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Staphylococcus argenteus and Staphylococcus schweitzeri, previously known as divergent Staphylococcus aureus clonal lineages, have been recently established as novel, difficult-to-delimit, coagulase-positive species within the S. aureus complex. Methicillin-resistant strains of S. argenteus are known from Australia and the UK. Knowledge of their epidemiology, medical significance and transmission risk is limited and partly contradictory, hampering definitive recommendations. There is mounting evidence that the pathogenicity of S. argenteus is similar to that of 'classical' S. aureus , while as yet no S. schweitzeri infections have been reported. To provide decision support on whether and how to distinguish and report both species. PubMed, searched for S. argenteus and S. schweitzeri. This position paper reviews the main characteristics of both species and draws conclusions for microbiological diagnostics and surveillance as well as infection prevention and control measures. We propose not distinguishing within the S. aureus complex for routine reporting purposes until there is evidence that pathogenicity or clinical outcome differ markedly between the different species. Primarily for research purposes, suitably equipped laboratories are encouraged to differentiate between S. argenteus and S. schweitzeri. Caution is urged if these novel species are explicitly reported. In such cases, a specific comment should be added (i.e. 'member of the S.aureus complex') to prevent confusion with less- or non-pathogenic staphylococci. Prioritizing aspects of patient safety, methicillin-resistant isolates should be handled as recommended for methicillin-resistant Staphylococcus aureus (MRSA). In these cases, the clinician responsible should be directly contacted and informed by the diagnosing microbiological laboratory, as they would be for MRSA. Research is warranted to clarify the epidemiology, clinical impact and implications for infection control of such isolates. [ABSTRACT FROM AUTHOR]

Summary: Objectives: Leptospirosis is a serious neglected disease in the Pacific. Because sensitive and specific laboratory tests are largely unavailable, the burden of disease and epidemiological data are often unreliable and do not allow informed disease prioritization and efficient control. We report the use of serum spotted on filter paper to improve the surveillance of leptospirosis in remote and resource-limited settings. Methods: A total of 172 acute-phase serum samples collected from patients with suspected dengue at Yap State Hospital, Federated States of Micronesia, were spotted on filter paper and sent by regular mail to the Institut Louis Malardé, French Polynesia. Real-time PCR protocols for dengue and leptospirosis confirmation were performed on all specimens. Results: A total of five leptospirosis infections were detected amongst the patients with suspected dengue. Conclusions: This study confirms the use of filter paper as a convenient tool to improve leptospirosis surveillance capacity in remote areas. New surveillance strategies, notably based on the regular use of this type of tool, are essential to more adequately describe the epidemiology and burden of neglected diseases. [ABSTRACT FROM AUTHOR]

[Display omitted] "Biological plausibility" is a concept frequently referred to in environmental and public health when researchers are evaluating how confident they are in the results and inferences of a study or evidence review. Biological plausibility is not, however, a domain of one of the most widely-used approaches for assessing the certainty of evidence (CoE) which underpins the findings of a systematic review, the Grading of Recommendations Assessment, Development and Evaluation (GRADE) CoE Framework. Whether the omission of biological plausibility is a potential limitation of the GRADE CoE Framework is a topic that is regularly discussed, especially in the context of environmental health systematic reviews. We analyse how the concept of "biological plausibility", as applied in the context of assessing certainty of the evidence that supports the findings of a systematic review, is accommodated under the processes of systematic review and the existing GRADE domains. We argue that "biological plausibility" is a concept which primarily comes into play when direct evidence about the effects of an exposure on a population of concern (usually humans) is absent, at high risk of bias, is inconsistent, or limited in other ways. In such circumstances, researchers look toward evidence from other study designs in order to draw conclusions. In this respect, we can consider experimental animal and in vitro evidence as "surrogates" for the target populations, exposures, comparators and outcomes of actual interest. Through discussion of 10 examples of experimental surrogates, we propose that the concept of biological plausibility consists of two principal aspects: a "generalisability aspect" and a "mechanistic aspect". The "generalisability aspect" concerns the validity of inferences from experimental models to human scenarios, and asks the same question as does the assessment of external validity or indirectness in systematic reviews. The "mechanistic aspect" concerns certainty in knowledge of biological mechanisms and would inform judgements of indirectness under GRADE, and thus the overall CoE. While both aspects are accommodated under the indirectness domain of the GRADE CoE Framework, further research is needed to determine how to use knowledge of biological mechanisms in the assessment of indirectness of the evidence in systematic reviews. [ABSTRACT FROM AUTHOR]

• Collected papers on estimations of four epidemiological parameters regarding COVID-19. • Quantitatively compared and synthesized preprints and peer-reviewed publications. • Verified the validity of the COVID-19 parameter estimations of the preprints. • Synthesized parameters can effectively capture the patterns of COVID-19. We aimed to explore the collective wisdom of preprints related to COVID-19 by comparing and synthesizing them with results of peer-reviewed publications. PubMed, Google Scholar, medRxiv, bioRxiv, arXiv, and SSRN were searched for papers regarding the estimation of four epidemiological parameters of COVID-19: the basic reproduction number, incubation period, infectious period, and case-fatality-rate. Distributions of parameters and timeliness of preprints and peer-reviewed papers were compared. Four parameters in two groups were synthesized by bootstrapping, and their validities were evaluated by simulated cumulative cases of the susceptible-exposed-infectious-recovered-dead-cumulative (SEIRDC) model. A total of 106 papers were included for analysis. The distributions of four parameters in two literature groups were close, and the timeliness of preprints was better. Synthesized estimates of the basic reproduction number (3.18, 95% CI 2.85–3.53), incubation period (5.44 days, 95% CI 4.98–5.99), infectious period (6.25 days, 95% CI 5.09–7.51), and case-fatality-rate (4.51%, 95% CI 3.41%–6.29%) were obtained. Simulated cumulative cases of the SEIRDC model matched well with the onset cases in China. The validity of the COVID-19 parameter estimations of the preprints was on par with that of peer-reviewed publications, and synthesized results of literatures could reduce the uncertainty and be used for epidemic decision-making. [ABSTRACT FROM AUTHOR]

• Morbidity and mortality in children due to COVID-19 remained low • Adolescents had higher reported cases than younger children • Reported cases were lower in pediatric population than adult population • Testing protocols vary between countries; reflects bias in reported cases Few data on the COVID-19 epidemiological characteristics among the pediatric population in Africa exists. This paper examines the age and sex distribution of the morbidity and mortality rate in children with COVID-19 and compares it to the adult population in 15 Sub-Saharan African countries. A merge line listing dataset shared by countries within the Regional Office for Africa was analyzed. Patients diagnosed within 1 March and 1 September 2020 with a confirmed positive RT-PCR test for SARS-CoV-2 were analyzed. Children's data were stratified into three age groups: 0-4 years, 5-11 years, and 12-17 years, while adults were combined. The cumulative incidence of cases, its medians, and 95% confidence intervals were calculated. 9% of the total confirmed cases and 2.4% of the reported deaths were pediatric cases. The 12-17 age group in all 15 countries showed the highest cumulative incidence proportion in children. Adults had a higher case incidence per 100,000 people than children. The cases and deaths within the children's population were smaller than the adult population. These differences may reflect biases in COVID-19 testing protocols and reporting implemented by countries, highlighting the need for more extensive investigation and focus on the effects of COVID-19 in children. [ABSTRACT FROM AUTHOR]

Highlights • This paper describes the epidemiology of influenza viruses among children in Wuhan, China during nine influenza seasons (2007–2015) and predicts the positive rate of different types of influenza virus in the future. • In contrast to previous research at home and abroad, this paper is the first study that explores the application of time series analysis using the positive rate of influenza virus in children to predict the future incidence. • The ARIMA model is a good instrument that forecasts the positive rate of different types of influenza virus. • The wide use of influenza vaccines, especially for influenza B(Yamagata) and B(Victoria), can potentially reduce the effects of influenza on the children of China. Abstract Objective Influenza is a common childhood disease and protecting children by predicting the positive rate of influenza virus is important as vaccines are not routinely administered in China. Our study aims to describe the epidemiology of influenza viruses among children in Wuhan, China during the past nine influenza seasons (2007–2015) and to predict the positive rate of different types of influenza virus in the future. Methods During the last nine influenza seasons (2007–2015), a total of 10,232 nasopharyngeal swabs collected from pediatric outpatients (age <15 years) with influenza-like illness (ILI) infections in two sentinel children’s hospitals were examined for influenza A and B by real-time one step RT-PCR. An autoregressive integrated moving average (ARIMA) model was used to fit the time series and to predict the future (first half of 2016) positive rates of different types of influenza virus. Results A total of 1,341 specimens were positive for influenza A and 490 for influenza B. The majority of infected patients were 1–11 years old (87.7%). The ARIMA model could effectively predict the positive rate of influenza virus in a short time. ARIMA(0,0,11), SARIMA(1,0,0)(0,1,1) 12 , ARIMA(0,0,1) and SARIMA(0,0,1)(1,0,1) 12 were suitable for B(Victoria), B(Yamagata), A(H1N1)pdm09, and A(H3N2), respectively. Conclusion Additional policies must be formulated to prevent and control influenza. The wide use of influenza vaccines, especially for influenza B, especially for influenza B(Yamagata) and B(Victoria), can potentially reduce the effects of influenza on children of China. [ABSTRACT FROM AUTHOR]

Background Increasing evidence is becoming available on the aetiology and management of fevers in Asia; the importance of these fevers has increased with the decline in the incidence of malaria. Aims To conduct a narrative review of the epidemiology and management of fevers in South and South-East Asia and to highlight gaps in our knowledge that impair evidence-based health policy decisions. Sources A narrative review of papers published since 2012 on developments in fever epidemiology, diagnosis and treatment in South and South-East Asia. The papers that the authors felt were pivotal, from their personal perspectives, are discussed. Content We identified 100 studies. Among the 30 studies (30%)—including both children and adults—that investigated three or more pathogens, the most frequently reported fever aetiology was dengue (reported by 15, 50%), followed by leptospirosis (eight, 27%), scrub typhus (seven, 23%) and Salmonella serovar Typhi (six, 20%). Among four studies investigating three or more pathogens in children, dengue and Staphylococcus aureus were the most frequent, followed by non-typhoidal Salmonella spp, Streptococcus pneumoniae , Salmonella serovar Typhi, and Orientia tsutsugamushi . Increased awareness is needed that rickettsial pathogens are common but do not respond to cephalosporins, and that alternative therapies, such as tetracyclines, are required. Implications Many key gaps remain, and consensus guidelines for study design are needed to aid comparative understanding of the epidemiology of fevers. More investment in developing accurate and affordable diagnostic tests for rural Asia and independent evaluation of those already on the market are needed. Treatment algorithms, including simple biomarker assays, appropriate for empirical therapy of fevers in different areas of rural Asia should be a major aim of fever research. Enhanced antimicrobial resistance (AMR) surveillance and openly accessible databases of geography-specific AMR data would inform policy on empirical and specific therapy. More investment in innovative strategies facilitating infectious disease surveillance in remote rural communities would be an important component of poverty reduction and improving public health. [ABSTRACT FROM AUTHOR]

• The early COVID-19 epidemic in South Africa was highly heterogeneous looking at the epidemiological progression between major provinces. • Early transmission in KwaZulu-Natal (KZN) was associated with multiple international introductions of SARS-CoV-2. • The dominating lineages during this time of the epidemic were B.1 and B, which mainly originated from Europe. • Evidence for transmission clusters during the first month of the epidemic suggested locally acquired infection. • A clustered outbreak was linked to a major hospital outbreak in Durban, which inflated the early mortality in KZN. The Network for Genomic Surveillance in South Africa (NGS-SA) was formed to investigate the introduction and understand the early transmission dynamics of the SARS-CoV-2 epidemic in South-Africa. This paper presents the first results from this group, which is a molecular epidemiological study of the first 21 SARS-CoV-2 whole genomes sampled in the first port of entry – KwaZulu-Natal (KZN) – during the first month of the epidemic. By combining this with calculations of the effective reproduction number (R), it aimed to shed light on the patterns of infections in South Africa. Two of the largest provinces – Gauteng and KZN – had a slow growth rate for the number of detected cases, while the epidemic spread faster in the Western Cape and Eastern Cape. The estimates of transmission potential suggested a decrease towards R = 1 since the first cases and deaths, but a subsequent estimated R average of 1.39 between 6–18 May 2020. It was also demonstrated that early transmission in KZN was associated with multiple international introductions and dominated by lineages B1 and B. Evidence for locally acquired infections in a hospital in Durban within the first month of the epidemic was also provided. The COVID-19 pandemic in South Africa was very heterogeneous in its spatial dimension, with many distinct introductions of SARS-CoV2 in KZN and evidence of nosocomial transmission, which inflated early mortality in KZN. The epidemic at the local level was still developing and NGS-SA aimed to clarify the dynamics in South Africa and devise the most effective measures as the outbreak evolved. [ABSTRACT FROM AUTHOR]

The recent coronavirus disease (COVID-19) outbreak has dramatically increased the public awareness and appreciation of the utility of dynamic models. At the same time, the dissemination of contradictory model predictions has highlighted their limitations. If some parameters and/or state variables of a model cannot be determined from output measurements, its ability to yield correct insights – as well as the possibility of controlling the system – may be compromised. Epidemic dynamics are commonly analysed using compartmental models, and many variations of such models have been used for analysing and predicting the evolution of the COVID-19 pandemic. In this paper we survey the different models proposed in the literature, assembling a list of 36 model structures and assessing their ability to provide reliable information. We address the problem using the control theoretic concepts of structural identifiability and observability. Since some parameters can vary during the course of an epidemic, we consider both the constant and time-varying parameter assumptions. We analyse the structural identifiability and observability of all of the models, considering all plausible choices of outputs and time-varying parameters, which leads us to analyse 255 different model versions. We classify the models according to their structural identifiability and observability under the different assumptions and discuss the implications of the results. We also illustrate with an example several alternative ways of remedying the lack of observability of a model. Our analyses provide guidelines for choosing the most informative model for each purpose, taking into account the available knowledge and measurements. • Structural identifiability and observability are desirable model properties. • They describe a model's ability to inform about unmeasured parameters and states. • We collect and analyse hundreds of compartmental models of the COVID-19 pandemics. • We show which parameters and states can be determined from output measurements. • We discuss how to choose the most informative model for the available knowledge. [ABSTRACT FROM AUTHOR]

• The incidence of Japanese encephalitis in the Philippines was found to be a minimum of 0.7/100,000 in children aged <15 years. • Cases peaked annually from July to October, but occurred all year round. • Most confirmed cases were of children aged 2–4 years (n = 194, 23.0%). • Annual minimum incidences were found to be higher in the northern regions of the Philippines. Findings were published in 2015 that highlighted the endemicity of Japanese Encephalitis (JE) in the Philippines. The policymakers responded by conducting an immunization campaign and strengthening the surveillance system. Using data on the revitalized surveillance system, the epidemiology of JE in the country was updated. Electronic databases were searched, and conference proceedings related to JE in the Philippines were identified until 31 December 2018. Surveillance data from 01 January 2014 to 31 December 2017 were used. The 2015 population census was used to estimate the national and regional incidence for children aged <15 years. Four studies reported the seroprevalence of JE in the Philippines, which showed increasing seroprevalence with increasing age. Seroprevalence rates were from 0% for infants (aged <1 year) to 65.7% in adolescents (12–18 years) before the immunization campaign. Among five studies on the clinical profile of JE, case fatality ranged from 0 to 21.1% and neurologic sequelae ranged from 5.2 to 81.8% of diagnosed cases. In the surveillance data, JE cases peaked annually from July to October, coinciding with the wet season. The national incidence was estimated at a minimum of 0.7 JE cases/100,000 among children aged <15 years, but higher rates were seen in the northern regions of the country. Improved surveillance affirmed the burden of JE in the Philippines. A subnational immunization campaign in April 2019 was conducted in the northern regions of the country. This paper highlights the importance of including the JE vaccine in the immunization program and sustained high-quality surveillance to monitor its impact on JE control. [ABSTRACT FROM AUTHOR]

By July 25, Colombia had confirmed 240 795 cases of COVID-19 and 8269 deaths (case fatality rate of 3.4%). All departments had reported cases, but 292 municipalities were apparently free of COVID-19 (26%) and 373 (33.2%) had seen limited transmission. Specific mortality rates by department ranged from 0 in Vichada to 1278 in Amazonas, which was 7.8 times the national rate (incidence rate ratio (IRR) = 7.8, 95% confidence interval 6.4–9.5). Using a conservative approach to assess the potential underestimation of cases, it was estimated that, by July 25, Colombia should have detected 1 328 175 cases instead of the actual 240 795 observed, an underestimation of 82%. Colombia detected its first coronavirus disease 2019 (COVID-19) case on March 2, 2020. From March 22 to April 25, it implemented a national lockdown that, apparently, allowed the country to keep a low incidence and mortality rate up to mid-May. Forced by the economic losses, the government then opened many commercial activities, which was followed by an increase in cases and deaths. This paper presents a critical analysis of the Colombian surveillance data in order to identify strengths and pitfalls of the control measures. A descriptive analysis of PCR-confirmed cases between March and July 25 was performed. Data were described according to the level of measurement. Incidence and mortality rates of COVID-19 were estimated by age, sex, and geographical area. Sampling rates for suspected cases were estimated by geographical area, and the potential for case underestimation was assessed using sampling differences. By July 25, Colombia (population 50 372 424) had reported 240 745 cases and 8269 deaths (case fatality rate of 3.4%). A total of 1 370 271 samples had been analyzed (27 405 samples per million people), with a positivity rate of 17%. Sampling rates per million varied by region from 2664 to 158 681 per million, and consequently the incidence and mortality rates also varied. Due to geographical variations in surveillance capacity, Colombia may have overlooked up to 82% of the actual cases. Colombia has a lower case and mortality incidence compared to other South American countries. This may be an effect of the lockdown, but may also be attributed, to some extent, to geographical differences in surveillance capacity. Indigenous populations with little health infrastructure have been hit the hardest. [ABSTRACT FROM AUTHOR]

• First autochthonous DENV cases were detected by the surveillance system in 2019. • Sustained and strengthened surveillance is required for early detection of DENV. • Afghanistan needs to develop preparedness and a response plan for DENV. • The cross-border spread of DENV has been reported between Afghanistan and Pakistan. • Enhanced cross-border collaboration is needed for active response and preventing the spread. This paper aims to describe the epidemiological characteristics and clinical manifestations of the first 15 dengue fever cases reported in Afghanistan. A retrospective descriptive analysis of the data on confirmed dengue cases detected by the national disease surveillance system was conducted. Epidemiological, socio-demographic, clinical, laboratory and outcome data from the cases were analyzed. Between May and December 2019, 62 samples were tested for DENV, among which 15 (24.2%) were positive. Seven of the cases were probable autochthonous with no travel history, the other seven cases had a travel history to dengue-endemic countries (five Pakistan, two India) and the travel history for one of the cases was not known. The 15 confirmed cases were reported from six provinces, seven cases (46.7%) were reported from Nangarhar Province, two (13%) from Paktya, and one (6.7%) from Paktika province, bordering with Pakistan, three (20%) were reported from Kabul, and one each (each 6.7%) from Faryab and Laghman provinces. All of the cases manifested fever, headache, myalgia, and arthralgia. Other clinical features were low platelet count (50%), pain behind eyes (36%), rash, and nausea/vomiting (each 21%). For the first time, the surveillance system detected and reported locally acquired DENV cases in Afghanistan, mostly in provinces bordering with Pakistan. Population movements between Afghanistan and Pakistan facilitate the cross-border spread of DENV between two countries. [ABSTRACT FROM AUTHOR]

Background: Despite the greater prevalence of familial hypercholesterolemia (FH) in subjects with ischemic heart disease (IHD), premature IHD, and severe hypercholesterolemia (low-density lipoprotein ≥190 mg/dl), overall prevalence estimates are not available.Objectives: The aim of this study was to provide worldwide estimates of FH prevalence in subjects with IHD, premature IHD, and severe hypercholesterolemia compared with those in the general population.Methods: In this systematic review and meta-analyses, Embase, PubMed, and the Web of Science were searched until June 3, 2019, for peer-reviewed papers and conference abstracts reporting heterozygous FH prevalence in nonfounder populations, revealing 104 studies eligible for inclusion.Results: Estimates of FH prevalence were pooled using random-effects meta-analyses and were 0.32% (95% confidence interval [CI]: 0.26% to 0.39% [corresponding to 1:313]) among 10,921,310 unique subjects in the general population (33,036 patients with FH) on the basis of 44 studies, 3.2% (95% CI: 2.2% to 4.3% [1:31]) among 84,479 unique subjects with IHD (2,103 patients with FH) on the basis of 28 studies, 6.7% (95% CI: 4.9% to 8.7% [1:15]) among 31,316 unique subjects with premature IHD (1,471 patients with FH) on the basis of 32 studies, and 7.2% (95% CI: 4.6% to 10.8% [1:14]) among 17,728 unique subjects with severe hypercholesterolemia (920 patients with FH) on the basis of 7 studies. FH prevalence in the general population was similar using genetic versus clinical diagnoses. Seventeen of 195 countries (9%) in the world have reported FH prevalence for the general population, leaving 178 (91%) countries in the world with unknown prevalence.Conclusions: Compared with 1:313 among subjects in the general population, FH prevalence is 10-fold higher among those with IHD, 20-fold higher among those with premature IHD, and 23-fold higher among those with severe hypercholesterolemia. The prevalence of FH is unknown in 90% of countries in the world. [ABSTRACT FROM AUTHOR]

• The latest summary of the COVID-19 outbreak in China; • There might be an oral-fecal transmission of the virus; • Aggregates and consolidates the epidemiology, clinical manifestations, diagnosis, treatments and preventions of this new type of coronavirus. There is a current worldwide outbreak of the novel coronavirus Covid-19 (coronavirus disease 2019; the pathogen called SARS-CoV-2; previously 2019-nCoV), which originated from Wuhan in China and has now spread to 6 continents including 66 countries, as of 24:00 on March 2, 2020. Governments are under increased pressure to stop the outbreak from spiraling into a global health emergency. At this stage, preparedness, transparency, and sharing of information are crucial to risk assessments and beginning outbreak control activities. This information should include reports from outbreak site and from laboratories supporting the investigation. This paper aggregates and consolidates the epidemiology, clinical manifestations, diagnosis, treatments and preventions of this new type of coronavirus. [ABSTRACT FROM AUTHOR]

• Crimean-Congo Hemorrhagic Fever (CCHF) has significantly increased in Afghanistan during recent years. • Those who are exposed to the vector (Hyalomma ticks), infected animals, the blood and tissues of freshly slaughtered livestock are most at risk. • The cases reach to its peak during Eid-al-Adha when people are sacrificing animals. • Information on CCHF pathogen genotypes and lineage, strain movement and sequence diversity of the CCHF in Afghanistan is not known yet. This study aims to provide descriptive epidemiology of human CCHF cases in Afghanistan by demographic, geographical, and seasonal characteristics. This paper's findings are based on the retrospective analysis of the National Surveillance System's collected data from 2016 to 2018. Weekly cases exceeding the 90th percentile of the expected number of cases were considered to be exceptional and above normal. The National Surveillance System detected 1,284 CCHF cases from 2007 to 2018, of which 163 cases were in 2016, 245 cases in 2017 and 483 cases in 2018. A total of 891 suspected and confirmed cases were reported between 2016 and 2018, 293 (33%) of these cases were confirmed by detecting IgM antibody using ELISA and RT-PCR. Among confirmed cases, the three-year case fatality ratio (CFR) was 43.3%. Among the reported cases, 68.5% were males and 31.5% females. The frequent reported occupational groups were housewives (15%), health staff (13%), shepherds (11%), butchers (6%), students (6%), animal dealers and farmers (both 2%) respectively, 19% were unemployed, and occupation was not recorded for 26% of cases. Recently, CCHF has significantly increased in Afghanistan. Despite the increased frequency of cases, the laboratory capacity to test specimens and overall knowledge of CCHF management remains limited. [ABSTRACT FROM AUTHOR]

• We summarize the detection frequency of BLV in samples of human origin. • Nested PCR and tax gene are the main technique and gene targets reported for detecting the bovine leukemia virus. • We calculated an overall bovine leukemia virus detection frequency of 27%. To review the available studies on the frequency of detection of the bovine leukemia virus in human samples, a systematic review with meta-analysis of the scientific literature was carried out, including papers published in English, Spanish, and Portuguese in 5 multidisciplinary databases. We collected information from different populations following a detailed and reproducible search protocol in which two researchers verified the inclusion and exclusion criteria. We identified 759 articles, of which only 33 met the inclusion criteria. Analyzed studies reported that the presence of the virus was measured in human samples, such as paraffin-embedded breast tissue and peripheral blood from 10,398 individuals, through serological and molecular techniques. An overall virus frequency of 27% (Ranging between 17 and 37%) was observed, with a high-frequency data heterogeneity between studies. The presence of this virus in different human biological samples suggests the need to investigate further its transmission route to humans and its potential role in developing and progressing diseases. [ABSTRACT FROM AUTHOR]

The high rates of cholera epidemic mortality in less developed countries is a challenge for health facilities to which it is necessary to equip itself with the epidemiological surveillance. To strengthen the capacity of epidemiological surveillance, this paper focuses on remote sensing satellite data processing using data mining methods to discover risk areas of the epidemic disease by connecting the environment, climate and health. These satellite data are combined with field data collected during the same set of periods in order to explain and deduct the causes of the epidemic evolution from one period to another in relation to the environment. The existing technical (algorithms) for processing satellite images are mature and efficient, so the challenge today is to provide the most suitable means allowing the best interpretation of obtained results. For that, we focus on supervised classification algorithm to process a set of satellite images from the same area but on different periods. A novel research methodology (describing pre-treatment, data mining, and post-treatment) is proposed to ensure suitable means for transforming data, generating information and extracting knowledge. This methodology consists of six phases: (1.A) Acquisition of information from the field about epidemic, (1.B) Satellite data acquisition, (2) Selection and transformation of data (Data derived from images), (3) Remote sensing measurements, (4) Discretization of data, (5) Data treatment, and (6) Interpretation of results. The main contributions of the paper are: to establish the nature of links between the environment and the epidemic, and to highlight those risky environments when the public awareness of the problem and the prevention policies are absolutely necessary for mitigation of the propagation and emergence of the epidemic. This will allow national governments, local authorities and the public health officials to effective management according to risk areas. The case study concerns the knowledge discovery in databases related to risk areas of the cholera epidemic in Mopti region, Mali (West Africa). The results generate from data mining association rules indicate that the level of the Niger River in the wintering periods and some societal factors have an impact on the variation of cholera epidemic rate in Mopti town. More the river level is high, at 66% the rate of contamination is high. [ABSTRACT FROM AUTHOR]

To address limitations of observational epidemiology studies of air pollution and health effects, including residual confounding by temporal and spatial factors, several studies have taken advantage of ‘natural experiments’, where an environmental policy or air quality intervention has resulted in reductions in ambient air pollution concentrations. Researchers have examined whether the population impacted by these air quality improvements, also experienced improvements in various health indices (e.g. reduced morbidity/mortality). In this paper, I review key accountability studies done previously and new studies done over the past several years in Beijing, Atlanta, London, Ireland, and other locations, describing study design and analysis strengths and limitations of each. As new ‘natural experiment’ opportunities arise, several lessons learned from these studies should be applied when planning a new accountability study. Comparison of health outcomes during the intervention to both before and after the intervention in the population of interest, as well as use of a control population to assess whether any temporal changes in the population of interest were also seen in populations not impacted by air quality improvements, should aid in minimizing residual confounding by these long term time trends. Use of either detailed health records for a population, or prospectively collected data on relevant mechanistic biomarkers coupled with such morbidity/mortality data may provide a more thorough assessment of if the intervention beneficially impacted the health of the community, and if so by what mechanism(s). Further, prospective measurement of a large suite of air pollutants may allow a more thorough understanding of what pollutant source(s) is/are responsible for any health benefit observed. The importance of using multiple statistical analysis methods in each paper and the difference in how the timing of the air pollution/outcome association may impact which of these design features is most important is also discussed. Based on these and other lessons learned, researchers may provide a more epidemiologically rigorous evaluation of cause-specific health impacts of an air quality intervention or action. [ABSTRACT FROM AUTHOR]

The European Study of Cohorts for Air Pollution Effects (ESCAPE) is a13-nation study of long-term health effects of air pollution based on subjects pooled from up to 22 cohorts that were intended for other purposes. Twenty-five papers have been published on associations of various health endpoints with long-term exposures to NOx, NO2, traffic indicators, PM10, PM2.5 and PM constituents including absorbance (elemental carbon). Seven additional ESCAPE papers found moderate correlations (R2 = 0.3–0.8) between measured air quality and estimates based on land-use regression that were used; personal exposures were not considered. I found no project summaries or comparisons across papers; here I conflate the 25 ESCAPE findings in the context of other recent European epidemiology studies. Because one ESCAPE cohort contributed about half of the subjects, I consider it and the other 18 cohorts separately to compare their contributions to the combined risk estimates. I emphasize PM2.5 and confirm the published hazard ratio of 1.14 (1.04–1.26) per 10 μg/m3 for all-cause mortality. The ESCAPE papers found 16 statistically significant (p < 0.05) risks among the125 pollutant-endpoint combinations; 4 each for PM2.5 and PM10, 1 for PM absorbance, 5 for NO2, and 2 for traffic. No PM constituent was consistently significant. No significant associations were reported for cardiovascular mortality; low birthrate was significant for all pollutants except PM absorbance. Based on associations with PM2.5, I find large differences between all-cause death estimates and the sum of specific-cause death estimates. Scatterplots of PM2.5 mortality risks by cause show no consistency across the 18 cohorts, ostensibly because of the relatively few subjects. Overall, I find the ESCAPE project inconclusive and I question whether the efforts required to estimate exposures for small cohorts were worthwhile. I suggest that detailed studies of the large cohort using historical exposures and additional cardiovascular risk factors might be productive. [ABSTRACT FROM AUTHOR]

Personal exposure measurements of radio frequency electromagnetic fields are important for epidemiological studies and developing prediction models. Minimizing biases and uncertainties and handling spatial and temporal variability are important aspects of these measurements. This paper reviews the lessons learnt from testing the different types of exposimeters and from personal exposure measurement surveys performed between 2005 and 2015. Applying them will improve the comparability and ranking of exposure levels for different microenvironments, activities or (groups of) people, such that epidemiological studies are better capable of finding potential weak correlations with health effects. Over 20 papers have been published on how to prevent biases and minimize uncertainties due to: mechanical errors; design of hardware and software filters; anisotropy; and influence of the body. A number of biases can be corrected for by determining multiplicative correction factors. In addition a good protocol on how to wear the exposimeter, a sufficiently small sampling interval and sufficiently long measurement duration will minimize biases. Corrections to biases are possible for: non-detects through detection limit, erroneous manufacturer calibration and temporal drift. Corrections not deemed necessary, because no significant biases have been observed, are: linearity in response and resolution. Corrections difficult to perform after measurements are for: modulation/duty cycle sensitivity; out of band response aka cross talk; temperature and humidity sensitivity. Corrections not possible to perform after measurements are for: multiple signals detection in one band; flatness of response within a frequency band; anisotropy to waves of different elevation angle. An analysis of 20 microenvironmental surveys showed that early studies using exposimeters with logarithmic detectors, overestimated exposure to signals with bursts, such as in uplink signals from mobile phones and WiFi appliances. Further, the possible corrections for biases have not been fully applied. The main findings are that if the biases are not corrected for, the actual exposure will on average be underestimated. [ABSTRACT FROM AUTHOR]

Abstract Background Few epidemiological studies have investigated associations of exposure to multiple metals with thyroid hormone homeostasis, especially for the pregnant women. Methods Among all the 1644 participants enrolled in Hangzhou Birth Cohort Study (HBCS) at baseline, a total of 915 pregnant women with complete data of interest were analyzed. Eleven metals were measured in blood samples collected around 25 weeks gestation. Serum levels of thyroid hormones including free triiodothyronine (FT3), total triiodothyronine (TT3), free thyroxine (FT4), total thyroxine (TT4) and thyroid-stimulating hormone (TSH) were abstracted from the medical records. Relationships between tertiles of metal levels (setting the lowest tertile as the reference) and percent changes in thyroid hormones were estimated by multivariable adjusted linear regression models. Results Five metals [arsenic (As), selenium (Se), manganese (Mn), nickel (Ni), antimony (Sb)] were significantly linked to decreased levels of one or more thyroid hormones based on trend tests in the single-metal models. Percent changes [95% confidence intervals (CIs)] in thyroid hormones for the third tertiles of metals remained significant between FT3 and As [−3.53% (−5.48%, −1.54%)]; and between TT3 and As [−4.19% (−7.00%, −1.31%)]; and between FT4 and Mn [−2.05% (−3.49%, −0.58%)], Sb [−1.99% (−3.44%, −0.52%)] in the multiple-metal models. Conclusions Thyroid hormone concentrations were reversely related to the levels of blood metals of As, Mn and Sb among Chinese pregnant women. Additional prospective studies are warranted to confirm the causality. Paper capsule: Exposure to multiple metals was reversely associated with one or more thyroid hormones in the Chinese pregnant women. Graphical abstract Unlabelled Image Highlights • Associations of multiple metals with thyroid hormones were examined at pregnancy. • Both single- and multiple-metal models were employed for data analyses. • Blood metals of As, Mn and Sb were reversely linked to thyroid hormones. [ABSTRACT FROM AUTHOR]

The paper presents a numerical procedure for solving a class of optimal control problems for heterogeneous systems. The latter are described by parameterized systems of ordinary differential equations, coupled by integrals along the parameter space. Such problems arise in economics, demography, epidemiology, management of biological resources, etc. The numerical procedure includes discretization and a gradient projection method for solving the resulting discrete problem. A main point of the paper is the performed error analysis, which is based on the property of metric regularity of the system of necessary optimality conditions associated with the considered problem. [ABSTRACT FROM AUTHOR]

The mortality rate associated with HIV infection plummeted after the introduction of effective antiretroviral therapy pioneered two decades ago. As a result, HIV-infected people now have life expectancies comparable to that of HIV-uninfected individuals. Despite this, increased rates of osteoporosis, chronic liver disease, and in particular cardiovascular disease have been reported among people living with HIV infection. With the aging HIV-infected population, the burden of these comorbid illnesses may continue to accrue over time. In this paper, we present an overview of the aging HIV-infected population, its epidemiology and the many challenges faced. How to define and measure successful aging will also be reviewed. Finally, opportunities that may help mitigate the challenges identified and ensure successful aging among people living with HIV infection will be examined. [ABSTRACT FROM AUTHOR]

Density-dependent diffusion plays an important role in the process of viral infection. In this paper, we construct mathematical models to investigate the dynamics of the viruses and their control. Single strain and multi-strain viral infections are both considered in this work. Using the method proposed by Pao and Ruan (2013), we prove the well-posedness of the models. By constructing appropriate Lyapunov functions, we proved the global asymptotical stabilities of the models. For the multi-strain model, we show that when the basic reproduction number for each strain is greater than one, all viral strains coexist. Since the effect of different treatments may result in competitive exclusion, it is essential to employ the treatment with combined therapy. We find with surprise that the density-dependent diffusion of the virus does not influence the global stabilities of the model with homogeneous Neumann boundary conditions. [ABSTRACT FROM AUTHOR]

Energy demand reduction from buildings is widely recognised as a key component of greenhouse gas abatement strategies. As governments shift towards large-scale sectoral interventions, a far more robust research and evidence base is needed to support the development, implementation, and on-going evaluation of energy demand policy. The shift to a low carbon built environment will require both a step change in the energy performance of buildings alongside more efficient provision of energy services, and an aggressive decarbonisation of the energy used. Yet the prerequisite data of building stocks needed to support this essential shift in energy performance of buildings are not necessarily available or are inaccessible or incomplete. As more information on building energy use is collected through high frequency sensors and building form analytics become more sophisticated, the analysis methods applied to the myriad and diverse sub-sectors of the building stock ‘population’ need to be commensurate with the heterogeneity of the building stock. This paper describes and illustrates the basis of the IEA EBC Annex 70: Building Energy Epidemiology, which draws on the health sciences to posit ‘energy epidemiology’ as a whole-system approach for empirical research that provides a methodological framework for building physicists, engineers, social scientists, and economists to engage in cross-disciplinary studies. It makes the case that the development and application of an epidemiological approach to investigating energy demand can advance understanding of the inter-related factors for policy guidance and evaluation and provide insights on the mechanisms that influence energy demand. The aim of the IEA EBC Annex 70 is to work in an international collaboration to identify user needs around energy demand in buildings and to establish best practice methods and harmonized formats for data collection, analysis and modelling. To illustrate this process, we present an example from the UK on the application of energy epidemiological methods to building energy performance in the residential sector. The case study investigates the potential effectiveness of the policy and technical measures proposed by the UK Government. Policy implementation for broad, deep, and urgent reductions in energy demand from the building sector requires a far better understanding of the underlying relationships between people, energy use, buildings and the environment. [ABSTRACT FROM AUTHOR]

This paper describes measurements and computational modelling carried out in the MOBI-Kids case-control study to assess the extremely low frequency (ELF) exposure of the brain from use of mobile and cordless phones. Four different communication systems were investigated: Global System for Mobile (GSM), Universal Mobile Telecommunications System (UMTS), Digital Enhanced Cordless Telecommunications (DECT) and Wi-Fi Voice over Internet Protocol (VoIP). The magnetic fields produced by the phones during transmission were measured under controlled laboratory conditions, and an equivalent loop was fitted to the data to produce three-dimensional extrapolations of the field. Computational modelling was then used to calculate the induced current density and electric field strength in the brain resulting from exposure to these magnetic fields. Human voxel phantoms of four different ages were used: 8, 11, 14 and adult. The results indicate that the current densities induced in the brain during DECT calls are likely to be an order of magnitude lower than those generated during GSM calls but over twice that during UMTS calls. The average current density during Wi-Fi VoIP calls was found to be lower than for UMTS by 30%, but the variability across the samples investigated was high. Spectral contributions were important to consider in relation to current density, particularly for DECT phones. This study suggests that the spatial distribution of the ELF induced current densities in brain tissues is determined by the physical characteristics of the phone (in particular battery position) while the amplitude is mainly dependent on communication system, thus providing a feasible basis for assessing ELF exposure in the epidemiological study. The number of phantoms was not large enough to provide definitive evidence of an increase of induced current density with age, but the data that are available suggest that, if present, the effect is likely to be very small. [ABSTRACT FROM AUTHOR]

Little is known about specific modes of death in patients with heart failure with preserved ejection fraction (HFpEF). Herein, the authors critically appraise the current state of data and offer potential future directions. They conducted a systematic review of 1,608 published HFpEF papers from January 1, 1985, to December 31, 2015, which yielded 8 randomized clinical trials and 24 epidemiological studies with mode-of-death data. Noncardiovascular modes of death represent an important competing risk in HFpEF. Although sudden death accounted for ∼25% to 30% of deaths in trials, its definition is nonspecific; it is unclear what proportion represents arrhythmic deaths. Moving forward, reporting and definitions of modes of death must be standardized and tailored to the HFpEF population. Broad-scale systematic autopsies and long-term rhythm monitoring may clarify the underlying pathology and mechanisms driving mortal events. There is an unmet need for a longitudinal multicenter, global registry of patients with HFpEF to map its natural history. [ABSTRACT FROM AUTHOR]

The information obtained from the chemical analysis of specific human excretion products (biomarkers) in urban wastewater can be used to estimate the exposure or consumption of the population under investigation to a defined substance. A proper biomarker can provide relevant information about lifestyle habits, health and wellbeing, but its selection is not an easy task as it should fulfil several specific requirements in order to be successfully employed. This paper aims to summarize the current knowledge related to the most relevant biomarkers used so far. In addition, some potential wastewater biomarkers that could be used for future applications were evaluated. For this purpose, representative chemical classes have been chosen and grouped in four main categories: (i) those that provide estimates of lifestyle factors and substance use, (ii) those used to estimate the exposure to toxicants present in the environment and food, (iii) those that have the potential to provide information about public health and illness and (iv) those used to estimate the population size. To facilitate the evaluation of the eligibility of a compound as a biomarker, information, when available, on stability in urine and wastewater and pharmacokinetic data (i.e. metabolism and urinary excretion profile) has been reviewed. Finally, several needs and recommendations for future research are proposed. [ABSTRACT FROM AUTHOR]

Measurement of glycated hemoglobin (HbA1c), the most widely accepted indicator of long-term glycemic exposure, is central for the diagnosis and management of diabetes mellitus. Levels of HbA1c track epidemiologically with diabetic complications, and glycemic control, as reflected by HbA1c reduction, results in decreased risk of microvascular complications, including diabetic kidney disease, neuropathy, and retinopathy. The relationship between HbA1c reduction and cardiovascular disease prevention in patients with diabetes is more complex, with data from large randomized trials published over the past decade providing clear evidence that lowering of HbA1c per se is an inadequate marker for a therapeutic regimen's impact on cardiovascular outcomes and patient survival. Recent revisions in professional society guidelines moved away from uniform recommendations and toward a more nuanced, patient-centered approach to HbA1c therapeutic targets. The context and key evidence underpinning these recent changes are discussed in this paper, alongside a brief overview of HbA1c contemporary assays and their limitations. [ABSTRACT FROM AUTHOR]

The objectives of the present study were to assess the prevalence of cytological endometritis (CYTO) at the time of artificial insemination (AI) and its effect on pregnancy outcomes in nulliparous dairy heifers. In total, 512 endometrial cytology samples were taken during AI from 351 nulliparous Holstein-Friesian heifers using cytotape (a 1.5-cm piece of paper tape rolled on the top of an AI catheter covered with a double guard sheet). After sampling, the top of the AI catheter was gently rolled onto a glass slide, air-dried, and stained using Diff-Quick (Fisher Diagnostics, Newark, DE). For each slide, 300 nucleated cells were counted, and the polymorphonuclear cell ratio (% PMN) was assessed at 400× magnification. We constructed a receiver operating characteristic curve to find the cutoff point at which sensitivity and specificity (% PMN) affected pregnancy outcomes. The receiver operating characteristic curve revealed that the threshold level for diagnosing CYTO in nulliparous dairy heifers was 1% PMN. An insemination was considered successful when pregnancy was confirmed by rectal palpation at least 45 d post-AI. Heifers were considered not pregnant when they received a subsequent insemination or were diagnosed empty by rectal palpation. We built multilevel generalized mixed-effect models to test factors affecting pregnancy outcomes and the occurrence of CYTO at AI. We excluded 16 samples harvested from 12 heifers due to poor sample quality or unavailability of reproductive data. Of the 496 AI samples, the prevalence of CYTO at AI was 7.86% (n = 39). The conception rate was 62.8% (n = 287) in CYTO-negative samples (n = 457) and 38.46% (n = 15) in CYTO-positive samples. Risk factors for non-pregnancy were a previous AI (odds ratio 2.96; 95% confidence interval: 1.21-7.26) and the interaction between CYTO and previous AI. The only risk factor identified as being associated with the occurrence of CYTO was a previous AI (odds ratio 4.7; 95% confidence interval: 2.15-10.34). The performance of unsuccessful inseminations significantly affects reproductive outcomes in subsequent AI and may lead to CYTO in nulliparous dairy heifers. [ABSTRACT FROM AUTHOR]

Knowledge of spatial and temporal trends in the environmental exposure to radiofrequency electromagnetic fields (RF-EMF) is a key prerequisite for RF-EMF risk assessment studies attempting to establish a link between RF-EMF and potential effects on human health as well as on fauna and flora. In this paper, we determined the validity of RF exposure modelling based on inner-area kriging interpolation of measurements on the surrounding streets. The results vary depending on area size and shape and structural factors; a Spearman coefficient of 0.8 and a relative error of less than 3.5 dB are achieved on a data set featuring a closed measurement ring around a decently sized area (1 km 2 , with an average minimum distance of the encircled area to the ring of less than 100 m), containing mainly low, detached buildings. In larger areas, additional inner-area sampling is advised, lowering the average minimum distance between sampled and interpolated locations to 100 m, to achieve the same level of accuracy. [ABSTRACT FROM AUTHOR]

Objectives Results of epidemiological studies of lipid profiles in individuals with Down Syndrome (DS) in different settings showed discordant results but laboratory norms for this population has been lacking. The aim of our study is to evaluate lipid profiles in a large population of Italian children with DS. Methods Lipid profiles of 357 patients with diagnosis of DS were recorded. RESULTS: Multiple linear regression was employed to estimate models for each lipid fraction as a function of sex and age in patients with DS. Conclusions The main contribution of this paper is to provide data about lipid profile on a large cohort of people with Down syndrome. Long-term surveillance will be crucial to establish if this specific lipid profile may translate into increased morbidity and mortality from cardiovascular diseases (CVD) [ABSTRACT FROM AUTHOR]

Abstract: Using the data on all live births (∼400,000) and criteria pollutants from the Chicago Metropolitan Statistical Area (MSA) between 2000 and 2004, this paper empirically demonstrates how mismatches in the spatiotemporal scales of health and air pollution data can result in inconsistency and uncertainty in the linkages between air pollution and birth outcomes. This paper suggests that the risks of low birth weight associated with air pollution exposure changes significantly as the distance interval (around the monitoring stations) used for exposure estimation changes. For example, when the analysis was restricted within 3 miles distance of the monitoring stations the odds of LBW (births <2500 g) increased by a factor of 1.045 (±0.0285 95% CI) with a unit increase in the average daily exposure to PM10 (in μg m−3) during the gestation period; the value dropped to 1.028 when the analysis was restricted within 6 miles distance of air pollution monitoring stations. The effect of PM10 exposure on LBW became null when controlled for confounders. But PM2.5 exposure showed a significant association with low birth weight when controlled for confounders. These results must be interpreted with caution, because the distance to monitoring station does not influence the risks of adverse birth outcomes, but uncertainty in exposure increases with the increase in distance from the monitoring stations, especially for coarse particles such as PM10 that settle with gravity within short distance and time interval. The results of this paper have important implications for the research design of environmental epidemiological studies, and the way air pollution (and potentially other environmental) and health data are collocated to compute exposure. While this paper challenges the findings of pervious epidemiological studies that have relied on coarse resolution air pollution data (such as county level aggregated data), the paper also calls for time-space resolved estimate of air pollution to minimize uncertainty in exposure estimation. [Copyright &y& Elsevier]

Concerns about medical exposure to ionizing radiation have become heightened in recent years as a result of rapid growth in procedure volumes and the high radiation doses incurred from some procedures. This paper summarizes the evidence base undergirding concerns about radiation exposure in cardiac imaging. After classifying radiation effects, explaining terminology used to quantify the radiation received by patients, and describing typical doses from cardiac imaging procedures, this paper will address the major epidemiological studies having bearing on radiation effects at doses comparable to those received by patients undergoing cardiac imaging. These include studies of atomic bomb survivors, nuclear industry workers, and children exposed in utero to x-rays, all of which have evidenced increased cancer risks at low doses. Additional higher-dose epidemiological studies of cohorts exposed to radiation in the context of medical treatment are described and found to be generally compatible with these cardiac dose–level studies, albeit with exceptions. Using risk projection models developed by the U.S. National Academies that incorporate these data and reflect several evidence-based assumptions, cancer risk from cardiac imaging can be estimated and compared with the benefits from imaging. Several ongoing epidemiological studies will provide better understanding of radiation-associated cancer risks. [ABSTRACT FROM AUTHOR]

Abstract: The aim of this paper is to demonstrate how temporal reasoning techniques can assist in the analysis of epidemiological data to determine the possibility of contagion among humans of the avian influenza virus (H5N1). To do so, we use a documented real case of a possible infection of H5N1 between humans, and formally substantiate the medical evidence. The need to represent and manage time is implicit in many reasoning processes. This is particularly evident in the field of medicine, in which the temporal distribution of symptoms is crucial for understanding the evolution of diseases. Many models have been proposed for time representation and management. In this paper we propose the use of a generic temporal reasoner, FuzzyTIME, which is able to represent both points and intervals, as well as relations, including quantitative and qualitative ones, through a specifically designed language. Moreover, being based on FTCN (fuzzy temporal constraint networks), the proposed model also allows us to capture both temporal imprecision and uncertainty present in complex domains as the medical one. Nevertheless, the reasoner has been design to have an easy integration with any knowledge based system that need this kind of representation and reasoning. To perform the analysis of the real case selected, we first clearly identified the temporal information in each of the timelines of the subjects under study. Subsequently, this information was formalized in the language provided by FuzzyTIME. After verifying the temporal consistency of such information in every subject, we proceeded to check the temporal consistency of such information with the generic clinical symptoms of evolution of avian influenza. Finally, the queries which were modeled allowed us to determine the temporal possibility of infection between human of the H5N1 virus. First, we demonstrate the usefulness of temporal reasoning in the modeling and analysis of epidemiological data, showing how the FTCN formalism and the proposed language is sufficiently expressive to represent qualitative and quantitative temporal relations as well as the temporal imprecision implicit in certain expressions extracted from the real case selected. Moreover, the temporal reasoner permits efficient determination of the temporal consistency of the medical evidence concerning the possibility of infection of H5N1 between humans. [Copyright &y& Elsevier]

Abstract: This is the third article related to a review of the literature based on data from national cystic fibrosis (CF) patient registries up to June 2008 and covering a total of 115 published studies. It focuses on several topics: CF incidence, genotype/phenotype correlation, microbiology, pregnancy/paternity, clinical complications, lung transplantation, and others. Seventy seven papers meeting the inclusion criteria were found to be related to the topics listed above. Another seven studies, already evaluated in previous papers of this series, were recalled for specific topics. Incidence is described by several studies, results being quite different from one country to another and quite inhomogeneous among regions within the same country. Studies on genetics address the genotype/phenotype correlation and look for a predictive value of CFTR mutations in terms of clinical outcome, with controversial results. Papers on microbiology describe the clinical relevance of different pathogens and their role in the progress of CF lung disease. A few articles give information on the features of CF women undergoing a pregnancy and try to identify the ones associated with a better outcome. Studies on clinical complications discuss prevalence and the role of haemoptysis, pneumothorax, CF related diabetes, ABPA and cancer. Papers on lung transplantation focus on models able to improve the selection criteria for transplantation candidates and the factors linked to post transplantation survival. Finally, several studies deal with a number of interesting topics related to CF epidemiology: clinical trial methodology, quality of care comparison among countries and centers, relationship between diagnosis and age/gender, and evaluation of pharmacological therapy. On the whole, CF Registries have already contributed to important advances in the knowledge of the natural history of CF, establishing the foundations for future improvement in CF research and care. [Copyright &y& Elsevier]

Early repolarization, involving ST-segment elevation and, sometimes, prominent J waves at the QRS-ST junction, has been considered a normal electrocardiographic variant for over 60 years. A growing number of case reports and case-control studies indicate that in some instances, early repolarization patterns are associated with increased risk of idiopathic ventricular fibrillation. Epidemiological evidence indicates a dose effect for the risk of cardiac and sudden death with the extent of J-point elevation. This paper reviews present knowledge regarding the epidemiology, presentation, therapeutic response, and mechanisms characteristic of early repolarization. We highlight major unanswered questions relating to our limited ability to determine which individuals with this common electrocardiographic variant are at risk for sudden death, our incomplete understanding of underlying mechanisms, the inadequate information regarding genetic determinants and therapeutic responses, and the unclear relationship between early repolarization and other conditions involving accelerated repolarization and sudden arrhythmic death such as Brugada and short-QT syndromes. This review paper intends to inform the practicing physician about important clinical issues and to stimulate investigators to address the many unresolved questions in this rapidly evolving field. [ABSTRACT FROM AUTHOR]

Systematic reviews and meta-analyses are increasingly popular study designs in clinical research. A systematic review is a summary of the medical literature that uses explicit and reproducible methods for searching the literature and critical appraisal of individual studies; in contrast, a meta-analysis is a mathematical synthesis of the results of these individual studies. These study designs can be useful tools for summarizing the increasing amount of knowledge that is gained from scientific papers on a certain topic. In addition, combining individual studies in a meta-analysis increases statistical power, resulting in more precise effect estimates. Although the specific methodology of systematic reviews includes steps to minimize bias in all stages of the process, investigators should be aware of potential biases such as poor quality of included studies, heterogeneity between studies, and the presence of publication and outcome reporting bias. This paper explains how systematic reviews and meta-analyses should be performed and how to interpret and implement their results. In addition, we discuss when meta-analyses are useful and when they are not. [ABSTRACT FROM AUTHOR]

In this paper we examine whether discourses of tropicality were affected by paradigm shifts in Western thinking about medicine. If tropicalist thinking reflects latent Western assumptions about the 'Other', tropicalism should persist through major shifts in Western thought. Here we explore whether or not such persistence is evident in representations in the scientific literature of mosquito-borne diseases on the Indian Ocean island of Réunion and where discrete epidemics occurred before, during and after a paradigm shift in Western thinking about disease causation. Late in the 19th Century, miasma theory (epidemics caused by unhealthy air) was replaced by microbial theory (epidemics caused by transmission of microbes) as the dominant scientific understanding of disease causation. We analyse representations of mosquito-borne epidemics in the contemporaneous scientific literature about Réunion for evidence of both tropicalism and a shift in the scientific paradigm. In pre-microbial representations, the unhealthy tropical environments thought to be responsible for miasmatic disease transmission are associated predominantly with the non-white population; in microbial representations non-whites are directly blamed for the spread of tropical infections. The paper argues that the persistence of tropicalist thinking through a major paradigm shift in the Western understanding of disease causation supports Said's (1979) contention that 'Othering' is a generalisable ahistorical phenomenon, and discusses issues of economic exigency that may have supported an ongoing tropicalist influence on public health practice in French overseas departments. [ABSTRACT FROM AUTHOR]

Abstract: Fossil fuel energy use in heating and cooling buildings is considered to be a major contributor to observed climate change effects, so there is an environmental imperative to reduce energy use in buildings. We should also improve buildings’ energy efficiency on health grounds. Climate change is predicted to produce more frequent extreme weather events, while epidemiological evidence indicates relationships between ambient temperature and ill health. This points to the need for addressing both climate change itself and the way buildings mediate outdoor conditions, for the sake of vulnerable occupants. The UK government requires evidence in support of policy-making concerning energy use in buildings and consequences for health. This paper reviews epidemiological research to illustrate problems associated with measuring the direct health impact of indoor temperatures, for which evidence remains limited. Conventionally, temperature-related health effects are discussed in terms of seasonal excess deaths. The paper goes on to describe a population-based study in London that considers morbidity rather than mortality. A new methodology is developed that links the risk of cold homes with excess winter hospital episodes, demonstrating its potential for identifying small areas for priority action on improving domestic energy efficiency in terms of health as well as the environment. [Copyright &y& Elsevier]

Epidemiologic studies directly contribute data on risk (or benefit) in humans as the investigated species, and in the full food intake range normally encountered by humans. This paper starts with introducing the epidemiologic approach, followed by a discussion of perceived differences between toxicological and epidemiologic risk assessment. Areas of contribution of epidemiology to the risk assessment process are identified, and ideas for tailoring epidemiologic studies to the risk assessment procedures are suggested, dealing with data collection, analyses and reporting of both existing and new epidemiologic studies. The dietary habits and subsequent disease occurrence of over three million people are currently under observation worldwide in cohort studies, offering great potential for use in risk assessment. The use of biomarkers and data on genetic susceptibility are discussed. The paper describes a scheme to classify epidemiologic studies for use in risk assessment, and deals with combining evidence from multiple studies. Using a matrix approach, the potential contribution to each of the steps in the risk assessment process is evaluated for categories of food substances. The contribution to risk assessment of specific food substances depends on the quality of the exposure information. Strengths and weaknesses are summarized. It is concluded that epidemiology can contribute significantly to hazard identification, hazard characterisation and exposure assessment. [Copyright &y& Elsevier]

Very recently, Zika virus (ZIKV) has gained a medical importance following the large-scale epidemics in South Pacific and Latin America. This paper reviews information on the epidemiology and clinical features of Zika disease with a particular emphasis on the host-virus interactions that contribute to the pathogenicity of ZIKV in humans. [ABSTRACT FROM AUTHOR]

Modelling, pollution monitoring and epidemiological studies all have a role to play in developing effective policies to improve air quality and human health. Epidemiological studies have shown that of particular importance are the effects of fine particulate matter, PM 10 and PM 2.5 which can penetrate into human lungs. At present it is not clear which components of PM are responsible for health effects although toxicological studies have identified several potential factors. Hence, based on WHO guidance, current legislation has focused on the total mass, with the EC setting limit values on total PM 10 , followed by target reductions for population exposure to PM 2.5 in urban agglomerations. Trends in measured concentrations at selected urban monitoring stations are required as evidence for achievement of these reductions. This paper addresses these issues at the borough level in London using the integrated assessment model UKIAM, developed originally for application at the national scale, with illustrations comparing abatement of two contrasting sources – domestic combustion and road transport. The former, dominated by natural gas generating NO X emissions, contributes to longer range secondary PM formation extending beyond the city. The latter is an important source of black carbon as a primary pollutant causing local exposure, as well as NO X . WHO data is used in relation to impacts of particle concentrations by mass, and response functions for black carbon are taken from the literature. The results show that from a city perspective there are enhanced benefits from reducing the road transport emissions, especially with regard to potential toxicity of black carbon. The scenarios modelled also highlight the spatial variations of benefits across London, and illustrate deviations from trends as represented by limited monitoring data from the different boroughs, together with the influence upon exposure of mobile population within the city. [ABSTRACT FROM AUTHOR]

Purpose The purpose of this paper is to review exposure assessment issues that need to be addressed in designing and interpreting epidemiology studies of phthalates, a class of chemicals commonly used in consumer and personal care products. Specific issues include population trends in exposure, temporal reliability of a urinary metabolite measurement, and how well a single urine sample may represent longer-term exposure. The focus of this review is on seven specific phthalates: diethyl phthalate (DEP); di-n-butyl phthalate (DBP); diisobutyl phthalate (DiBP); butyl benzyl phthalate (BBzP); di(2-ethylhexyl) phthalate (DEHP); diisononyl phthalate (DiNP); and diisodecyl phthalate (DiDP). Methods Comprehensive literature search using multiple search strategies. Results Since 2001, declines in population exposure to DEP, BBzP, DBP, and DEHP have been reported in the United States and Germany, but DEHP exposure has increased in China. Although the half-lives of various phthalate metabolites are relatively short (3 to 18 h), the intraclass correlation coefficients (ICCs) for phthalate metabolites, based on spot and first morning urine samples collected over a week to several months, range from weak to moderate, with a tendency toward higher ICCs (greater temporal stability) for metabolites of the shorter-chained (DEP, DBP, DiBP and BBzP, ICCs generally 0.3 to 0.6) compared with those of the longer-chained (DEHP, DiNP, DiDP, ICCs generally 0.1 to 0.3) phthalates. Additional research on optimal approaches to addressing the issue of urine dilution in studies of associations between biomarkers and different type of health effects is needed. Conclusions In conclusion, the measurement of urinary metabolite concentrations in urine could serve as a valuable approach to estimating exposure to phthalates in environmental epidemiology studies. Careful consideration of the strengths and limitations of this approach when interpreting study results is required. [ABSTRACT FROM AUTHOR]

Background A number of studies have been conducted to investigate associations between genetic polymorphisms in interleukin-17 (IL-17) pathway and the risk of gastrointestinal diseases. Results, however, have been inconclusive. We aimed to evaluate these associations through a meta-analysis. Methods We searched electronic databases (PubMed, Embase, Web of Science, CBM and CNKI) to identify papers, published before October 2014, on associations between polymorphisms in the IL-17 pathway genes (rs2275913, rs763780, rs3748067, rs3819025, rs9382084, rs12203582 and rs8193036) and the risk of gastrointestinal diseases. We estimated the strength of candidate associations through calculating pooled odds ratios (ORs) and 95% confidence intervals (CIs). A test of heterogeneity, a false-positive report probability (FPRP) test, sensitivity analyses and examination for bias were further conducted to evaluate cumulative evidence of these associations. Results We identified 25 eligible case–control studies retrieved from 16 articles involved in a total of 4507 cases and 5733 controls. Of them, IL-17 (−197G/A) polymorphism (rs2275913) was statistically significantly associated with risk of gastrointestinal diseases, especially for gastrointestinal malignancy and gastroduodenal diseases. Based on heterogeneity ( P < 0.05) and FPRP ( P < 0.2) identified in this study, we graded cumulative epidemiological evidence of an association with gastrointestinal diseases for this polymorphism. However, IL-17 (7488T/C) polymorphism (rs763780) did not show significant associations with gastrointestinal diseases either individually or overall ( P > 0.05). Conclusion Our study provides moderate evidence that IL-17 (− 197G/A) polymorphism may be a potential risk factor for gastrointestinal diseases, particularly for malignancy. Further validation of this association in a large homogeneous study is warranted. [ABSTRACT FROM AUTHOR]

Q fever epidemiological investigations of the likely sources of contamination may involve Coxiella burnetii MLVA for direct and rapid typing from clinical samples. However, little information is available with regards to PCR amplification failures in C. burnetii MLVA typing. This paper focuses on difficulties encountered with MLVA loci that may impact the interpretation of MLVA data and shows that some loci may constitute hotspots for mutational events. MLVA genotyping, using 17 different loci, was used on vaginal swabs (VS) from clinically infected animals as described elsewhere (Chmielewski et al., 2009). Amplicons of interest were sequenced and identified using the BLAST software by comparison with sequences available in GenBank. All VS samples produced MLVA patterns. However, amplification failures or unexpected sizes amplicons (>to 1.5 kbp), making the interpretation of MLVA complicated, were also observed. Sequencing of these amplicons revealed the presence of IS 1111 element insertion. In this C. burnetii MLVA study some difficulties encountered with genotyping are highlighted and the role of IS 1111 element in genome plasticity is confirmed. Finally, the need for the selection of a set of VNTRs for an efficient MLVA scheme and the question of standardization and harmonization for comparable MLVA typing data are raised again. [ABSTRACT FROM AUTHOR]

It has been well documented that air pollution adversely affects health, and epidemiological pollution-health studies utilise pollution data from automatic monitors. However, these automatic monitors are small in number and hence spatially sparse, which does not allow an accurate representation of the spatial variation in pollution concentrations required for these epidemiological health studies. Nitrogen dioxide (NO 2 ) diffusion tubes are also used to measure concentrations, and due to their lower cost compared to automatic monitors are much more prevalent. However, even combining both data sets still does not provide sufficient spatial coverage of NO 2 for epidemiological studies, and modelled concentrations on a regular grid from atmospheric dispersion models are also available. This paper proposes the first modelling approach to using all three sources of NO 2 data to make fine scale spatial predictions for use in epidemiological health studies. We propose a geostatistical fusion model that regresses combined NO 2 concentrations from both automatic monitors and diffusion tubes against modelled NO 2 concentrations from an atmospheric dispersion model in order to predict fine scale NO 2 concentrations across our West Central Scotland study region. Our model exhibits a 47% improvement in fine scale spatial prediction of NO 2 compared to using the automatic monitors alone, and we use it to predict NO 2 concentrations across West Central Scotland in 2006. [ABSTRACT FROM AUTHOR]

This paper presents a two stage SIS epidemiological model in animal population with bovine tuberculosis (BTB) in African buffalo as a guiding example. The proposed model is rigorously analyzed. The analysis reveals that the model exhibits the phenomenon of backward bifurcation, where a stable disease-free equilibrium (DFE) coexists with a stable endemic equilibrium (EE) when the associated reproduction number ( R v ) is less than unity. It is shown under two special cases of the presented model, that this phenomenon of backward bifurcation does not arise depending on vaccination coverage and efficacy of vaccine. Numerical simulations of the model show that, the use of an imperfect vaccine can lead to effective control of the disease if the vaccination coverage and the efficacy of vaccine are high enough. [ABSTRACT FROM AUTHOR]

The purpose of this paper is to propose new indicators of the dynamics of infectious disease spread in stochastic epidemic models, including both global system-oriented descriptors (e.g. the final size measured as the number of individuals infected on a least one occasion during an outbreak) and individual-oriented descriptors (e.g. the time to reach an individual run of infections). We focus on birth-and-death models and the basic SIR epidemic model but the methodology remains valid for other nonlinear stochastic epidemic models. The theory is illustrated by numerical experiments which demonstrate that the proposed behavioral indicators can be applied efficiently. [ABSTRACT FROM AUTHOR]