Influenza seasonality goes south in the Yucatan Peninsula: The case for a different influenza vaccine calendar in this Mexican region

Ayora-Talavera, Guadalupe; Flores, Gerardo Montalvo-Zurbia; Gómez-Carballo, Jesús; González-Losa, Refugio; Conde-Ferráez, Laura; Puerto-Solı́s, Marylı́n; López-Martı́nez, Irma; Díaz-Quiñonez, José Alberto; Barrera-Badillo, Gisela; Acuña-Soto, Rodolfo; Livinski, Alicia A.; Alonso, Wladimir J.

doi:10.1016/j.vaccine.2017.07.020

Cited by 7 publications

(10 citation statements)

References 27 publications

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“…In this study we have described the emergence of genetic variants of influenza A(H1N1)pdm09 viruses in a specific region of Mexico. Overall, this study underlines the need of continuous monitoring of influenza viruses in different regions of Mexico with different seasonal patterns as we have recently shown [ 43 ], and the need to increase the number of sequences available to better characterize the influenza viruses circulating in larger countries as Mexico.…”

Section: Discussionmentioning

confidence: 63%

Temporal distribution and genetic variants in influenza A(H1N1)pdm09 virus circulating in Mexico, seasons 2012 and 2013

et al. 2017

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The 2012 and 2013 annual influenza epidemics in Mexico were characterized by presenting different seasonal patterns. In 2012 the A(H1N1)pdm09 virus caused a high incidence of influenza infections after a two-year period of low circulation; whereas the 2013 epidemic presented circulation of the A(H1N1)pdm09 virus throughout the year. We have characterized the molecular composition of the Hemagglutinin (HA) and Neuraminidase (NA) genes of the A(H1N1)pdm09 virus from both epidemic seasons, emphasizing the genetic characteristics of viruses isolated from Yucatan in Southern Mexico. The molecular analysis of viruses from the 2012 revealed that all viruses from Mexico were predominantly grouped in clade 7. Strikingly, the molecular characterization of viruses from 2013 revealed that viruses circulating in Yucatan were genetically different to viruses from other regions of Mexico. In fact, we identified the occurrence of two genetic variants containing relevant mutations at both the HA and NA surface antigens. There was a difference on the temporal circulation of each genetic variant, viruses containing the mutations HA-A141T / NA-N341S were detected in May, June and July; whereas viruses containing the mutations HA-S162I / NA-L206S circulated in August and September. We discuss the significance of these novel genetic changes.

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Section: Discussionmentioning

confidence: 63%

Temporal distribution and genetic variants in influenza A(H1N1)pdm09 virus circulating in Mexico, seasons 2012 and 2013

et al. 2017

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“…O momento correspondente ao pico de mortalidade em cada estado é plotado então em relação à latitude de cada estado. Esta análise de gradientes latitudinais foi pioneira no Brasil (11), e aplicada posteriormente no estudo da sazonalidade de várias doenças em diversos países (12)(13)(14)(15)(16)(17). Todas as análises e resultados foram gerados com o software Epipoi 10…”

Section: Análisesunclassified

Covid-19 em contexto: comparação com a mortalidade mensal por causas respiratórias nos estados brasileiros

Alonso¹,

Schuck‐Paim²,

Freitas³

et al. 2020

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Decisões críticas no combate à pandemia causada pelo SARS-CoV-2 têm sido realizadas frequentemente com dados e informações ainda incompletas. Enquanto os órgãos pertinentes não solucionam os gargalos no fluxo de informações de vital importância, epidemiólogos e outros pesquisadores devem produzir subsídios técnicos para o enfrentamento da crise contornando essas limitações. No presente estudo, focado no Brasil, comparamos os óbitos pelo SARS-CoV-2, disponibilizados diariamente, com os dados de óbitos por doenças respiratórias e outras doenças nos anos de 2014 a 2018 (os últimos cinco anos completos para os quais os dados estão disponíveis). Adicionalmente, extraímos os sinais temporais anuais dos óbitos por doenças respiratórias para que o período típico de pico na mortalidade por essas doenças possa ser considerado em cada estado Brasileiro. A porcentagem de óbitos pelo SARS-CoV-2 até o dia 15 de abril equivale a 24% da mortalidade esperada por causas respiratórias no mesmo período, com base em anos anteriores, com grande variação entre os estados (desde o Amazonas, 151%, até o Tocantins, com 3%). Estamos na época típica de pico de mortalidade associada a doenças respiratórias em grande parte do Norte e Nordeste (com exceção de Roraima). Nas regiões Sudeste e Sul, esse pico é mais tardio (junho–agosto). A evolução da pandemia em cada estado dependerá, no entanto, de vários outros fatores, como o comportamento do patógeno – ainda não conhecido suficientemente. Ressaltamos a necessidade de ações para aumento da agilidade na disponibilização dos dados atuais de mortalidade (por diversas causas), para que equipes de pesquisa com diferentes abordagens analíticas possam se somar no combate a este desafio sanitário global.

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“…Increased recognition of the global burden of influenza in tropical and semi-tropical regions also has encouraged uptake of routine annual vaccination in many middle-income countries. However, several MISMS studies rooted in epidemiological and virological data have pointed out that the semi-annual schedule is designed for wealthier countries in the temperate regions in the Northern and Southern hemispheres, and are suboptimal for many tropical countries that experience influenza at different times of the year, or have multiple peaks (Alonso et al, 2007;de Mello, de Paiva et al 2009;Tamerius et al, 2011;Bloom-Feshbach, Alonso et al 2012;Green, Andrews et al 2013;Alonso et al, 2015a,b;Ayora-Talavera, Flores et al 2017). MISMS research has informed whether a tropical country should opt for the Northern or Southern hemisphere vaccine formulation -or in some cases both.…”

Section: New Vaccination Strategiesmentioning

confidence: 99%

“…MISMS research has informed whether a tropical country should opt for the Northern or Southern hemisphere vaccine formulation -or in some cases both. Large countries with heterogenous influenza patterns and climate, such as China, Mexico and Brazil, may require different vaccine recommendations for their northern and southern regions (Alonso et al, 2007;de Mello, de Paiva et al 2009;Ayora-Talavera, Flores et al 2017). Additionally, MISMS research demonstrating the low impact of senior vaccination programs in the US and Italy paved the way for expanded vaccination…”

Section: New Vaccination Strategiesmentioning

confidence: 99%

Fogarty International Center collaborative networks in infectious disease modeling: Lessons learnt in research and capacity building

et al. 2019

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A B S T R A C TDue to a combination of ecological, political, and demographic factors, the emergence of novel pathogens has been increasingly observed in animals and humans in recent decades. Enhancing global capacity to study and interpret infectious disease surveillance data, and to develop data-driven computational models to guide policy, represents one of the most cost-effective, and yet overlooked, ways to prepare for the next pandemic. Epidemiological and behavioral data from recent pandemics and historic scourges have provided rich opportunities for validation of computational models, while new sequencing technologies and the 'big data' revolution present new tools for studying the epidemiology of outbreaks in real time. For the past two decades, the Division of International Epidemiology and Population Studies (DIEPS) of the NIH Fogarty International Center has spearheaded two synergistic programs to better understand and devise control strategies for global infectious disease threats. The Multinational Influenza Seasonal Mortality Study (MISMS) has strengthened global capacity to study the epidemiology and evolutionary dynamics of influenza viruses in 80 countries by organizing international research activities and training workshops. The Research and Policy in Infectious Disease Dynamics (RAPIDD) program and its precursor activities has established a network of global experts in infectious disease modeling operating at the research-policy interface, with collaborators in 78 countries. These activities have provided evidence-based recommendations for disease control, including during large-scale outbreaks of pandemic influenza, Ebola and Zika virus. Together, these programs have coordinated international collaborative networks to advance the study of emerging disease threats and the field of computational epidemic modeling. A global community of researchers and policy-makers have used the tools and trainings developed by these programs to interpret infectious disease patterns in their countries, understand modeling concepts, and inform control policies. Here we reflect on the scientific achievements and lessons learnt from these programs (hindex = 106 for RAPIDD and 79 for MISMS), including the identification of outstanding researchers and fellows; funding flexibility for timely research workshops and working groups (particularly relative to more traditional investigator-based grant programs); emphasis on group activities such as large-scale modeling reviews, model comparisons, forecasting challenges and special journal issues; strong quality control with a light touch on outputs; and prominence of training, data-sharing, and joint publications.

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Influenza seasonality goes south in the Yucatan Peninsula: The case for a different influenza vaccine calendar in this Mexican region

Cited by 7 publications

References 27 publications

Temporal distribution and genetic variants in influenza A(H1N1)pdm09 virus circulating in Mexico, seasons 2012 and 2013

Temporal distribution and genetic variants in influenza A(H1N1)pdm09 virus circulating in Mexico, seasons 2012 and 2013

Covid-19 em contexto: comparação com a mortalidade mensal por causas respiratórias nos estados brasileiros

Fogarty International Center collaborative networks in infectious disease modeling: Lessons learnt in research and capacity building

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