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Background: The cestode Taenia solium causes the neglected (zoonotic) tropical disease cysticercosis, a leading cause of preventable epilepsy in endemic low and middle-income countries. Transmission models can inform current scaling-up of control efforts by helping to identify, validate and optimise control and elimination strategies as proposed by the World Health Organization (WHO). Methodology/Principal findings: A systematic literature search was conducted using the PRISMA approach to identify and compare existing T. solium transmission models, and related Taeniidae infection transmission models. In total, 28 modelling papers were identified, of which four modelled T. solium exclusively. Different modelling approaches for T. solium included deterministic, Reed-Frost, individual-based, decision-tree, and conceptual frameworks. Simulated interventions across models agreed on the importance of coverage for impactful effectiveness to be achieved. Other Taeniidae infection transmission models comprised force-of-infection (FoI), population-based (mainly Echinococcus granulosus) and individual-based (mainly E. multilocularis) modelling approaches. Spatial structure has also been incorporated (E. multilocularis and Taenia ovis) in recognition of spatial aggregation of parasite eggs in the environment and movement of wild animal host populations. Conclusions/Significance: Gaps identified from examining the wider Taeniidae family models highlighted the potential role of FoI modelling to inform model parameterisation, as well as the need for spatial modelling and suitable structuring of interventions as key areas for future T. solium model development. We conclude that working with field partners to address data gaps and conducting cross-model validation with baseline and longitudinal data will be critical to building consensus-led and epidemiological setting-appropriate intervention strategies to help fulfil the WHO targets. [ABSTRACT FROM AUTHOR]

To eliminate and eradicate gambiense human African trypanosomiasis (HAT), maximizing the effectiveness of active case finding is of key importance. The progression of the epidemic is largely influenced by the planning of these operations. This paper introduces and analyzes five models for predicting HAT prevalence in a given village based on past observed prevalence levels and past screening activities in that village. Based on the quality of prevalence level predictions in 143 villages in Kwamouth (DRC), and based on the theoretical foundation underlying the models, we consider variants of the Logistic Model—a model inspired by the SIS epidemic model—to be most suitable for predicting HAT prevalence levels. Furthermore, we demonstrate the applicability of this model to predict the effects of planning policies for screening operations. Our analysis yields an analytical expression for the screening frequency required to reach eradication (zero prevalence) and a simple approach for determining the frequency required to reach elimination within a given time frame (one case per 10000). Furthermore, the model predictions suggest that annual screening is only expected to lead to eradication if at least half of the cases are detected during the screening rounds. This paper extends knowledge on control strategies for HAT and serves as a basis for further modeling and optimization studies. [ABSTRACT FROM AUTHOR]

One of the main strategies to control the spread of infectious animal diseases is the implementation of movement restrictions. This paper shows a loss in efficiency of the movement restriction policy (MRP) when behavioral responses of farmers are taken into account. Incorporating the strategic behavior of farmers in an epidemiologic model reveals that the MRP can trigger premature animal sales by farms at high risk of becoming infected that significantly reduce the efficacy of the policy. The results are validated in a parameterized network via Monte Carlo simulations and measures to mitigate the loss of efficiency of the MRP are discussed. Financial aid to farmers can be justified by public health concerns, not only for equity. This paper contributes to developing an interdisciplinary analytical framework regarding the expansion of infectious diseases combining economic and epidemiologic dimensions. [ABSTRACT FROM AUTHOR]

Introduction: The field of diagnostics for active tuberculosis (TB) is rapidly developing. TB diagnostic modeling can help to inform policy makers and support complicated decisions on diagnostic strategy, with important budgetary implications. Demand for TB diagnostic modeling is likely to increase, and an evaluation of current practice is important. We aimed to systematically review all studies employing mathematical modeling to evaluate cost-effectiveness or epidemiological impact of novel diagnostic strategies for active TB. Methods: Pubmed, personal libraries and reference lists were searched to identify eligible papers. We extracted data on a wide variety of model structure, parameter choices, sensitivity analyses and study conclusions, which were discussed during a meeting of content experts. Results & Discussion: From 5619 records a total of 36 papers were included in the analysis. Sixteen papers included population impact/transmission modeling, 5 were health systems models, and 24 included estimates of cost-effectiveness. Transmission and health systems models included specific structure to explore the importance of the diagnostic pathway (n = 4), key determinants of diagnostic delay (n = 5), operational context (n = 5), and the pre-diagnostic infectious period (n = 1). The majority of models implemented sensitivity analysis, although only 18 studies described multi-way sensitivity analysis of more than 2 parameters simultaneously. Among the models used to make cost-effectiveness estimates, most frequent diagnostic assays studied included Xpert MTB/RIF (n = 7), and alternative nucleic acid amplification tests (NAATs) (n = 4). Most (n = 16) of the cost-effectiveness models compared new assays to an existing baseline and generated an incremental cost-effectiveness ratio (ICER). Conclusion: Although models have addressed a small number of important issues, many decisions regarding implementation of TB diagnostics are being made without the full benefits of insight from mathematical models. Further models are needed that address a wider array of diagnostic and epidemiological settings, that explore the inherent uncertainty of models and that include additional epidemiological data on transmission implications of false-negative diagnosis and the pre-diagnostic period. [ABSTRACT FROM AUTHOR]

The propagation of concepts in a population of agents is a form of influence spread, which can be modelled as a cascade from a set of initially activated individuals. The study of such influence cascades, in particular the identification of influential individuals, has a wide range of applications including epidemic control, viral marketing and the study of social norms. In real-world environments there may be many concepts spreading and interacting. These interactions can affect the spread of a given concept, either boosting it and allowing it to spread further, or inhibiting it and limiting its capability to spread. Previous work does not consider how the interactions between concepts affect concept spread. Taking concept interactions into consideration allows for indirect concept manipulation, meaning that we can affect concepts we are not able to directly control. In this paper, we consider the problem of indirect concept manipulation, and propose heuristics for indirectly boosting or inhibiting concept spread in environments where concepts interact. We define a framework that allows for the interactions between any number of concepts to be represented, and present a heuristic that aims to identify important influence paths for a given target concept in order to manipulate its spread. We compare the performance of this heuristic, called maximum probable gain, against established heuristics for manipulating influence spread. [ABSTRACT FROM AUTHOR]

In recent years there has been growing availability of individual-level spatio-temporal disease data, particularly due to the use of modern communicating devices with GPS tracking functionality. These detailed data have been proven useful for inferring disease transmission to a more refined level than previously. However, there remains a lack of statistically sound frameworks to model the underlying transmission dynamic in a mechanistic manner. Such a development is particularly crucial for enabling a general epidemic predictive framework at the individual level. In this paper we propose a new statistical framework for mechanistically modelling individual-to-individual disease transmission in a landscape with heterogeneous population density. Our methodology is first tested using simulated datasets, validating our inferential machinery. The methodology is subsequently applied to data that describes a regional Ebola outbreak in Western Africa (2014-2015). Our results show that the methods are able to obtain estimates of key epidemiological parameters that are broadly consistent with the literature, while revealing a significantly shorter distance of transmission. More importantly, in contrast to existing approaches, we are able to perform a more general model prediction that takes into account the susceptible population. Finally, our results show that, given reasonable scenarios, the framework can be an effective surrogate for susceptible-explicit individual models which are often computationally challenging. [ABSTRACT FROM AUTHOR]

Objective: Irrational use of antimicrobial agents for preventing postoperative SSIs is a common phenomenon in China, which results in more bacterial resistance, higher hospital infection rates, extra costs of antimicrobial agents. The aim of the study is to evaluate the effect of Drug Rational Usage Guidelines System (DRUGS) on the surgeon's prescription behavior of antimicrobial agents. Methods: 10 common surgical operations which included 1543 cases (where 778 cases using paper-based guidelines and 765 cases using DRUGS) were selected and their demographic and clinical data were collected. The selected operations include thyroid resection, breast mass resection, myomectomy, etc. The evaluation criteria were antibiotic administrative categories, the time of initial dose, duration of administration, length of stay, the costs of antibiotics, SSIs and drug adverse reactions(ADR). Results: The antimicrobial agents were mostly administrated within 0.5 h to 2 h before incision, 656 patients (85.75%) were intervened with DRUGS and 256 (32.90%) with paper-based guidelines according to the protocol. For the clean wounds incision, 547 patients (91.62%) were within 24 h of withdrawal antibiotics with using paper-based guidelines versus 91 (14.79%) with using DRUGS. A total of 19 kinds of antibiotics were used in the 1543 cases. The leading three on the list of frequency were piperacillin and sulbactam sodium, cefathiamidine and cefoperazone. While after the intervention, the list of frequency changed to cefazolin, cefathiamidine, cefoperazone. The average hospital stay was (7.00±4.31)d with paper-based guidelines and (2.54±1.57)d with DRUGS, respectively. The average cost of antibiotics was ¥(3481.36±2584.46) with paper-based guidelines and ¥(1693.39±1478.27) with DRUGS, respectively. However, there were no significant differences in the incidence of SSIs and ADR between two groups. Conclusion: In this study, the increased availability of antibiotic guidelines at the time of drug ordering, combined with DRUGS, was associated with an enhanced surgeon adherence to guidelines. [ABSTRACT FROM AUTHOR]

Background: Outbreaks of hand-foot-mouth disease (HFMD) have been reported for many times in Asia during the last decades. This emerging disease has drawn worldwide attention and vigilance. Nowadays, the prevention and control of HFMD has become an imperative issue in China. Early detection and response will be helpful before it happening, using modern information technology during the epidemic. Method: In this paper, a hybrid model combining seasonal auto-regressive integrated moving average (ARIMA) model and nonlinear auto-regressive neural network (NARNN) is proposed to predict the expected incidence cases from December 2012 to May 2013, using the retrospective observations obtained from China Information System for Disease Control and Prevention from January 2008 to November 2012. Results: The best-fitted hybrid model was combined with seasonal ARIMA and NARNN with 15 hidden units and 5 delays. The hybrid model makes the good forecasting performance and estimates the expected incidence cases from December 2012 to May 2013, which are respectively −965.03, −1879.58, 4138.26, 1858.17, 4061.86 and 6163.16 with an obviously increasing trend. Conclusion: The model proposed in this paper can predict the incidence trend of HFMD effectively, which could be helpful to policy makers. The usefulness of expected cases of HFMD perform not only in detecting outbreaks or providing probability statements, but also in providing decision makers with a probable trend of the variability of future observations that contains both historical and recent information. [ABSTRACT FROM AUTHOR]

Background: In August 2011, the German Protection against Infection Act was amended, mandating the reporting of healthcare associated infection (HAI) outbreak notifications by all healthcare workers in Germany via local public health authorities and federal states to the Robert Koch Institute (RKI). Objective: To describe the reported HAI-outbreaks and the surveillance system’s structure and capabilities. Methods: Information on each outbreak was collected using standard paper forms and notified to RKI. Notifications were screened daily and regularly analysed. Results: Between November 2011 and November 2012, 1,326 paper forms notified 578 HAI-outbreaks, between 7 and 116 outbreaks per month. The main causative agent was norovirus (n = 414/578; 72%). Among the 108 outbreaks caused by bacteria, the most frequent pathogens were Clostridium difficile (25%) Klebsiella spp. (19%) and Staphylococcus spp. (19%). Multidrug-resistant bacteria were responsible for 54/108 (50%) bacterial outbreaks. Hospitals were affected most frequently (485/578; 84%). Hospital outbreaks due to bacteria were mostly reported from intensive care units (ICUs) (45%), followed by internal medicine wards (16%). Conclusion: The mandatory HAI-outbreak surveillance system describes common outbreaks. Pathogens with a particular high potential to cause large or severe outbreaks may be identified, enabling us to further focus research and preventive measures. Increasing the sensitivity and reliability of the data collection further will facilitate identification of outbreaks able to increase in size and severity, and guide specific control measures to interrupt their propagation. [ABSTRACT FROM AUTHOR]

Introduction: Role of vaginal sex in heterosexual transmission of HIV has been investigated but that of heterosexual anal sex (HAS) is not fully understood. This paper examines practice of HAS among Female Sex Workers (FSWs) and its correlates in India where the HIV epidemic is being primarily driven by core groups like FSWs. Methods: Data for this paper are drawn from Round I survey of 9667 FSWs in the Integrated Biological and Behavioral Assessment (IBBA) from 23 districts of 4 high HIV prevalent states of India. Bivariate and multivariate analysis identified factors associated with HAS. Results: Ever having anal sex was reported by 11.9% FSWs (95% CI: 11.3%–12.6%). Typology (AOR 2.20, 95% CI 1.64–2.95) and literacy (AOR 1.28, 95% CI 1.10–1.49) were positively associated with practice of HAS. Longer duration in sex trade (AOR 1.69, 95% CI 1.44–1.99), entertaining larger number of clients the previous week (AOR 1.78, 95% CI 1.47–2.15), alcohol consumption (AOR 1.21, 95% CI 1.03–1.42) and inability to negotiate condom use (AOR 1.53, 95% CI 1.28–1.83) were also correlated with HAS. Self-risk perception for HIV (AOR 1.46, 95% CI 1.25–1.71) did not impede HAS. Although symptoms of sexually transmitted infections (STIs) in the last 12 months were associated with anal sex (AOR 1.39, 95% CI 1.13–1.72) there was no significant association between laboratory confirmed HIV and other STIs with HAS. Conclusion: Practice of HAS by FSWs might significantly contribute to HIV transmission in India. This study also shows that despite self-risk perception for HIV, even literate FSWs with longer duration in sex work report HAS. General messages on condom use may not influence safe HAS. FSWs need to be targeted with specific messages on HIV transmission during anal sex. Women controlled prevention methods, such as rectal microbicides and vaginal microbicides are needed. [ABSTRACT FROM AUTHOR]

Introduction: Respondent-driven sampling (RDS) offers a recruitment strategy for hard-to-reach populations. However, RDS faces logistical and theoretical challenges that threaten efficiency and validity in settings worldwide. We present innovative adaptations to conventional RDS to overcome barriers encountered in recruiting a large, representative sample of men who have sex with men (MSM) who travel internationally. Methods: Novel methodological adaptations for the “International Travel Research to Inform Prevention” or “I-TRIP” study were offering participants a choice between electronic and paper coupons referrals for recruitment and modifying the secondary incentives structure from small cash amounts to raffle entries for periodic large cash prize raffle drawings. Staged referral limit increases from 3 to 10 referrals and progressive addition of 70 seeds were also implemented. Results: There were 501 participants enrolled in up to 13 waves of growth. Among participants with a choice of referral methods, 81% selected electronic referrals. Of participants who were recruited electronically, 90% chose to remain with electronic referrals when it was their turn to recruit. The mean number of enrolled referrals was 0.91 for electronic referrals compared to 0.56 for paper coupons. Median referral lag time, i.e., the time interval between when recruiters were given their referrals and when a referred individual enrolled in the study, was 20 days (IQR 10–40) for electronic referrals, 20 days (IQR 8–58) for paper coupons, 20 days (IQR 10–41) for raffle entries and 33 days (IQR 16–148) for small cash incentives. Conclusions: The recruitment of MSM who travel internationally required maximizing known flexible tools of RDS while at the same time necessitating innovations to increase recruitment efficiency. Electronic referrals emerged as a major advantage in recruiting this hard-to-reach population who are of high socio-economic status, geographically diffuse and highly mobile. These enhancements may improve the performance of RDS in target populations with similar characteristics. [ABSTRACT FROM AUTHOR]

Background: In 2005, there were outbreaks of febrile polyarthritis due to Chikungunya virus (CHIKV) in the Comoros Islands. CHIKV then spread to other islands in the Indian Ocean: La Réunion, Mauritius, Seychelles and Madagascar. These outbreaks revealed the lack of surveillance and preparedness of Madagascar and other countries. Thus, it was decided in 2007 to establish a syndrome-based surveillance network to monitor dengue-like illness. Objective: This study aims to evaluate the use of capillary blood samples blotted on filter papers for molecular diagnosis of CHIKV infection. Venous blood samples can be difficult to obtain and the shipment of serum in appropriate temperature conditions is too costly for most developing countries. Methodology and principal findings: Venous blood and dried-blood blotted on filter paper (DBFP) were collected during the last CHIKV outbreak in Madagascar (2010) and as part of our routine surveillance of dengue-like illness. All samples were tested by real-time RT-PCR and results with serum and DBFP samples were compared for each patient. The sensitivity and specificity of tests performed with DBFP, relative to those with venous samples (defined as 100%) were 93.1% (95% CI:[84.7–97.7]) and 94.4% (95% CI:[88.3–97.7]), respectively. The Kappa coefficient 0.87 (95% CI:[0.80–0.94]) was excellent. Conclusion: This study shows that DBFP specimens can be used as a cost-effective alternative sampling method for the surveillance and monitoring of CHIKV circulation and emergence in developing countries, and probably also for other arboviruses. The loss of sensitivity is insignificant and involved a very small number of patients, all with low viral loads. Whether viruses can be isolated from dried blood spots remains to be determined. [ABSTRACT FROM AUTHOR]

Malaria prevalence remains high in many African countries despite massive scaling-up of insecticide treated nets (ITN) and indoor residual spraying (IRS). This paper evaluates the protective effect of pyrethroid IRS and ITNs in relation to risk factors for malaria based on a study conducted in North-West Tanzania, where IRS has been conducted since 2007 and universal coverage of ITNs has been carried out recently. In 2011 community-based cross-sectional surveys were conducted in the two main malaria transmission periods that occur after the short and long rainy seasons. These included 5,152 and 4,325 children aged 0.5–14 years, respectively. Data on IRS and ITN coverage, household demographics and socio-economic status were collected using an adapted version of the Malaria Indicator Survey. Children were screened for malaria by rapid diagnostic test. In the second survey, haemoglobin density was measured and filter paper blood spots were collected to determine age-specific sero-prevalence in each community surveyed. Plasmodium falciparum infection prevalence in children 0.5–14 years old was 9.3% (95%CI:5.9–14.5) and 22.8% (95%CI:17.3–29.4) in the two surveys. Risk factors for infection after the short rains included households not being sprayed (OR = 0.39; 95%CI:0.20–0.75); low community net ownership (OR = 0.45; 95%CI:0.21–0.95); and low community SES (least poor vs. poorest tertile: OR = 0.13, 95%CI:0.05–0.34). Risk factors after the long rains included household poverty (per quintile increase: OR = 0.89; 95%CI:0.82–0.97) and community poverty (least poor vs. poorest tertile: OR = 0.26, 95%CI:0.15–0.44); household IRS or high community ITN ownership were not protective. Despite high IRS coverage and equitable LLIN distribution, poverty was an important risk factor for malaria suggesting it could be beneficial to target additional malaria control activities to poor households and communities. High malaria prevalence in some clusters and the limited protection given by pyrethroid IRS and LLINs suggest that it may be necessary to enhance established vector control activities and consider additional interventions. [ABSTRACT FROM AUTHOR]

Background: Climate change is likely to be one of the most important threats to public health in the coming years. Yet despite the large number of papers considering the health impact of climate change, few have considered what public health interventions may be of most value in reducing the disease burden. We aimed to evaluate the effectiveness of public health interventions to reduce the disease burden of high priority climate sensitive diseases. Methods and Findings: For each disease, we performed a systematic search with no restriction on date or language of publication on Medline, Web of Knowledge, Cochrane CENTRAL and SCOPUS up to December 2010 to identify systematic reviews of public health interventions. We retrieved some 3176 records of which 85 full papers were assessed and 33 included in the review. The included papers investigated the effect of public health interventions on various outcome measures. All interventions were GRADE assessed to determine the strength of evidence. In addition we developed a systematic review quality score. The interventions included environmental interventions to control vectors, chemoprophylaxis, immunization, household and community water treatment, greening cities and community advice. For most reviews, GRADE showed low quality of evidence because of poor study design and high heterogeneity. Also for some key areas such as floods, droughts and other weather extremes, there are no adequate systematic reviews of potential public health interventions. Conclusion: In conclusion, we found the evidence base to be mostly weak for environmental interventions that could have the most value in a warmer world. Nevertheless, such interventions should not be dismissed. Future research on public health interventions for climate change adaptation needs to be concerned about quality in study design and should address the gap for floods, droughts and other extreme weather events that pose a risk to health. [ABSTRACT FROM AUTHOR]

In social networks, individuals have relationships with their neighbor nodes (acquaintance contacts) and also randomly contact other nodes without direct links (stranger contacts). However, these two types of contact patterns are rarely considered together. In this paper, we propose a modified SIS (Susceptible-Infected-Susceptible) model in which a node not only contacts neighbor nodes but also randomly contacts other nodes in the network. We implement the model on a scale-free network and study the influence of different types of contact patterns on epidemic dynamics as well as three possible strategies people adopt when disease outbreaks. The results show that a greater preference for acquaintance contacts makes a disease outbreak less likely. Moreover, the best protective strategy to control the disease is to adjust both the contact number and the contact pattern. In addition, the epidemic is more likely to be controlled when individuals take more information into consideration. [ABSTRACT FROM AUTHOR]

Abdominal aortic aneurysm (AAA) is a localized enlargement of the abdominal aorta, such that the diameter exceeds 3 cm. The natural history of AAA is progressive growth leading to rupture, an event that carries up to 90% risk of mortality. Hence there is a need to predict the growth of the diameter of the aorta based on the diameter of a patient’s aneurysm at initial screening and aided by non-invasive biomarkers. IL-6 is overexpressed in AAA and was suggested as a prognostic marker for the risk in AAA. The present paper develops a mathematical model which relates the growth of the abdominal aorta to the serum concentration of IL-6. Given the initial diameter of the aorta and the serum concentration of IL-6, the model predicts the growth of the diameter at subsequent times. Such a prediction can provide guidance to how closely the patient’s abdominal aorta should be monitored. The mathematical model is represented by a system of partial differential equations taking place in the aortic wall, where the media is assumed to have the constituency of an hyperelastic material. [ABSTRACT FROM AUTHOR]

Exploring the interplay between information spreading and epidemic spreading is a topic that has been receiving increasing attention. As an efficient means of depicting the spreading of information, which manifests as a cascade phenomenon, awareness cascading is utilized to investigate this coupled transmission. Because in reality, different individuals facing the same epidemic will exhibit distinct behaviors according to their own experiences and attributes, it is important for us to consider the heterogeneity of individuals. Consequently, we propose a heterogeneous spreading model. To describe the heterogeneity, two of the most important but radically different methods for this purpose, the degree and k-core measures, are studied in this paper through three models based on different assumptions. Adopting a Markov chain approach, we succeed in predicting the epidemic threshold trend. Furthermore, we find that when the k-core measure is used to classify individuals, the spreading process is robust to these models, meaning that regardless of the model used, the spreading process is nearly identical at the macroscopic level. In addition, the k-core measure leads to a much larger final epidemic size than the degree measure. These results are cross-checked through numerous simulations, not only of a synthetic network but also of a real multiplex network. The presented findings provide a better understanding of k-core individuals and reveal the importance of considering network structure when investigating various dynamic processes. [ABSTRACT FROM AUTHOR]

This paper is focused on the transmission dynamics and optimal control of Anthroponotic Cutaneous Leishmania. The threshold condition R0 for initial transmission of infection is obtained by next generation method. Biological sense of the threshold condition is investigated and discussed in detail. The sensitivity analysis of the reproduction number is presented and the most sensitive parameters are high lighted. On the basis of sensitivity analysis, some control strategies are introduced in the model. These strategies positively reduce the effect of the parameters with high sensitivity indices, on the initial transmission. Finally, an optimal control strategy is presented by taking into account the cost associated with control strategies. It is also shown that an optimal control exists for the proposed control problem. The goal of optimal control problem is to minimize, the cost associated with control strategies and the chances of infectious humans, exposed humans and vector population to become infected. Numerical simulations are carried out with the help of Runge-Kutta fourth order procedure. [ABSTRACT FROM AUTHOR]

In this paper, by taking full consideration of distributed delay, demographics and contact heterogeneity of the individuals, we present a detailed analytical study of the Susceptible-Infected-Removed (SIR) epidemic model on complex population networks. The basic reproduction number of the model is dominated by the topology of the underlying network, the properties of individuals which include birth rate, death rate, removed rate and infected rate, and continuously distributed time delay. By constructing suitable Lyapunov functional and employing Kirchhoff’s matrix tree theorem, we investigate the globally asymptotical stability of the disease-free and endemic equilibrium points. Specifically, the system shows threshold behaviors: if , then the disease-free equilibrium is globally asymptotically stable, otherwise the endemic equilibrium is globally asymptotically stable. Furthermore, the obtained results show that SIR models with different types of delays have different converge time in the process of contagion: if , then the system with distributed time delay stabilizes fastest; while , the system with distributed time delay converges most slowly. The validness and effectiveness of these results are demonstrated through numerical simulations. [ABSTRACT FROM AUTHOR]

Background: Despite being the most widely distributed mosquito-borne viral infection, estimates of dengue transmission intensity and associated burden remain ambiguous. With advances in the development of novel control measures, obtaining robust estimates of average dengue transmission intensity is key for assessing the burden of disease and the likely impact of interventions. Methodology/Principle Findings: We estimated the force of infection (λ) and corresponding basic reproduction numbers (R0) by fitting catalytic models to age-stratified incidence data identified from the literature. We compared estimates derived from incidence and seroprevalence data and assessed the level of under-reporting of dengue disease. In addition, we estimated the relative contribution of primary to quaternary infections to the observed burden of dengue disease incidence. The majority of R0 estimates ranged from one to five and the force of infection estimates from incidence data were consistent with those previously estimated from seroprevalence data. The baseline reporting rate (or the probability of detecting a secondary infection) was generally low (<25%) and varied within and between countries. Conclusions/Significance: As expected, estimates varied widely across and within countries, highlighting the spatio-temporally heterogeneous nature of dengue transmission. Although seroprevalence data provide the maximum information, the incidence models presented in this paper provide a method for estimating dengue transmission intensity from age-stratified incidence data, which will be an important consideration in areas where seroprevalence data are not available. [ABSTRACT FROM AUTHOR]

This paper presents a propagation dynamics model for congestion propagation in complex networks of airspace. It investigates the application of an epidemiology model to complex networks by comparing the similarities and differences between congestion propagation and epidemic transmission. The model developed satisfies the constraints of actual motion in airspace, based on the epidemiology model. Exploiting the constraint that the evolution of congestion cluster in the airspace is always dynamic and heterogeneous, the SIR epidemiology model (one of the classical models in epidemic spreading) with logistic increase is applied to congestion propagation and shown to be more accurate in predicting the evolution of congestion peak than the model based on probability, which is common to predict the congestion propagation. Results from sample data show that the model not only predicts accurately the value and time of congestion peak, but also describes accurately the characteristics of congestion propagation. Then, a numerical study is performed in which it is demonstrated that the structure of the networks have different effects on congestion propagation in airspace. It is shown that in regions with severe congestion, the adjustment of dissipation rate is more significant than propagation rate in controlling the propagation of congestion. [ABSTRACT FROM AUTHOR]

This paper contributes evidence documenting the continued decline in all-cause mortality and changes in the cause of death distribution over time in four developing country populations in Africa and Asia. We present levels and trends in age-specific mortality (all-cause and cause-specific) from four demographic surveillance sites: Agincourt (South Africa), Navrongo (Ghana) in Africa; Filabavi (Vietnam), Matlab (Bangladesh) in Asia. We model mortality using discrete time event history analysis. This study illustrates how data from INDEPTH Network centers can provide a comparative, longitudinal examination of mortality patterns and the epidemiological transition. Health care systems need to be reconfigured to deal simultaneously with continuing challenges of communicable disease and increasing incidence of non-communicable diseases that require long-term care. In populations with endemic HIV, long-term care of HIV patients on ART will add to the chronic care needs of the community. [ABSTRACT FROM AUTHOR]

To effectively and efficiently reduce the morbidity and mortality that may be caused by outbreaks of emerging infectious diseases, it is very important for public health agencies to make informed decisions for controlling the spread of the disease. Such decisions must incorporate various kinds of intervention strategies, such as vaccinations, school closures and border restrictions. Recently, researchers have paid increased attention to searching for effective vaccine distribution strategies for reducing the effects of pandemic outbreaks when resources are limited. Most of the existing research work has been focused on how to design an effective age-structured epidemic model and to select a suitable vaccine distribution strategy to prevent the propagation of an infectious virus. Models that evaluate age structure effects are common, but models that additionally evaluate geographical effects are less common. In this paper, we propose a new SEIR (susceptible—exposed—infectious šC recovered) model, named the hybrid SEIR-V model (HSEIR-V), which considers not only the dynamics of infection prevalence in several age-specific host populations, but also seeks to characterize the dynamics by which a virus spreads in various geographic districts. Several vaccination strategies such as different kinds of vaccine coverage, different vaccine releasing times and different vaccine deployment methods are incorporated into the HSEIR-V compartmental model. We also design four hybrid vaccination distribution strategies (based on population size, contact pattern matrix, infection rate and infectious risk) for controlling the spread of viral infections. Based on data from the 2009–2010 H1N1 influenza epidemic, we evaluate the effectiveness of our proposed HSEIR-V model and study the effects of different types of human behaviour in responding to epidemics. [ABSTRACT FROM AUTHOR]

Estimates of contact among children, used for infectious disease transmission models and understanding social patterns, historically rely on self-report logs. Recently, wireless sensor technology has enabled objective measurement of proximal contact and comparison of data from the two methods. These are mostly small-scale studies, and knowledge gaps remain in understanding contact and mixing patterns and also in the advantages and disadvantages of data collection methods. We collected contact data from a middle school, with 7th and 8th grades, for one day using self-report contact logs and wireless sensors. The data were linked for students with unique initials, gender, and grade within the school. This paper presents the results of a comparison of two approaches to characterize school contact networks, wireless proximity sensors and self-report logs. Accounting for incomplete capture and lack of participation, we estimate that “sensor-detectable”, proximal contacts longer than 20 seconds during lunch and class-time occurred at 2 fold higher frequency than “self-reportable” talk/touch contacts. Overall, 55% of estimated talk-touch contacts were also sensor-detectable whereas only 15% of estimated sensor-detectable contacts were also talk-touch. Contacts detected by sensors and also in self-report logs had longer mean duration than contacts detected only by sensors (6.3 vs 2.4 minutes). During both lunch and class-time, sensor-detectable contacts demonstrated substantially less gender and grade assortativity than talk-touch contacts. Hallway contacts, which were ascertainable only by proximity sensors, were characterized by extremely high degree and short duration. We conclude that the use of wireless sensors and self-report logs provide complementary insight on in-school mixing patterns and contact frequency. [ABSTRACT FROM AUTHOR]

Introduction: Reports of high rates of primary microcephaly and Guillain–Barré syndrome associated with Zika virus infection in French Polynesia and Brazil have raised concerns that the virus circulating in these regions is a rapidly developing neuropathic, teratogenic, emerging infectious public health threat. There are no licensed medical countermeasures (vaccines, therapies or preventive drugs) available for Zika virus infection and disease. The Pan American Health Organization (PAHO) predicts that Zika virus will continue to spread and eventually reach all countries and territories in the Americas with endemic Aedes mosquitoes. This paper reviews the status of the Zika virus outbreak, including medical countermeasure options, with a focus on how the epidemiology, insect vectors, neuropathology, virology and immunology inform options and strategies available for medical countermeasure development and deployment. Methods: Multiple information sources were employed to support the review. These included publically available literature, patents, official communications, English and Lusophone lay press. Online surveys were distributed to physicians in the US, Mexico and Argentina and responses analyzed. Computational epitope analysis as well as infectious disease outbreak modeling and forecasting were implemented. Field observations in Brazil were compiled and interviews conducted with public health officials. [ABSTRACT FROM AUTHOR]

Epidemiological modeling for infectious disease is important for disease management and its routine implementation needs to be facilitated through better description of models in an operational context. A standardized model characterization process that allows selection or making manual comparisons of available models and their results is currently lacking. A key need is a universal framework to facilitate model description and understanding of its features. Los Alamos National Laboratory (LANL) has developed a comprehensive framework that can be used to characterize an infectious disease model in an operational context. The framework was developed through a consensus among a panel of subject matter experts. In this paper, we describe the framework, its application to model characterization, and the development of the Biosurveillance Analytics Resource Directory (BARD; ), to facilitate the rapid selection of operational models for specific infectious/communicable diseases. We offer this framework and associated database to stakeholders of the infectious disease modeling field as a tool for standardizing model description and facilitating the use of epidemiological models. [ABSTRACT FROM AUTHOR]

Background: We conducted a survival analysis of all the confirmed cases of Adult Tuberculosis (TB) patients treated in Cork-City, Ireland. The aim of this study was to estimate Survival time (ST), including median time of survival and to assess the association and impact of covariates (TB risk factors) to event status and ST. The outcome of the survival analysis is reported in this paper. Methods: We used a retrospective cohort study research design to review data of 647 bacteriologically confirmed TB patients from the medical record of two teaching hospitals. Mean age 49 years (Range 18–112). We collected information on potential risk factors of all confirmed cases of TB treated between 2008–2012. For the survival analysis, the outcome of interest was ‘treatment failure’ or ‘death’ (whichever came first). A univariate descriptive statistics analysis was conducted using a non- parametric procedure, Kaplan -Meier (KM) method to estimate overall survival (OS), while the Cox proportional hazard model was used for the multivariate analysis to determine possible association of predictor variables and to obtain adjusted hazard ratio. P value was set at <0.05, log likelihood ratio test at >0.10. Data were analysed using SPSS version 15.0. Results: There was no significant difference in the survival curves of male and female patients. (Log rank statistic  = 0.194, df  = 1, p = 0.66) and among different age group (Log rank statistic  = 1.337, df = 3, p = 0.72). The mean overall survival (OS) was 209 days (95%CI: 92–346) while the median was 51 days (95% CI: 35.7–66). The mean ST for women was 385 days (95%CI: 76.6–694) and for men was 69 days (95%CI: 48.8–88.5). Multivariate Cox regression showed that patient who had history of drug misuse had 2.2 times hazard than those who do not have drug misuse. Smokers and alcohol drinkers had hazard of 1.8 while patients born in country of high endemicity (BICHE) had hazard of 6.3 and HIV co-infection hazard was 1.2. Conclusion: There was no significant difference in survival curves of male and female and among age group. Women had a higher ST compared to men. But men had a higher hazard rate compared to women. Anti-TNF, immunosuppressive medication and diabetes were found to be associated with longer ST, while alcohol, smoking, RICHE, BICHE was associated with shorter ST. [ABSTRACT FROM AUTHOR]

Background: Knowledge of tuberculosis incidence and associated factors is required for the development and evaluation of strategies to reduce the burden of HIV-associated tuberculosis. Methods: Systematic literature review and meta-analysis of tuberculosis incidence rates among HIV-infected individuals taking combination antiretroviral therapy. Results: From PubMed, EMBASE and Global Index Medicus databases, 42 papers describing 43 cohorts (32 from high/intermediate and 11 from low tuberculosis burden settings) were included in the qualitative review and 33 in the quantitative review. Cohorts from high/intermediate burden settings were smaller in size, had lower median CD4 cell counts at study entry and fewer person-years of follow up. Tuberculosis incidence rates were higher in studies from Sub-Saharan Africa and from World Bank low/middle income countries. Tuberculosis incidence rates decreased with increasing CD4 count at study entry and duration on combination antiretroviral therapy. Summary estimates of tuberculosis incidence among individuals on combination antiretroviral therapy were higher for cohorts from high/intermediate burden settings compared to those from the low tuberculosis burden settings (4.17 per 100 person-years [95% Confidence Interval (CI) 3.39–5.14 per 100 person-years] vs. 0.4 per 100 person-years [95% CI 0.23–0.69 per 100 person-years]) with significant heterogeneity observed between the studies. Conclusions: Tuberculosis incidence rates were high among individuals on combination antiretroviral therapy in high/intermediate burden settings. Interventions to prevent tuberculosis in this population should address geographical, socioeconomic and individual factors such as low CD4 counts and prior history of tuberculosis. [ABSTRACT FROM AUTHOR]

Background: Lymphatic filariasis is a neglected tropical disease leading to profound disfiguring causing socio economic burden in the tropics. Current diagnosis strategies available during field surveys and epidemics are based on traditional microscopic detections and a few antigen/antibody assays. We have compared different sampling methodologies and standardized the highly sensitive and reliable rWbSXP-1 antigen detection assay to our new sampling methodology. Methodology: Samples collected as serum, whole blood, whole blood on filter paper and whole blood on microscopic slides from patients belonging to various clinical groups of filariasis [endemic normal(EN), chronic pathology(CP), microfilaraemic(MF) and non-endemic normal(NEN)] were collected and standardized the rWbSXP-1 antigen detection assay using monoclonal antibody raised against rWbSXP-1 protein. The whole blood collected on microscopic slide based sampling method was employed in the field and the presence of circulating filarial antigen (CFA) was assessed using the rWbSXP-1 assay. Principal Findings: The sampling methods were compared and no significant difference was observed for the detection of CFA (MF, P = 0.304, EN, P = 0.675, CP, P = 0.5698, NEN, P = 0.4494). Further the optimized sampling method was utilized to collect the 1106 samples from Polur, Tiruvannamalai. The rWbSXP-1 assay gave 98 antigen positive results whereas the microscopic method gave only 17. Conclusions: Four sampling methodologies were analyzed and the new sampling methodology of whole blood collected on microscopic slide was found to be convenient for the detection of CFA using rWbSXP-1 antigen detection assay. The 1106 samples from Polur were collected using the new method. The rWbSXP-1 antigen assay perceived a 7.32% increased result which was read as false negatives on the conventional microscopic staining method. This new sampling methodology coupled with the rWbSXP-1 antigen assay can be used in epidemiological surveys for lymphatic filariasis and the same sampling methodology can be expanded to other antigen based high affinity assays. [ABSTRACT FROM AUTHOR]

The HIV-1 epidemic among men-who-have-sex-with-men (MSM) continues to expand in China. A large-scale national survey we conducted on HIV-1 strains among MSM in 11 provinces in China from 2008 to 2013 (n = 920) identified a novel transmission cluster consisting of six strains (0.7%) that belonged to a new circulating recombinant form (designated CRF59_01B). CRF59_01B contains two subtype B segments of U.S.-European origin (in the pol and vpu-env regions) in a CRF01_AE backbone. CRF59_01B is the second CRF (after CRF55_01B) circulating primarily among MSM in China. CRF59_01B occurs at a low frequency (less than 1%), but it was detected in four different provinces/regions in China: Liaoning (northeast China) (n = 3); Hunan (central China) (n = 1); Guangdong (south China) (n = 1); Yunnan (southwest China) (n = 1). One additional recombinant strain was detected in a heterosexual individual in Liaoning province but is not the focus of this paper. Bayesian molecular clock analyses indicate that CRF59_01B emerged as a result of recombination between CRF01_AE and subtype B around the year 2001. The emergence of multiple forms of recombinants and CRFs reflects the ever-increasing contribution of homosexual transmission in China's HIV epidemic and indicates an active HIV transmission network among MSM in China. [ABSTRACT FROM AUTHOR]

Previous models of disease spread involving delay have used basic SIR (susceptible – infectious – recovery) formulae and approaches. This paper demonstrates how time-varying SEIRS (S – exposed – I – R – S) models can be extended with delay to produce wave propagations that simulate periodic wave fronts of disease spread in the context of population movements. The model also takes into account the natural mortality associated with the disease spread. Understanding the delay of an infectious disease is critical when attempting to predict where and how fast the disease will propagate. We use cellular automata to model the delay and its effect on the spread of infectious diseases where population movement occurs. We illustrate an approach using wavelet transform analysis to understand the impact of the delay on the spread of infectious diseases. The results indicate that including delay provides novel ways to understand the effects of migration and population movement on disease spread. [ABSTRACT FROM AUTHOR]

Although the incidence of variant Creutzfeldt-Jakob disease (vCJD) has declined to 1 since 2012 in the UK, uncertainty remains regarding possible future cases and the size of the subclinical population that may cause secondary transmission of the disease through blood transfusion. Estimating the number of individuals who were exposed to the bovine spongiform encephalopathy (BSE) infectious agent and may be susceptible to vCJD will help to clarify related public health concerns and plan strategies. In this paper, we explore this estimate by describing the probability of potential exposure due to dietary intake throughout the BSE epidemic period from 1980 to 1996 as a stochastic Poisson process. We estimate the age- and gender-specific exposure intensities in food categories of beef and beef-containing dishes, burgers and kebabs, pies, and sausages, separating the two periods of 1980–1989 and 1990–1996 due to the specified bovine offal legislation of 1989. The estimated total number of (living) exposed individuals during each period is 5,089,027 (95% confidence interval [CI] 4,514,963–6,410,317), which was obtained by multiplying the population size of different birth cohorts by the probability of exposure via dietary intake and the probability of survival until the end of 2013. The estimated number is approximately doubled, assuming a contamination rate of . Among those individuals estimated, 31,855 (95% CI 26,849–42,541) are susceptible to infection. We also examined the threshold hypothesis by fitting an extreme-value distribution to the estimated infectious dose of the exposed individuals and obtained a threshold estimate of 13.7 bID50 (95% CI 6.6–26.2 bID50) (Weibull). The results provide useful information on potential carriers of prion disease who may pose a threat of infection via blood transfusion and thus provide insight into the likelihood of new incidents of vCJD occurring in the future. [ABSTRACT FROM AUTHOR]

The high sensitivity of qPCR makes it a desirable diagnostic method in epidemiological surveillance programs. However, due to high costs, the use of pooling has been suggested. In this paper, an algorithm based on the Montecarlo method has been designed and implemented. The algorithm had been tested in many different situations, and finally it was validated with a real dataset. Moreover, based on the results obtained and depending on pooling conditions, a drastic decrease of sensitivity is observed. [ABSTRACT FROM AUTHOR]

The objective of this manuscript is to present a systematic review of biosurveillance models that operate on select agents and can forecast the occurrence of a disease event. We define a disease event to be a biological event with focus on the One Health paradigm. These events are characterized by evidence of infection and or disease condition. We reviewed models that attempted to predict a disease event, not merely its transmission dynamics and we considered models involving pathogens of concern as determined by the US National Select Agent Registry (as of June 2011). We searched commercial and government databases and harvested Google search results for eligible models, using terms and phrases provided by public health analysts relating to biosurveillance, remote sensing, risk assessments, spatial epidemiology, and ecological niche modeling. After removal of duplications and extraneous material, a core collection of 6,524 items was established, and these publications along with their abstracts are presented in a semantic wiki at http://BioCat.pnnl.gov. As a result, we systematically reviewed 44 papers, and the results are presented in this analysis. We identified 44 models, classified as one or more of the following: event prediction (4), spatial (26), ecological niche (28), diagnostic or clinical (6), spread or response (9), and reviews (3). The model parameters (e.g., etiology, climatic, spatial, cultural) and data sources (e.g., remote sensing, non-governmental organizations, expert opinion, epidemiological) were recorded and reviewed. A component of this review is the identification of verification and validation (V&V) methods applied to each model, if any V&V method was reported. All models were classified as either having undergone Some Verification or Validation method, or No Verification or Validation. We close by outlining an initial set of operational readiness level guidelines for disease prediction models based upon established Technology Readiness Level definitions. [ABSTRACT FROM AUTHOR]

This paper explored our hypothesis that sRNA (18∼30 bp) deep sequencing technique can be used as an efficient strategy to identify microorganisms other than viruses, such as prokaryotic and eukaryotic pathogens. In the study, the clean reads derived from the sRNA deep sequencing data of wild-caught ticks and mosquitoes were compared against the NCBI nucleotide collection (non-redundant nt database) using Blastn. The blast results were then analyzed with in-house Python scripts. An empirical formula was proposed to identify the putative pathogens. Results showed that not only viruses but also prokaryotic and eukaryotic species of interest can be screened out and were subsequently confirmed with experiments. Specially, a novel Rickettsia spp. was indicated to exist in Haemaphysalis longicornis ticks collected in Beijing. Our study demonstrated the reuse of sRNA deep sequencing data would have the potential to trace the origin of pathogens or discover novel agents of emerging/re-emerging infectious diseases. [ABSTRACT FROM AUTHOR]

Background: Dried blood spots (DBS) have been used as alternative specimens to plasma to increase access to HIV viral load (VL) monitoring and early infant diagnosis (EID) in remote settings. We systematically reviewed evidence on the performance of DBS compared to plasma for VL monitoring and EID. Methods and Findings: Thirteen peer reviewed HIV VL publications and five HIV EID papers were included. Depending on the technology and the viral load distribution in the study population, the percentage of DBS samples that are within 0.5 log of VL in plasma ranged from 52–100%. Because the input sample volume is much smaller in a blood spot, there is a risk of false negatives with DBS. Sensitivity of DBS VL was found to be 78–100% compared to plasma at VL below 1000 copies/ml, but this increased to 100% at a threshold of 5000 copies/ml. Unlike a plasma VL test which measures only cell free HIV RNA, a DBS VL also measures proviral DNA as well as cell-associated RNA, potentially leading to false positive results when using DBS. The systematic review showed that specificity was close to 100% at DBS VL above 5000 copies/ml, and this threshold would be the most reliable for predicting true virologic failure using DBS. For early infant diagnosis, DBS has a sensitivity of 100% compared to fresh whole blood or plasma in all studies. Conclusions: Although limited data are available for EID, DBS offer a highly sensitive and specific sampling strategy to make viral load monitoring and early infant diagnosis more accessible in remote settings. A standardized approach for sampling, storing, and processing DBS samples would be essential to allow successful implementation. Trial Registration: PROSPERO Registration #: CRD42013003621. [ABSTRACT FROM AUTHOR]

Background: Around 67 million pets are owned by households in the United Kingdom, and an increasing number of these are exotic animals. Approximately a third of pets are purchased through retail outlets or direct from breeders. A wide range of infections can be associated with companion animals. Objectives: This study uses a systematic literature review to describe the transmission of zoonotic disease in humans associated with a pet shop or other location selling pets (incidents of rabies tracebacks and zoonoses from pet food were excluded). Data sources: PubMed and EMBASE. Results: Fifty seven separate case reports or incidents were described in the 82 papers that were identified by the systematic review. Summary information on each incident is included in this manuscript. The infections include bacterial, viral and fungal diseases and range in severity from mild to life threatening. Infections associated with birds and rodents were the most commonly reported. Over half of the reports describe incidents in the Americas, and three of these were outbreaks involving more than 50 cases. Many of the incidents identified relate to infections in pet shop employees. Limitations: This review may have been subject to publication bias, where unusual and unexpected zoonotic infections may be over-represented in peer-reviewed publications. It was also restricted to English-language articles so that pathogens that are more common in non-Western countries, or in more exotic animals not common in Europe and the Americas, may have been under-represented. Conclusions/implications: A wide spectrum of zoonotic infections are acquired from pet shops. Salmonellosis and psittacosis were the most commonly documented diseases, however more unusual infections such as tularemia also appeared in the review. Given their potential to spread zoonotic infection, it is important that pet shops act to minimise the risk as far as possible. [ABSTRACT FROM AUTHOR]

Objective: This paper describes the physical structure and environmental contamination in selected hospital wards in three government hospitals in Bangladesh. Methods: The qualitative research team conducted 48 hours of observation in six wards from three Bangladeshi tertiary hospitals in 2007. They recorded environmental contamination with body secretions and excretions and medical waste and observed ward occupant handwashing and use of personal protective equipment. They recorded number of persons, number of open doors and windows, and use of fans. They measured the ward area and informally observed waste disposal outside the wards. They conducted nine focus group discussions with doctors, nurses and support staff. Results: A median of 3.7 persons were present per 10 m2 of floor space in the wards. A median of 4.9 uncovered coughs or sneezes were recorded per 10 m2 per hour per ward. Floors in the wards were soiled with saliva, spit, mucous, vomitus, feces and blood 125 times in 48 hours. Only two of the 12 patient handwashing stations had running water and none had soap. No disinfection was observed before or after using medical instruments. Used medical supplies were often discarded in open containers under the beds. Handwashing with soap was observed in only 32 of 3,373 handwashing opportunities noted during 48 hours. Mosquitoes and feral cats were commonly observed in the wards. Conclusions: The physical structure and environment of our study hospitals are conducive to the spread of infection to people in the wards. Low-cost interventions on hand hygiene and cleaning procedures for rooms and medical equipment should be developed and evaluated for their practicality and effectiveness. [ABSTRACT FROM AUTHOR]

Multi-drug resistant tuberculosis (MDR-TB) represents a threat to health and development in countries with high TB burden. China’s MDR-TB prevalence rate of 6.8% is the highest in the world. Interventions to remove barriers against effective TB control, and prevention of MDR-TB are urgently needed in the country. This paper reports a cross-sectional questionnaire survey of 513 pulmonary TB (PTB) patients, and qualitative interviews of 10 healthcare workers (HCWs), and 15 PTB patients. The objective was to assess barriers against effective control of PTB and prevention of MDR-TB by elucidating the perspectives of patients and healthcare providers. Results showed that more than half of the patients experienced patient delay of over 12.5 days. A similar proportion also experienced detection delay of over 30 days, and delay in initiating treatment of over 31 days. Consulting a non-TB health facility ≥3 times before seeking care at TB dispensary was a risk factor for both detection delay [AOR (95% CI): 1.89(1.07, 3.34) and delay in initiating treatment[AOR (95% CI): 1.88 (1.06, 3.36). Results revealed poor implementation of Directly Observed Therapy (DOT), whereby treatment of 34.3% patients was never monitored by HCWs. Only 31.8% patients had ever accessed TB health education before their TB diagnosis. Qualitative data consistently disclosed long patient delay, and indicated that patient’s poor TB knowledge and socioeconomic barriers were primary reasons for patient delay. Seeking care and being treated at a non-TB hospital was an important reason for detection delay. Patient’s long work hours and low income increased risk for treatment non-adherence. Evidence-based measures to improve TB health seeking behavior, reduce patient and detection delays, improve the quality of DOT, address financial and system barriers, and increase access to TB health promotion are urgently needed to address the burgeoning prevalence of MDR-TB in China. [ABSTRACT FROM AUTHOR]

Public health surveillance systems provide valuable data for reliable predication of future epidemic events. This paper describes a study that used nine types of infectious disease data collected through a national public health surveillance system in mainland China to evaluate and compare the performances of four time series methods, namely, two decomposition methods (regression and exponential smoothing), autoregressive integrated moving average (ARIMA) and support vector machine (SVM). The data obtained from 2005 to 2011 and in 2012 were used as modeling and forecasting samples, respectively. The performances were evaluated based on three metrics: mean absolute error (MAE), mean absolute percentage error (MAPE), and mean square error (MSE). The accuracy of the statistical models in forecasting future epidemic disease proved their effectiveness in epidemiological surveillance. Although the comparisons found that no single method is completely superior to the others, the present study indeed highlighted that the SVMs outperforms the ARIMA model and decomposition methods in most cases. [ABSTRACT FROM AUTHOR]

Murray Valley encephalitis virus (MVEV) is the most serious of the endemic arboviruses in Australia. It was responsible for six known large outbreaks of encephalitis in south-eastern Australia in the 1900s, with the last comprising 58 cases in 1974. Since then MVEV clinical cases have been largely confined to the western and central parts of northern Australia. In 2011, high-level MVEV activity occurred in south-eastern Australia for the first time since 1974, accompanied by unusually heavy seasonal MVEV activity in northern Australia. This resulted in 17 confirmed cases of MVEV disease across Australia. Record wet season rainfall was recorded in many areas of Australia in the summer and autumn of 2011. This was associated with significant flooding and increased numbers of the mosquito vector and subsequent MVEV activity. This paper documents the outbreak and adds to our knowledge about disease outcomes, epidemiology of disease and the link between the MVEV activity and environmental factors. Clinical and demographic information from the 17 reported cases was obtained. Cases or family members were interviewed about their activities and location during the incubation period. In contrast to outbreaks prior to 2000, the majority of cases were non-Aboriginal adults, and almost half (40%) of the cases acquired MVEV outside their area of residence. All but two cases occurred in areas of known MVEV activity. This outbreak continues to reflect a change in the demographic pattern of human cases of encephalitic MVEV over the last 20 years. In northern Australia, this is associated with the increasing numbers of non-Aboriginal workers and tourists living and travelling in endemic and epidemic areas, and also identifies an association with activities that lead to high mosquito exposure. This outbreak demonstrates that there is an ongoing risk of MVEV encephalitis to the heavily populated areas of south-eastern Australia. [ABSTRACT FROM AUTHOR]

Knowledge of the incubation period of infectious diseases (time between host infection and expression of disease symptoms) is crucial to our epidemiological understanding and the design of appropriate prevention and control policies. Plant diseases cause substantial damage to agricultural and arboricultural systems, but there is still very little information about how the incubation period varies within host populations. In this paper, we focus on the incubation period of soilborne plant pathogens, which are difficult to detect as they spread and infect the hosts underground and above-ground symptoms occur considerably later. We conducted experiments on Rhizoctonia solani in sugar beet, as an example patho-system, and used modelling approaches to estimate the incubation period distribution and demonstrate the impact of differing estimations on our epidemiological understanding of plant diseases. We present measurements of the incubation period obtained in field conditions, fit alternative probability models to the data, and show that the incubation period distribution changes with host age. By simulating spatially-explicit epidemiological models with different incubation-period distributions, we study the conditions for a significant time lag between epidemics of cryptic infection and the associated epidemics of symptomatic disease. We examine the sensitivity of this lag to differing distributional assumptions about the incubation period (i.e. exponential versus Gamma). We demonstrate that accurate information about the incubation period distribution of a pathosystem can be critical in assessing the true scale of pathogen invasion behind early disease symptoms in the field; likewise, it can be central to model-based prediction of epidemic risk and evaluation of disease management strategies. Our results highlight that reliance on observation of disease symptoms can cause significant delay in detection of soil-borne pathogen epidemics and mislead practitioners and epidemiologists about the timing, extent, and viability of disease control measures for limiting economic loss. [ABSTRACT FROM AUTHOR]

No matching vaccine is immediately available when a novel influenza strain breaks out. Several nonvaccine-related strategies must be employed to control an influenza epidemic, including antiviral treatment, patient isolation, and immigration detection. This paper presents the development and application of two regional dynamic models of influenza with Pontryagin’s Maximum Principle to determine the optimal control strategies for an epidemic and the corresponding minimum antiviral stockpiles. Antiviral treatment was found to be the most effective measure to control new influenza outbreaks. In the case of inadequate antiviral resources, the preferred approach was the centralized use of antiviral resources in the early stage of the epidemic. Immigration detection was the least cost-effective; however, when used in combination with the other measures, it may play a larger role. The reasonable mix of the three control measures could reduce the number of clinical cases substantially, to achieve the optimal control of new influenza. [ABSTRACT FROM AUTHOR]

Individual behavioral response to the spreading of an epidemic plays a crucial role in the progression of the epidemic itself. The risk perception induces individuals to adopt a protective behavior, as for instance reducing their social contacts, adopting more restrictive hygienic measures or undergoing prophylaxis procedures. In this paper, starting with a previously developed lattice-gas SIR model, we construct a coupled behavior-disease model for influenza spreading with spontaneous behavioral changes. The focus is on self-initiated behavioral changes that alter the susceptibility to the disease, without altering the contact patterns among individuals. Three different mechanisms of awareness spreading are analyzed: the local spreading due to the presence in the neighborhood of infective individuals; the global spreading due to the news published by the mass media and to educational campaigns implemented at institutional level; the local spreading occurring through the “thought contagion” among aware and unaware individuals. The peculiarity of the present approach is that the awareness spreading model is calibrated on available data on awareness and concern of the population about the risk of contagion. In particular, the model is validated against the A(H1N1) epidemic outbreak in Italy during the season, by making use of the awareness data gathered by the behavioral risk factor surveillance system (PASSI). We find that, increasing the accordance between the simulated awareness spreading and the PASSI data on risk perception, the agreement between simulated and experimental epidemiological data improves as well. Furthermore, we show that, within our model, the primary mechanism to reproduce a realistic evolution of the awareness during an epidemic, is the one due to globally available information. This result highlights how crucial is the role of mass media and educational campaigns in influencing the epidemic spreading of infectious diseases. [ABSTRACT FROM AUTHOR]

This paper explores the effect of social relations and gender-based conflicts on the uptake of HIV testing in the South and Central provinces of Zambia. We conducted a community-based cross-sectional study of 1716 randomly selected individuals. Associations were examined using mixed-effect multivariable logistic regression. A total of 264 men (64%) and 268 women (56%) had never tested for HIV. The strongest determinants for not being tested were disruptive couple relationships (OR = 2.48 95% CI = 1.00–6.19); tolerance to gender-based violence (OR = 2.10 95% CI = 1.05–4.32) and fear of social rejection (OR = 1.48 95% CI = 1.23–1.80). In the Zambian context, unequal power relationships within the couple and the community seem to play a pivotal role in the decision to test which until now have been largely underestimated. Policies, programs and interventions to rapidly increase HIV testing need to urgently address gender-power inequity in relationships and prevent gender-based violence to reduce the negative impact on the lives of couples and families. [ABSTRACT FROM AUTHOR]

In this study, we describe a novel porcine parechovirus-like virus (tentatively named PLV-CHN) from healthy piglets in China using 454 high-throughput sequencing. The complete genome of the virus comprises 6832 bp, encoding a predicted polyprotein of 2132 amino acids that is most similar to Ljungan virus (32% identity). A similar virus that belongs to a novel Picornaviridae genus, named swine pasivirus 1 (SPaV-1), was reported during the preparation of this paper. Sequence analysis revealed that PLV-CHN and SPaV1 shared 82% nucleotide identity and 89% amino acid identity. Further genomic and phylogenetic analyses suggested that both SPaV1 and PLV-CHN shared similar genomic characteristics and belong to the same novel Picornaviridae genus. A total of 36 (20.0%) fecal samples from 180 healthy piglets were positive for PLV-CHN by RT-PCR, while no fecal samples from 100 healthy children and 100 children with diarrhea, and no cerebrospinal fluid samples from 196 children with suspected viral encephalitis, was positive for the virus. However, Western blot and enzyme-linked immunosorbent assays using recombinant PLV-CHN VP1 polypeptide as an antigen showed a high seroprevalence of 63.5% in the healthy population. When grouped by age, the antibody-positivity rates showed that the majority of children under 12 years of age have been infected by the virus. It was suggested that PLV-CHN, SPaV1, or an as-yet-uncharacterized virus can infect humans early in life. Thus, investigation of the role of this novel virus is vital. [ABSTRACT FROM AUTHOR]

We consider the recently introduced edge-based compartmental models (EBCM) for the spread of susceptible-infected-recovered (SIR) diseases in networks. These models differ from standard infectious disease models by focusing on the status of a random partner in the population, rather than a random individual. This change in focus leads to simple analytic models for the spread of SIR diseases in random networks with heterogeneous degree. In this paper we extend this approach to handle deviations of the disease or population from the simplistic assumptions of earlier work. We allow the population to have structure due to effects such as demographic features or multiple types of risk behavior. We allow the disease to have more complicated natural history. Although we introduce these modifications in the static network context, it is straightforward to incorporate them into dynamic network models. We also consider serosorting, which requires using dynamic network models. The basic methods we use to derive these generalizations are widely applicable, and so it is straightforward to introduce many other generalizations not considered here. Our goal is twofold: to provide a number of examples generalizing the EBCM method for various different population or disease structures and to provide insight into how to derive such a model under new sets of assumptions. [ABSTRACT FROM AUTHOR]

One of network epidemiology's central assumptions is that the contact structure over which infectious diseases propagate can be represented as a static network. However, contacts are highly dynamic, changing at many time scales. In this paper, we investigate conceptually simple methods to construct static graphs for network epidemiology from temporal contact data. We evaluate these methods on empirical and synthetic model data. For almost all our cases, the network representation that captures most relevant information is a so-called exponential-threshold network. In these, each contact contributes with a weight decreasing exponentially with time, and there is an edge between a pair of vertices if the weight between them exceeds a threshold. Networks of aggregated contacts over an optimally chosen time window perform almost as good as the exponential-threshold networks. On the other hand, networks of accumulated contacts over the entire sampling time, and networks of concurrent partnerships, perform worse. We discuss these observations in the context of the temporal and topological structure of the data sets. [ABSTRACT FROM AUTHOR]

Age at infection with hepatitis B virus (HBV) is a known risk factor for chronic HBV infection. However, in addition, there is some evidence that early age at infection further increases the risk of primary liver cancer beyond its association with increased risk of chronic infection. This systematic review of observational studies assesses the association between age at initiation of chronic HBV infection and liver cirrhosis, hepatocellular carcinoma, and their predictors including indicators of ongoing viral replication and hepatic damage. The review includes birth order and maternal HBV serology as proxies for age at infection. Electronic searches in two English-language (Medline and Embase, until Jan 2012) and two Chinese-language (CNKI and SinoMed, until Sep 2012) databases without language restriction and manual search through reference lists identified 7,077 papers, of which 19 studies of 21 outcomes (8 primary liver cancer, 1 liver cirrhosis, 10 viral replication and 2 liver inflammation) are included. One study directly examined the age at infection in a longitudinal cohort, 12 assessed maternal sero-status and 6 investigated birth order. The direction of associations in all studies was in accordance with our hypothesis that earlier age at infection is associated with worse outcomes in addition to its effect of increasing the probability of chronic HBV infection. This has implications for the control of hepatitis B. [ABSTRACT FROM AUTHOR]

Several approaches have been proposed for near real-time detection and prediction of the spread of influenza. These include search query data for influenza-related terms, which has been explored as a tool for augmenting traditional surveillance methods. In this paper, we present a method that uses Internet search query data from Baidu to model and monitor influenza activity in China. The objectives of the study are to present a comprehensive technique for: (i) keyword selection, (ii) keyword filtering, (iii) index composition and (iv) modeling and detection of influenza activity in China. Sequential time-series for the selected composite keyword index is significantly correlated with Chinese influenza case data. In addition, one-month ahead prediction of influenza cases for the first eight months of 2012 has a mean absolute percent error less than 11%. To our knowledge, this is the first study on the use of search query data from Baidu in conjunction with this approach for estimation of influenza activity in China. [ABSTRACT FROM AUTHOR]