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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]

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]

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]

Contact tracing forms a crucial part of the public-health toolbox in mitigating and understanding emergent pathogens and nascent disease outbreaks. Contact tracing in the United States was conducted during the pre-Omicron phase of the ongoing COVID-19 pandemic. This tracing relied on voluntary reporting and responses, often using rapid antigen tests due to lack of accessibility to PCR tests. These limitations, combined with SARS-CoV-2's propensity for asymptomatic transmission, raise the question "how reliable was contact tracing for COVID-19 in the United States"? We answered this question using a Markov model to examine the efficiency with which transmission could be detected based on the design and response rates of contact tracing studies in the United States. Our results suggest that contact tracing protocols in the U.S. are unlikely to have identified more than 1.65% (95% uncertainty interval: 1.62-1.68%) of transmission events with PCR testing and 1.00% (95% uncertainty interval 0.98-1.02%) with rapid antigen testing. When considering a more robust contact tracing scenario, based on compliance rates in East Asia with PCR testing, this increases to 62.7% (95% uncertainty interval: 62.6-62.8%). We did not assume presence of asymptomatic transmission or superspreading, making our estimates upper bounds on the actual percentages traced. These findings highlight the limitations in interpretability for studies of SARS-CoV-2 disease spread based on U.S. contact tracing and underscore the vulnerability of the population to future disease outbreaks, for SARS-CoV-2 and other pathogens. [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]

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]

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]

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: 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]

The aim of this paper is to show that a large class of epidemic models, with both demography and non-permanent immunity incorporated in a rather general manner, can be mathematically formulated as a scalar renewal equation for the force of infection. [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]

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]

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]

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]

This paper reports the first recreation-related leptospirosis outbreak in Sri Lanka in 20 office workers who were involved in white-water rafting during a staff outing. Two weeks after the rafting event on 7 September 2012, six participants developed fever, of which four had classical clinical features of leptospirosis. Four weeks after the exposure, an outbreak investigation was conducted for 19 of the 20 participants. Of the six fever patients, four were confirmed as having acute leptospirosis using either single sample MAT titre ⩾1/400 (n = 2) or positive IgM ELISA (n = 2). An afebrile patient with headache and myalgia also had a MAT titre ⩾1/400. Seventeen of the 19 participants investigated showed anti-leptospiral antibodies. None of the participants had a history of leptospirosis or recent outdoor exposures other than the rafting event. This outbreak provides evidence of the changing epidemiology of leptospirosis and suggests a wider range of risk exposures including those related to recreational activities of more affluent urban populations in addition to the well recognized occupational hazards of rural farming. [ABSTRACT FROM PUBLISHER]

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]

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]

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]

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]

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]

Background: A large proportion of patients receiving antiretroviral therapy (ART) in low and middle income countries (LMICs) have unknown treatment outcomes and are classified as lost to follow-up (LTFU). Physical tracing of patients classified as LTFU is common; however, effects of tracing on outcomes remains unclear. The objective of this systematic review is to compare estimates of LTFU, mortality and retention in LMIC in cohorts of patients with and without physical tracing. Methods and Findings: We systematically identified studies in LMIC programmatic settings using MEDLINE (2003–2011) and HIV conference abstracts (2009–2011). Studies reporting the proportion LTFU 12-months after ART initiation were included. Tracing activities were determined from manuscripts or by contacting study authors. Studies were classified as “tracing studies” if physical tracing was available for the majority of patients. Summary estimates from the 2 groups of studies (tracing and non-tracing) for LTFU, mortality, stop of ART, transfers out, and retention on ART were determined. 261 papers and 616 abstracts were identified of which 39 studies comprising 54 separate cohorts (n = 187,666) met inclusion criteria. Of those, physical tracing was available for 46% of cohorts. Treatment programs with physical tracing activities had lower estimated LTFU (7.6% vs. 15.1%; p<.001), higher estimated mortality (10.5% vs. 6.6%; p = .006), higher retention on ART (80.0 vs. 75.8%; p = .04) and higher retention at the original site (80.0% vs. 72.9%; p = .02). Conclusions: Knowledge of patient tracing is critical when interpreting program outcomes of LTFU, mortality and retention. The reduction of the proportion LTFU in tracing studies was only partially explained by re-classification of unknown outcomes. These data suggest that tracing may lead to increased re-engagement of patients in care, rather than just improved classification of unknown outcomes. [ABSTRACT FROM AUTHOR]

Background: An important issue associated with the control of visceral leishmaniasis is the need to identify and understand the relevance of asymptomatic infection caused by Leishmania infantum. The aim of this study was to follow the course of asymptomatic L. infantum infection in children in an area of Brazil where it is endemic. The children were assessed twice during a 12-month period. Methodology: In this population study, 1875 children, ranging from 6 months to 7 years of age, were assessed. Blood samples were collected on filter papers via finger prick and tested by ELISA (L. infantum soluble antigen and rk39). Seropositives samples (n = 317) and a number of seronegatives samples (n = 242) were subjected to qPCR. After 12 months, blood samples were collected from a subgroup of 199 children and tested for Leishmania spp. to follow the course of infection. Principal Findings: At baseline qPCR testing identified 82 positive samples. The prevalence rate, as estimated for 1875 children based on the qPCR results, was 13.9%. The qPCR testing of whole blood samples collected from a cohort of children after 12 months (n = 199) yielded the following results: of the 44 (22.1%) children with positive qPCR results at baseline, only 10 (5.0%) remained positive, and 34 (17.1%) became negative; and of the 155 (77.9%) children with negative qPCR results, 131 (65.8%) remained negative, and 24 (12.1%) became positive at the follow-up measurement. The samples with positive findings at baseline (n = 82) had a mean of 56.5 parasites/mL of blood; and at follow-up the mean positive result was 7.8 parasites/mL. Conclusions: The peripheral blood of asymptomatic children had a low and fluctuating quantity of Leishmania DNA and a significant decrease in parasitemia at 1-year follow-up. Quantitative PCR enables adequate monitoring of Leishmania infection. [ABSTRACT FROM AUTHOR]

Healthcare generates large amounts of data that require professional skills to analyze it for decisionmaking. In the case of pandemics, generated data is used for analysis and interpretation. Healthcare professionals, governments, researchers, and the general public use the information and analysis results for awareness, alerting the public about conditions to curb the spread of diseases. Currently, the world is battling the virulent COVID-19 pandemic. Data related to the disease is streaming from around the world. This data has to be analyzed, processed, and transformed into easily consumed information by users. Different skills are needed when interacting with this data to draw inferences. This paper seeks to carry out a systematic literature review (SLR) on the COVID-19 pandemic and investigate the role of data literacy in the information systems response. The classification of literature focuses on the types of data, users, and technologies utilized in response to COVID-19. [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]

Primary infection with varicella-zoster virus in pregnancy poses a risk of severe infection and embryopathies. Upon exposure, seronegative women are candidates for varicella-zoster immunoglobulin (VZIG). The aim of this paper was to describe risk factors for VZIG treatment including sources of varicella exposure and to study how many women developed clinical infection and received postpartum vaccination. We identified all pregnant women who received VZIG from December 2005 to March 2015. Additional information was obtained from Danish registers and a follow-up questionnaire. A total of 104 women were included and 88 completed the questionnaire. Significantly more women had ‘other country of origin’ than Denmark. They were more often second para (57%) and had most commonly been exposed to varicella by their own child (58%). Five women developed clinical varicella infection, and only 26·5% were vaccinated after delivery. The study concludes that few women developed infection after VZIG and none developed pneumonia. General practitioners should be particularly aware of obtaining varicella anamnesis in parous women from non-temperate countries in order to perform selective vaccination prior to pregnancy. In case of varicella exposure during pregnancy in a seronegative woman, postpartum vaccination is crucial. [ABSTRACT FROM PUBLISHER]

During the COVID-19 pandemic in Germany, a variety of societal activities were restricted to minimize direct personal interactions and, consequently, reduce SARS-CoV-2 transmission. The aim of the CoViRiS study was to investigate whether certain behaviours and societal factors were associated with the risk of sporadic symptomatic SARS-CoV-2 infections. Adult COVID-19 cases and frequency-matched population controls were interviewed by telephone regarding activities that involved contact with other people during the 10 days before illness onset (cases) or before the interview (controls). Associations between activities and symptomatic SARS-CoV-2 infection were analysed using logistic regression models adjusted for potential confounding variables. Data of 859 cases and 1 971 controls were available for analysis. The risk of symptomatic SARS-CoV-2 infection was lower for individuals who worked from home (adjusted odds ratio (aOR) 0.5; 95% confidence interval (CI) 0.3–0.6). Working in a health care setting was associated with a higher risk (aOR: 1.5; 95% CI: 1.1–2.1) as were private indoor contacts, personal contacts that involved shaking hands or hugging, and overnight travelling within Germany. Our results are in line with some of the public health recommendations aimed at reducing interpersonal contacts during the COVID-19 pandemic. [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 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]

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]

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]

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]

We conducted a matched case-control (MCC), test-negative case-control (TNCC) and case cohort study in 2016 in Lusaka, Zambia, following a mass vaccination campaign. Confirmed cholera cases served as cases in all three study designs. In the TNCC, control-subjects were cases with negative cholera culture and polymerase chain reaction results. Matched controls by age and sex were selected among neighbours of the confirmed cases in the MCC study. For the case-cohort study, we recruited a cohort of randomly selected individuals living in areas considered at-risk of cholera. We recruited 211 suspected cases (66 confirmed cholera cases and 145 non-cholera diarrhoea cases), 1055 matched controls and a cohort of 921. Adjusted vaccine effectiveness of one dose of oral cholera vaccine (OCV) was 88.9% (95% confidence interval (CI) 42.7–97.8) in the MCC study, 80.2% (95% CI: 16.9–95.3) in the TNCC design and 89.4% (95% CI: 64.6–96.9) in the case-cohort study. Three study designs confirmed the short-term effectiveness of single dose OCV. Major healthcare-seeking behaviour bias did not appear to affect our estimates. Most of the protection among vaccinated individuals could be attributed to the direct effect of the vaccine. [ABSTRACT FROM AUTHOR]

Introduction: Febrile illnesses (FI) represent a typical spectrum of diseases in low-resource settings, either in isolation or with other common symptoms. They contribute substantially to morbidity and mortality in India. The primary objective was to study the burden of FI based on Integrated Disease Surveillance Programme (IDSP) data in Punjab, analyze geospatial and temporal trends and patterns, and identify the potential hotspots for effective intervention. Methods: A retrospective ecological study used the district-level IDSP reports between 2012 and 2019. Diseases responsible for FI on a large scale, like Dengue, Chikungunya, Malaria (Plasmodium Falciparum, P. Vivax), Enteric fever, and Pyrexia of Unknown Origin (PUO), were included in the analysis. The digital map of Punjab was obtained from GitHub. Spatial autocorrelation and cluster analysis were done using Moran's I and Getis-Ord G* to determine hotspots of FI using the incidence and crude disease numbers reported under IDSP. Further, negative binomial regression was used to determine the association between Spatio-temporal and population variables per the census 2011. Stable hotspots were depicted using heat maps generated from district-wise yearly data. Results: PUO was the highest reported FI. We observed a rising trend in the incidence of Dengue, Chikungunya, and Enteric fever, which depicted occasional spikes during the study period. FI expressed significant inter-district variations and clustering during the start of the study period, with more dispersion in the latter part of the study period. P.Vivax malaria depicted stable hotspots in southern districts of Punjab. In contrast, P. Falciparum malaria, Chikungunya, and PUO expressed no spatial patterns. Enteric Fever incidence was high in central and northeastern districts but depicted no stable spatial patterns. Certain districts were common incidence hotspots for multiple diseases. The number of cases in each district has shown over-dispersion for each disease and has little dependence on population, gender, or residence as per regression analysis. Conclusions: The study demonstrates that information obtained through IDSP can describe the spatial epidemiology of FI at crude spatial scales and drive concerted efforts against FI by identifying actionable points. [ABSTRACT FROM AUTHOR]

This paper summarizes influenza activity in the European Union/European Economic Area (EU/EEA) in 2012–2013. The influenza season 2012–2013 in Europe lasted from early December to late April. Overall the severity of the season could be described as moderate, based on the ILI/ARI consultation rates and the percentage of sentinel specimens positive for influenza compared to previous seasons. Both influenza A and B viruses circulating accounted for 47% and 53% of positive sentinel specimens, respectively, with both A(H1) and A(H3) varying for dominance. Compared to outpatients, the proportion of laboratory-confirmed influenza hospitalized cases infected by A(H1N1)pdm09 was significantly higher in middle-aged patients (33% vs. 17%, χ2 = 66·6, P < 0·01). Despite a relatively good match between vaccine and circulating strains, vaccine effectiveness was estimated to be moderate. [ABSTRACT FROM PUBLISHER]

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]

Background: Typhoid fever remains a major health problem in the developing world. Intestinal perforation is a lethal complication and continues to occur in impoverished areas despite advances in preventive and therapeutic strategies. Objectives: To estimate the case fatality rate (CFR) and length of hospital stay among patients with typhoid intestinal perforation in developing countries. Data Sources: Peer-reviewed publications listed in PubMed and Google Scholar. Study Eligibility: The publications containing data on CFR or length of hospitalization for typhoid fever from low, lower middle and upper middle income countries based on World Bank classification. Limits are English language, human research and publication date from 1st January 1991 to 31st December 2011. Participants: Subjects with reported typhoid intestinal perforation. Interventions: None, standard practice as reported in the publication. Study Appraisal and Synthesis Methods: Systematic literature review followed by meta-analysis after regional classification on primary data. Descriptive methods were applied on secondary data. Results: From 42 published reports, a total of 4,626 hospitalized typhoid intestinal perforation cases and 706 deaths were recorded (CFR = 15·4%; 95% CI; 13·0%–17·8%) with a significant regional differences. The overall mean length of hospitalization for intestinal perforation from 23 studies was 18.4 days (N = 2,542; 95% CI; 15.6–21.1). Limitations: Most typhoid intestinal perforation studies featured in this review were from a limited number of countries. Conclusions: The CFR estimated in this review is a substantial reduction from the 39.6% reported from a literature review for years 1960 to 1990. Aggressive resuscitation, appropriate antimicrobial coverage, and prompt surgical intervention may have contributed to decrease mortality. Implications: The quantification of intestinal perforation outcomes and its regional disparities as presented here is valuable in prioritizing and targeting typhoid-preventive interventions to the most affected areas. [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]

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]

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]