Dataset Information

Sex bias in infectious disease epidemiology: patterns and processes.

ABSTRACT:

Background

Infectious disease incidence is often male-biased. Two main hypotheses have been proposed to explain this observation. The physiological hypothesis (PH) emphasizes differences in sex hormones and genetic architecture, while the behavioral hypothesis (BH) stresses gender-related differences in exposure. Surprisingly, the population-level predictions of these hypotheses are yet to be thoroughly tested in humans.

Methods and findings

For ten major pathogens, we tested PH and BH predictions about incidence and exposure-prevalence patterns. Compulsory-notification records (Brazil, 2006-2009) were used to estimate age-stratified ?:? incidence rate ratios for the general population and across selected sociological contrasts. Exposure-prevalence odds ratios were derived from 82 published surveys. We estimated summary effect-size measures using random-effects models; our analyses encompass ?0.5 million cases of disease or exposure. We found that, after puberty, disease incidence is male-biased in cutaneous and visceral leishmaniasis, schistosomiasis, pulmonary tuberculosis, leptospirosis, meningococcal meningitis, and hepatitis A. Severe dengue is female-biased, and no clear pattern is evident for typhoid fever. In leprosy, milder tuberculoid forms are female-biased, whereas more severe lepromatous forms are male-biased. For most diseases, male bias emerges also during infancy, when behavior is unbiased but sex steroid levels transiently rise. Behavioral factors likely modulate male-female differences in some diseases (the leishmaniases, tuberculosis, leptospirosis, or schistosomiasis) and age classes; however, average exposure-prevalence is significantly sex-biased only for Schistosoma and Leptospira.

Conclusions

Our results closely match some key PH predictions and contradict some crucial BH predictions, suggesting that gender-specific behavior plays an overall secondary role in generating sex bias. Physiological differences, including the crosstalk between sex hormones and immune effectors, thus emerge as the main candidate drivers of gender differences in infectious disease susceptibility.

SUBMITTER: Guerra-Silveira F

PROVIDER: S-EPMC3634762 | biostudies-literature | 2013

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Sex bias in infectious disease epidemiology: patterns and processes.

Guerra-Silveira Felipe F Abad-Franch Fernando F

PloS one 20130424 4

<h4>Background</h4>Infectious disease incidence is often male-biased. Two main hypotheses have been proposed to explain this observation. The physiological hypothesis (PH) emphasizes differences in sex hormones and genetic architecture, while the behavioral hypothesis (BH) stresses gender-related differences in exposure. Surprisingly, the population-level predictions of these hypotheses are yet to be thoroughly tested in humans.<h4>Methods and findings</h4>For ten major pathogens, we tested PH a ...[more]

PMID: 23638062

Similar Datasets

Project description:Bycatch is a common occurrence in heavily fished areas such as the Fraser River, British Columbia, where fisheries target returning adult Pacific salmon (Oncorhynchus spp.) en route to spawning grounds. The extent to which these encounters reduce fish survival through injury and physiological impairment depends on multiple factors including capture severity, river temperature and infectious agents. In an effort to characterize the mechanisms of post-release mortality and address fishery and managerial concerns regarding specific regulations, wild-caught Early Stuart sockeye salmon (Oncorhynchus nerka) were exposed to either mild (20 s) or severe (20 min) gillnet entanglement and then held at ecologically relevant temperatures throughout their period of river migration (mid-late July) and spawning (early August). Individuals were biopsy sampled immediately after entanglement and at death to measure indicators of stress and immunity, and the infection intensity of 44 potential pathogens. Biopsy alone increased mortality (males: 33%, females: 60%) when compared with non-biopsied controls (males: 7%, females: 15%), indicating high sensitivity to any handling during river migration, especially among females. Mortality did not occur until 5-10 days after entanglement, with severe entanglement resulting in the greatest mortality (males: 62%, females: 90%), followed by mild entanglement (males: 44%, females: 70%). Infection intensities of Flavobacterium psychrophilum and Ceratonova shasta measured at death were greater in fish that died sooner. Physiological indicators of host stress and immunity also differed depending on longevity, and indicated anaerobic metabolism, osmoregulatory failure and altered immune gene regulation in premature mortalities. Together, these results implicate latent effects of entanglement, especially among females, resulting in mortality days or weeks after release. Although any entanglement is potentially detrimental, reducing entanglement durations can improve post-release survival.

Project description:BackgroundA myriad of new tools and algorithms have been developed to help public health professionals analyze and visualize the complex data used in infectious disease control. To better understand approaches to meet these users' information needs, we conducted a systematic literature review focused on the landscape of infectious disease visualization tools for public health professionals, with a special emphasis on geographic information systems (GIS), molecular epidemiology, and social network analysis. The objectives of this review are to: (1) identify public health user needs and preferences for infectious disease information visualization tools; (2) identify existing infectious disease information visualization tools and characterize their architecture and features; (3) identify commonalities among approaches applied to different data types; and (4) describe tool usability evaluation efforts and barriers to the adoption of such tools.MethodsWe identified articles published in English from January 1, 1980 to June 30, 2013 from five bibliographic databases. Articles with a primary focus on infectious disease visualization tools, needs of public health users, or usability of information visualizations were included in the review.ResultsA total of 88 articles met our inclusion criteria. Users were found to have diverse needs, preferences and uses for infectious disease visualization tools, and the existing tools are correspondingly diverse. The architecture of the tools was inconsistently described, and few tools in the review discussed the incorporation of usability studies or plans for dissemination. Many studies identified concerns regarding data sharing, confidentiality and quality. Existing tools offer a range of features and functions that allow users to explore, analyze, and visualize their data, but the tools are often for siloed applications. Commonly cited barriers to widespread adoption included lack of organizational support, access issues, and misconceptions about tool use.Discussion and conclusionAs the volume and complexity of infectious disease data increases, public health professionals must synthesize highly disparate data to facilitate communication with the public and inform decisions regarding measures to protect the public's health. Our review identified several themes: consideration of users' needs, preferences, and computer literacy; integration of tools into routine workflow; complications associated with understanding and use of visualizations; and the role of user trust and organizational support in the adoption of these tools. Interoperability also emerged as a prominent theme, highlighting challenges associated with the increasingly collaborative and interdisciplinary nature of infectious disease control and prevention. Future work should address methods for representing uncertainty and missing data to avoid misleading users as well as strategies to minimize cognitive overload.

Dataset Information

Sex bias in infectious disease epidemiology: patterns and processes.

Background

Methods and findings

Conclusions

Publications

Sex bias in infectious disease epidemiology: patterns and processes.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets