INTRODUCTION

With the advancement of epidemiology and understanding of infectious diseases, social relations, demography, and mobility resulting from the globalization process are increasingly becoming protagonists in the dissemination and transmissibility of microorganisms with the potential to be infectious in humans¹. According to the World Health Organization (WHO), the term pandemic refers to a state caused by the emergence and dissemination of a new pathogen, with the ability to trigger a disease, often severe, with significant ease, by its replication and transmissibility between humans^2,3.

Among the pandemics that have plagued humanity in the last 100 years, those caused by influenza viruses belonging to the Orthomyxoviridae family stand out. Three virus genera (A, B, and C) involved in respiratory conditions belong to this family. The genera A and B cause higher mortality; however, only genus A has pandemic potential. Viruses of the genus Alphaorthomyxovirus (genus A) are classified according to the antigenic subtype of two surface structures, hemagglutinin (H, 19 subtypes) and neuraminidase (N, 11 subtypes), responsible for the processes of viral adsorption and cell receptor cleavage, respectively. In the A H1N1 virus, antigenic subtype 1 of structure H and antigenic subtype 1 of structure N are present. Because it has animal reservoirs and has high virulence in humans, this subtype and its mutations still affect the population today^1,4.

Between 1918 and 1920, Influenza A (H1N1), of avian origin, became responsible for the so-called Spanish flu, commonly cited as "the greatest medical holocaust in history", with millions of deaths worldwide^5,6. In later years, the constant remodeling and antigenic mutability of the virus brought about new pandemic scenarios. In 1957, a new strain of Influenza (H2N2) caused epidemic outbreaks in several regions of the globe, becoming known as Asian flu⁷. The H3N2 strain recreated, in 1968, the same scenario with the Hong Kong flu⁸; and, finally, in 2009, the A(H1N1)pdm09 strain, of swine-origin, had its first cases notified in Mexico, being disseminated, soon after, throughout the European continent and Oceania⁹. Samples from previous pandemics, such as Spanish flu, English flu, Hong Kong flu, and the Influenza A(H1N1)pdm09 virus, originated from shift-type mutations that occur by viral genome segments recombination of viral samples from different animal origins¹⁰.

In an analysis of the severity of the last pandemic brought about by the Influenza A(H1N1)pdm09 variant, according to the survey carried out by the WHO, around 150,000 deaths were registered on the planet until the 1st of April 2010. In Brazil, there had been about 40,000 cases of severe acute respiratory syndrome (SARS) and approximately 1,700 deaths in the eight-month period since the declaration of Public Health Emergency of International Concern (PHEIC) by the WHO in April 2009¹¹. The severity of the pandemic, although with medical and scientific resources superior to previous scenarios, revealed the need and urgency for a new approach to epidemiological surveillance and, as a basic requirement, greater efficiency in the detection and monitoring of new cases¹².

After five PHEIC declarations (H1N1 in 2009, poliomyelitis in 2014, ebola in 2014 and 2018, and zika in 2016), an outbreak in late 2019 related to the emergence of SARS cases in Wuhan, capital of Hubei Province, China, was caused by a new etiological agent that, in a short time, became the target of the sixth emergency declared by the WHO, showing its potential as a threat to global health: the so-called new coronavirus (SARS-CoV-2)^13,14.

The world had already faced a pandemic and an epidemic due to infection by the SARS-CoV and MERS-CoV coronaviruses, both originating in animal reservoirs, of the genus Betacoronavirus and subgenus Sarbecovirus. Between 2002 and 2003, the first was caused by SARS-CoV, thus identified as having caused SARS in infected individuals; the second, caused by MERS-CoV, responsible for the Middle East respiratory syndrome (MERS) in 2011. Finally, emerging, in late 2019, a pandemic caused by another coronavirus, also related to respiratory diseases, with high pathogenicity¹³.

Based on the similarities and contrasts between the aforementioned pandemics, the present study aims to analyze the epidemiological manifestation of infection by Influenza A(H1N1)pdm09 and SARS-CoV-2 in Pará State, Brazil, in hopes that it may guide the decision-making of health managers in future similar situations.

MATERIALS AND METHODS

This is a descriptive epidemiological study, in which a comparison was made between the epidemiological analysis of influenza caused by the Influenza A(H1N1)pdm09 virus, based on data from the Notifiable Diseases Information System (SINAN), tabulated by the Department of Informatics of the Brazilian Unified Health System (DATASUS), for the period from June 2009 to May 2010. For COVID-19 pandemic, caused by SARS-CoV-2, the data were extracted from the Epidemiological Bulletins of the Secretariat of Health of Pará State (SESPA) for the period from March to July 2020. For both platforms, the last data collection date was July 10, 2020, at 6:01 pm.

An epidemiological study involves the delimitation of variables associated with diseases in a given population sample and in a specific period to verify the association between the variables, characteristic of an observational approach in which the researcher uses data already available and does not directly interfere in research. For the categorization of the information obtained in the analysis of the collected data, the following variables were selected: age, gender, symptoms, number of cases and deaths, mortality rate, hospitalizations due to SARS, final classification, and microregions of notification.

The data obtained were tabulated and analyzed in Microsoft Excel, and graphs, maps, and tables were generated. The maps were elaborated and designed using the Qgis program, where the representation of the incidence of cases directly reflects on the chosen color tone. The creation of the table, the statistical analysis of the incidence and fatality rates, and the calculations aimed at establishing confidence intervals and percentage analyses were performed using the SigmaPlot v12.0 tool.

Finally, the inclusion criteria established was a positive diagnosis for one of the two pathologies. As this research used secondary public data, the Free and Informed Consent Form was not required, as there is no individual identification.

RESULTS

Considering the beginning of notifications of COVID-19 cases in early March 2020, 136,184 tests were carried out in Pará until the date of data collection, of which 124,934 had diagnostic confirmation, 10,900 were discarded, and 350 were still under analysis - numbers that made Pará reach the 5th position among the Brazilian states with the highest number of cases. Of the total number of infected, 109,699 recovered, 9,961 were still hospitalized or in voluntary quarantine, and 5,274 progressed to death, generating a mortality rate of 4.22%.

As for influenza A(H1N1)pdm09, Brazil reached 54,171 confirmed cases between 2009 and 2010, and Pará were the 6th in the ranking nation of infected. A total of 2,184 tests were carried out in the State, with 783 confirmed, 1,265 discarded, and 136 under investigation. Among the confirmed cases, 690 were cured, and 41 progressed to death, with a fatality rate of 5.23%, and 52 were deaths that did not occur directly by influenza, but by other causes, according to DATASUS. In a temporal analysis of the incidence of cases of the two pandemics in the State, it can be observed, in figure 1, the noticeable peak, common to both pandemics, in the third month after the notification of the first case, with 61,300 new cases of COVID-19 and 147 cases of influenza A(H1N1)pdm09. It is also noteworthy that, in relation to notifications of influenza A(H1N1)pdm09, the second wave of notifications was recorded in the second semester.

Source: SESPA (COVID-19) and SINAN-DATASUS (influenza A(H1N1)pdm09), July/2020.

* The initial month of analysis corresponds to when the first confirmed case of the pathologies analyzed in the State was notified. The month of June 2009 is for influenza A(H1N1)pdm09 and March 2020 for COVID-19. The information for the month of July 2020 corresponds to the data available until July 10, 2020.

Figure 1 - Distribution of confirmed cases of COVID-19 and influenza A(H1N1)pdm09 over the months* in Pará State, Brazil 

As for mortality, in addition to the substantial difference in the number of absolute deaths, there was a less abrupt drop in deaths from influenza A(H1N1)pdm09 than that observed from the fourth month of the COVID-19 pandemic, associated with a second wave of influenza A(H1N1)pdm09, greater and longer-lasting, reaching, in the eighth month, the peak of new deaths, as seen in figure 2.

Source: SESPA (COVID-19) and SINAN-DATASUS (influenza A(H1N1)pdm09), July/2020.

* The initial month of analysis corresponds to when the first confirmed case of the pathologies analyzed in the State was notified. The month of June 2009 is for influenza A(H1N1)pdm09 and March 2020 for COVID-19.The information for the month of July 2020 corresponds to the data available until July 10, 2020.

Figure 2 - Distribution of new deaths caused by COVID-19 and influenza A(H1N1)pdm09 over the months* in Pará State, Brazil 

While SARS-CoV-2 affected more adults in the 30 to 39 year age group, the Influenza A(H1N1)pdm09 virus affected more children and young people from 10 to 19 years. Regarding the incidence by gender of those affected by COVID-19, there was an equivalence of virus infection in the State, with 60,525 (48.45%) male and 64,409 (51.55%) female. Regarding influenza A(H1N1)pdm09, the number of infected women was higher, totaling 477 (60.92%), and men was 306 (39.08%) (Table 1).

In addition, the death rate from COVID-19 was predominant among men, with 63.80% (3,365), while among women, it was 36.20% (1,909). For influenza A(H1N1)pdm09, the number of deaths reported was 31 (75.61%) female and 10 (24.39%) male. While infection with the Influenza A(H1N1)pdm09 virus promoted higher fatality among individuals under 30 years of age, SARS-CoV-2 reached the elderly.

According to the symptoms presented, influenza A(H1N1)pdm09 syndromes were identified in 2009: flu syndrome, characterized by at least two of the signs and symptoms (fever, chills, sore throat, headache, cough, runny nose, olfactory disorders, or taste disorders), in 3.07% of cases; SARS, having the same symptoms as the flu syndrome plus dyspnea or respiratory distress, oxygen saturation lower than 95% in room air, and cyanosis, in 60% of cases; and SARS with hospitalization, in 79.43% of the reported cases. In the case of the COVID-19 pandemic, the predominant symptoms were, in descending order: fever, cough, sore throat, headache, myalgia, and arthralgia.

As for the spatial distribution of the respective pandemics by the microregions of the territory of Pará, a more homogeneous profile of involvement of COVID-19 was evidenced, with a greater distribution of cases in the state, compared to influenza A(H1N1)pdm09, affecting several microregions, such as the located on the outskirts of the city of Belém, capital of Pará, Guamá (5,630), and Cametá (9,695); several centers in the southwest of Pará, such as Itaituba (5,361) and Altamira (5,839); and the Baixo Amazonas, reaching the microregions Parauapebas (14,815), Óbidos (2,997), and Santarém (5,967).

Both pandemics had a high number of cases in the northeast of Pará, especially in the Belém microregion, with 86.72% (679) of the total cases for influenza A(H1N1)pdm09 and 24.86% (31,056) for COVID-19, while the microregions Conceição do Araguaia (influenza A(H1N1)pdm09 = 2; COVID-19 = 616) and Almeirim (influenza A(H1N1)pdm09 = 0; COVID-19 = 698) remained significantly less affected in both pandemics, as visualized in figures 3 and 4, which show the microregions according to the degree of incidence of cases.

Source: SINAN-DATASUS, July/2020.

Figure 3 - Incidence of influenza A(H1N1)pdm09 cases in Pará State, Brazil, from June 2009 to May 2010 

Source: SESPA, July/2020.

Figure 4 - Incidence of COVID-19 cases in Pará State, Brazil, from March to July 2020 

DISCUSSION

The SARS-CoV-2 virus was officially detected in Brazilian territory on February 26, 2020, when the first case was notified, an older man living in the city of São Paulo, São Paulo State¹⁵. The first reported records of the Influenza A(H1N1)pdm09 virus in Brazil date back to May 7, 2009, with six confirmed cases¹⁶. Assessing the transmissibility indices (R₀) for a better comparison between the pathologies, the SARS-CoV-2 initial estimates ranged from 1.6 to 4.1, reflecting a mortality rate of about 3.9/100,000 inhabitants in the country, while the Influenza A(H1N1)pdm09 virus had R₀ between 1.3 and 1.8, representing mortality around 0.85/100,000 inhabitants^{17,18,19,20,21,22}.

From the analysis of data collected in Pará, it was possible to observe a substantial difference in the impact caused between the two pandemics that occurred in recent years, even though their means of contamination and transmissibility are similar. The number of confirmed cases of COVID-19 in Pará, from March to July 2020, exceeded by more than twice the total number of cases of influenza A(H1N1)pdm09 from June 2009 to May 2010, in all the Brazilian territory, becoming the 5th State more affected by the COVID-19 pandemic, but also significantly affected by the 2009 pandemic, in which it also ranked in a prominent position, as the 6th in the number of cases. The purpose of comparing the time series carried out in this study is related to the possibility of predicting scenarios of the distribution profile of SARS-CoV-2 based on epidemiological experiences with similar characteristics due to their mechanism of contamination, infectivity, and dissemination, as in the case of the pandemic caused by the Influenza A(H1N1)pdm09 virus. Therefore, the analysis compares the differences and similarities departing from the profile of population involvement and territorial distribution of cases in Pará State among the index patients. This is done taking into account the same starting point (Figures 1 and 2) in the analysis of the infection and mortality curves, which are fundamental for the understanding and discussion in the literature regarding the multifactorial analysis regarding the impact on health services caused in each period analyzed, in addition to enabling the construction of scientific bases aimed at targeting of health surveillance measures and epidemiological monitoring in the region. The absence of an anti-SARS-CoV-2 vaccine until December 2020 and, therefore, of a mass vaccination campaign, as has occurred for years for H1N1, may justify the high numbers of cases of the new coronavirus in the population in question, as a result of the absence of pre-existing herd immunity. This immunological aspect certainly impacted the numbers of these infections by SARS-CoV-2 and Influenza A(H1N1)pdm09.

The discrepancy evidenced in raw values between the pathologies, highlighting the greater diffusion of COVID-19 in the State, can be elucidated by marked differences regarding its transmissibility. According to the report by the Centers for Disease Control and Prevention, 81% of COVID-19 cases had mild symptoms, and 1.2% were asymptomatic. Those factors facilitated the dissemination of SARS-CoV-2 due to the greater difficulty of screening the virus, unlike pathologies that have high hospitalization rates, such as MERS, and which, consequently, limit the movement of the pathogen to health facilities²³. Another hypothesis favorable to its high spread is related to its different viral tropism for the respiratory tract, resulting in milder disease but highly transmissible when the virus replicates in the upper respiratory tract. When viral tropism is greater for the lower respiratory tract, there is a greater severity but less potential for propagation. This hypothesis derives from the example of the Influenza A(H1N1)pdm09 viruses, such as seasonal influenza caused by the Influenza A (H1N1) and Influenza (H3N2) viruses^24,25.

In relation to other national findings on COVID-19, the data for Pará State are superior, for example, to the epidemiological survey conducted in Maranhão State²⁶, from March to April 2020, which indicated 2,105 confirmed cases of the disease, a number about 12 times lower than in Pará, in the same time window, demonstrating that, despite the territorial proximity, each federation unit is affected in different ways when comparing the number of cases of the disease. When analyzing the data related to the influenza A(H1N1)pdm09 pandemic, the results are inferior to the findings of the observational study with 4,740 confirmed cases in Paraná State²⁷, showing that, like COVID-19, the Influenza A(H1N1)pdm09 virus pandemic affected Brazilian regions in different ways. The variability of the incidence of influenza A(H1N1)pdm09 pandemic can be explained by the complex degree of immunological heterogeneity of local populations to circulating influenza strains, with geographic and social conditions, the degree of viral infectivity, and seasonality as transmission factors.

From the temporal analysis of incidence between pandemics, peaks of contamination and similar deaths were evidenced three months after the first notified case of the two pathologies. In the case of influenza A(H1N1)pdm09, the return of an even more ascending curve between the seventh and ninth month of the pandemic, a period that is still unknown about the COVID-19 pandemic, at the time of data collection. Among the factors listed for a new wave of infection by the Influenza A(H1N1)pdm09 virus is the seasonal characteristic of the virus²⁸. Given the population's naive immunity to SARS-CoV-2 and its contagion potential higher than seasonal flu, the hypothesis of the emergence of a second wave of cases, in a scenario of the inexistence of effective treatments for the disease or unavailability of vaccines has been increasingly raised in recent studies²⁹.

Comparing the incidence of the pandemics over the age group, in the case of COVID-19, the data showed a significant difference concerning the findings of Influenza A(H1N1)pdm09 virus infection, with individuals aged 30 to 39 years being the most affected by SARS-CoV-2. These results are similar to other findings, such as the epidemiological study with the population of Teresina, Piauí State, which showed that the above-mentioned age group was also the most affected, representing 32.06% of confirmed cases in that State³⁰. A reasonable hypothesis for the prevalence in this group would be the fact that this age group is economically active, with greater exposure outside the home environment, even though pioneer studies are establishing possible degrees of cross-protection for people who came into contact with other coronaviruses in addition to the association between the severity of the disease and the blood type^31,32.

Regarding the incidence of infection by the Influenza A(H1N1)pdm09 virus, there was a greater predominance of confirmed cases between 0 and 19 years of age, with 31.71% of all notified cases. This finding corroborates the findings of a cross-sectional study³² and an epidemiological survey¹⁴, in which the same age group was the most affected by influenza A(H1N1)pdm09. A possible explanation for this phenomenon is the fact that, in the 2009 pandemic, the elderly were relatively more protected, due to an immunological memory of the viral variant epitopes after being exposed to a similar strain early in life, as the one responsible for the 1918 pandemic and its variants in later years³³. Therefore, such exposure over the years may have provided different degrees of immunity for individuals aged 45 years or over, thus limiting the onset at older ages and avoiding more severe symptoms in these patients^34,35.

Although COVID-19 had a higher incidence among adults in Pará, the number of cases did not differ in relation to the patient's gender since there was an equivalence between the number of men (48.45%) and women (51.55%) infected. However, when the focus of the analysis was the death rate, there was a higher fatality rate among men (63.80%), with the most affected age group being 60 years old or more. Despite being relatively inferior to that described in the study by Orellana et al.³⁶, carried out in Manaus, Amazonas State, with men over 60 years of age representing 69.1% of the total deaths, this finding is very close to those described in the international literature^37,38. Although not intrinsically associated with such an outcome in this portion, the factors related to this reality are divided into biological - such as immunological differences - and behavioral, as the higher rate of smoking or neglect during quarantine³⁹.

As for the influenza A(H1N1)pdm09 pandemic, there was a higher incidence of cases (60.92%) and deaths (75.61%) in females. Such data confront the relative equivalence of the involvement of women by the virus in other studies^40,41, possibly related to inconsistencies in official data or even to underreporting of cases among men, since, historically, this group tends to seek less the health units for care⁴².

It was possible to observe a similarity in the symptoms between the two pathologies, emphasizing the presence of fever associated with respiratory problems such as cough. In 2011, Khandaker et al.⁴³ corroborated this fact by highlighting, in their systematic review, that 84% of confirmed cases had cough and fever as the most prevalent symptoms in those infected with the Influenza A(H1N1)pdm09 virus, being classified as important markers for screening for similar respiratory diseases. Furthermore, the similarity of the clinical findings extends, according to the data collected, to symptoms such as myalgia and arthralgia, reported in a significant number of cases of COVID-19 in the State, a factor also reported in another study⁴⁴, which added fatigue, gastrointestinal symptoms, and productive cough as preponderant factors for patients with SARS-CoV-2, a condition also registered in people infected with the Influenza A(H1N1)pdm09 virus.

Regarding the evolution of symptoms and the severity related to the need for hospitalization, there was a high rate of cases of SARS with hospitalization (79.43%) caused by the Influenza A(H1N1)pdm09 virus in 2009, almost double the finding in a study by Lenzi et al.⁴⁵, carried out with 4,740 patients with laboratory confirmation, in Paraná State, of which 40.3% were hospitalized. Among the factors associated with the fact, it is noteworthy that, as of 2009, only cases of hospitalizations due to SARS were reported in the SINAN database (SINAN Influenza Web)⁴⁶.

Among the factors associated with the control of the number of new cases and deaths by COVID-19 are the interruption of non-essential activities during the period of lockdown (from 07/05/2020 to 24/05/2020) and the adoption of the use of masks as a mandatory measure, under penalty of fine^47,48. That was because of the publication of new studies associating high exposures to the SARS-CoV-2 inoculum with greater penetration into the lower respiratory tract, which would be related to the worsening of the disease, while lower exposures to the inoculums, due to the physical barrier of the masks, allow contact with a lower viral load, increasing the time for the immune response and resulting in a milder infection^49,50.

From comparing the spatial incidence between the two pandemics, it was possible to observe the percentage concentration of cases in the Belém microregion, having, respectively, 86.72% and 24.86% of the total notifications of cases of influenza A(H1N1)pdm09 and COVID-19. Among the factors associated with greater homogeneity in the incidence of COVID-19 cases among the microregions of the State is the issue of the long incubation period for SARS-CoV-2 (from one to 14 days), compared to the Influenza A(H1N1)pdm09 virus (from one to seven days), favoring contagion, as asymptomatic people are potential sources of contamination^51,52. Another point to be considered concerns the substantial difference in the number of tests performed in the two pandemics. In the COVID-19 pandemic, this number exceeded approximately 60 times the testing carried out in 2009, and, therefore, the greatest potential for screening is associated with the lowest underreporting of cases. In addition, it is important to emphasize, as a factor for inducing immunity and lower circulation of pandemic viruses, that the Influenza A(H1N1)pdm09 virus has seasonally circulating strains and as part of the annual vaccine, strains that suffer frequent mutations in their RNA (drifts)⁵³.

It is important to note that Pará has microregions with significant population rates, allowing greater dissemination of SARS-CoV-2, according to studies carried out by the WHO⁵⁴. A possible hypothesis for internalization, according to Ribeiro et al.⁵⁵, is due to the connection between Brazilian cities of different sizes and complexities through the air, road, and river networks, which allows the contact of people from the most diverse locations, a fact that occurs in the metropolitan region of Pará, especially in the microregion where is the capital, one of the main economic centers of the Amazon Region, favoring the interiorization of COVID-19.

Given the use of secondary databases, this study recognizes the limitations related to the detailing of notified cases, reiterating, in addition to its focus on the participation of complementing the epidemiological panoramas already developed regarding the aforementioned pandemics, the need for constant updating of research focused on the theme, in view of the seriousness related to the current epidemiological scenario.

CONCLUSION

The results found in this study demonstrate the discrepancy in the impact of both pathologies in Pará State, with COVID-19 showing a number of infected people approximately 60 times higher than influenza A(H1N1)pdm09. The superiority in the values found is also reflected in other factors such as the mortality rate and the spatial distribution in the State. It is worth highlighting the differences in incidence and fatality according to age group, with the most prevalent cases of Influenza A(H1N1)pdm09 virus in children and young people between 10 and 19 years old and higher mortality between 20 and 29 years old, while for the SARS-CoV-2 was observed in adults, between 30 and 39 years old, with significant mortality in the age group above 60 years. The epidemiological comparison of the time series in the present study allows us to foresee different scenarios of the impact of each pathology, such as the territorial distribution and dissemination of each pathology, based on the analysis of its first paired cases. Thus, these findings highlight that the documented experience of the influenza A(H1N1)pdm09 pandemic in Pará reflects the need to change the strategic planning that should be implemented in the COVID-19 pandemic, in view of affecting different publics and their pathophysiological differences, it enhances the need for greater support from public policies to improve the capacity to provide medical care to the population and epidemiological surveillance in the Amazon Region.