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Our objective was to determine the frequency of zika (ZIKV), chikungunya (CHIKV) and dengue (DENV) virus coinfection and describe the mortality cases that occurred during the epidemiologic surveillance of the ZIKV epidemic in Colombia. We analysed all cases of suspected ZIKV infection that were reported to the National Institute of Health (October 2015-December 2016). DENV, CHIKV and ZIKV RNA were detected in serum or tissue samples using polymerase chain reaction assay. Medical records of the fatal cases were reviewed. We identified that 23 871 samples were processed. The frequency of viral agents was 439 (1.84%) for DENV, 257 (1.07%) for CHIKV and 10118 (42.38%) for ZIKV. Thirty-four (0.14%) cases of coinfection were identified. The CHIKV-ZIKV coinfection was present in 28 cases (82.3%), DENV-CHIKV in three (8.8%) and DENV-ZIKV in three (8.8%). Seven (20.6%) coinfection cases were fatal (two DENV-CHIKV cases and five CHIKV-ZIKV cases). Two cases were foetal deaths and the others were related to neurological syndrome and sepsis. In conclusion, the frequency of arbovirus coinfection during epidemic of ZIKV was low, and CHIKV-ZIKV coinfection was the most common. Mortality was high among coinfection patients. The role of each virus in the mortality cases of coinfection warrants further studies.

Objectives: The pneumonia severity index and CURB-65 are risk assessment tools widely used in community-acquired pneumonia (CAP). However, limitations in these prognostic scores have led to increasing interest in finding biomarkers that might provide additional information. To date, the role of these biomarkers has not been fully elucidated., Methods: We systematically searched the Medline, Web of Knowledge, Science Direct, and LILACS databases. We included studies that assessed the accuracy of biomarkers for the prediction of in-hospital or ≤30-day mortality, in hospitalized adults with CAP. Two independent investigators extracted patient and study characteristics, which were thereafter pooled using a random effects model. Relationships between sensitivity and specificity of biomarkers and prognostic scores were plotter using the area under the receiver operator characteristic curve (AUC)., Results: We included 24 articles and 2 databases from 1069 reviewed abstracts, which provided 10,319 patients for analysis. Reported mortality rates varied from 2.4% to 34.6%. The highest AUC values for predicting mortality were associated with pro-adrenomedullin (0.80) and prohormone forms of atrial natriuretic peptide (0.79), followed by cortisol (0.78), procalcitonin (0.75), copeptin (0.71), and C-reactive protein (0.62). There were no statistically significant differences between the AUCs of the studied biomarkers, other than for copeptin and C-reactive protein, which performed comparatively poorly. When compared with the CAP-specific scores, the AUCs were not significantly different from those of most biomarkers., Conclusions: The identified biomarkers are able to predict mortality with moderate to good accuracy in CAP. However, biomarkers have no clear advantage over CAP-specific scores for predicting mortality., (Copyright © 2016 The British Infection Association. Published by Elsevier Ltd. All rights reserved.)