good humoral and cellular responses, also considering the inflammatory component and leading to ideal protection for the elderly ²⁴24. Andrew MK, Bowles SK, Pawelec G, Haynes L, Kuchel GA, MsNeil AS, et al. Influenza vaccination in older adults: recent innovations and practical applications. Drugs Aging 2019; 36:29-37.^,2525. Ciabattinia A, Nardini C, Santoroa F, Garagnani P, Franceschig S, Medaglin D. Vaccination in the elderly: the challenge of immune changes with aging. Semin Immunol 2018; 40:83-94.^,3030. Smetana J, Chlibek R, Shaw J, Splinoa M, Prymula R. Influenza vaccination in the elderly. Hum Vaccin Immunother 2018; 14:540-9..

Another study highlights not only the importance of obtaining high vaccination coverage rates in the groups that most need them and the development of high-level vaccines, but also the relevance of elaborating more comprehensive strategies aimed at avoiding transmission of acute respiratory diseases, with preventive interventions that involve the context (water and food supply, basic sanitation, electricity, etc.) and the adoption of habits like hand-washing ²⁹29. Jefferson T, Rivetti D, Rivetti A, Rudin M, Pietrantonj CD, Demicheli V. Efficacy and effectiveness of influenza vaccines in elderly people: a systematic review. Lancet 2005; 366:1165-74..

The Brazilian literature reports the relationship between influenza vaccination and morbidity and mortality rates. A study in 496 municipalities (counties) in the southernmost state of Rio Grande do Sul found that in municipalities that reach the target for influenza vaccination coverage, the mortality rate from respiratory tract diseases was significantly lower ³¹31. Bós AJG, Mirandola AR. Cobertura vacinal está relacionada à menor mortalidade por doenças respiratórias. Ciênc Saúde Colet 2013; 18:1459-62.. Another study in the South of Brazil identified a reduction in hospitalizations in the first quarter of the year and an increase in the third trimester, revealing the impact of seasonality on influenza-related diseases. Still another study found that a 1% increase in vaccination coverage represents a 0.1% reduction in the hospitalization rate ³²32. Cruzeta APS, Schneider IJC, Traebert J. Impact of seasonality and annual immunization of elderly people upon influenza-related hospitalization rates. Int J Infec Dis 2013; 17:e1194-7.. Note the high morbidity rate in the South of Brazil in the current study, which may be related to the region’s climate, cooler than the other regions of the country, favoring survival of the virus ⁵5. World Health Organization. Influenza (seasonal). https://www.who.int/news-room/fact-sheets/detail/influenza-(seasonal) (acessado em 16/Jan/2020).
https://www.who.int/news-room/fact-sheet... .

A study that aimed to assess the impact of influenza vaccination campaigns in Brazil analyzed the trend in hospital morbidity rates (HMR) from causes related to influenza in the elderly from 1992 to 2006 and found downward trends in HMR in Brazil and in the major geographic regions, except for the North. The regions with the largest reductions were the South, Central, and Southeast. The HMR showed a reduction when comparing the periods before (1992-1998) and after (1999-2000) the beginning of the influenza vaccination campaigns ¹⁴14. Daufenbach LZ, Duarte EC, Carmo EH, Campagna AS, Santos CAST. Impacto da vacinação contra a influenza na morbidade hospitalar por causas relacionadas à influenza em idosos no Brasil. Epidemiol Serv Saúde 2014; 23:9-20.. The data for the North of Brazil are similar to those of the current study.

A publication that aimed to analyze mortality from respiratory diseases from 1980 to 2004 in the state of São Paulo found a reduction in mortality in the two years after the start of the vaccination campaigns (2000 and 2001), followed by a rebound in the rates, similar to previous years ¹⁵15. Donalisio MR, Francisco PMSB, Latorre MRO. Tendência da mortalidade por doenças respiratórias em idosos antes e depois das campanhas de vacinação contra influenza no Estado de São Paulo - 1980 a 2004. Rev Bras Epidemiol 2006; 9:32-4.. Another study in the state of São Paulo investigated the relationship between mortality from respiratory diseases from 1980 to 2000 and implementation of the influenza campaigns and identified a drop in mortality in 1999 and 2000, following the campaign’s implementation ¹⁶16. Francisco PMS, Donalisio MRC, Latorre MRDO. Impacto da vacinação contra influenza na mortalidade por doenças respiratórias em idosos. Rev Saúde Pública 2005; 39:75-81.. Interestingly, although Southeast Brazil has one of the lowest morbidity rates, it has the highest mortality rates, which may be related to the health system’s case-resolution capacity, as well as the profile of elderly in the region. This fact needs to be investigated in greater depth in future studies.

Some seniors are more aware of the vaccine’s importance, and thus the increase in adherence to the campaign. Studies show that increasing age, not smoking, and presence of chronic noncommunicable diseases increase adherence to the vaccine ¹⁰10. Moura RF, Andrade FB, Duarte YAO, Lebrão ML, Antunes JLF. Fatores associados à adesão à vacinação anti-influenza em idosos não institucionalizados, São Paulo, Brasil. Cad Saúde Pública 2015; 31:2157-68.^,3333. Sato AP, Antunes JLF, Lima-Costa MFF, Andrade FB. Influenza vaccine uptake among older adults in Brazil: socioeconomic equality and the role of preventive policies and public services. J Infect Public Health 2020; 13:211-5.. Meanwhile, socioeconomic inequalities, characteristics of health system access and use, cultural beliefs, and behavioral factors can also be related to vaccination ¹³13. Nagata JM, Ramos IH, Kurup AS, Albrecht D, Torrealba CV, Paredes CF. Social determinants of health and seasonal influenza vaccination in adults = 65 years: a systematic review of qualitative and quantitative data. BMC Public Health 2013; 13:388. and may have influenced the current study’s results. It is also possible that health education does not reach the entire population, since the reasons claimed by the elderly for not vaccinating are mostly fear of reactions, not wanting or not liking the vaccine, and rarely having the flu ¹¹11. Neves RG, Duro SMS, Tomasi E. Vacinação contra influenza em idosos de Pelotas-RS, 2014: um estudo transversal de base populacional. Epidemiol Serv Saúde 2016; 25:755-66.^,3333. Sato AP, Antunes JLF, Lima-Costa MFF, Andrade FB. Influenza vaccine uptake among older adults in Brazil: socioeconomic equality and the role of preventive policies and public services. J Infect Public Health 2020; 13:211-5.. Thus, since health workers are the preferred source of information on the vaccine ³⁴34. Alotaibi FY, Alhetheel AF, Alluhaymid YM, Alshibani MG, Almuhaydili AO, Alhuqayl TA, et al. Influenza vaccine coverage, awareness, and beliefs regarding seasonal influenza vaccination among people aged 65 years and older in Central Saudi Arabia. Saudi Med J 2019; 40:1013-8. these professionals play an essential role in recommending vaccination, answering controversial questions on adverse events, and publicizing the benefits of influenza vaccination ³⁵35. Mo PKH, Lau JTF. Influenza vas consideraram, no denominador, a população de idosos multiplicada por 1.000. ccination uptake and associated factors among elderly population in Hong Kong: the application of the Health Belief Model. Health Educ Res 2015; 30:706-18.^,3636. Ellen M. Factors that influence influenza vaccination rates among the elderly: nurses' perspectives. J Nurs Manag 2018; 26:158-66..

We highlight the fact that we used the hospital (SIH) and mortality (SIM) databases with ICD-10 codes J09-J18 (influenza and pneumonia), which may have overestimated the cases and deaths, since the classifications may encompass other viruses related to lung infections and their complications. In addition, the circulation of other respiratory viruses, bacteria, and other pathogens, besides environmental factors, may interfere in the data ¹⁵15. Donalisio MR, Francisco PMSB, Latorre MRO. Tendência da mortalidade por doenças respiratórias em idosos antes e depois das campanhas de vacinação contra influenza no Estado de São Paulo - 1980 a 2004. Rev Bras Epidemiol 2006; 9:32-4.. For the type of study, the SIH and SIM databases were adequate for the objective. However, further studies aimed at assessing cases of acute respiratory distress syndrome (ARDS) and outbreaks of flu syndrome (FS) can be conducted with data from the SINAN/SIVEP-gripe database.

In addition, although the SIH and SIM databases are widely used in Brazil, both have limitations, such as gaps in the coverage of data on hospitalizations and deaths ³⁷37. Bittencourt SA, Camacho LAB, Leal MC. O Sistema de Informação Hospitalar e sua aplicação na saúde coletiva. Cad Saúde Pública 2006; 22:19-30.^,3838. Laurenti R, Jorge MHPM, Lebrão ML, Gotlieb SLD, Almeida MF. Estatísticas vitais: contando os nascimentos e as mortes. Rev Bras Epidemiol 2005; 8:108-10.^,3939. Laurenti R, Jorge MHPM, Gotlieb SLD. A confiabilidade dos dados de mortalidade e morbidade por doenças crônicas não-transmissíveis. Ciênc Saúde Colet 2004; 9:909-20.. The main problem with the SIH database is diagnosis at hospital admission, since many patient charts have incomplete data on this item ³⁷37. Bittencourt SA, Camacho LAB, Leal MC. O Sistema de Informação Hospitalar e sua aplicação na saúde coletiva. Cad Saúde Pública 2006; 22:19-30.. The SIM database is increasingly complete and accurate but still presents gaps in physicians’ recording of causes of death ³⁸38. Laurenti R, Jorge MHPM, Lebrão ML, Gotlieb SLD, Almeida MF. Estatísticas vitais: contando os nascimentos e as mortes. Rev Bras Epidemiol 2005; 8:108-10., with many deaths recorded as resulting from ill-defined causes ⁴⁰40. Franca EB, Souza FM, Ishitani LH, Teixeira R, Szwarcwald CL. Strengthening vital statistics in Brazil: investigation of ill-defined causes of death and implications on mortality statistics. Lancet 2013; 381 Suppl 2:S51., besides gaps in data coding ³⁹39. Laurenti R, Jorge MHPM, Gotlieb SLD. A confiabilidade dos dados de mortalidade e morbidade por doenças crônicas não-transmissíveis. Ciênc Saúde Colet 2004; 9:909-20.. Thus, there may be hospitalizations and deaths that are not recorded or are recorded incorrectly in these systems, which limits the data’s generalization. It is also possible that the same person is admitted to hospital more than once, which may generate duplicate data in the SIH, unlike the mortality and vaccination coverage rates, which are calculated per person rather than per event.

The data show that morbidity and mortality rates vary by region of the country, thus underlining the need to design specific strategies for follow-up of seniors from diagnosis through hospitalization in the different regions.

The maintenance of high and homogeneous vaccination coverage rates is essential for maintaining and reducing morbidity and mortality from vaccine-preventable diseases. Considering that the results were unfavorable, lower vaccination coverages could result in even more hazardous data from the epidemiological point of view, with higher morbidity and mortality rates.

Strategies for uptake of the elderly and health education should be intensified in the search for excellent quality of services. When permanent measures are taken to recruit the target public, a valuable tactic is achieved for the health indicators, considered essential for prevention of the disease throughout the country.

Health administrators and professionals face various challenges in planning and operationalizing vaccination campaigns. They need to be informed and updated in relation to the programs’ processes and results for the services’ continuous improvement. The professionals involved in the health process must be familiar with the data on influenza to assist the development of tools for continuous actions in the improvement of care for the population.

It is essential for the data to be updated continuously, in step with the Brazilian population’s aging, since the use and publication of outdated data can produce a false sense of protection in the population.

Given that the mortality data are only available up to 2018 in the SIM database, the current study presents a gap, since it was not possible to analyze whether the upward trend in the mortality rate was maintained in 2019, a point that can be explored in future studies.

Conclusion

Influenza vaccination coverage rates in elderly Brazilians have remained above the target set by the Ministry of Health in all regions of the country since 2011. An increase was observed in the morbidity and mortality rates from causes related to influenza and pneumonia during the period analyzed here. However, the rates’ calculation was seen not to take the population’s aging into account, using data from outdated census estimates. In addition, the data on hospitalizations and deaths may have included other circulating viruses and bacteria besides influenza.

Importantly, data on vaccination coverage, mortality, and morbidity are essential for orienting public health interventions and thus need to be adequately calculated and analyzed. Finally, we highlight the importance of encouraging vaccination among elderly people as a way of promoting healthy aging and the development of more effective vaccines, considering the particularities of elderly persons and the co-circulation of influenza strains.

Acknowledgments

The study was conducted with support from the Brazilian Graduate Studies Coordinating Board (CAPES; funding code 001), and also received support from the Federal University of Mato Grosso do Sul, Brazil.

References

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