Abstract
Influenza epidemiology differs substantially in tropical and temperate zones, but estimates of seasonal influenza mortality in developing countries in the tropics are lacking. We aimed to quantify mortality due to seasonal influenza in Thailand, a tropical middle-income country. Time series of polymerase chain reaction–confirmed influenza infections between 2005 and 2009 were constructed from a sentinel surveillance network. These were combined with influenza-like illness data to derive measures of influenza activity and relationships to mortality by using a Bayesian regression framework. We estimated 6.1 (95% credible interval: 0.5, 12.4) annual deaths per 100,000 population attributable to influenza A and B, predominantly in those aged ≥60 years, with the largest contribution from influenza A(H1N1) in 3 out of 4 years. For A(H3N2), the relationship between influenza activity and mortality varied over time. Influenza was associated with increases in deaths classified as resulting from respiratory disease (posterior probability of positive association, 99.8%), cancer (98.6%), renal disease (98.0%), and liver disease (99.2%). No association with circulatory disease mortality was found. Seasonal influenza infections are associated with substantial mortality in Thailand, but evidence for the strong relationship between influenza activity and circulatory disease mortality reported in temperate countries is lacking.
Highlights
The World Health Organization asserts that seasonal influenza results in 250,000–500,000 deaths annually in industrialized countries [1]
Very little is currently known about mortality due to seasonal influenza in the tropics with the exception of one very highly developed and fully urbanized population, Singapore [4, 5]
A major challenge in estimating seasonal influenza mortality is that symptoms are nonspecific, and few patients are tested for active influenza
Summary
The World Health Organization asserts that seasonal influenza results in 250,000–500,000 deaths annually in industrialized countries [1]. It is evident that, for most deaths where influenza is likely to have played a causal role, no mention of influenza is given as the cause of death [2, 4,5,6,7] To overcome these limitations, approaches have been developed to estimate influenza-related mortality by using routine surveillance data [2, 4,5,6,7,8,9,10,11,12]. A seminal approach, the Serfling model [9], used a sine wave to model the regular seasonal component of variation and a polynomial in time to account for long-term trends Mortality exceeding this baseline model in “epidemic months” is termed “excess mortality.”.
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