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Displaying 10 papers, 240 pages, start at 1, 37 Hits
29 section matches

Keywords

Spatial clusters; spatial scan statistic; zero-inflated Poisson (1). However, this system may not represent the true epidemic situation of infectious disease in community, particularly those who do not seek medical care (2) . Moreover, the epidemiological settings, sources of the infection and social network all together may still facilitate the transmissions. These rooted problems cannot be rapidly solved.

Conclusions

In conclusion, easily defined syndrome groups for public surveillance is feasible and can complement with traditional passive surveillance systems. More potential case can be detected earlier, particularly those who do not seek medical care. Certainly, this newly developed and user-friendly surveillance system can be applied to study transmission of infectious disease within socialnetwork and also to allow public's participating surveillance leading to public health efforts in disease prevention will be no longer limited to healthcare system and thus become more effective.

Methods

Taiwan's Mortality Information Regulations require medical institutions to report any mortality to DOH through the National Death Certificate System (NDCS) within 7 days after a death certification is issued. Automated data from the NDCS were daily submitted to TCDC by secure electronic transmission and processed and analyzed using SAS Enterprise Guide 4.3 (SAS Institute Inc, Cary, NC). For each report, the underlying cause of death was determined by applying the World Health Organization classification principles (2) and searched for freetext traditional Chinese 'pneumonia', 'influenza', or 'flu' to identify P&I deaths. Reporting timeliness and completeness of this surveillance system was assessed by comparing reporting data with post-hoc mortality statistics for the year of 2008. We used an R-package 'surveillance' to detect aberrations in the P&I mortality weekly data (3) .

Introduction

It is admitted that real time surveillance system permits to reduce delay of outbreak detection and preventive measures implementation (1) . It is usually based on prediagnostic numeric data collection and transmission (2) . ASTER (Alerte et surveillance en temps réel) is a real time surveillance system for French Armed Forces deployed in French Guiana and Djibouti ( Fig. 1) , constituted by 2 kinds of networks: several declaration networks and one analysis network (3). On June 2011, an outbreak occurred among a French Army Regiment in Djibouti, which has permitted to evaluate ASTER in real conditions.

Conclusions

To effectively perform surveillance, public health agencies require access to 'timely, accurate, and complete data' (4) . Unfortunately, data quality is an issue for many clinical information systems that capture data utilized in public health surveillance processes. This study assessed the completeness of real-world ELR data from multiple provider organizations using a variety of laboratory information systems, documenting evidence that ELR data are heterogeneous in their completeness across and within information systems. In many cases, data important to public health surveillance processes are missing, indicating suboptimal ELR data quality. The study further documented evidence that a statewide or regional HIE can employ methods to mitigate ELR data deficiencies, leading to improvements in the completeness of ELR data prior to transmission to public health agencies.

Results

Of the 894 outbreaks documenting year of occurrence, 72% occurred between 2000 and 2010. More than 90% of outbreaks occurred in the northern hemisphere and 45% took place during the winter. In general, we found the number of primary cases and persons at risk was significantly lower in outbreaks related to food and waterborne transmission as well as foodservice and healthcare settings. The attack rates were significantly higher in outbreaks related to food, water and those that occurred in the winter. Attack rates were also lower in healthcare-related outbreaks, perhaps on account of proper infection control practices and active surveillance by healthcare facilities to limit the spread of disease.

Conclusions

Food and waterborne outbreaks may have greater attack rates due to: (1) efficient viral transmission, especially within smaller confines, via drinking water or food items, and (2) more accurate identification of persons at risk.
Decreased mobility of infected persons in healthcare settings may also limit transmission of NoV to healthy individuals. As mentioned previously, the clustering of people indoors during seasonal cold weather may facilitate person-to-person NoV transmission. These results identify important trends for epidemic NoV detection, prevention and control.

Introduction

Modern public health surveillance systems have great potential for improving public health. However, evaluating the performance of surveillance systems is challenging because examples of baseline disease distribution in the population are limited to a few years of data collection. Agent-based simulations of infectious disease transmission in highly detailed synthetic populations can provide unlimited realistic baseline data.

Conclusions

Highly detailed simulations of infectious disease transmission can be configured to represent nearly infinite scenarios, making them a powerful tool for evaluating the performance of surveillance systems and the methods used for outbreak detection.

Methods

We selected a series of providers using NYC DOHMH's EHR network, from which we could obtain practice characteristics (i.e., number of patient visits, type of practice and age distribution) and evaluation score developed to rate a practice's ability to use EHRs. We then set up an electronic template at each practice and scheduled the transmission of a report with de-identified patient characteristics and patient counts. Nasopharyngeal samples were collected from each patient presenting with ILI to test for influenza subtypes including influenza A (H1, H3 and H1N1) and influenza B by RT-PCR. Samples negative for influenza were tested for other respiratory viruses including rhinovirus, metapneumovirus (MPV), respiratory syncytial virus (RSV), parainfluenza virus (PIV) and adenovirus by RT-PCR by Luminex. We analyzed the data for completeness to evaluate the success of electronic surveillance. We also compared the data by gender, age group, symptoms as well as evaluated virus frequency over time.

Results

Disease awareness questionnaires, educational materials and further details of our study design will be presented at the conference. The anticipated increase in knowledge about risk practices associated with the transmission of brucellosis from animals in at-risk populations should lead to a reduction in human cases of brucellosis in the intervention group, compared to control groups.

Conclusions

The epidemiology of brucellosis among humans and animals is well-characterized. Preventive measures for the diseases are well known; yet, applying this knowledge in resource-poor countries remains a constant challenge. Having effective health education programs is a vital component in efforts to reduce the disease burden by reducing the animal-to-human transmission rate. (3) an isolated case, uninvolved in recent transmission (i.e., neither source nor recipient). Source and secondary cases require more intense intervention due to their involvement in a chain of transmission; thus, accurate and rapid classification of new patients should help public health personnel to effectively prioritize control activities. However, the currently accepted method for classification, DNA fingerprint analysis, takes many weeks to produce the results (1); therefore, public health personnel often solely rely on their intuition to identify the case who is most likely to be involved in transmission.

Keywords

Various clinical and sociodemographic features are known to be associated with TB transmission (2). By using these readily available data at the time of diagnosis, it is possible to rapidly estimate the probabilities of the case being source, secondary and isolated.

Conclusions

Performance of the prediction model was promising as it was significantly better than random prediction (i.e., the AUCs were higher than 0.5). Small proportions of source and secondary cases in the available data may have limited performance. However, the model can be an effective decision support tool if its ability to identify a case likely to be involved in transmission is superior to the intuition of public health officials. Thus, further evaluation of the model in the context of TB control program should be conducted. If effective, the model would be particularly useful when incidence of TB increases in a resource limited setting, in which efficient prioritization of investigation is desired. Overall, the current study has important implications in promoting the approach of evidence-based practice in control of TB.

Keywords

Tuberculosis; transmission; prediction model; public health; decision support

Results

The literature demonstrates the many diverse, yet successful, syndromic surveillance efforts being implemented at the national and regional levels. Existing systems utilize a variety of data sources, data transmission techniques and analysis methodologies, ranging from low-tech, highly manual systems to automated, electronic systems. Frequently, syndromic surveillance systems are a coordinated effort among several partners, supplement existing systems, incorporate both specific and nonspecific disease detection and are used in conjunction with laboratory-based surveillance.

Mobile technology; informatics; open source; low resource settings; surveillance systems

Introduction Disease screening facilitates the reduction of disease prevalence in two ways: (1) by preventing transmission and (2) allowing for treatment of infected individuals. Hospitals choosing an optimal screening level must weigh the benefits of decreased prevalence against the costs of screening and subsequent treatment. If screening decisions are made by multiple decision units (DU; e.g., hospital wards), then they must consider the disease prevalence among admissions to their unit. Thus, the screening decisions made by one DU directly affect the disease prevalence of the other units when patients are shared.

Results

Retrospective review of Argus reports later identified 3 key factors that limited the effectiveness of disease management in the region: (1) a lack of government leadership and accountability, (2) poor sanitation leading to an inability to decrease the vector population and (3) an inadequate regional healthcare infrastructure (4) . Media sources recognized discrepancies in medical information provided by health officials and the medical community, and as the outbreak continued, protests erupted over poor sanitary conditions and insufficient medical resources as observed by healthcare workers. In August, the Minister of Health (MOH) declared that the outbreak had been 'controlled'; however, the media continued to report human plague cases and noted concern regarding the potential danger of plague spreading to urban markets. Travel restrictions were applied and reports later speculated that the World Health Organization (WHO) would close ports and issue a national quarantine if plague extended into coastal export areas (5, 6) . Further, officials declared a latent risk of disease transmission to bordering countries. At the end of the study reporting timeframe, media continued to identify the confirmation of new human bubonic plague cases, the implementation of vector control efforts, and the ongoing risk to residents despite attempted disease management efforts.
Disadvantages of using Distribute include limitations in the common data transmission format, limitations in stratifiers and limitations in compartmentalization.

Introduction

Detection of the signs of HIV epidemic transition from concentrated to generalized stage is an important issue for many countries including Ukraine. Objective and timely detection of the generalization of HIV epidemic is a significant factor for the development and implementation of appropriate preventive programs. As an additional method for estimating HIV epidemic stage, the spatial analysis of the reported new HIV cases among injection drug users (IDU) and other populations (due to sexual way of transmission) has been recommended. For studying new HIV cases in small societies, relative risk (RR) rates are preferred over incidence indicators. Spatial clustering based on the calculation of RR rates allows us to locate the high-risk areas of HIV infection with greater accuracy.
In our opinion, in the process of epidemic generalization, the spatial divergence of epidemic will be observed as well. In particular, clusters with high RR of sexual HIV transmission independent from the clusters with high RR of injection HIV transmission may appear.

Methods

We used spatial clustering based on reported HIV cases acquired through IDU and sexual transmission from 1994 to 2009 in the smallest administrative units (called Radas) in the rural territory of the Odessa region, Ukraine. For the formal spatial clustering, we used Kulldolf Spatial Statistics, realized in the SatScan program. Clustering was conducted by the Poisson model. We used the circle window and set the cluster size limit empirically at 15% of the at-risk population. The study was done in clusters with high RR.

Results

With clustering, the HIV incidence due to IDU and sexual intercourse were mostly identical in the 1994Á1999 and 2000Á 2004 periods. However, three spatial clusters of sexually acquired HIV emerged in the 2005Á2009 period (RR 0 3.44, p 0 0.0005; RR 0 10.60, p0 0.011; RR 0 2.18, p 0 0.0265), which did not correspond to an increased RR of IDU-acquired HIV (see Fig. 1 ). Proportion of Radas, simultaneously included in the clusters of both types of HIV transmission, decreased from 64.58% in 2000Á2004 to 48.33% in 2005Á2009.
To test the effectiveness of the method, we compared the number of Radas where HIV cases were registered due to sexual transmission only and were not detected due to IDU. In the 2005Á2009 period, we observed an increase in the number of Radas reporting sexually acquired HIV cases but not IDUacquired HIV cases.
Of the 52 case-seeking reports posted on Epi-X during calendar year 2010, all were posted with the intent of seeking cases of illness caused by infectious disease. One report was broad based and also sought cases of illness caused by injury. These reports were categorized by type of infectious agent, depending upon commonality of symptoms and routes of transmission. Epi-X contributors posted case-seeking reports for 19 individual confirmed or suspected infectious agents in 2010. The top four infectious agents for which case-seeking reports were posted on Epi-X in 2010 were Salmonella (10 reports), Legionella (9), hepatitis A virus (4) and measles virus (4) . Other infectious agents included Influenza, Bordetella, Cryptosporidium, Escherichia coli and Listeria. Three reports were posted for which the infectious agent was unknown.

Methods

In 2011, NH DPHS initiated a project with Orion Health to build a Rhapsody integration engine (1) portal to receive the three types of Public Health data. A Syndromic surveillance pilot was chosen since 25 of 26 hospitals were already sending real-time data in HL7 format to the statewide syndromic surveillance system. NH DPHS collaborated with the NH Regional Extension Center (REC) to host MU guidance and brokered with Orion Health, the Office of the National Coordinator (ONC), and CMS to offer hospitals the option to use a modular certification for MU public health measures by selecting the Orion Health module (2) . Selecting this module allows hospitals to send data to the NH DPHS Rhapsody portal in whatever format they choose; then, the NH DPHS Rhapsody system converts these messages to the approved ONC standards for public health reporting. Orion Health contractors set up the Rhapsody server, configured data routes and built validation, filtering, and mapping logic. Mapping to HL7 2.5.1 was performed, but additional mapping to 2.3.1 was done before sending data to the syndromic surveillance application. Hospitals were directed to reroute data transmissions to the new Rhapsody VPN IP address and port, and Rhapsody was configured to pass traffic to the original surveillance application address and port. Additionally, data was sent through the normal VPN connection to compare the accuracy and performance of the new path.

Results

Negligible syndromic surveillance processing time degradation was realized with the added Rhapsody processing. This processing allowed NH DPHS to implement its last acute care hospital into the existing syndromic surveillance application (using Rhapsody mapping), filter existing hospital syndromic surveillance transmissions on specific patient types (preventing unwanted types), receive MU ELR and immunization data prior to expected timelines, increase hospital MU certification reimbursement without additional MU expenditure and decrease the hospital laboratory staff reporting burden, which previously was manual.

Methods

This together with a 'Google'-like query tool allow NH surveillance staff to quickly assess any situation. Recently, a single portal infrastructure, based on AHEDD, was created to receive all external syndromic surveillance, Electronic Lab Reporting and immunization transmissions, helping hospital partners meet Meaningful Use (MU), which paves the way for integration with a statewide Health Information Exchange.
1 section matches

ID26 ECTOPARASITES AND VECTOR-BORNE PATHOGENS OF

Vector-borne agents detected to date likely reflect common exposure to R. sanguineus, as this tick vectors each of the PCRconfirmed agents. Further information will be gained by completion of the PCR assay analysis of the blood, fleas, and ticks. Canine group settings, locations or events where dogs temporarily come together in a shared environment (e.g., shows, sporting events, dog parks) pose an increased risk for infectious disease transmission. Despite this increased risk, few guidelines exist to provide recommendations for reducing disease risk in these settings. During 2014-2015 a panel of canine infectious disease experts reviewed the current literature and drafted a set of 44 evidence-based recommendations for prevention of infectious diseases for dogs in group settings. In August 2015 a survey of attendees at the AKC Canine Health Foundation Parent Organization conference was completed to determine agreement with and perceived barriers to these recommendations. The 15-minute self-administered survey was provided to 238 Conference attendees and consisted of a series of Likert-type and open-ended questions (online and paper format) seeking feedback on 22 of the recommendations. The survey was completed by 185 individuals (78%), and all responses were reviewed, summarized, and open-ended comments categorized by theme. Respondents self-identified as: participants, judges, and breeders in a variety of local, national, and international canine group events. Most respondents (> 40%) agreed with all but three of the panel's recommendations, yet a majority of respondents stated the recommendations would be difficult or very difficult to implement in their setting (primarily dog shows). Common survey result themes related to difficulty of implementation included: administrative concerns (cost, human resources/manpower), enforcement issues, ethical concerns, privacy concerns, and strong need for official outreach to promote awareness and education related to canine infectious diseases. Survey responses identified needs for: further refinement of recommendations to aid comprehension and clarity (especially around ecto-and endoparasite control), and education to promote culture changes related to disease risk prevention. In order to raise awareness of canine infectious disease in group settings amoungst event participants, attendees, and organizers; an online freely available canine infectious disease risk calculator tool is being developed. Mycoplasma species are one of the most common infectious causes of conjunctivitis in cats. Mycoplasma felis is commonly implicated as a primary pathogen, but other Mycoplasma species have also been detected in clinically ill cats. Findings from previous studies using conventional PCR (cPCR) to investigate the role of Mycoplasma species in causation of feline conjunctivitis have been mixed as Mycoplasma can be carried by apparently normal cats. Therefore, the purpose of this study was to determine if increasing severity of conjunctivitis in cats correlates with higher Mycoplasma species copy numbers using qPCR.
1 section matches

Background

The Asia Pacific Region has, unfortunately, been at the epicentre of such epidemics. Over 30 new infectious agents have been detected in the last three decades, 75% of which were zoonotic. 2 A number of factors contribute to these circumstances. The absence of effective surveillance and control programs, prevailing socio-cultural practices and weak public health and veterinary services infrastructure exacerbates the vulnerability of these settings. Other factors including climate change, environmental degradation, encroachment of humans on areas where wildlife exists, cohabitation of humans and food animals within households, and the mixing of species in live animal markets play a role in increased disease transmission.
3 section matches

Abstract

For many infectious disease processes such as emerging zoonoses and vaccine-preventable diseases, 0vR 0 v1 and infections occur as self-limited stuttering transmission chains. A mechanistic understanding of transmission is essential for characterizing the risk of emerging diseases and monitoring spatio-temporal dynamics. Thus methods for inferring R 0 and the degree of heterogeneity in transmission from stuttering chain data have important applications in disease surveillance and management. Previous researchers have used chain size distributions to infer R 0 , but estimation of the degree of individual-level variation in infectiousness (as quantified by the dispersion parameter, k) has typically required contact tracing data. Utilizing branching process theory along with a negative binomial offspring distribution, we demonstrate how maximum likelihood estimation can be applied to chain size data to infer both R 0 and the dispersion parameter that characterizes heterogeneity. While the maximum likelihood value for R 0 is a simple function of the average chain size, the associated confidence intervals are dependent on the inferred degree of transmission heterogeneity. As demonstrated for monkeypox data from the Democratic Republic of Congo, this impacts when a statistically significant change in R 0 is detectable. In addition, by allowing for superspreading events, inference of k shifts the threshold above which a transmission chain should be considered anomalously large for a given value of R 0 (thus reducing the probability of false alarms about pathogen adaptation). Our analysis of monkeypox also clarifies the various ways that imperfect observation can impact inference of transmission parameters, and highlights the need to quantitatively evaluate whether observation is likely to significantly bias results.

Introduction

Knowledge of R 0 and k has important applications for stuttering chains, including quantifying the risk of endemic spread, predicting the frequency of larger chains, identifying risk factors for acquiring disease, and designing effective control measures. Such information helps to predict how changes in environmental or demographic factors might affect the risk of emergence. Meanwhile, the dispersion parameter alone is a useful measure of transmission heterogeneity, and serves as a stepping stone towards understanding whether heterogeneity arises from variance in social contacts, different intensities of pathogen shedding, variability in the duration of infectious period or some other mechanism.

Results/Discussion

We define a 'stuttering transmission chain' as a group of cases connected by an unbroken series of transmission events. Transmission chains always start with a 'spillover' event in which a primary case (sometimes referred to as an index case) has been infected from an infection reservoir outside the population of interest. Mechanisms of spillover differ among pathogens and circumstances, but include animal-to-human transmission, infection from environmental sources or geographical movement of infected hosts. The primary case can then lead to a series of