Seasonal dynamics of influenza in Brazil: the latitude effect

Abstract

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.

COVID-19 e hospitalizações por SRAG no Brasil: uma comparação até a 12ª semana epidemiológica de 2020

“…Saúde Pública 2020; 36(4):e00070120 COVID-19 arrived in Brazil during the season of the year in which respiratory virus activity is generally low. Only in 2010 and 2016, SARI seasonality occurred earlier (in the late summer and autumn) in most of Brazil's states 11 , with a predominance of Influenza A virus. The increase in hospitalizations for SARI so early in 2020 calls our attention, since there is an upward tendency in SARI cases between the autumn and winter, especially in higher-latitude states 11 .…”

Comparative global epidemiology of influenza, respiratory syncytial and parainfluenza viruses, 2010–2015

“…A continuous wavelet transform was applied to the incidence time series, as has been previously used for various infectious disease studies. 10,36 This wavelet method decomposes the underlying time series process to the wavelet form that is a function of frequency.…”

“…Finally, 10 0 0 bootstrap samples were conducted to obtain the 95% confidence interval (CI) of the centre of gravity. 10,39…”

“…Despite multiple single-site or national surveillance data for influenza and/or RSV being available either via publication or online, e.g. from Argentina, 9 Brazil, 10 Canada, 11 UK, 12 The Netherlands, 13 Finland, 14 Bulgaria, 15 Russia, 16 South Africa, 17 Rwanda, 18 Madagascar, 19 Cambodia, 20 Thailand, 21 Malaysia, 22 Singapore, 23 The Philippines, 24 Indonesia, 25 Hong Kong, 26 Mongolia, 27 Japan, 28 Australia, 29 and New Zealand, 30 there are still relatively few global-scale studies that compare the contemporaneous (i.e. over the same time period) incidence patterns of common respiratory viruses across different countries -and nearly all of these used mostly publicly available surveillance data extracted from national surveillance websites, or published studies.…”

Comparative Seasonal Respiratory Virus Epidemic Timing in Utah

“…Wavelet analysis is nuanced but has many features that are similar to other wave decomposition methods. It has been shown to be a useful tool in comparing infectious disease rates in several studies [13,19]. Its strength is in allowing the timing of the epidemic curves to change from year to year by Data are lacking for metapneumovirus prior to January 2007 and for rhinovirus prior to November 2007.…”