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Co-diagnosis of HIV and tuberculosis presents a treatment dilemma. Starting both treatments at the same time can cause a flood of immune response called immune reconstitution inflammatory syndrome (IRIS) which can be lethal. But, how long to delay HIV treatment is less understood. In 2011, based on the conclusions of three separate studies, WHO recommended starting HIV treatment earlier for those with later HIV disease progression. This paper conducts a replication study of one of the three studies, by Havlir and colleagues. Using their publicly available data, we were able to replicate most of the results presented in the original paper. In our measurement and estimation analyses we use different estimation techniques to assess the robustness of the results. We find that adjusting for loss to follow-up does not affect the main results of the paper. However, an ANCOVA estimation and an instrumental variable model weaken the main result of the paper of better outcomes with early HIV treatment only for those who are sicker, reducing significance from the 5% to the 10% level. A change-point analysis also detects no changes in effect by timing of HIV treatment initiation or different thresholds of CD4 count for the primary outcome. This result suggests that the choice of start time for HIV treatment initiation should be based on other factors including potential drug interactions, overlapping side effects, a high pill burden and severity of illness rather than CD4 threshold and preset timeframes. While we caution against overgeneralizing, the result of this replication is aligned with more recent studies that show no evidence that early initiation of HIV treatment reduces mortality for any patients. [ABSTRACT FROM AUTHOR]

TB is rated as one of the world’s deadliest diseases and South Africa ranks 9th out of the 22 countries with hardest hit of TB. Although many pieces of research have been carried out on this subject, this paper steps further by inculcating past knowledge into the model, using Bayesian approach with informative prior. Bayesian statistics approach is getting popular in data analyses. But, most applications of Bayesian inference technique are limited to situations of non-informative prior, where there is no solid external information about the distribution of the parameter of interest. The main aim of this study is to profile people living with TB in South Africa. In this paper, identical regression models are fitted for classical and Bayesian approach both with non-informative and informative prior, using South Africa General Household Survey (GHS) data for the year 2014. For the Bayesian model with informative prior, South Africa General Household Survey dataset for the year 2011 to 2013 are used to set up priors for the model 2014. [ABSTRACT FROM AUTHOR]

Image segmentation applied to medical image analysis is still a critical and important task. Although there exist several segmentation algorithms that have been widely studied in literature, these are subject to segmentation problems such as over- and under-segmentation as well as non-closed edges. In this paper, a simple method that combines well-known segmentation algorithms is presented. This method is applied to detect acid-fast bacilli (AFB) in bacilloscopies used to diagnose pulmonary tuberculosis (TB). This diagnosis can be performed through different tests, and the most used worldwide is smear microscopy because of its low cost and effectiveness. This diagnosis technique is based on the analysis and counting of the bacilli in the bacilloscopy observed under an optical microscope. The proposed method is used to segment the bacilli in digital images from bacilloscopies processed using Ziehl-Neelsen (ZN) staining. The proposed method is fast, has a low computational cost and good efficiency compared to other methods. The bacilli image segmentation is performed by image processing and analysis techniques, probability concepts and classifiers. In this work, a Bayesian classifier based on a Gaussian mixture model (GMM) is used. The segmentations' results are validated by using the Jaccard index, which indicates the efficiency of the classifier. [ABSTRACT FROM AUTHOR]

Leptospirosis is probably the most widespread zoonotic disease in the world especially in tropical countries. There has been an increase in individual studies, which assessed the frequency of leptospirosis in flood conditions. Some studies showed contact with floods was significantly associated with the occurrence of leptospirosis while other studies reported differently. The objective of this meta-analysis was to synthesize the evidence on the risk factors which are associated with human leptospirosis following flooding. We set up the inclusion criteria and searched for the original studies, addressing leptospirosis in human with related to flood in health-related electronic databases including PubMed, Embase, Ovid Medline, google scholar and Scopus sources. We used the terms ‘leptospirosis’, ‘flood’, ‘risk factor’ and terms from the categories were connected with “OR” within each category and by “AND” between categories. The initial search yielded 557 citations. After the title and abstract screening, 49 full-text papers were reviewed and a final of 18 observational studies met the pre-specified inclusion criteria. Overall, the pooled estimates of 14 studies showed that the contact with flooding was a significant factor for the occurrence of leptospirosis (pooled OR: 2.19, 95%CI: 1.48–3.24, I2:86%). On stratification, the strength of association was greater in the case-control studies (pooled OR: 4.01, 95%CI: 1.26–12.72, I2:82%) than other designs (pooled OR:1.77,95%CI:1.18–2.65, I2:87%). Three factors such as ‘being male’(pooled OR:2.06, 95%CI:1.29–2.83), the exposure to livestock animals (pooled OR: 1.95, 95%CI:1.26–2.64), the lacerated wound (pooled OR:4.35, 95%CI:3.07–5.64) were the risk factors significantly associated with the incidence of leptospirosis following flooding in the absence of within-study heterogeneity (I2: 0%). We acknowledge study limitations such as publication bias and type 2 statistical errors. We recommended flood control and other environmental modifications that are expected to reduce the risk of leptospiral infection, and a multi-sectoral effort to this aspect would have long-term benefits. [ABSTRACT FROM AUTHOR]

Background: Migrant labourers living in the slums of urban and industrial patches across India make up a key sub-population so far controlling Tuberculosis (TB) in the country is concerned. This is because many TB patients from these communities- remain under reached by the Revised National Tuberculosis Control Programme (RNTCP) of India. This marginalized community usually seeks early-stage healthcare from “friendly neighbourhood” non-formal health providers (NFHPs). Because, RNTCP has limited capacity to involve the NFHPs, an implementation research project was conceived, whereby an external partner would engage with the NFHPs to enable them to identify early TB symptomatics from this key sub-population who would be then tested using Xpert MTB/RIF technology. Diagnosed TB cases among them would be referred promptly to RNTCP for treatment. This paper aimed to describe the project and its impact. Methods: Adopting a quasi-experimental before-after design, four RNTCP units from two major urban-industrial areas of Odisha were selected for intervention, which spanned five quarters and covered 151,400 people, of which 30% were slum-dwelling migrants. Two similar units comprised the control population. The hypothesis was, reaching the under reached in the intervention area through NFHPs would increase TB notification from these traditionally under-notifying units. RNTCP notification data during intervention was compared with pre-intervention era, adjusted for contemporaneous changes in control population Results: The project detected 488 Xpert+ TB cases, of whom 466 were administered RNTCP treatment. This translated into notification of additional 198 new bacteriologically positive cases to RNTCP, a 30% notification surge, after adjustment for 2% decline in control. This meant an average quarterly increase in notification of 41.20(20.08, 62.31; p<0.001) cases. The increase was immediate, evident from the rise in level in the time series analysis by 50.42(10.28, 90.55; p = 0.02) cases. Conclusion: Engagement with NFHPs contributed to an increase in TB notification to RNTCP from key under reached, slum-dwelling migrant populations. [ABSTRACT FROM AUTHOR]

The study aimed to evaluate the efficacy of the combination of CPP-ACP and fluorides compared with fluorides monotherapy on patients with early caries lesions. The Medline, Embase and Cochrane databases up to August 2017 were scanned, with no restrictions. Studies satisfied the guideline of randomised controlled trials (RCTs), the patients with early caries lesions and data considering the efficacy of fluorides and CPP-ACP versus fluorides alone were selected. There was no language restriction during the literature search process, however, only papers in English or Chinese were included during the selection process. Outcome variables include laser fluorescence, quantitative light-induced fluorescence, lesion area and visual inspection scores. Mean differences were calculated during the data extraction process. Ten studies including 559 patients were selected in the meta-analysis. Fluorides combined with CPP-ACP achieved the same efficacy for early caries lesions on smooth surfaces compared with fluorides monotherapy (mean difference: -13.90, 95% confidence interval: [-39.25, 11.46], P = 0.28), and the combination treatment showed significantly better efficacy than fluorides monotherapy for occlusal early caries lesions (mean difference: -21.02, 95% confidence interval: [-27.94, -14.10], P<0.01). However, further well-designed studies are still needed. [ABSTRACT FROM AUTHOR]

This paper aims to reschedule online metro trains in delay scenarios. A graph representation and a mixed integer programming model are proposed to formulate the optimization problem. The solution approach is a two-stage optimization method. In the first stage, based on a proposed train state graph and system analysis, the primary and flow-on delays are specifically analyzed and identified with a critical path algorithm. For the second stage a hybrid genetic algorithm is designed to optimize the schedule, with the delay identification results as input. Then, based on the infrastructure data of Beijing Subway Line 4 of China, case studies are presented to demonstrate the effectiveness and efficiency of the solution approach. The results show that the algorithm can quickly and accurately identify primary delays among different types of delays. The economic cost of energy consumption and total delay is considerably reduced (by more than 10% in each case). The computation time of the Hybrid-GA is low enough for rescheduling online. Sensitivity analyses further demonstrate that the proposed approach can be used as a decision-making support tool for operators. [ABSTRACT FROM AUTHOR]

This paper models the prevalence of antibodies to Borrelia burgdorferi in domestic dogs in the United States using climate, geographic, and societal factors. We then use this model to forecast the prevalence of antibodies to B. burgdorferi in dogs for 2016. The data available for this study consists of 11,937,925 B. burgdorferi serologic test results collected at the county level within the 48 contiguous United States from 2011-2015. Using the serologic data, a baseline B. burgdorferi antibody prevalence map was constructed through the use of spatial smoothing techniques after temporal aggregation; i.e., head-banging and Kriging. In addition, several covariates purported to be associated with B. burgdorferi prevalence were collected on the same spatio-temporal granularity, and include forestation, elevation, water coverage, temperature, relative humidity, precipitation, population density, and median household income. A Bayesian spatio-temporal conditional autoregressive (CAR) model was used to analyze these data, for the purposes of identifying significant risk factors and for constructing disease forecasts. The fidelity of the forecasting technique was assessed using historical data, and a Lyme disease forecast for dogs in 2016 was constructed. The correlation between the county level model and baseline B. burgdorferi antibody prevalence estimates from 2011 to 2015 is 0.894, illustrating that the Bayesian spatio-temporal CAR model provides a good fit to these data. The fidelity of the forecasting technique was assessed in the usual fashion; i.e., the 2011-2014 data was used to forecast the 2015 county level prevalence, with comparisons between observed and predicted being made. The weighted (to acknowledge sample size) correlation between 2015 county level observed prevalence and 2015 forecasted prevalence is 0.978. A forecast for the prevalence of B. burgdorferi antibodies in domestic dogs in 2016 is also provided. The forecast presented from this model can be used to alert veterinarians in areas likely to see above average B. burgdorferi antibody prevalence in dogs in the upcoming year. In addition, because dogs and humans can be exposed to ticks in similar habitats, these data may ultimately prove useful in predicting areas where human Lyme disease risk may emerge. [ABSTRACT FROM AUTHOR]

Background: India has 23% of the global burden of active tuberculosis (TB) patients and 27% of the world's "missing" patients, which includes those who may not have received effective TB care and could potentially spread TB to others. The "cascade of care" is a useful model for visualizing deficiencies in case detection and retention in care, in order to prioritize interventions.Methods and Findings: The care cascade constructed in this paper focuses on the Revised National TB Control Programme (RNTCP), which treats about half of India's TB patients. We define the TB cascade as including the following patient populations: total prevalent active TB patients in India, TB patients who reach and undergo evaluation at RNTCP diagnostic facilities, patients successfully diagnosed with TB, patients who start treatment, patients retained to treatment completion, and patients who achieve 1-y recurrence-free survival. We estimate each step of the cascade for 2013 using data from two World Health Organization (WHO) reports (2014-2015), one WHO dataset (2015), and three RNTCP reports (2014-2016). In addition, we conduct three targeted systematic reviews of the scientific literature to identify 39 unique articles published from 2000-2015 that provide additional data on five indicators that help estimate different steps of the TB cascade. We construct separate care cascades for the overall population of patients with active TB and for patients with specific forms of TB-including new smear-positive, new smear-negative, retreatment smear-positive, and multidrug-resistant (MDR) TB. The WHO estimated that there were 2,700,000 (95%CI: 1,800,000-3,800,000) prevalent TB patients in India in 2013. Of these patients, we estimate that 1,938,027 (72%) TB patients were evaluated at RNTCP facilities; 1,629,906 (60%) were successfully diagnosed; 1,417,838 (53%) got registered for treatment; 1,221,764 (45%) completed treatment; and 1,049,237 (95%CI: 1,008,775-1,083,243), or 39%, of 2,700,000 TB patients achieved the optimal outcome of 1-y recurrence-free survival. The separate cascades for different forms of TB highlight different patterns of patient attrition. Pretreatment loss to follow-up of diagnosed patients and post-treatment TB recurrence were major points of attrition in the new smear-positive TB cascade. In the new smear-negative and MDR TB cascades, a substantial proportion of patients who were evaluated at RNTCP diagnostic facilities were not successfully diagnosed. Retreatment smear-positive and MDR TB patients had poorer treatment outcomes than the general TB population. Limitations of our analysis include the lack of available data on the cascade of care in the private sector and substantial uncertainty regarding the 1-y period prevalence of TB in India.Conclusions: Increasing case detection is critical to improving outcomes in India's TB cascade of care, especially for smear-negative and MDR TB patients. For new smear-positive patients, pretreatment loss to follow-up and post-treatment TB recurrence are considerable points of attrition that may contribute to ongoing TB transmission. Future multisite studies providing more accurate information on key steps in the public sector TB cascade and extension of this analysis to private sector patients may help to better target interventions and resources for TB control in India. [ABSTRACT FROM AUTHOR]

Objective: To carry out a systematic review with meta-analysis of prevalence of caries in Latin America and Caribbean children considering studies performed in this new century. Methods: Two reviewers searched PubMed, Embase, LILACS and governmental databases through May 2016 to identify papers published in English, Portuguese or Spanish. Studies in those countries performed with 5–6 or 11–13 year-old children and that presented separate prevalence figures from primary and permanent teeth were selected. We performed a descriptive analysis of studies and meta-analysis to calculate the overall prevalence and 95% confidence intervals (95% CI) in both primary and permanent teeth. We also analyzed the trends of prevalence of caries through the years and influence of other variables on caries prevalence using multilevel analysis. Results: Seventy-five studies were included from the 1,306 articles initially retrieved. The meta-analysis of caries prevalence grouped for Latin American and the Caribbean countries were highly different from Brazil and other investigated countries for primary teeth (5–6 years-old—Brazil: 0.52, other countries:0.70) and permanent teeth (11–12 years-old—Brazil: 0.56, other countries: 0.63). For studies conducted only in Brazil the prevalence was significant lower for primary but not for permanent teeth. In Brazil, a downward trend of caries prevalence was observed in 11-13-year-old children. Conclusion: Despite the decline of caries prevalence in permanent teeth, mainly in Brazil, the disease still affects more than half of the children population in Latin American and Caribbean countries in the 21st Century. [ABSTRACT FROM AUTHOR]

An unfused tetanus of a motor unit (MU) evoked by a train of pulses at variable interpulse intervals is the sum of non-equal twitch-like responses to these stimuli. A tool for a precise prediction of these successive contractions for MUs of different physiological types with different contractile properties is crucial for modeling the whole muscle behavior during various types of activity. The aim of this paper is to develop such a general mathematical algorithm for the MUs of the medial gastrocnemius muscle of rats. For this purpose, tetanic curves recorded for 30 MUs (10 slow, 10 fast fatigue-resistant and 10 fast fatigable) were mathematically decomposed into twitch-like contractions. Each contraction was modeled by the previously proposed 6-parameter analytical function, and the analysis of these six parameters allowed us to develop a prediction algorithm based on the following input data: parameters of the initial twitch, the maximum force of a MU and the series of pulses. Linear relationship was found between the normalized amplitudes of the successive contractions and the remainder between the actual force levels at which the contraction started and the maximum tetanic force. The normalization was made according to the amplitude of the first decomposed twitch. However, the respective approximation lines had different specific angles with respect to the ordinate. These angles had different and non-overlapping ranges for slow and fast MUs. A sensitivity analysis concerning this slope was performed and the dependence between the angles and the maximal fused tetanic force normalized to the amplitude of the first contraction was approximated by a power function. The normalized MU contraction and half-relaxation times were approximated by linear functions depending on the normalized actual force levels at which each contraction starts. The normalization was made according to the contraction time of the first contraction. The actual force levels were calculated initially from the recorded tetanic curves and subsequently from the modeled curves obtained from the summation of all models of the preceding contractions (the so called “full prediction”). The preciseness of the prediction was verified by two coefficients estimating the error between the modeled and the experimentally recorded curves. The proposed approach was tested for 30 MUs from the database and for three additional MUs, not included in the initial set. It was concluded that this general algorithm can be successfully used for modeling of a unfused tetanus course of a single MU of fast and slow type. [ABSTRACT FROM AUTHOR]

Background: Accurate diagnosis of latent tuberculosis infection (LTBI) is becoming increasingly concerning due to the increasing the HIV epidemic, which have increased the risk for reactivation to active tuberculosis (TB) infection. LTBI is diagnosed by tuberculin skin test (TST) and interferon-gamma release assays (IGRAs). Objectives: The aim of the present study was to conduct a meta-analysis of published papers on the agreement (kappa) between TST and QuantiFERON-TB Gold In-Tube (QFT-GIT) tests for diagnosis of LTBI in HIV patient. Methods: Electronic databases including PubMed/Medline, Elsevier/Scopus and Embase/Ovid were reviewed up Jan. 2016. We performed a random effect model meta-analysis for estimation of pooled Kappa between the two methods of diagnosis. Meta regression was used for assessing potential heterogeneity and Egger’s test was used for assessing small study effect and publication bias. Results: The initial search strategy produced 6744 records. Of them, 23 cross-sectional studies met the inclusion criteria and 20 studies entered in meta-analysis. The pooled kappa was and prevalence-adjusted and bias-adjusted kappa (PABAK) were 0.37 (95% CI: 0.28, 0.46) and 0.59 (0.49, 0.69). The discordance of TST-/QFT-GIT+ was more than TST+/QFT-GIT-. Kappa estimate between two tests was linearly associated with age and prevalence index and inversely associated with bias index. Conclusion: Fair agreement between TST and QFT-GIT makes it difficult to know whether TST is as useful as the QFT-GIT in HIV-infected patients. The higher discordance of TST-/QFT-GIT+ in compared to TST+/QFT-GIT- can induce the higher sensitivity of QFT-GIT for diagnosis LTBI in HIV patients. Disagreement between two tests can be influenced by error in measurements and prevalence of HIV. [ABSTRACT FROM AUTHOR]

Pertussis is a contagious respiratory disease which mainly affects young children and can be fatal if left untreated. The World Health Organization estimates 16 million pertussis cases annually worldwide resulting in over 200,000 deaths. It is prevalent mainly in developing countries where it is difficult to diagnose due to the lack of healthcare facilities and medical professionals. Hence, a low-cost, quick and easily accessible solution is needed to provide pertussis diagnosis in such areas to contain an outbreak. In this paper we present an algorithm for automated diagnosis of pertussis using audio signals by analyzing cough and whoop sounds. The algorithm consists of three main blocks to perform automatic cough detection, cough classification and whooping sound detection. Each of these extract relevant features from the audio signal and subsequently classify them using a logistic regression model. The output from these blocks is collated to provide a pertussis likelihood diagnosis. The performance of the proposed algorithm is evaluated using audio recordings from 38 patients. The algorithm is able to diagnose all pertussis successfully from all audio recordings without any false diagnosis. It can also automatically detect individual cough sounds with 92% accuracy and PPV of 97%. The low complexity of the proposed algorithm coupled with its high accuracy demonstrates that it can be readily deployed using smartphones and can be extremely useful for quick identification or early screening of pertussis and for infection outbreaks control. [ABSTRACT FROM AUTHOR]

Background: The infection rate of syphilis in China has increased dramatically in recent decades, becoming a serious public health concern. Early prediction of syphilis is therefore of great importance for heath planning and management. Methods: In this paper, we analyzed surveillance time series data for primary, secondary, tertiary, congenital and latent syphilis in mainland China from 2005 to 2012. Seasonality and long-term trend were explored with decomposition methods. Autoregressive integrated moving average (ARIMA) was used to fit a univariate time series model of syphilis incidence. A separate multi-variable time series for each syphilis type was also tested using an autoregressive integrated moving average model with exogenous variables (ARIMAX). Results: The syphilis incidence rates have increased three-fold from 2005 to 2012. All syphilis time series showed strong seasonality and increasing long-term trend. Both ARIMA and ARIMAX models fitted and estimated syphilis incidence well. All univariate time series showed highest goodness-of-fit results with the ARIMA(0,0,1)×(0,1,1) model. Conclusion: Time series analysis was an effective tool for modelling the historical and future incidence of syphilis in China. The ARIMAX model showed superior performance than the ARIMA model for the modelling of syphilis incidence. Time series correlations existed between the models for primary, secondary, tertiary, congenital and latent syphilis. [ABSTRACT FROM AUTHOR]