Dataset Information

Identifying future zoonotic disease threats: Where are the gaps in our understanding of primate infectious diseases?

ABSTRACT:

Background and objectives

Emerging infectious diseases often originate in wildlife, making it important to identify infectious agents in wild populations. It is widely acknowledged that wild animals are incompletely sampled for infectious agents, especially in developing countries, but it is unclear how much more sampling is needed, and where that effort should focus in terms of host species and geographic locations. Here, we identify these gaps in primate parasites, many of which have already emerged as threats to human health.

Methodology

We obtained primate host-parasite records and other variables from existing databases. We then investigated sampling effort within primates relative to their geographic range size, and within countries relative to their primate species richness. We used generalized linear models, controlling for phylogenetic or spatial autocorrelation, to model variation in sampling effort across primates and countries. Finally, we used species richness estimators to extrapolate parasite species richness.

Results

We found uneven sampling effort within all primate groups and continents. Sampling effort among primates was influenced by their geographic range size and substrate use, with terrestrial species receiving more sampling. Our parasite species richness estimates suggested that, among the best sampled primates and countries, almost half of primate parasites remain to be sampled; for most primate hosts, the situation is much worse.

Conclusions and implications

Sampling effort for primate parasites is uneven and low. The sobering message is that we know little about even the best studied primates, and even less regarding the spatial and temporal distribution of parasitism within species.

SUBMITTER: Cooper N

PROVIDER: S-EPMC3868449 | biostudies-literature | 2013 Jan

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Identifying future zoonotic disease threats: Where are the gaps in our understanding of primate infectious diseases?

Cooper Natalie N Nunn Charles L CL

Evolution, medicine, and public health 20130122 1

<h4>Background and objectives</h4>Emerging infectious diseases often originate in wildlife, making it important to identify infectious agents in wild populations. It is widely acknowledged that wild animals are incompletely sampled for infectious agents, especially in developing countries, but it is unclear how much more sampling is needed, and where that effort should focus in terms of host species and geographic locations. Here, we identify these gaps in primate parasites, many of which have a ...[more]

PMID: 24481184

Similar Datasets

Project description:ObjectivesEradicated infectious diseases like smallpox can re-emerge through accident or the designs of bioterrorists, and cause heavy casualties. Presently, the populace is largely susceptible as only a small percentage is vaccinated, and their immunity is likely to have waned. And when the disease re-emerges, the susceptible individuals may be manipulated by disinformation on Social Media to refuse vaccines. Thus, a combination of countermeasures consisting of antiviral drugs and vaccines and a range of policies for their application need to be investigated. Opinions regarding whether to receive vaccines evolve over time through social exchanges via networks that overlap with but are not identical to the disease propagation networks. These couple the spread of the biological and information contagion and necessitate a joint investigation of the two.MethodsWe develop a computationally tractable metapopulation epidemiological model that captures the joint spatio-temporal evolution of an infectious disease (e.g., smallpox, COVID-19) and opinion dynamics.ResultsConsidering smallpox, the computations based on the model show that opinion dynamics have a substantial impact on the fatality count. Towards understanding how perpetrators are likely to seed the infection, we identify a) the initial distribution of infected individuals that maximize the overall fatality count; and b) which habitation structures are more vulnerable to outbreaks. We assess the relative efficacy of different countermeasures and conclude that a combination of vaccines and drugs minimize the fatalities, and by itself, drugs reduce fatalities more than the vaccine. Accordingly, we assess the impact of increase in the supply of drugs and identify the most effective among a collection of policies for administering of drugs for various parameter combinations. Many of the observed patterns are stable to variations of a diverse set of parameters.ConclusionsOur findings provide a quantitative foundation for various important elements of public health discourse that have largely been conducted qualitatively.

Project description:BackgroundInfectious diseases pose a significant threat to health and readiness of military personnel deployed globally during wartime and peacekeeping activities. Surveillance and improvement in mitigation through research of infectious disease threats remain an integral part of Force Health Protection. Herein, we review research efforts of the Infectious Disease Clinical Research Program related to deployment and travel-related infections.MethodsThe objectives of the Deployment and Travel-Related Infections Research Area are to (1) provide epidemiologic and clinical data, including pathogen-specific estimates of disease incidence among deployed troops, (2) execute clinical trials and effectiveness studies to improve recommendations regarding prevention and treatment of infections during deployment, and (3) evaluate the knowledge and practice patterns of health care providers engaged in deployment/travel medicine and the impact on outcomes. The centerpiece protocol of the research area is the Deployment and Travel-Related Infectious Disease Risk Assessment, Outcomes, and Prevention Strategies cohort study (TravMil), which was initiated in 2010 and collects data on a broad range of deployment-related infections.ResultsTo date, 4,154 deployed military personnel and traveling Department of Defense (DoD) beneficiaries have been enrolled in TravMil. Surveillance data collected through the TravMil study provide assessment of deployment and travel-related infectious disease threats, and the effectiveness of mitigation strategies. The incidence of travelers' diarrhea, influenza-like illness, and undifferentiated febrile illness is 20.48%, 9.34%, and 6.16%, respectively. The cohort study also provides necessary infrastructure to execute clinical trials. The TrEAT TD clinical trial evaluated the effectiveness of single-dose antibiotic therapy for travelers' diarrhea in the deployed setting. When compared to levofloxacin, azithromycin was not inferior; however, inferiority was not demonstrated with use of single dose of rifaximin. The trial findings supported the development of a deployment-related health guideline for the management of acute diarrheal disease. A clinical trial evaluating the effectiveness of rifaximin for prevention for travelers' diarrhea (Prevent TD) is underway.ConclusionsThe research area has proven its ability to conduct impactful research, including the development of field-expedient diagnostics, the largest DoD multi-site travelers' diarrhea randomized control trial in peacetime and combat settings, and informed Force Health Protection guidance. The research area continues to provide surveillance data to military commands via an established collaborative network of military treatment facilities, DoD laboratories (both within and outside the continental United States), foreign militaries, and academia. The conduct of clinical and translational research in a deployment setting presents significant challenges, most notably in recruitment/enrollment and compliance with study-related procedures during deployment.

Project description:Understanding complexity in healthcare has the potential to reduce decision and treatment uncertainty. Therefore, identifying both patient and task complexity may offer better task allocation and design recommendation for next-generation health information technology system design.To identify specific complexity-contributing factors in the infectious disease domain and the relationship with the complexity perceived by clinicians.We observed and audio recorded clinical rounds of three infectious disease teams. Thirty cases were observed for a period of four consecutive days. Transcripts were coded based on clinical complexity-contributing factors from the clinical complexity model. Ratings of complexity on day 1 for each case were collected. We then used statistical methods to identify complexity-contributing factors in relationship to perceived complexity of clinicians.A factor analysis (principal component extraction with varimax rotation) of specific items revealed three factors (eigenvalues>2.0) explaining 47% of total variance, namely task interaction and goals (10 items, 26%, Cronbach's Alpha=0.87), urgency and acuity (6 items, 11%, Cronbach's Alpha=0.67), and psychosocial behavior (4 items, 10%, Cronbach's alpha=0.55). A linear regression analysis showed no statistically significant association between complexity perceived by the physicians and objective complexity, which was measured from coded transcripts by three clinicians (Multiple R-squared=0.13, p=0.61). There were no physician effects on the rating of perceived complexity.Task complexity contributes significantly to overall complexity in the infectious diseases domain. The different complexity-contributing factors found in this study can guide health information technology system designers and researchers for intuitive design. Thus, decision support tools can help reduce the specific complexity-contributing factors. Future studies aimed at understanding clinical domain-specific complexity-contributing factors can ultimately improve task allocation and design for intuitive clinical reasoning.

Project description:BackgroundAs demonstrated during the global Ebola crisis of 2014-2016, healthcare institutions in high resource settings need support concerning preparedness during threats of infectious disease outbreaks. This study aimed to exploratively develop a standardized preparedness system to use during unfolding threats of severe infectious diseases.MethodsA qualitative three-step study among infectious disease prevention and control experts was performed. First, interviews (n = 5) were conducted to identify which factors trigger preparedness activities during an unfolding threat. Second, these triggers informed the design of a phased preparedness system which was tested in a focus group discussion (n = 5) were conducted to identify which factors trigger preparedness activities during an unfolding threat. Second, these triggers informed the design of a phased preparedness system which was tested in a focus group discussion (n = 5) were conducted to identify which factors trigger preparedness activities during an unfolding threat. Second, these triggers informed the design of a phased preparedness system which was tested in a focus group discussion (.ResultsFour preparedness phases were identified: preparedness phase green is a situation without the presence of the infectious disease threat that requires centralized care, anywhere in the world. Phase yellow is an outbreak in the world with some likelihood of imported cases. Phase orange is a realistic chance of an unexpected case within the country, or unrest developing among population or staff; phase red is cases admitted to hospitals in the country, potentially causing a shortage of resources. Specific preparedness activities included infection prevention, diagnostics, patient care, staff, and communication. Consensus was reached on the need for the development of a preparedness system and national coordination during threats.ConclusionsIn this study, we developed a standardized system to support institutional preparedness during an increasing threat. Use of this system by both curative healthcare institutions and the (municipal) public health service, could help to effectively communicate and align preparedness activities during future threats of severe infectious diseases.

Dataset Information

Identifying future zoonotic disease threats: Where are the gaps in our understanding of primate infectious diseases?

Background and objectives

Methodology

Results

Conclusions and implications

Publications

Identifying future zoonotic disease threats: Where are the gaps in our understanding of primate infectious diseases?

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets