No temporal trends in the prevalence of atypical scrapie in British sheep, 2002–2006

<p>Abstract</p> <p>Background</p> <p>So-called atypical scrapie was first identified in Great Britain (GB) in 2002 following the introduction of wide-scale scrapie surveillance. In particular, abattoir and fallen stock surveys have been carried out in GB since 2002, with a total of 147 atypical positives identified by the end of 2006. The results of these surveys provide data with which to assess temporal trends in the prevalence of atypical scrapie in sheep in Great Britain between 2002 and 2006.</p> <p>Results</p> <p>Using the results of abattoir and fallen stock surveys, the prevalence of atypical scrapie (percentage of samples positive) was estimated. The prevalence in the abattoir and fallen stock surveys, for all years combined, was 0.09% (95% confidence interval (CI): 0.08%–0.11%) and 0.07% (95% CI: 0.05%–0.11%), respectively. There were no significant temporal trends in either survey. Comparing the surveys' results, there were no significant differences in annual prevalence or the prevalence within <it>PrP </it>genotypes. For the abattoir survey, the <it>PrP </it>genotype with the highest prevalence was AHQ/AHQ, which was significantly higher than all other genotypes, except ARR/AHQ, AHQ/ARH and ARH/ARQ.</p> <p>Conclusion</p> <p>The estimated prevalence of atypical scrapie was similar in both the abattoir and fallen stock surveys. Our results indicate there was no significant temporal trend in prevalence, adding to evidence that this atypical form of scrapie may be a sporadic condition or, if it is infectious, that the force of infection is very low.</p

Evidence for more cost-effective surveillance options for bovine spongiform encephalopathy (bse) and scrapie in Great Britain

Transmissible spongiform encephalopathies (TSEs) are an important public health concern. Since the emergence of bovine spongiform encephalopathy (BSE) during the 1980s and its link with human Creutzfeldt- Jakob disease, active surveillance has been a key element of the European Union’s TSE control strategy. Success of this strategy means that now, very few cases are detected compared with the number of animals tested. Refining surveillance strategies would enable resources to be redirected towards other public health priorities. Cost-effectiveness analysis was performed on several alternative strategies involving reducing the number of animals tested for BSE and scrapie in Great Britain and, for scrapie, varying the ratio of sheep sampled in the abattoir to fallen stock (which died on the farm). The most cost-effective strategy modelled for BSE involved reducing the proportion of fallen stock tested from 100% to 75%, producing a cost saving of ca GBP 700,000 per annum. If 50% of fallen stock were tested, a saving of ca GBP 1.4 million per annum could be achieved. However, these reductions are predicted to increase the period before surveillance can detect an outbreak. For scrapie, reducing the proportion of abattoir samples was the most costeffective strategy modelled, with limited impact on surveillance effectiveness

New methodologies for the estimation of population vulnerability to diseases: a case study of Lassa fever and Ebola in Nigeria and Sierra Leone.

Public health practitioners require measures to evaluate how vulnerable populations are to diseases, especially for zoonoses (i.e. diseases transmitted from animals to humans) given their pandemic potential. These measures would be valuable to support strategic and operational decision making and allocation of resources. Although vulnerability is well defined for natural hazards, for public health threats the concept remains undetermined. Here, we develop new methodologies to: (i) quantify the impact of zoonotic diseases and the capacity of countries to cope with these diseases, and (ii) combine these two measures (impact and capacity) into one overall vulnerability indicator. The adaptive capacity is calculated from estimations of disease mortality, although the method can be adapted for diseases with no or low mortality but high morbidity. As an example, we focused on the vulnerability of Nigeria and Sierra Leone to Lassa Fever and Ebola. We develop a simple analytical form that can be used to estimate vulnerability scores for different spatial units of interest, e.g. countries or regions. We show how some populations can be highly vulnerable despite low impact threats. We finally outline future research to more comprehensively inform vulnerability with the incorporation of relevant factors depicting local heterogeneities (e.g. bio-physical and socio-economic factors). This article is part of the theme issue 'Modelling infectious disease outbreaks in humans, animals and plants: epidemic forecasting and control'. This theme issue is linked with the earlier issue 'Modelling infectious disease outbreaks in humans, animals and plants: approaches and important themes'.FRSF Pump Prime Gran

Spatial distribution of the active surveillance of sheep scrapie in Great Britain: an exploratory analysis

<p>Abstract</p> <p>Background</p> <p>This paper explores the spatial distribution of sampling within the active surveillance of sheep scrapie in Great Britain. We investigated the geographic distribution of the birth holdings of sheep sampled for scrapie during 2002 – 2005, including samples taken in abattoir surveys (c. 83,100) and from sheep that died in the field ("fallen stock", c. 14,600). We mapped the birth holdings by county and calculated the sampling rate, defined as the proportion of the holdings in each county sampled by the surveys. The Moran index was used to estimate the global spatial autocorrelation across Great Britain. The contributions of each county to the global Moran index were analysed by a local indicator of spatial autocorrelation (LISA).</p> <p>Results</p> <p>The sampling rate differed among counties in both surveys, which affected the distribution of detected cases of scrapie. Within each survey, the county sampling rates in different years were positively correlated during 2002–2005, with the abattoir survey being more strongly autocorrelated through time than the fallen stock survey. In the abattoir survey, spatial indices indicated that sampling rates in neighbouring counties tended to be similar, with few significant contrasts. Sampling rates were strongly correlated with sheep density, being highest in Wales, Southwest England and Northern England. This relationship with sheep density accounted for over 80% of the variation in sampling rate among counties. In the fallen stock survey, sampling rates in neighbouring counties tended to be different, with more statistically significant contrasts. The fallen stock survey also included a larger proportion of holdings providing many samples.</p> <p>Conclusion</p> <p>Sampling will continue to be uneven unless action is taken to make it more uniform, if more uniform sampling becomes a target. Alternatively, analyses of scrapie occurrence in these datasets can take account of the distribution of sampling. Combining the surveys only partially reduces uneven sampling. Adjusting the distribution of sampling between abattoirs to reduce the bias in favour of regions with high sheep densities could probably achieve more even sampling. However, any adjustment of sampling should take account of the current understanding of the distribution of scrapie cases, which will be improved by further analysis of this dataset.</p

Participation in One Health Networks and Involvement in the COVID-19 Pandemic Response: A Global Study

The COVID-19 pandemic exemplifies a One Health issue at the intersection of human, animal, and environmental health that requires collaboration across sectors to manage it successfully. The global One Health community includes professionals working in many different fields including human medicine, veterinary medicine, public health, ecosystem health, and, increasingly, social sciences. The aims of this cross-sectional study were to describe the involvement of the global One Health community in COVID-19 pandemic response activities. One Health networks (OHNs) have formed globally to serve professionals with common interests in collaborative approaches. We assessed the potential association between being part of an OHN and involvement in COVID-19 response activities. Data were collected in July-August 2020 using an online questionnaire that addressed work characteristics, perceived connection to OHNs, involvement in COVID-19 pandemic response activities, and barriers and facilitators to the involvement. The sample included 1,050 respondents from 94 countries across a range of organizations and work sectors including, but not restricted to, those typically associated with a One Health approach. Sixty-four percent of survey respondents indicated involvement in pandemic response activities. Being part of an OHN was positively associated with being involved in the COVID-19 response (odds ratio: 1.8, 95% confidence interval: 1.3–2.4). Lack of opportunities was a commonly reported barrier to involvement globally, with lack of funding the largest barrier in the WHO African region. This insight into diverse workforce involvement in the pandemic helps fill a gap in the global health workforce and public health education literature. An expanded understanding of the perceived roles and value of OHNs can inform targeted interventions to improve public health education and workforce capacity to prepare for and respond to public health emergencies

Integration of animal health and public health surveillance sources to exhaustively inform the risk of zoonosis: An application to echinococcosis in Rio Negro, Argentina

Fil: Lawson, Andrew. Medical University of South Carolina, Charleston, South Carolina, United States of America.Fil: Boaz, Robertr. Medical University of South Carolina, Charleston, South Carolina, United States of America.Fil: Corberan Vallet, Ana. University of Valencia, Valencia, Spain.Fil: Arezo, Marcos. Ministerio de Salud, Viedma, Rio Negro, Argentina.Fil: Larrieu, Edmundo. Universidad Nacional de Río Negro, Río Negro, Argentina.Fil: Vigilato, Marcos. Organización Panamericana de la Salud, San Salvador, El Salvador.Fil: Del Rio, Vilas. Centre for Universal Health,Chatham House, London, United Kingdom.The analysis of zoonotic disease risk requires the consideration of both human and animal geo-referenced disease incidence data. Here we show an application of joint Bayesian analyses to the study of echinococcosis granulosus (EG) in the province of Rio Negro, Argentina. We focus on merging passive and active surveillance data sources of animal and human EG cases using joint Bayesian spatial and spatio-temporal models. While similar spatial clustering and temporal trending was apparent, there appears to be limited lagged dependence between animal and human outcomes. Beyond the data quality issues relating to missingness at different times, we were able to identify relations between dog and human data and the highest 'at risk' areas for echinococcosis within the province.El análisis del riesgo de enfermedades zoonóticas requiere la consideración de datos de incidencia de enfermedades georreferenciados tanto en humanos como en animales. Aquí mostramos una aplicación de análisis bayesianos conjuntos al estudio de la equinococosis granulosus (EG) en la provincia de Río Negro, Argentina. Nos enfocamos en fusionar fuentes de datos de vigilancia pasiva y activa de casos de EG animales y humanos utilizando modelos espaciales y espacio-temporales conjuntos bayesianos. Si bien fue evidente una agrupación espacial y una tendencia temporal similares, parece haber una dependencia rezagada limitada entre los resultados animales y humanos. Más allá de los problemas de calidad de los datos relacionados con la falta de datos en diferentes momentos, pudimos identificar las relaciones entre los datos de perros y humanos y las áreas de mayor 'riesgo' de equinococosis dentro de la provincia

Explaining the heterogeneous scrapie surveillance figures across Europe: a meta-regression approach

<p>Abstract</p> <p>Background</p> <p>Two annual surveys, the abattoir and the fallen stock, monitor the presence of scrapie across Europe. A simple comparison between the prevalence estimates in different countries reveals that, in 2003, the abattoir survey appears to detect more scrapie in some countries. This is contrary to evidence suggesting the greater ability of the fallen stock survey to detect the disease. We applied meta-analysis techniques to study this apparent heterogeneity in the behaviour of the surveys across Europe. Furthermore, we conducted a meta-regression analysis to assess the effect of country-specific characteristics on the variability. We have chosen the odds ratios between the two surveys to inform the underlying relationship between them and to allow comparisons between the countries under the meta-regression framework. Baseline risks, those of the slaughtered populations across Europe, and country-specific covariates, available from the European Commission Report, were inputted in the model to explain the heterogeneity.</p> <p>Results</p> <p>Our results show the presence of significant heterogeneity in the odds ratios between countries and no reduction in the variability after adjustment for the different risks in the baseline populations. Three countries contributed the most to the overall heterogeneity: Germany, Ireland and The Netherlands. The inclusion of country-specific covariates did not, in general, reduce the variability except for one variable: the proportion of the total adult sheep population sampled as fallen stock by each country. A large residual heterogeneity remained in the model indicating the presence of substantial effect variability between countries.</p> <p>Conclusion</p> <p>The meta-analysis approach was useful to assess the level of heterogeneity in the implementation of the surveys and to explore the reasons for the variation between countries.</p

Towards integrated surveillance of zoonoses : spatiotemporal joint modeling of rodent population data and human tularemia cases in Finland

Abstract Background There are an increasing number of geo-coded information streams available which could improve public health surveillance accuracy and efficiency when properly integrated. Specifically, for zoonotic diseases, knowledge of spatial and temporal patterns of animal host distribution can be used to raise awareness of human risk and enhance early prediction accuracy of human incidence. Methods To this end, we develop a spatiotemporal joint modeling framework to integrate human case data and animal host data to offer a modeling alternative for combining multiple surveillance data streams in a novel way. A case study is provided of spatiotemporal modeling of human tularemia incidence and rodent population data from Finnish health care districts during years 1995–2012. Results Spatial and temporal information of rodent abundance was shown to be useful in predicting human cases and in improving tularemia risk estimates in 40 and 75% of health care districts, respectively. The human relative risk estimates’ standard deviation with rodent’s information incorporated are smaller than those from the model that has only human incidence. Conclusions These results support the integration of rodent population variables to reduce the uncertainty of tularemia risk estimates. However, more information on several covariates such as environmental, behavioral, and socio-economic factors can be investigated further to deeper understand the zoonotic relationship

Pengembangan Lembar Kegiatan Siswa (Lks) Kimia Sma/ma Berbasis Learning Cycle 5e Pada Materi Laju Reaksi

Penelitian ini bertujuan untuk: (1) mengembangkan Lembar Kegiatan Siswa (LKS) berbasis Learning Cycle 5E, (2) mengetahui kualitas Lembar Kegiatan Siswa (LKS) berbasis Learning Cycle 5E, (3) mengetahui efektivitas Lembar Kegiatan Siswa (LKS) berbasis Learning Cycle 5E untuk meningkatkan prestasi belajar siswa. Penelitian dan pengembangan Lembar Kegiatan Siswa (LKS) berbasis Learning Cycle 5E menggunakan prosedur penelitian dan pengembangan dari Borg and Gall yang disederhanakan menjadi 9 tahapan yaitu: (1) penelitian pendahuluan dan pengumpulan data, (2) perencanaan, (3) pengembangan produk, (4) uji coba lapangan awal, (5) revisi produk awal, (6) uji coba pelaksanaan lapangan, (7) penyempurnaan produk hasil uji coba lapangan, (8) uji coba pelaksanaan lapangan, (9) penyempurnaan produk akhir. Analisis Data yang digunakan adalah analisis deskriptif kualitatif. Hasil Penelitian menunjukkan: (1) telah berhasil dikembangkan Lembar Kegiatan Siswa (LKS) berbasis Learning Cycle 5E pada materi Laju Reaksi yang dilakukan berdasarkan tahapan penelitian dan pengembangan R&amp;D yang terdiri dari 9 tahapan, (2) kualitas Lembar Kegiatan Siswa (LKS) berbasis Learning Cycle 5E pada materi Laju Reaksi memiliki kualitas sangat baik pada aspek komponen kelayakan isi, bahasa, penyajian dan kegrafisan dengan persentase sebesar 84,06% berdasarkan penilaian siswa dan 90,88% berdasarkan penilaian guru, (hasil uji efektivitas pada aspek pengetahuan terdapat perbedaan antara kelas eksperimen (pembelajaran dengan menggunakan model Learning Cycle 5E disertai Lembar Kegiatan Siswa (LKS) berbasis Learning Cycle 5E ) dan kelas baseline (pembelajaran dengan menggunakan model pembelajaran Learning Cycle 5E tanpa disertai Lembar Kegiatan Siswa (LKS) berbasis Learning Cycle 5E ),, sedangkan pada aspek sikap dan keterampilan tidak terdapat perbedaan

What works, and how can we make it fairer? Developing new guidance for contact tracing

As countries struggle to contain COVID outbreaks, contact tracing continues to be vital. Researchers from the Thai Ministry of Public Health, National University of Singapore, World Health Organisation and LSE explain how they have developed a new approach to assessing its effectiveness and share some early findings from Thailand