The epidemic wave of influenza A (H1N1) in Brazil, 2009

Codeço, Cláudia Torres; Cordeiro, Josiane; Lima, Arthur Weiss da Silva; Colpo, Rodrigo Amarante; Cruz, Oswaldo Gonçalves; Coelho, Flávio Codeço; Luz, Paula M.; Struchiner, Cláudio J.; Barros, Fernando R. de Moraes

doi:10.1590/s0102-311x2012000700011

Cited by 12 publications

(14 citation statements)

References 19 publications

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“…This pattern is similar to those found in the Brazilian Southern (subtropical) states, the ones that are most affected by the disease, as shown in Fig. 5 and also by [38, 39]. …”

Section: Discussionsupporting

confidence: 87%

Seasonal dynamics of influenza in Brazil: the latitude effect

2018

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BackgroundInfluenza is a global transmissible disease. Its dynamics is far better understood in temperate climates than in the tropics. We aim to close this knowledge gap between tropical and temperate regions by showing how the influenza seasonality evolves in Brazil, a tropical country that encompasses a wide range of latitudes and six climatic sub-types.MethodsWe analyzed a state-level, weekly Syndrome of Acute Respiratory Disease (SARI) incidence data ranging from 2010 to 2016. We combined two techniques hierarchically: first the wavelet decomposition technique to detect annual periodicity and then circular statistics to describe seasonal measures of the periodic states.ResultsWe found significant annual periodicity in 44% of the states. For these, we calculated several seasonal measures such as the center of gravity or mean timing of activity. The relationship between the seasonal signatures and latitude was clear and statistically significant. States with seasonal signature are clustered along the coast. Most Amazonian and Central West states exhibit no seasonal behavior. Among the seasonal states, influenza starts in Northeast region, spreading southbound.ConclusionsOur study advances the comprehension of influenza seasonality in tropical areas and could be used to design more effective prevention and control strategies.Electronic supplementary materialThe online version of this article (10.1186/s12879-018-3484-z) contains supplementary material, which is available to authorized users.

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“…This pattern is similar to those found in the Brazilian Southern (subtropical) states, the ones that are most affected by the disease, as shown in Fig. 5 and also by [38, 39]. …”

Section: Discussionsupporting

confidence: 87%

Seasonal dynamics of influenza in Brazil: the latitude effect

2018

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“…Esta discusión adquiere escasa resonancia en Brasil 41,42,43,44,45,46,47 y en Argentina 37,48,49 , tanto a nivel de los medios masivos de comunicación, como de la producción científica.…”

Section: Discussionunclassified

Dimensiones políticas de una epidemia: el caso de la gripe A (H1N1) en la prensa escrita de Argentina

Spinelli

2016

Cad. Saúde Pública

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El objetivo de este estudio se orienta a comprender las representaciones sociales que expresan los periódicos, en torno a la epidemia de gripe A (H1N1) en Argentina para el año 2009, a través del análisis cuali-cuantitativo de dos dimensiones fundamentales: la forma en que se construye el "objeto" epidemia y las fuentes de información de las noticias. A partir de ello, es posible identificar que en la forma de nombrar y construir la epidemia subyace cierta decisión política de eliminar la responsabilidad que cabe a un modo de producción pecuaria riesgosa, responsabilizando al individuo que incurre en conductas de riesgo. El análisis muestra la vigencia de la hegemonía biomédica en las recomendaciones de representantes políticos, especialmente a nivel internacional, lo que contribuye a la farmacologización de una epidemia, posicionamiento que reproduce la población en sus reclamos. El comportamiento de la prensa ante la epidemia, no responde a eventos vinculados a la epidemiología del virus, sino que publica la mayor parte de noticias ante eventos asociados a la política local.

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“…In July 2009, there was a recommendation for restricting notification to patients with severe acute respiratory illness (SARI) only. However, in Paraná, this recommendation was not followed, as the proportion of mild cases remained high throughout the epidemic [5]. Time series of influenza cases were created by summing the number of weekly confirmed and autochthonous cases, from April 5 to September 26,2009.…”

Section: Epidemiological Datamentioning

confidence: 99%

“…On some occasions, there was no record for initial day of symptoms. In these cases, missing data were estimated using imputation technique, and the corresponding value for first day of symptoms was calculated as 2.76 days prior to the day-of-report (the mean time between onset of symptoms and notification of illness), following the estimation of Codeço et al [5].…”

Section: Epidemiological Datamentioning

confidence: 99%

“…According to Ministry of Health data, up to the epidemiological week (EW) 47 (11/22/2009 to 11/28/2009), 30,055 cases of Severe Acute Respiratory Infection (SARI) had been registered, with 93% identified as resulting from H1N1 infections. The H1N1 pandemic disproportionately affected the southern and southeast regions of Brazil, with Paraná being the most affected state, accounting for 52% of the total cases reported in the country [5]. Despite low lethality rates, the rapid spread of the disease generated panic in Paraná.…”

Section: Introductionmentioning

confidence: 99%

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Spatiotemporal diffusion of influenza A (H1N1): Starting point and risk factors

et al. 2018

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Influenza constitutes a major challenge to world health authorities due to high transmissibility and the capacity to generate large epidemics. This study aimed to characterize the diffusion process of influenza A (H1N1) by identifying the starting point of the epidemic as well as climatic and sociodemographic factors associated with the occurrence and intensity of transmission of the disease. The study was carried out in the Brazilian state of Paraná, where H1N1 caused the largest impact. The units of spatial and temporal analysis were the municipality of residence of the cases and the epidemiological weeks of the year 2009, respectively. Under the Bayesian paradigm, parametric inference was performed through a two-part spatiotemporal model and the integrated nested Laplace approximation (INLA) algorithm. We identified the most likely starting points through the effective distance measure based on mobility networks. The proposed estimation methodology allowed for rapid and efficient implementation of the spatiotemporal model, and provided evidence of different patterns for chance of occurrence and risk of influenza throughout the epidemiological weeks. The results indicate the capital city of Curitiba as the probable starting point, and showed that the interventions that focus on municipalities with greater migration and density of people, especially those with higher Human Development Indexes (HDIs) and the presence of municipal air and road transport, could play an important role in mitigation of effects of future influenza pandemics on public health. These results provide important information on the process of introduction and spread of influenza, and could contribute to the identification of priority areas for surveillance as well as establishment of strategic measures for disease prevention and control. The proposed model also allows identification of epidemiological weeks with high chance of influenza occurrence, which can be used as a reference criterion for creating an immunization campaign schedule.

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The epidemic wave of influenza A (H1N1) in Brazil, 2009

Cited by 12 publications

References 19 publications

Seasonal dynamics of influenza in Brazil: the latitude effect

Seasonal dynamics of influenza in Brazil: the latitude effect

Dimensiones políticas de una epidemia: el caso de la gripe A (H1N1) en la prensa escrita de Argentina

Spatiotemporal diffusion of influenza A (H1N1): Starting point and risk factors

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