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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]

Objectives: This paper examines the ethnic and gender differentials in high blood pressure (HBP), diabetes, coronary heart disease (CHD), arthritis and asthma among older people in Malaysia, and how these diseases along with other factors affect self-rated health. Differentials in the prevalence of non-communicable diseases among older people are examined in the context of socio-cultural perspectives in multi-ethnic Malaysia. Methods: Data for this paper are obtained from the 2004 Malaysian Population and Family Survey. The survey covered a nationally representative sample of 3,406 persons aged 50 and over, comprising three main ethnic groups (Malays, Chinese and Indians) and all other indigenous groups. Bivariate analyses and hierarchical logistic regression were used in the analyses. Results: Arthritis was the most common non-communicable disease (NCD), followed by HBP, diabetes, asthma and CHD. Older females were more likely than males to have arthritis and HBP, but males were more likely to have asthma. Diabetes and CHD were most prevalent among Indians, while arthritis and HBP were most prevalent among the Indigenous groups. Older people were more likely to report poor health if they suffered from NCD, especially CHD. Controlling for socio-economic, health and lifestyle factors, Chinese were least likely to report poor health, whereas Indians and Indigenous people were more likely to do so. Chinese that had HBP were more likely to report poor health compared to other ethnic groups with the same disease. Among those with arthritis, Indians were more likely to report poor health. Conclusion: Perceived health status and prevalence of arthritis, HBP, diabetes, asthma and CHD varied widely across ethnic groups. Promotion of healthy lifestyle, early detection and timely intervention of NCDs affecting different ethnic groups and gender with socio-cultural orientations would go a long way in alleviating the debilitating effects of the common NCDs among older people. [ABSTRACT FROM AUTHOR]

Objectives: Increasing walking and cycling, and reducing motorised transport, are health and environmental priorities. This paper examines levels and trends in the use of different commute modes in England and Wales, both overall and with respect to small-area deprivation. It also investigates whether commute modal share can serve as a proxy for travel behaviour more generally. Methods: 23.7 million adult commuters reported their usual main mode of travelling to work in the 2011 census in England and Wales; similar data were available for 1971–2001. Indices of Multiple Deprivation were used to characterise socio-economic patterning. The National Travel Survey (2002–2010) was used to examine correlations between commute modal share and modal share of total travel time. These correlations were calculated across 150 non-overlapping populations defined by region, year band and income. Results: Among commuters in 2011, 67.1% used private motorised transport as their usual main commute mode (−1.8 percentage-point change since 2001); 17.8% used public transport (+1.8% change); 10.9% walked (−0.1% change); and 3.1% cycled (+0.1% change). Walking and, to a marginal extent, cycling were more common among those from deprived areas, but these gradients had flattened over the previous decade to the point of having essentially disappeared for cycling. In the National Travel Survey, commute modal share and total modal share were reasonably highly correlated for private motorised transport (r = 0.94), public transport (r = 0.96), walking (r = 0.88 excluding London) and cycling (r = 0.77). Conclusions: England and Wales remain car-dependent, but the trends are slightly more encouraging. Unlike many health behaviours, it is more common for socio-economically disadvantaged groups to commute using physically active modes. This association is, however, weakening and may soon reverse for cycling. At a population level, commute modal share provides a reasonable proxy for broader travel patterns, enhancing the value of the census in characterising background trends and evaluating interventions. [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: Bangladesh had one of the highest burdens of lymphatic filariasis (LF) at the start of the Global Programme to Eliminate Lymphatic Filariasis (GPELF) with an estimated 70 million people at risk of infection across 34 districts. In total 19 districts required mass drug administration (MDA) to interrupt transmission, and 15 districts were considered low endemic. Since 2001, the National LF Programme has implemented MDA, reduced prevalence, and been able to scale up the WHO standard Transmission Assessment Survey (TAS) across all endemic districts as part of its endgame surveillance strategy. This paper presents TAS results, highlighting the momentous geographical reduction in risk of LF and its contribution to the global elimination target of 2020. Methodology/Principal findings: The TAS assessed primary school children for the presence of LF antigenaemia in each district (known as an evaluation unit—EU), using a defined critical cut-off threshold (or ‘pass’) that indicates interruption of transmission. Since 2011, a total of 59 TAS have been conducted in 26 EUs across the 19 endemic MDA districts (99,148 students tested from 1,801 schools), and 22 TAS in the 15 low endemic non-MDA districts (36,932 students tested from 663 schools). All endemic MDA districts passed TAS, except in Rangpur which required two further rounds of MDA. In total 112 students (male n = 59; female n = 53), predominately from the northern region of the country were found to be antigenaemia positive, indicating a recent or current infection. However, the distribution was geographically sparse, with only two small focal areas showing potential evidence of persistent transmission. Conclusions/Significance: This is the largest scale up of TAS surveillance activities reported in any of the 73 LF endemic countries in the world. Bangladesh is now considered to have very low or no risk of LF infection after 15 years of programmatic activities, and is on track to meet elimination targets. However, it will be essential that the LF Programme continues to develop and maintain a comprehensive surveillance strategy that is integrated into the health infrastructure and ongoing programmes to ensure cost-effectiveness and sustainability. [ABSTRACT FROM AUTHOR]

Data concerning the effects of phthalate exposure on preterm delivery and fetal growth are limited in humans. In this paper, we assessed the relationship between 15 phthalate levels in cord blood and preterm delivery and fetal growth parameters in 207 Chinese women going into labor. Exposure to phthalates except DCHP was associated with gestational age reduction and preterm delivery (p<0.05). There were associations between phthalates and fetal growth parameters, many of which disappeared when analyses were adjusted for gestational age, especially in male infants (Only DEEP was associated with birth weight; DEP, DNHP, BBP, DNP with abdominal circumference; DEP, DBP, DCHP, DEHP with femur length in female infants. And DPP, DBEP was associated with birth length in male infants. p<0.05). This study indicates that prenatal exposure to phthalates is associated with younger gestational age and preterm delivery. Also, phthalate exposure may adversely affect fetal growth parameters via gestational age reduction and preterm delivery with a significant gender effect. [ABSTRACT FROM AUTHOR]

Developing appropriate risk messages during challenging situations like public health outbreaks is complicated. The focus of this paper is on how First Nations and Metis people in Manitoba, Canada, responded to the public health management of pandemic H1N1, using a focus group methodology (n = 23 focus groups). Focus group conversations explored participant reactions to messaging regarding the identification of H1N1 virus risk groups, the H1N1 vaccine and how priority groups to receive the vaccine were established. To better contextualize the intentions of public health professionals, key informant interviews (n = 20) were conducted with different health decision makers (e.g., public health officials, people responsible for communications, representatives from some First Nations and Metis self-governing organizations). While risk communication practice has improved, ‘one size’ messaging campaigns do not work effectively, particularly when communicating about who is most ‘at-risk’. Public health agencies need to pay more attention to the specific socio-economic, historical and cultural contexts of First Nations and Metis citizens when planning for, communicating and managing responses associated with pandemic outbreaks to better tailor both the messages and delivery. More attention is needed to directly engage First Nations and Metis communities in the development and dissemination of risk messaging. [ABSTRACT FROM AUTHOR]

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

The Water-associated Disease Index (WADI) was developed to identify and visualize vulnerability to different water-associated diseases by integrating a range of social and biophysical determinants in map format. In this study vulnerability is used to encompass conditions of exposure, susceptibility, and differential coping capacity to a water-associated health hazard. By assessing these conditions, the tool is designed to provide stakeholders with an integrated and long-term understanding of subnational vulnerabilities to water-associated disease and contribute to intervention strategies to reduce the burden of illness. The objective of this paper is to describe and validate the WADI tool by applying it to dengue. A systemic ecohealth framework that considers links between people, the environment and health was applied to identify secondary datasets, populating the index with components including climate conditions, land cover, education status and water use practices. Data were aggregated to create composite indicators of exposure and of susceptibility in a Geographic Information System (GIS). These indicators were weighted by their contribution to dengue vulnerability, and the output consisted of an overall index visualized in map format. The WADI was validated in this Malaysia case study, demonstrating a significant association with dengue rates at a sub-national level, and illustrating a range of factors that drive vulnerability to the disease within the country. The index output indicated high vulnerability to dengue in urban areas, especially in the capital Kuala Lumpur and surrounding region. However, in other regions, vulnerability to dengue varied throughout the year due to the influence of seasonal climate conditions, such as monsoon patterns. The WADI tool complements early warning models for water-associated disease by providing upstream information for planning prevention and control approaches, which increasingly require a comprehensive and geographically broad understanding of vulnerability for implementation. [ABSTRACT FROM AUTHOR]

Accurate incidence forecasting of infectious disease is critical for early prevention and for better government strategic planning. In this paper, we present a comprehensive study of different forecasting methods based on the monthly incidence of typhoid fever. The seasonal autoregressive integrated moving average (SARIMA) model and three different models inspired by neural networks, namely, back propagation neural networks (BPNN), radial basis function neural networks (RBFNN), and Elman recurrent neural networks (ERNN) were compared. The differences as well as the advantages and disadvantages, among the SARIMA model and the neural networks were summarized and discussed. The data obtained for 2005 to 2009 and for 2010 from the Chinese Center for Disease Control and Prevention 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 results showed that RBFNN obtained the smallest MAE, MAPE and MSE in both the modeling and forecasting processes. The performances of the four models ranked in descending order were: RBFNN, ERNN, BPNN and the SARIMA model. [ABSTRACT FROM AUTHOR]

Background: Mosquito-borne diseases are climate sensitive and there has been increasing concern over the impact of climate change on future disease risk. This paper projected the potential future risk of Barmah Forest virus (BFV) disease under climate change scenarios in Queensland, Australia. Methods/Principal Findings: We obtained data on notified BFV cases, climate (maximum and minimum temperature and rainfall), socio-economic and tidal conditions for current period 2000–2008 for coastal regions in Queensland. Grid-data on future climate projections for 2025, 2050 and 2100 were also obtained. Logistic regression models were built to forecast the otential risk of BFV disease distribution under existing climatic, socio-economic and tidal conditions. The model was applied to estimate the potential geographic distribution of BFV outbreaks under climate change scenarios. The predictive model had good model accuracy, sensitivity and specificity. Maps on potential risk of future BFV disease indicated that disease would vary significantly across coastal regions in Queensland by 2100 due to marked differences in future rainfall and temperature projections. Conclusions/Significance: We conclude that the results of this study demonstrate that the future risk of BFV disease would vary across coastal regions in Queensland. These results may be helpful for public health decision making towards developing effective risk management strategies for BFV disease control and prevention programs in Queensland. [ABSTRACT FROM AUTHOR]

Background: syndromic surveillance system has great advantages in promoting the early detection of epidemics and reducing the necessities of disease confirmation, and it is especially effective for surveillance in resource poor settings. However, most current syndromic surveillance systems are established in developed countries, and there are very few reports on the development of an electronic syndromic surveillance system in resource-constrained settings. Objective: this study describes the design and pilot implementation of an electronic surveillance system (ISS) for the early detection of infectious disease epidemics in rural China, complementing the conventional case report surveillance system. Methods: ISS was developed based on an existing platform ‘Crisis Information Sharing Platform’ (CRISP), combining with modern communication and GIS technology. ISS has four interconnected functions: 1) work group and communication group; 2) data source and collection; 3) data visualization; and 4) outbreak detection and alerting. Results: As of Jan. 31st 2012, ISS has been installed and pilot tested for six months in four counties in rural China. 95 health facilities, 14 pharmacies and 24 primary schools participated in the pilot study, entering respectively 74256, 79701, and 2330 daily records into the central database. More than 90% of surveillance units at the study sites are able to send daily information into the system. In the paper, we also presented the pilot data from health facilities in the two counties, which showed the ISS system had the potential to identify the change of disease patterns at the community level. Conclusions: The ISS platform may facilitate the early detection of infectious disease epidemic as it provides near real-time syndromic data collection, interactive visualization, and automated aberration detection. However, several constraints and challenges were encountered during the pilot implementation of ISS in rural China. [ABSTRACT FROM AUTHOR]

Background: Recent focus on earlier detection of pathogen introduction in human and animal populations has led to the development of surveillance systems based on automated monitoring of health data. Real- or near real-time monitoring of pre-diagnostic data requires automated classification of records into syndromes–syndromic surveillance–using algorithms that incorporate medical knowledge in a reliable and efficient way, while remaining comprehensible to end users. Methods: This paper describes the application of two of machine learning (Naïve Bayes and Decision Trees) and rule-based methods to extract syndromic information from laboratory test requests submitted to a veterinary diagnostic laboratory. Results: High performance (F1-macro = 0.9995) was achieved through the use of a rule-based syndrome classifier, based on rule induction followed by manual modification during the construction phase, which also resulted in clear interpretability of the resulting classification process. An unmodified rule induction algorithm achieved an F1-micro score of 0.979 though this fell to 0.677 when performance for individual classes was averaged in an unweighted manner (F1-macro), due to the fact that the algorithm failed to learn 3 of the 16 classes from the training set. Decision Trees showed equal interpretability to the rule-based approaches, but achieved an F1-micro score of 0.923 (falling to 0.311 when classes are given equal weight). A Naïve Bayes classifier learned all classes and achieved high performance (F1-micro = 0.994 and F1-macro = .955), however the classification process is not transparent to the domain experts. Conclusion: The use of a manually customised rule set allowed for the development of a system for classification of laboratory tests into syndromic groups with very high performance, and high interpretability by the domain experts. Further research is required to develop internal validation rules in order to establish automated methods to update model rules without user input. [ABSTRACT FROM AUTHOR]

The dynamics of infectious diseases that are spread through direct contact have been proven to depend on the strength of community structure or modularity within the underlying network. It has been recently shown that weighted networks with similar modularity values may exhibit different mixing styles regarding the number of connections among communities and their respective weights. However, the effect of mixing style on epidemic behavior was still unclear. In this paper, we simulate the spread of disease within networks with different mixing styles: a dense-weak style (i.e., many edges among the communities with small weights) and a sparse-strong style (i.e., a few edges among the communities with large weights). Simulation results show that, with the same modularity: 1) the mixing style significantly influences the epidemic size, speed, pattern and immunization strategy; 2) the increase of the number of communities amplifies the effect of the mixing style; 3) when the mixing style changes from sparse-strong to dense-weak, there is a ‘saturation point’, after which the epidemic size and pattern become stable. We also provide a mean-field solution of the epidemic threshold and size on weighted community networks with arbitrary external and internal degree distribution. The solution explains the effect of the second moment of the degree distribution, and a symmetric effect of internal and external connections (incl. degree distribution and weight). Our study has both potential significance for designing more accurate metrics for the community structure and exploring diffusion dynamics on metapopulation networks. [ABSTRACT FROM AUTHOR]

Background: Graphical representation of data is one of the most easily comprehended forms of explanation. The current study describes a simple visualization tool which may allow greater understanding of medical and epidemiological data. Method: We propose a simple tool for visualization of data, known as a “quilt plot”, that provides an alternative to presenting large volumes of data as frequency tables. Data from the Australian Needle and Syringe Program survey are used to illustrate “quilt plots”. Conclusion: Visualization of large volumes of data using “quilt plots” enhances interpretation of medical and epidemiological data. Such intuitive presentations are particularly useful for the rapid assessment of problems in the data which cannot be readily identified by manual review. We recommend that, where possible, “quilt plots” be used along with traditional quantitative assessments of the data as an explanatory data analysis tool. [ABSTRACT FROM AUTHOR]

Disease control is of paramount importance in public health, with infectious disease extinction as the ultimate goal. Although diseases may go extinct due to random loss of effective contacts where the infection is transmitted to new susceptible individuals, the time to extinction in the absence of control may be prohibitively long. Intervention controls are typically defined on a deterministic schedule. In reality, however, such policies are administered as a random process, while still possessing a mean period. Here, we consider the effect of randomly distributed intervention as disease control on large finite populations. We show explicitly how intervention control, based on mean period and treatment fraction, modulates the average extinction times as a function of population size and rate of infection spread. In particular, our results show an exponential improvement in extinction times even though the controls are implemented using a random Poisson distribution. Finally, we discover those parameter regimes where random treatment yields an exponential improvement in extinction times over the application of strictly periodic intervention. The implication of our results is discussed in light of the availability of limited resources for control. [ABSTRACT FROM AUTHOR]

Background: This population-based cohort study has the objective to understand the sociodemographic characteristics and health conditions of patients who do not receive surgery within 18 months following an ambulatory visit to an orthopaedic surgeon. Methods: Administrative healthcare databases in Ontario, Canada were linked to identify all patients making an initial ambulatory visit to orthopaedic surgeons between October 1st, 2004 and September 30th, 2005. Logistic regression was used to examine predictors of not receiving surgery within 18 months. Results: Of the 477,945 patients in the cohort 49% visited orthopaedic surgeons for injury, and 24% for arthritis. Overall, 79.3% did not receive surgery within 18 months of the initial visit, which varied somewhat by diagnosis at first visit (84.5% for injury and 73.0% for arthritis) with highest proportions in the 0–24 and 25–44 age groups. The distribution by income quintile of patients visiting was skewed towards higher incomes. Regression analysis for each diagnostic group showed that younger patients were significantly more likely to be non-surgical than those aged 65+ years (age 0–24: OR 3.45 95%CI 3.33–3.57; age 25–44: OR 1.30 95%CI 1.27–1.33). The odds of not getting surgery were significantly higher for women than men for injury and other conditions; the opposite was true for arthritis and bone conditions. Conclusion: A substantial proportion of referrals were for expert diagnosis or advice on management and treatment. The findings also suggest socioeconomic inequalities in access to orthopaedic care. Further research is needed to investigate whether the high caseload of non-surgical cases affects waiting times to see a surgeon. This paper contributes to the development of evidence-based strategies to streamline access to surgery, and to develop models of care for non-surgical patients to optimize the use of scarce orthopaedic surgeon resources and to enhance the management of musculoskeletal disorders across the care continuum. [ABSTRACT FROM AUTHOR]

Background: Following the epidemiologic and demographic transition, non-communicable disease mortality is the leading cause of death in Iran. Projecting mortality trend can provide valuable tools for policy makers and planners. In this article, we have estimated the trend of non-communicable disease mortality during 2001–2015 and have projected it until 2030 at national and subnational levels in Iran. Methods: The data employed was gathered from the Iranian death registration system and using the Spatio-temporal model, the trends of 4 major categories of non-communicable diseases (cancers, cardiovascular diseases, asthma and COPD, and diabetes) by 2030 were projected at the national and subnational levels. Results: The results indicated that age standardized mortality rate for cancers, CVDs, and Asthma and COPD will continue to decrease in both sexes (cancers: from 81.8 in 2015 to 45.2 in 2030, CVDs: 307.3 to 173.0, and Asthma and COPD: from 52.1 to 46.6); however, in terms of diabetes, there is a steady trend in both sexes at national level (from 16.6 to 16.5). Age standardized mortality rates for cancers and CVDs, in males and females, were high in all provinces in 2001. The variation between the provinces is clearer in 2015, and it is expected to significantly decrease in all provinces by 2030. Conclusion: Generally, the age standardized mortality rate from NCDs will decrease by 2030. Of course, given the experience of the past two decades in Iran, believing that the mortality rate will decrease may not be an easy notion to understand. However hard to believe, this decrease may be the result of better management of risk factors and early detection of patients due to more comprehensive care in all segments of society, as well as improved literacy and awareness across the country. [ABSTRACT FROM AUTHOR]

Hemorrhagic fever with renal syndrome (HFRS) is a naturally-occurring, fecally transmitted disease caused by a Hantavirus (HV). It is extremely damaging to human health and results in many deaths annually, especially in Hubei Province, China. One of the primary characteristics of HFRS is the spatiotemporal heterogeneity of its occurrence, with notable seasonal differences. In view of this heterogeneity, the present study suggests that there is a need to focus on trend simulation and the spatiotemporal prediction of HFRS outbreaks. To facilitate this, we constructed a new Seasonal Difference Space-Time Autoregressive Integrated Moving Average (SD-STARIMA) model. The SD-STARIMA model is based on the spatial and temporal characteristics of the Space-Time Autoregressive Integrated Moving Average (STARMA) model first developed by Cliff and Ord in 1974, which has proven useful in modelling the temporal aspects of spatially located data. This model can simulate the trends in HFRS epidemics, taking into consideration both spatial and temporal variations. The SD-STARIMA model is also able to make seasonal difference calculations to eliminate temporally non-stationary problems that are present in the HFRS data. Experiments have demonstrated that the proposed SD-STARIMA model offers notably better prediction accuracy, especially for spatiotemporal series data with seasonal distribution characteristics. [ABSTRACT FROM AUTHOR]

Peter Godfrey-Faussett and colleagues present six epidemiological metrics for tracking progress in reducing the public health threat of HIV. [ABSTRACT FROM AUTHOR]

Introduction: There is a notable absence of consensus on how to generate estimates of population-level incidence. Incidence is a considerably more sensitive indicator of epidemiological trends than prevalence, but is harder to estimate. We used a novel hybrid method to estimate HIV incidence by age and sex in a rural district of KwaZulu-Natal, South Africa. Methods: Our novel method uses an ‘optimal weighting’ of estimates based on an implementation of a particular ‘synthetic cohort’ approach (interpreting the age/time structure of prevalence, in conjunction with estimates of excess mortality) and biomarkers of ‘recent infection’ (combining Lag-Avidity, Bio-Rad Avidity and viral load results to define recent infection, and adapting the method for age-specific incidence estimation). Data were obtained from a population-based cross-sectional HIV survey conducted in Mbongolwane and Eshowe health service areas in 2013. Results: Using the combined method, we find that age-specific HIV incidence in females rose rapidly during adolescence, from 1.33 cases/100 person-years (95% CI: 0.98,1.67) at age 15 to a peak of 5.01/100PY (4.14,5.87) at age 23. In males, incidence was lower, 0.34/100PY (0.00-0.74) at age 15, and rose later, peaking at 3.86/100PY (2.52-5.20) at age 30. Susceptible population-weighted average incidence in females aged 15-29 was estimated at 3.84/100PY (3.36-4.40), in males aged 15-29 at 1.28/100PY (0.68-1.50) and in all individuals aged 15-29 at 2.55/100PY (2.09-2.76). Using the conventional recency biomarker approach, we estimated HIV incidence among females aged 15-29 at 2.99/100PY (1.79-4.36), among males aged 15-29 at 0.87/100PY (0.22-1.60) and among all individuals aged 15-59 at 1.66/100PY (1.13-2.27). Discussion: HIV incidence was very high in women aged 15-30, peaking in the early 20s. Men had lower incidence, which peaked at age 30. The estimates obtained from the hybrid method are more informative than those produced by conventional analysis of biomarker data, and represents a more optimal use of available data than either the age-continuous biomarker or synthetic cohort methods alone. The method is mainly useful at younger ages, where excess mortality is low and uncertainty in the synthetic cohort estimates is reasonably small. Conclusion: Application of this method to large-scale population-based HIV prevalence surveys is likely to result in improved incidence surveillance over methods currently in wide use. Reasonably accurate and precise age-specific estimates of incidence are important to target better prevention, diagnosis and care strategies. [ABSTRACT FROM AUTHOR]

Determining the distribution of disease prevalence among heterogeneous populations at the national scale is fundamental for epidemiology and public health. Here, we use a combination of methods (spatial scan statistic, topological data analysis and epidemic profile) to study measurable differences in malaria intensity by regions and populations of Colombia. This study explores three main questions: What are the regions of Colombia where malaria is epidemic? What are the regions and populations in Colombia where malaria is endemic? What associations exist between epidemic outbreaks between regions in Colombia? Plasmodium falciparum is most prevalent in the Pacific Coast, some regions of the Amazon Basin, and some regions of the Magdalena Basin. Plasmodium vivax is the most prevalent parasite in Colombia, particularly in the Northern Amazon Basin, the Caribbean, and municipalities of Sucre, Antioquia and Cordoba. We find an acute peak of malarial infection at 25 years of age. Indigenous and Afrocolombian populations experience endemic malaria (with household transmission). We find that Plasmodium vivax decreased in the most important hotspots, often with moderate urbanization rate, and was re-introduced to locations with moderate but sustained deforestation. Infection by Plasmodium falciparum, on the other hand, steadily increased in incidence in locations where it was introduced in the 2009-2010 generalized epidemic. Our findings suggest that Colombia is entering an unstable transmission state, where rapid decreases in one location of the country are interconnected with rapid increases in other parts of the country. [ABSTRACT FROM AUTHOR]

Risk maps of dengue disease offer to the public health officers a tool to model disease risk in space and time. We analyzed the geographical distribution of relative incidence risk of dengue disease in a high incidence city from Colombia, and its evolution in time during the period January 2009—December 2015, identifying regional effects at different levels of spatial aggregations. Cases of dengue disease were geocoded and spatially allocated to census sectors, and temporally aggregated by epidemiological periods. The census sectors are nested in administrative divisions defined as communes, configuring two levels of spatial aggregation for the dengue cases. Spatio-temporal models including census sector and commune-level spatially structured random effects were fitted to estimate dengue incidence relative risks using the integrated nested Laplace approximation (INLA) technique. The final selected model included two-level spatial random effects, a global structured temporal random effect, and a census sector-level interaction term. Risk maps by epidemiological period and risk profiles by census sector were generated from the modeling process, showing the transmission dynamics of the disease. All the census sectors in the city displayed high risk at some epidemiological period in the outbreak periods. Relative risk estimation of dengue disease using INLA offered a quick and powerful method for parameter estimation and inference. [ABSTRACT FROM AUTHOR]

Background: The incidence and prevalence of diabetes is increasing worldwide and it is the fifth leading cause of mortality accounting for over 3.8 million deaths annually. Despite the enormity of the diabetes-related health burdens, very few studies have evaluated the factors associated with mortality among people with diabetes in India. We sought to study the causes and predictors of mortality among urban Asian Indians with and without diabetes. Methods and findings: Of 2273 adults (27,850 person-years of follow-up) from the 10-year follow-up of the Chennai Urban Rural Epidemiology Study (CURES), the cause of death could be ascertained in 552 individuals out of the 671 who had died (response rate 82.3%). Verbal autopsy was obtained from the family members of the deceased and this was adjudicated by trained physicians. The age-standardized mortality rate was 28.2 (95%CI 25.9–30.6) per 100,000 population. Mortality rates were significantly higher in individuals with diabetes compared to those without [27.9(95% CI 25.5–30.6) vs. 8.0 (6.6–9.9) per 1000 person years]. Compared to individuals of normal body mass index, underweight individuals had higher risk of mortality (Hazard ratio 1.49; 95% CI 1.11–2.0), whereas overweight and obese individuals did not show a higher risk. The population-attributable risk for all-cause mortality in the entire study cohort was highest for ischemic heart disease and diabetes. The excess mortality attributable to diabetes was highest in the age group of 51 to 70 years, and was mostly accounted for by renal disease (Rate ratio 5.68, 95%CI 2.43–6.23), ischemic heart disease (4.23,2.78–6.67), and cerebrovascular disease (4.00,1.87–9.81). Conclusion: Underweight (but not overweight or obesity) was strongly associated with mortality in this Asian Indian population. Ischemic heart disease and diabetes contributed the most to risk for all cause mortality. Excess mortality due to diabetes was higher in relatively younger individuals and was mostly accounted for by renal disease. [ABSTRACT FROM AUTHOR]

Background: Despite remarkable progress in the reduction of under-five mortality, childhood diarrhea is still the leading cause of mortality and morbidity in this highly susceptible and vulnerable population. In Ethiopia, study findings regarding prevalence and determinants of diarrhea amongst under-five children have been inconsistent. Therefore, this systematic review and meta-analysis estimates the pooled prevalence of diarrhea and its determinants among under-five children in Ethiopia. Methods: International databases, including PubMed, Web of Science, EMBASE, CINAHL, Google Scholar, Science Direct, and the Cochrane Library, were systematically searched. All identified observational studies reporting the prevalence and determinants of diarrhea among under-five children in Ethiopia were included. Two authors independently extracted all necessary data using a standardized data extraction format. STATA Version 13 statistical software was used. The Cochrane Q test statistics and I2 test were used to assess the heterogeneity of the studies. A random effects model was computed to estimate the pooled prevalence of diarrhea. Moreover, the associations between determinant factors and childhood diarrhea were examined using the random effect model. Results: After reviewing of 535 studies, 31studies fulfilled the inclusion criteria and were included in the meta-analysis. The findings from the 31 studies revealed that the pooled prevalence of diarrhea among under-five children in Ethiopia was 22% (95%CI: 19, 25%). Subgroup analysis of this study revealed that the highest prevalence was observed in Afar region (27%), followed by Somali and Dire Dawa regions (26%), then Addis Abeba (24%). Lack of maternal education (OR: 2.5, 95% CI: 1.3, 2.1), lack of availability of latrine (OR: 2.0, 95%CI: 1.3, 3.2), urban residence (OR: 1.9, 95%CI: 1.2, 3.0), and maternal hand washing (OR: 2.2, 95%CI: 2.0, 2.6) were significantly associated with childhood diarrhea. Conclusion: In this study, diarrhea among under-five children in Ethiopia was significantly high. Lack of maternal education, lack of availability of latrine, urban residence, and lack of maternal hand washing were significantly associated with childhood diarrhea. [ABSTRACT FROM AUTHOR]

Disease tolerance is a defense strategy against infections that aims at maintaining host health even at high pathogen replication or load. Tolerance mechanisms are currently intensively studied with the long-term goal of exploiting them therapeutically. Because tolerance-based treatment imposes less selective pressure on the pathogen it has been hypothesised to be “evolution-proof”. However, the primary public health goal is to reduce the incidence and mortality associated with a disease. From this perspective, tolerance-based treatment bears the risk of increasing the prevalence of the disease, which may lead to increased mortality. We assessed the promise of tolerance-based treatment strategies using mathematical models. Conventional treatment was implemented as an increased recovery rate, while tolerance-based treatment was assumed to reduce the disease-related mortality of infected hosts without affecting recovery. We investigated the endemic phase of two types of infections: acute and chronic. Additionally, we considered the effect of pathogen resistance against conventional treatment. We show that, for low coverage of tolerance-based treatment, chronic infections can cause even more deaths than without treatment. Overall, we found that conventional treatment always outperforms tolerance-based treatment, even when we allow the emergence of pathogen resistance. Our results cast doubt on the potential benefit of tolerance-based over conventional treatment. Any clinical application of tolerance-based treatment of infectious diseases has to consider the associated detrimental epidemiological feedback. [ABSTRACT FROM AUTHOR]

Background: Migrant and ethnic minority groups are often assumed to have poor health relative to the majority population. Few countries have the capacity to study a key indicator, mortality, by ethnicity and country of birth. We hypothesized at least 10% differences in mortality by ethnic group in Scotland that would not be wholly attenuated by adjustment for socio-economic factors or country of birth.Methods and Findings: We linked the Scottish 2001 Census to mortality data (2001-2013) in 4.62 million people (91% of estimated population), calculating age-adjusted mortality rate ratios (RRs; multiplied by 100 as percentages) with 95% confidence intervals (CIs) for 13 ethnic groups, with the White Scottish group as reference (ethnic group classification follows the Scottish 2001 Census). The Scottish Index of Multiple Deprivation, education status, and household tenure were socio-economic status (SES) confounding variables and born in the UK or Republic of Ireland (UK/RoI) an interacting and confounding variable. Smoking and diabetes data were from a primary care sub-sample (about 53,000 people). Males and females in most minority groups had lower age-adjusted mortality RRs than the White Scottish group. The 95% CIs provided good evidence that the RR was more than 10% lower in the following ethnic groups: Other White British (72.3 [95% CI 64.2, 81.3] in males and 75.2 [68.0, 83.2] in females); Other White (80.8 [72.8, 89.8] in males and 76.2 [68.6, 84.7] in females); Indian (62.6 [51.6, 76.0] in males and 60.7 [50.4, 73.1] in females); Pakistani (66.1 [57.4, 76.2] in males and 73.8 [63.7, 85.5] in females); Bangladeshi males (50.7 [32.5, 79.1]); Caribbean females (57.5 [38.5, 85.9]); and Chinese (52.2 [43.7, 62.5] in males and 65.8 [55.3, 78.2] in females). The differences were diminished but not eliminated after adjusting for UK/RoI birth and SES variables. A mortality advantage was evident in all 12 minority groups for those born abroad, but in only 6/12 male groups and 5/12 female groups of those born in the UK/RoI. In the primary care sub-sample, after adjustment for age, UK/RoI born, SES, smoking, and diabetes, the RR was not lower in Indian males (114.7 [95% CI 78.3, 167.9]) and Pakistani females (103.9 [73.9, 145.9]) than in White Scottish males and females, respectively. The main limitations were the inability to include deaths abroad and the small number of deaths in some ethnic minority groups, especially for people born in the UK/RoI.Conclusions: There was relatively low mortality for many ethnic minority groups compared to the White Scottish majority. The mortality advantage was less clear in UK/RoI-born minority group offspring than in immigrants. These differences need explaining, and health-related behaviours seem important. Similar analyses are required internationally to fulfil agreed goals for monitoring, understanding, and improving health in ethnically diverse societies and to apply to health policy, especially on health inequalities and inequities. [ABSTRACT FROM AUTHOR]

Background: Survival represents the single most important indicator of successful HIV treatment. Routine monitoring fails to capture most deaths. As a result, both regional assessments of the impact of HIV services and identification of hotspots for improvement efforts are limited. We sought to assess true mortality on treatment, characterize the extent under-reporting of mortality in routine health information systems in Zambia, and identify drivers of mortality across sites and over time using a multistage, regionally representative sampling approach.Methods and Findings: We enumerated all HIV infected adults on antiretroviral therapy (ART) who visited any one of 64 facilities across 4 provinces in Zambia during the 24-month period from 1 August 2013 to 31 July 2015. We identified a probability sample of patients who were lost to follow-up through selecting facilities probability proportional to size and then a simple random sample of lost patients. Outcomes among patients lost to follow-up were incorporated into survival analysis and multivariate regression through probability weights. Of 165,464 individuals (64% female, median age 39 years (IQR 33-46), median CD4 201 cells/mm3 (IQR 111-312), the 2-year cumulative incidence of mortality increased from 1.9% (95% CI 1.7%-2.0%) to a corrected rate of 7.0% (95% CI 5.7%-8.4%) (all ART users) and from 2.1% (95% CI 1.8%-2.4%) to 8.3% (95% CI 6.1%-10.7%) (new ART users). Revised provincial mortality rates ranged from 3-9 times higher than naïve rates for new ART users and were lowest in Lusaka Province (4.6 per 100 person-years) and highest in Western Province (8.7 per 100 person-years) after correction. Corrected mortality rates varied markedly by clinic, with an IQR of 3.5 to 7.5 deaths per 100 person-years and a high of 13.4 deaths per 100 person-years among new ART users, even after adjustment for clinical (e.g., pretherapy CD4) and contextual (e.g., province and clinic size) factors. Mortality rates (all ART users) were highest year 1 after treatment at 4.6/100 person-years (95% CI 3.9-5.5), 2.9/100 person-years (95% CI 2.1-3.9) in year 2, and approximately 1.6% per year through 8 years on treatment. In multivariate analysis, patient-level factors including male sex and pretherapy CD4 levels and WHO stage were associated with higher mortality among new ART users, while male sex and HIV disclosure were associated with mortality among all ART users. In both cases, being late (>14 days late for appointment) or lost (>90 days late for an appointment) was associated with deaths. We were unable to ascertain the vital status of about one-quarter of those lost and selected for tracing and did not adjudicate causes of death.Conclusions: HIV treatment in Zambia is not optimally effective. The high and sustained mortality rates and marked under-reporting of mortality at the provincial-level and unexplained heterogeneity between regions and sites suggest opportunities for the use of corrected mortality rates for quality improvement. A regionally representative sampling-based approach can bring gaps and opportunities for programs into clear epidemiological focus for local and global decision makers. [ABSTRACT FROM AUTHOR]

Public health related decisions often have to balance the cost of intervention strategies with the benefit of the reduction in disease burden. While the cost can often be inferred, forward modelling of the effect of different intervention options is complicated and disease specific. Here we introduce a package that is aimed to simplify this process. The package allows one to infer parameters using a Bayesian approach, perform forward modelling of the likely results of the proposed intervention and finally perform cost effectiveness analysis of the results. The package is based on a method previously used in the UK to inform vaccination strategies for influenza, with extensions to make it easily adaptable to other diseases and data sources. [ABSTRACT FROM AUTHOR]

Japan has been free from rabies since the 1950s. However, during the early 1900s several large-scale epidemics spread throughout the country. Here we investigate the dynamics of these epidemics between 1914 and 1933 in Osaka Prefecture, using archival data including newspapers. The association between dog rabies cases and human population density was investigated using Mixed-effects models and epidemiological parameters such as the basic reproduction number (R0), the incubation and infectious period and the serial interval were estimated. A total of 4,632 animal rabies cases were reported, mainly in dogs (99.0%, 4,584 cases) during two epidemics from 1914 to 1921, and 1922 to 1933 respectively. The second epidemic was larger (3,705 cases) than the first (879 cases), but had a lower R0 (1.50 versus 2.42). The first epidemic was controlled through capture of stray dogs and tethering of pet dogs. Dog mass vaccination began in 1923, with campaigns to capture stray dogs. Rabies in Osaka Prefecture was finally eliminated in 1933. A total of 3,805 rabid dog-bite injuries, and 75 human deaths were reported. The relatively low incidence of human rabies, high ratio of post-exposure vaccines (PEP) and bite injuries by rabid dogs (minimum 6.2 to maximum 73.6, between 1924 and 1928), and a decline in the proportion of bite victims that developed hydrophobia over time (slope = -0.29, se = 3, p < 0.001), indicated that increased awareness and use of PEP might have prevented disease. Although significantly more dog rabies cases were detected at higher human population densities (slope = 0.66, se = 0.03, p < 0.01), there were fewer dog rabies cases detected per capita (slope = -0.34, se = 0.03, p < 0.01). We suggest that the combination of mass vaccination and restriction of dog movement enabled by strong legislation was key to eliminate rabies. Moreover, the prominent role of the media in both reporting rabies cases and efforts to control the disease likely contributed to promoting the successful participation required to achieve rabies elimination. [ABSTRACT FROM AUTHOR]

Background: There was a dengue epidemic in several regions of China in 2013. No study has explored the dynamics of dengue transmission between different geographical locations with dengue outbreaks in China. The purpose of the study is to analyze the epidemiological characteristics and to explore the dynamic transmission of dengue in China, 2013. Methodology and Principal Findings: Records of dengue cases of 2013 were obtained from the China Notifiable Disease Surveillance System. Full E-gene sequences of dengue virus detected from the outbreak regions of China were download from GenBank. Geographical Information System and heatmaps were used to describe the epidemiological characteristics. Maximum Likelihood phylogenetic and Bayesian phylogeographic analyses were conducted to explore the dengue dynamic transmission. Yunnan Province and Guangdong Province had the highest imported cases in the 2013 epidemic. In the locations with local dengue transmission, most of imported cases occurred from June to November 2013 while local dengue cases developed from July to December, 2013. There were significant variations for the incidences of dengue, in terms of age distributions, among different geographic locations. However, gender differences were identified in Guangzhou, Foshan and Xishuangbanna. DENV 1–3 were detected in all locations with the disease outbreaks. Some genotypes were detected in more than one locations and more than one genotypes have been detected in several locations. The dengue viruses introduced to outbreak areas were predominantly from Southeast Asia. In Guangdong Province, the phylogeographical results indicated that dengue viruses of DENV 1 were transmitted to neighboring cities Foshan and Zhongshan from Guangzhou city, and then transmitted to Jiangmen city. The virus in DENV 3 was introduced to Guangzhou city, Guangdong Province from Xishuangbanna prefecture, Yunnan Province. Conclusions: Repeated dengue virus introductions from Southeast Asia and subsequent domestic dengue transmission within different regions may have contributed to the dengue epidemics in China, 2013. [ABSTRACT FROM AUTHOR]

Background: Sporadic Japanese encephalitis (JE) cases still have been reported in Zhejiang Province in recent years, and concerns about vaccine cross-protection and population-level immunity have been raised off and on within the public health sphere. Genotype I (GI) has replaced GIII as the dominant genotype in Asian countries during the past few decades, which caused considerable concerns about the potential change of epidemiology characteristics and the vaccine effectiveness. The aim of this study was to investigate the prevalence of JE neutralizing antibody and its waning antibody trend after live attenuated JE vaccine immunization. Additionally, this study analyzed the molecular characteristics of the E gene of Zhejiang Japanese encephalitis virus (JEV) strains, and established genetic relationships with other JEV strains. Methodology/Principal Findings: A total of 570 serum specimens were sampled from community population aged from 0 to 92 years old in Xianju county of Zhejiang Province in 2013–2014. Microseroneutralization test results were analyzed to estimate the population immunity and to observe antibody dynamics in vaccinated children. E genes of 28 JEV strains isolated in Zhejiang Province were sequenced for phylogenetic tree construction and molecular characteristics analysis with other selected strains. Positive JE neutralizing antibody rates were higher in residents ≥35 years old (81%~98%) and lower in residents <35 years old (0~57%). 7 or 8 years after the 2nd live attenuated vaccine dose, the antibodies against for 4 different strains with microseroneutralization test were decreased by 55%~73% on seropositive rates and by 25%~38% on GMTs respectively. JEV strains isolated in recent years were all grouped into GI, while those isolated in the 1980s belonged to GIII. On important amino acid sites related to antigenicity, there was no divergence between the Zhejiang JE virus strains and the vaccine strain (SA14-14-2). Conclusion/Significances: JE neutralizing antibody positive rates increase in age ≥10 years old population, likely reflecting natural infection or natural boosting of immunity through exposure to wild virus. JE seropositivity rates were quite low in <35 years old age groups in Zhejiang Province. Waning of neutralizing antibody after live attenuated vaccine immunization was observed, but the clinical significance should be further investigated. Both the peripheral antibody response and genetic characterization indicate that current live attenuated JE vaccine conferred equal neutralizing potency against GI or GIII of wild strains. GI has replaced GIII as the dominant genotype in Zhejiang in the past few decades. Although the chance of exposure to wild JE virus has reduced, the virus still circulates in nature; therefore, it is necessary to implement immunization program for children continually and to conduct surveillance activity periodically. [ABSTRACT FROM AUTHOR]

Aedes albopictus is a tropical invasive species which in the last decades spread worldwide, also colonizing temperate regions of Europe and US, where it has become a public health concern due to its ability to transmit exotic arboviruses, as well as severe nuisance problems due to its aggressive daytime outdoor biting behaviour. While several studies have been carried out in order to predict the potential limits of the species expansions based on eco-climatic parameters, few studies have so far focused on the specific effects of these variables in shaping its micro-geographic abundance and dynamics. The present study investigated eco-climatic factors affecting Ae. albopictus abundance and dynamics in metropolitan and sub-urban/rural sites in Rome (Italy), which was colonized in 1997 and is nowadays one of the most infested metropolitan areas in Southern Europe. To this aim, longitudinal adult monitoring was carried out along a 70 km-transect across and beyond the most urbanized and densely populated metropolitan area. Two fine scale spatiotemporal datasets (one with reference to a 20m circular buffer around sticky traps used to collect mosquitoes and the second to a 300m circular buffer within each sampling site) were exploited to analyze the effect of climatic and socio-environmental variables on Ae. albopictus abundance and dynamics along the transect. Results showed an association between highly anthropized habitats and high adult abundance both in metropolitan and sub-urban/rural areas, with “small green islands” corresponding to hot spots of abundance in the metropolitan areas only, and a bimodal seasonal dynamics with a second peak of abundance in autumn, due to heavy rains occurring in the preceding weeks in association with permissive temperatures. The results provide useful indications to prioritize public mosquito control measures in temperate urban areas where nuisance, human-mosquito contact and risk of local arbovirus transmission are likely higher, and highlight potential public health risks also after the summer months typically associated with high mosquito densities. [ABSTRACT FROM AUTHOR]

Both pulmonary tuberculosis (PTB) and intestinal helminth infection (IHI) affect millions of individuals every year in China. However, the national-scale estimation of prevalence predictors and prevalence maps for these diseases, as well as co-endemic relative risk (RR) maps of both diseases’ prevalence are not well developed. There are co-endemic, high prevalence areas of both diseases, whose delimitation is essential for devising effective control strategies. Bayesian geostatistical logistic regression models including socio-economic, climatic, geographical and environmental predictors were fitted separately for active PTB and IHI based on data from the national surveys for PTB and major human parasitic diseases that were completed in 2010 and 2004, respectively. Prevalence maps and co-endemic RR maps were constructed for both diseases by means of Bayesian Kriging model and Bayesian shared component model capable of appraising the fraction of variance of spatial RRs shared by both diseases, and those specific for each one, under an assumption that there are unobserved covariates common to both diseases. Our results indicate that gross domestic product (GDP) per capita had a negative association, while rural regions, the arid and polar zones and elevation had positive association with active PTB prevalence; for the IHI prevalence, GDP per capita and distance to water bodies had a negative association, the equatorial and warm zones and the normalized difference vegetation index had a positive association. Moderate to high prevalence of active PTB and low prevalence of IHI were predicted in western regions, low to moderate prevalence of active PTB and low prevalence of IHI were predicted in north-central regions and the southeast coastal regions, and moderate to high prevalence of active PTB and high prevalence of IHI were predicted in the south-western regions. Thus, co-endemic areas of active PTB and IHI were located in the south-western regions of China, which might be determined by socio-economic factors, such as GDP per capita. [ABSTRACT FROM AUTHOR]

Hepatitis A virus (HAV) is transmitted via the fecal-oral route from contaminated food or water. As part of the most recent survey of viral hepatitis burden in Thailand, we analyzed the current seroprevalence of HAV in the country and compared with data dating back to 1971. From March to October, 2014, a total of 4,260 individuals between one month and 71 years of age from different geographical regions (North = 961; Central = 1,125; Northeast = 1,109; South = 1,065) were screened for anti-HAV IgG antibody using an automated chemiluminescent microparticle immunoassay. Overall, 34.53% (1,471/4,260) possessed anti-HAV IgG antibody, and the age-standardized seroprevalence was 48.6%. Seroprevalence rates were 27.3% (North), 30.8% (Central), 33.8% (Northeast) and 45.8% (South) and were markedly lower than in the past studies especially among younger age groups. The overall trend showed an increase in the age by which 50% of the population were anti-HAV IgG antibody: 4.48 years (1971–1972), 6 (1976), 12.49 (1990), 36.02 (2004) and 42.03 (2014).This suggests that Thailand is transitioning from low to very low HAV endemicity. Lower prevalence of HAV correlated with improved healthcare system as measured by decreased infant mortality rate and improved national economy based on increased GDP per capita. The aging HAV immuno-naïve population may be rendered susceptible to potential HAV outbreaks similar to those in industrialized countries and may benefit from targeted vaccination of high-risk groups. [ABSTRACT FROM AUTHOR]

Background: Low- and middle-income countries are currently facing the massive public health challenge of road traffic injuries. The lack of effective surveillance systems hinders proper assessment of epidemiologic status and intervention priorities. The objective of our study was to estimate the mortality and morbidity attributable to road crashes in Bamako, Mali using the capture-recapture method. Methods: During the 1 January, 2012–31 April, 2012 period, we collected data on road traffic crashes from the road accident registers of the police forces of Bamako, Mali on the one hand, and from a register kept by health facilities in the same area. An automatic, then manual matching procedure was performed to find pairs of records related to the same crash victims. The number of victims and the number of fatalities were estimated by the capture-recapture method using the Chapman estimator. Results: The health facility and the police registries included 3587 and 1432 records, respectively. The matching procedure identified 603 common records, 31 of which were fatalities. The annual incidence estimate for road victims was 1038 in 100 000 and the annual incidence estimate for road fatalities was 12 in 100 000. Victims from both sources were more likely to be male, in the 15–34 age group, and almost half of all injured road users and two in three fatalities were using motorized two-wheelers. One victim out of five was a pedestrian. Conclusion: Our estimates are in line with available literature data from low-income countries. While more cases were reported by health facilities than by police forces, we believe that an effective surveillance system should not be based solely on medical reports as much would be missing as regards the crash circumstances and characteristics. [ABSTRACT FROM AUTHOR]

Background: Dengue is a major international public health concern, one of the most important arthropod-borne diseases. More than 3.5 billion people are at risk of dengue infection and there are an estimated 390 million dengue infections annually. This prolific increase has been connected to societal changes such as population growth and increasing urbanization generating intense agglomeration leading to proliferation of synanthropic mosquito species. Quantifying the spatio-temporal epidemiology of dengue in large cities within the context of a Geographic Information System is a first step in the identification of socio-economic risk factors. Methodology/Principal Findings: This Project has been approved by the ethical committee of Institut Pasteur. Data has been anonymized and de-identified prior to geolocalisation and analysis. A GIS was developed for Delhi, enabling typological characterization of the urban environment. Dengue cases identified in the Delhi surveillance system from 2008 to 2010 were collated, localised and embedded within this GIS. The spatio-temporal distribution of dengue cases and extent of clustering were analyzed. Increasing distance from the forest in Delhi reduced the risk of occurrence of a dengue case. Proximity to a hospital did not increase risk of a notified dengue case. Overall, there was high heterogeneity in incidence rate within areas with the same socio-economical profiles and substantial inter-annual variability. Dengue affected the poorest areas with high density of humans, but rich areas were also found to be infected, potentially because of their central location with respect to the daily mobility network of Delhi. Dengue cases were highly clustered in space and there was a strong relationship between the time of introduction of the virus and subsequent cluster size. At a larger scale, earlier introduction predicted the total number of cases. Conclusions/Significance: DENV epidemiology within Delhi has a forest fire signature. The stochastic nature of this invasion process likely smothers any detectable socio-economic risk factors. However, the significant finding that the size of the dengue case cluster depends on the timing of its emergence emphasizes the need for early case detection and implementation of effective mosquito control. A better understanding of the role of population mobility in contributing to dengue risk could also help focus control on areas at particular risk of dengue virus importation. [ABSTRACT FROM AUTHOR]

Background: Many public health and epidemiological studies have found differences between populations (e.g. maternal countries of birth) in average values of a health indicator (e.g. mean offspring birthweight). However, the approach based solely on population-level averages compromises our understanding of variability in individuals’ health around the averages. If this variability is high, the exclusive study of averages may give misleading information. This idea is relevant when investigating country of birth differences in health. Methods and Results: To exemplify this concept, we use information from the Swedish Medical Birth Register (2002–2010) and apply multilevel regression analysis of birthweight, with babies (n = 811,329) at the first, mothers (n = 571,876) at the second, and maternal countries of birth (n = 109) at the third level. We disentangle offspring, maternal and maternal country of birth components of the total offspring heterogeneity in birthweight for babies born within the normal timespan (37–42 weeks). We found that of such birthweight variation about 50% was at the baby level, 47% at the maternal level and only 3% at the maternal countries of birth level. Conclusion: In spite of seemingly large differences in average birthweight among maternal countries of birth (range 3290–3677g), knowledge of the maternal country of birth does not provide accurate information for ascertaining individual offspring birthweight because of the high inter-offspring heterogeneity around country averages. Our study exemplifies the need for a better understanding of individual health diversity for which group averages may provide insufficient and even misleading information. The analytical approach we outline is therefore relevant to investigations of country of birth (and ethnic) differences in health in general. [ABSTRACT FROM AUTHOR]

Aims: Type 1 diabetes has been associated with an elevated relative risk (RR) of mortality compared to the general population. To review published studies on the RR of mortality of Type 1 diabetes patients compared to the general population, we conducted a meta-analysis and examined the temporal changes in the RR of mortality over time. Methods: Systematic review of studies reporting RR of mortality for Type 1 diabetes compared to the general population. We conducted meta-analyses using a DerSimonian and Laird random effects model to obtain the average effect and the distribution of RR estimates. Sub-group meta-analyses and multivariate meta-regression analysis was performed to examine heterogeneity. Summary RR with 95% CIs was calculated using a random-effects model. Results: 26 studies with a total of 88 subpopulations were included in the meta-analysis and overall RR of mortality was 3.82 (95% CI 3.41, 3.4.29) compared to the general population. Observations using data prior to 1971 had a much larger estimated RR (5.80 (95% CI 4.20, 8.01)) when compared to: data between; 1971 and 1980 (5.06 (95% CI 3.44, 7.45)); 1981–90 (3.59 (95% CI 3.15, 4.09)); and those after 1990 (3.11 (95% CI 2.47, 3.91)); suggesting mortality of Type 1 diabetes patients when compared to the general population have been improving over time. Similarly, females (4.54 (95% CI 3.79–5.45)) had a larger RR estimate when compared to males (3.25 (95% CI 2.82–3.73) and the meta-regression found evidence for temporal trends and sex (p<0.01) accounting for heterogeneity between studies. Conclusions: Type 1 diabetes patients’ mortality has declined at a faster rate than the general population. However, the largest relative improvements have occurred prior to 1990. Emphasis on intensive blood glucose control alongside blood pressure control and statin therapy may translate into further reductions in mortality in coming years. [ABSTRACT FROM AUTHOR]

Social networks are believed to affect health-related behaviors and health. Data to examine the links between social relationships and health in low- and middle-income country settings are limited. We provide guidance for introducing an instrument to collect social network data as part of epidemiological surveys, drawing on experience in urban India. We describe development and fielding of an instrument to collect social network information relevant to health behaviors among adults participating in a large, population-based study of non-communicable diseases in Delhi, India. We discuss basic characteristics of social networks relevant to health including network size, health behaviors of network partners (i.e., network exposures), network homogeneity, network diversity, strength of ties, and multiplexity. Data on these characteristics can be collected using a short instrument of 11 items asked about up to 5 network members and 3 items about the network generally, administered in approximately 20 minutes. We found high willingness to respond to questions about social networks (97% response). Respondents identified an average of 3.8 network members, most often relatives (80% of network ties), particularly blood relationships. Ninety-one percent of respondents reported that their primary contacts for discussing health concerns were relatives. Among all listed ties, 91% of most frequent snack partners and 64% of exercise partners in the last two weeks were relatives. These results demonstrate that family relationships are the crux of social networks in some settings, including among adults in urban India. Collecting basic information about social networks can be feasibly and effectively done within ongoing epidemiological studies. [ABSTRACT FROM AUTHOR]

Background: Scrub typhus has been increasingly reported in Southern China, and public health authorities are concerned about its increased incidence. Additionally, little evidence is available on the epidemiology of scrub typhus in Southern China. This study aims to analyze the epidemiological and geographic features of ST in Guangzhou City, Southern China, to guide the future prevention efforts. Methods: Scrub typhus surveillance data in Guangzhou City during 2006–2012 were obtained from the Chinese National Communicable Disease Surveillance Network. We first conducted a descriptive analysis to analyze the epidemiological features of scrub typhus. Then we used space-time scan statistic based on a discrete Poisson model to detect and evaluate high-risk spatial-temporal clusters of scrub typhus. Results: There were 4,001 cases of scrub typhus in Guangzhou City during the study period. The incidence of scrub typhus increased from 3.29 per 100,000 in 2006 to 9.85 per 100,000 in 2012. A summer peak was observed in June and July with a second peak in September and October except year 2009 and 2011. The majority of the cases (71.4%) were among persons aged ≥40 years, and female incidence was higher than male incidence in persons ≥50 years. In the space-time analysis, high-risk clusters were concentrated in rural areas in Guangzhou City. Over the past 7 years, Haizhu District, an urban area, was found to be a high-risk cluster for the first time in 2012. Conclusion: The resurgence of scrub typhus epidemics in Guangzhou population in 2012 necessitates more effective measures for minimizing future epidemics. Consideration of high-risk population and historical spatial-temporal clusters may help prevent scrub typhus. The risk of scrub typhus in urban areas should not be neglected and needs more attention from public health authorities. [ABSTRACT FROM AUTHOR]

To develop public-health policies that extend the lifespan of affordable anti-malarial drugs as effective treatment options, it is necessary to understand the evolutionary processes leading to the origin and spread of mutations conferring drug resistance in malarial parasites. We built a population-genetic model for the emergence of resistance under combination drug therapy. Reproductive cycles of parasites are specified by their absolute fitness determined by clinical parameters, thus coupling the evolutionary-genetic with population-dynamic processes. Initial mutations confer only partial drug-resistance. Therefore, mutant parasites rarely survive combination therapy and within-host competition is very weak among parasites. The model focuses on the early phase of such unsuccessful recurrent mutations. This ends in the rare event of mutants enriching in an infected individual from which the successful spread of resistance over the entire population is initiated. By computer simulations, the waiting time until the establishment of resistant parasites is analysed. Resistance spreads quickly following the first appearance of a host infected predominantly by mutant parasites. This occurs either through a rare transmission of a resistant parasite to an uninfected host or through a rare failure of drugs in removing “transient” mutant alleles. The emergence of resistance is delayed with lower mutation rate, earlier treatment, higher metabolic cost of resistance, longer duration of high drug dose, and higher drug efficacy causing a stronger reduction in the sensitive and resistant parasites’ fitnesses. Overall, contrary to other studies’ proposition, the current model based on absolute fitness suggests that aggressive drug treatment delays the emergence of drug resistance. [ABSTRACT FROM AUTHOR]

Background: Hemorrhagic fever with renal syndrome (HFRS) is an important infectious disease in Hebei province, China. The average annual incidence is 3.10/100000. Although the incidence of HFRS is stable with a general decline in trend since 2004, an increase in the trend was observed in 2011. Few studies have been conducted to investigate the underlying risk factors for this disease. Methods: The epidemiological data of HFRS and the population data, meteorology, and remote sensing aspects of cities in Hebei province from 1999 to 2011 were collected. The epidemiological data included the population density in the region, seasonal data and rat density and rat's virus carriage rate. The data were analyzed by descriptive study, correlation analysis and multivariate linear analysis. Results: There were 26837 cases of HFRS was reported from 1999 to 2011. The infection occurred mainly in males, aged 20∼49 years, who were farmers. Rattus norvegicus was the main host animal. The incidence of HFRS was related to NDVI value, rat density and rat's virus carriage rate by multiple linear regression (F = 25.936, P<0.01). The pseudo- R2value for the model was 0.644. Conclusion: The incidence of HFRS was related to NDVI value, rat density and rat's virus carriage rate. Control of these factors should be used to prevent HFRS in Hebei province. [ABSTRACT FROM AUTHOR]

Introduction: In the last decades, dietary supplements consumption has increased in the Western world for all age groups. The long-term potentially dangerous effects related to an indiscriminate consumption of dietary supplements are still unknown and are becoming a matter of public health concern. Therefore, the aims of the present study were: to explore the contribution of dietary supplements to micronutrient daily intake, and to evaluate awareness and knowledge about dietary supplements. Methods: Participants (age ranging from 14 to 18 years) were recruited among students attending 8 high schools in the province of Frosinone (Italy). An anonymous questionnaire, composed of 12 multiple-choice items, was administered to all the participants. T-test and the analysis of variance (ANOVA) were performed to describe differences between means of the groups, while the chi-square test was used to compare observed and expected frequencies. The logistic regression model, aimed at identifying the characteristics of potential consumers of dietary supplements, Results: A total of 686 teenagers (288 males and 398 females, average age: 17,89±0,91 years) participated in the study. The 83,6% of participants affirmed to be aware of dietary supplements. 239 participants consumed dietary supplements: 118 males and 121 females. 49,1% of females consumed dietary supplements less than twice a week, whereas 43,6% of males consumed dietary supplements from 2 to 5 times per week. Statistically significant differences emerged between the genders with respect to the source of information regarding dietary supplements, the perceived indications for their use, and the choice of the store/place to purchase them. Discussion: Findings in the present study provide insight into the consumption of dietary supplements among young Italians, highlighting the need to foster further awareness among adolescents about the correct use of dietary supplements, especially in terms of indications and contraindications. [ABSTRACT FROM AUTHOR]