To what extent disparities between global mortality data reflect actual epidemiology or biases in research attention remains to be established, in part

hindered by current inadequacies in coinfection surveillance. The disparity between infections that feature highly in global mortality statistics and those receiving most attention in published coinfection studies poses a challenge to infectious disease research. A general understanding of the effects of coinfection is important for appropriate control of infectious diseases.4, 7, 8 and 35 Poor or uncertain observational data regarding coinfection hinders efforts to improve health strategies for infectious disease in at-risk populations.9 For example, global infectious disease mortality data28 report only single causes of death, even if comorbidities were identified. If health statistics better represent coinfection, published coinfection selleck compound research could be better evaluated. Moreover there is a lack of coherence in coinfection literature, with a variety of synonyms being used for the same phenomenon, which is multi-species infection (see the Methods for examples). CYC202 The term polymicrobial, while commonplace, is restricted

to coinfections involving microbes. Coinfection is a broader term encompassing all pathogen types including interactions between the same kinds of pathogens as well as cross-kingdom coinfections between, say, bacteria and helminths. Ultimately decisions over which term to prefer (if any) need to be made by a consensus of the diverse research communities concerned with this phenomenon. True patterns of coinfection remain unknown21 and our results suggest that it may be starkly different from existing data on important infectious diseases. Overall recently published reports of coinfection in humans show coinfection to be detrimental to human health. Understanding the nature and (-)-p-Bromotetramisole Oxalate consequences of coinfection is vital

for accurate estimates of infectious disease burden. In particular, more holistic data on infectious diseases would help to quantify the size of the effects on coinfection on human health. Improved knowledge of the factors controlling an individual’s risk of coinfection, circumstances when coinfecting pathogens interact, and the mechanisms behind these pathogen–pathogen interactions, especially from experimental studies, will also aid the design and evaluation of infectious disease management programmes. To date, most disease control programs typically adopt a vertical approach to intervention, dealing with each pathogen infection in isolation. If coinfecting pathogens generally interact to worsen human health, as suggested here, control measures may need to be more integrated and specialist treatments developed for clinical cases of coinfection.