BackgroundHuman infections with highly pathogenic avian influenza (HPAI) A (H5N1) viruses have occurred in 15 countries, with high mortality to date. Determining risk factors for morbidity and mortality from HPAI H5N1 can inform preventive and therapeutic interventions.MethodsWe included all cases of human HPAI H5N1 reported in World Health Organization Global Alert and Response updates and those identified through a systematic search of multiple databases (PubMed, Scopus, and Google Scholar), including articles in all languages. We abstracted predefined clinical and demographic predictors and mortality and used bivariate logistic regression analyses to examine the relationship of each candidate predictor with mortality. We developed and pruned a decision tree using nonparametric Classification and Regression Tree methods to create risk strata for mortality.FindingsWe identified 617 human cases of HPAI H5N1 occurring between December 1997 and April 2013. The median age of subjects was 18 years (interquartile range 6–29 years) and 54% were female. HPAI H5N1 case-fatality proportion was 59%. The final decision tree for mortality included age, country, per capita government health expenditure, and delay from symptom onset to hospitalization, with an area under the receiver operator characteristic (ROC) curve of 0.81 (95% CI: 0.76–0.86).InterpretationA model defined by four clinical and demographic predictors successfully estimated the probability of mortality from HPAI H5N1 illness. These parameters highlight the importance of early diagnosis and treatment and may enable early, targeted pharmaceutical therapy and supportive care for symptomatic patients with HPAI H5N1 virus infection.

BackgroundHuman cases of highly pathogenic avian influenza (HPAI) A (H5N1) have high mortality. Despite abundant data on seasonal patterns in influenza epidemics, it is unknown whether similar patterns exist for human HPAI H5N1 cases worldwide. Such knowledge could help decrease avian-to-human transmission through increased prevention and control activities during peak periods.MethodsWe performed a systematic search of published human HPAI H5N1 cases to date, collecting month, year, country, season, hemisphere, and climate data. We used negative binomial regression to predict changes in case incidence as a function of season. To investigate hemisphere as a potential moderator, we used AIC and the likelihood-ratio test to compare the season-only model to nested models including a main effect or interaction with hemisphere. Finally, we visually assessed replication of seasonal patterns across climate groups based on the Köppen-Geiger climate classification.FindingsWe identified 617 human cases (611 with complete seasonal data) occurring in 15 countries in Southeast Asia, Africa, and the Middle East. Case occurrence was much higher in winter (n = 285, p = 0.03) than summer (n = 64), and the winter peak occurred across diverse climate groups. There was no significant interaction between hemisphere and season.InterpretationAcross diverse climates, HPAI H5N1 virus infection in humans increases significantly in winter. This is consistent with increased poultry outbreaks and HPAI H5N1 virus transmission during cold and dry conditions. Prioritizing prevention and control activities among poultry and focusing public health messaging to reduce poultry exposures during winter months may help to reduce zoonotic transmission of HPAI H5N1 virus in resource-limited settings.

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