Browsing by Author "Spreeuwenberg, Peter"
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- Distribution of influenza virus types by age using case-based global surveillance data from twenty-nine countries, 1999-2014Publication . Caini, Saverio; Spreeuwenberg, Peter; Kusznierz, Gabriela F.; Rudi, Juan Manuel; Owen, Rhonda; Pennington, Kate; Wangchuk, Sonam; Gyeltshen, Sonam; Ferreira de Almeida, Walquiria Aparecida; Pessanha Henriques, Cláudio Maierovitch; Njouom, Richard; Vernet, Marie-Astrid; Fasce, Rodrigo A.; Andrade, Winston; Yu, Hongjie; Feng, Luzhao; Yang, Juan; Peng, Zhibin; Lara, Jenny; Bruno, Alfredo; de Mora, Doménica; de Lozano, Celina; Zambon, Maria; Pebody, Richard; Castillo, Leticia; Clara, Alexey W.; Matute, Maria Luisa; Kosasih, Herman; Nurhayati, null; Puzelli, Simona; Rizzo, Caterina; Kadjo, Herve A; Daouda, Coulibaly; Kiyanbekova, Lyazzat; Ospanova, Akerke; Mott, Joshua A.; Emukule, Gideon O.; Heraud, Jean-Michel; Razanajatovo, Norosoa Harline; Barakat, Amal; El Falaki, Fatima; Huang, Sue Q.; Lopez, Liza; Balmaseda, Angel; Moreno, Brechla; Rodrigues, Ana Paula; Guiomar, Raquel; Ang, Li Wei; Lee, Vernon Jian Ming; Venter, Marietjie; Cohen, Cheryl; Badur, Selim; Ciblak, Meral A.; Mironenko, Alla; Holubka, Olha; Bresee, Joseph; Brammer, Lynnette; Hoang, Phuong Vu Mai; Le, Mai Thi Quynh; Fleming, Douglas; Séblain, Clotilde El-Guerche; Schellevis, François; Paget, John; Global Influenza B Study groupBackground: Influenza disease burden varies by age and this has important public health implications. We compared the proportional distribution of different influenza virus types within age strata using surveillance data from twenty-nine countries during 1999-2014 (N=358,796 influenza cases). Methods: For each virus, we calculated a Relative Illness Ratio (defined as the ratio of the percentage of cases in an age group to the percentage of the country population in the same age group) for young children (0-4 years), older children (5-17 years), young adults (18-39 years), older adults (40-64 years), and the elderly (65+ years). We used random-effects meta-analysis models to obtain summary relative illness ratios (sRIRs), and conducted meta-regression and sub-group analyses to explore causes of between-estimates heterogeneity. Results: The influenza virus with highest sRIR was A(H1N1) for young children, B for older children, A(H1N1)pdm2009 for adults, and (A(H3N2) for the elderly. As expected, considering the diverse nature of the national surveillance datasets included in our analysis, between-estimates heterogeneity was high (I2>90%) for most sRIRs. The variations of countries’ geographic, demographic and economic characteristics and the proportion of outpatients among reported influenza cases explained only part of the heterogeneity, suggesting that multiple factors were at play. Conclusions: These results highlight the importance of presenting burden of disease estimates by age group and virus (sub)type.
- Global mortality associated with seasonal influenza epidemics: New burden estimates and predictors from the GLaMOR ProjectPublication . Paget, John; Spreeuwenberg, Peter; Charu, Vivek; Taylor, Robert J.; Iuliano, A Danielle; Bresee, Joseph; Simonsen, Lone; Viboud, Cecile; Global Seasonal Influenza-associated Mortality Collaborator Network; GLaMOR Collaborating TeamBackground: Until recently, the World Health Organization (WHO) estimated the annual mortality burden of influenza to be 250 000 to 500 000 all-cause deaths globally; however, a 2017 study indicated a substantially higher mortality burden, at 290 000-650 000 influenza-associated deaths from respiratory causes alone, and a 2019 study estimated 99 000-200 000 deaths from lower respiratory tract infections directly caused by influenza. Here we revisit global and regional estimates of influenza mortality burden and explore mortality trends over time and geography. Methods: We compiled influenza-associated excess respiratory mortality estimates for 31 countries representing 5 WHO regions during 2002-2011. From these we extrapolated the influenza burden for all 193 countries of the world using a multiple imputation approach. We then used mixed linear regression models to identify factors associated with high seasonal influenza mortality burden, including influenza types and subtypes, health care and socio-demographic development indicators, and baseline mortality levels. Results: We estimated an average of 389 000 (uncertainty range 294 000-518 000) respiratory deaths were associated with influenza globally each year during the study period, corresponding to ~ 2% of all annual respiratory deaths. Of these, 67% were among people 65 years and older. Global burden estimates were robust to the choice of countries included in the extrapolation model. For people <65 years, higher baseline respiratory mortality, lower level of access to health care and seasons dominated by the A(H1N1)pdm09 subtype were associated with higher influenza-associated mortality, while lower level of socio-demographic development and A(H3N2) dominance was associated with higher influenza mortality in adults ≥65 years. Conclusions: Our global estimate of influenza-associated excess respiratory mortality is consistent with the 2017 estimate, despite a different modelling strategy, and the lower 2019 estimate which only captured deaths directly caused by influenza. Our finding that baseline respiratory mortality and access to health care are associated with influenza-related mortality in persons <65 years suggests that health care improvements in low and middle-income countries might substantially reduce seasonal influenza mortality. Our estimates add to the body of evidence on the variation in influenza burden over time and geography, and begin to address the relationship between influenza-associated mortality, health and development.