Epidemiological investigations of footrot in the Norwegian sheep population

Footrot is a contagious disease where Dichelobacter nodosus, a Gram negative bacterium, is the necessary transmitting agent. The disease mainly affects small ruminants. The clinical signs range from mild inflammation in the interdigital space to under-running of the claw horn which causes welfare problems and economic losses. Footrot was detected in Norway in 2008 for the first time since 1948. A surveillance programme was initiated in 2008 which was followed by an elimination programme in 2009. From 2008 to 2012, severe footrot was only diagnosed in the county of Rogaland, but in 2013 the disease was also diagnosed in the county of Aust-Agder. Epidemiological and bacteriological investigations have indicated that the disease was introduced to Norway in 2005 through import of sheep from Denmark.Fotråte er en smittsom infeksjonssykdom der Dichelobacter nodosus, en Gram negativ bakterie, blir betegnet som det viktigste agenset for infeksjonen. Sykdommen berører hovedsakelig småfe. De kliniske tegnene varierer fra mild betennelsesreaksjon i klauvspalten til underminering av klauvkapselen. Dette gir velferdsproblemer og økonomiske tap. Fotråte ble oppdaget i Norge i 2008 for første gang siden 1948. Et overvåkningsprogram ble initiert i 2008 og ble etterfulgt av et bekjempelsesprogram i 2009. Fra 2008 til 2012 ble alvorlig fotråte kun funnet i Rogaland fylke, men i 2013 ble sykdommen også oppdaget i Aust-Agder fylke. Epidemiologiske og bakteriologiske undersøkelser tyder på at sykdommen ble introdusert til Norge i 2005 via import av sau fra Danmark

Epidemiological investigations of footrot in the Norwegian sheep population

Footrot is a contagious disease where Dichelobacter nodosus, a Gram negative bacterium, is the necessary transmitting agent. The disease mainly affects small ruminants. The clinical signs range from mild inflammation in the interdigital space to under-running of the claw horn which causes welfare problems and economic losses. Footrot was detected in Norway in 2008 for the first time since 1948. A surveillance programme was initiated in 2008 which was followed by an elimination programme in 2009. From 2008 to 2012, severe footrot was only diagnosed in the county of Rogaland, but in 2013 the disease was also diagnosed in the county of Aust-Agder. Epidemiological and bacteriological investigations have indicated that the disease was introduced to Norway in 2005 through import of sheep from Denmark

Epidemiological and Economic Evaluation of Alternative On-Farm Management Scenarios for Ovine Footrot in Switzerland

Footrot is a multifactorial infectious disease mostly affecting sheep, caused by the bacteria Dichelobacter nodosus. It causes painful feet lesions resulting in animal welfare issues, weight loss, and reduced wool production, which leads to a considerable economic burden in animal production. In Switzerland, the disease is endemic and mandatory coordinated control programs exist only in some parts of the country. This study aimed to compare two nationwide control strategies and a no intervention scenario with the current situation, and to quantify their net economic effect. This was done by sequential application of a maximum entropy model (MEM), epidemiological simulation, and calculation of net economic effect using the net present value method. Building upon data from a questionnaire, the MEM revealed a nationwide footrot prevalence of 40.2%. Regional prevalence values were used as inputs for the epidemiological model. Under the application of the nationwide coordinated control program without (scenario B) and with (scenario C) improved diagnostics [polymerase chain reaction (PCR) test], the Swiss-wide prevalence decreased within 10 years to 14 and 5%, respectively. Contrary, an increase to 48% prevalence was observed when terminating the current control strategies (scenario D). Management costs included labor and material costs. Management benefits included reduction of fattening time and improved animal welfare, which is valued by Swiss consumers and therefore reduces societal costs. The net economic effect of the alternative scenarios B and C was positive, the one of scenario D was negative and over a period of 17 years quantified at CHF 422.3, 538.3, and −172.3 million (1 CHF = 1.040 US$), respectively. This implies that a systematic Swiss-wide management program under the application of the PCR diagnostic test is the most recommendable strategy for a cost-effective control of footrot in Switzerland

Detecting flu outbreaks based on spatiotemporal information from urban systems - designing a novel study

This paper explores the application of real-time spatial information from urban transport systems to understand the outbreak, severity and spread of seasonal flu epidemics from a spatial perspective. We believe that combining travel data with epidemiological data will be the first step to develop a tool to predict future epidemics and to better understand the effects that these outbreaks have on societal functions over time. Real-time data-streams provide a powerful, yet underutilised tool when it comes to monitoring and detecting changes to the daily behaviour of inhabitants. In this paper, we describe and discuss the design of the geospatial project, in which we will draw upon data sources available from the Norwegian cities of Oslo and Bergen. Historical datasets from public transport and road traffic will serve as an initial indication of whether changes in daily transport patterns corresponds to seasonal flu data. It is expected that changes in daily transportation habits corresponds to swings in daily and weekly flu activity and that these differences can be measured through geostatistical analysis. Conceptually one could be able to monitor changes in human behaviour and activity in nearly true time by using indicators derived from outside the clinical health services. This type of more up-to-date and geographically precise information could contribute to earlier detection of flu outbreaks and serve as background for implementing tailor-made emergency response measures over the course of the outbreaks.publishedVersio

A longitudinal study of the risks for introduction of severe footrot into sheep flocks in the south west of Norway

In 2008, ovine footrot was detected in Norway for the first time since 1948. By December 2012 it had spread to 99 flocks, all in the county of Rogaland in the south west of Norway, and 42% of which were located in the municipality of Rennesøy in Rogaland. The aim of this study was to investigate risk factors for contracting severe footrot in flocks of sheep. A flock was considered positive for severe footrot based on positive virulence test or by clinical signs in addition to a positive PCR test. A retrospective longitudinal study was performed with a questionnaire as the main data source. All sheep farmers (107) in the municipality of Rennesøy were selected for inclusion in the study. The questions focused on direct and indirect contacts between sheep in different sheep flocks and general information about the farm. The questions covered the years 2007–2011. Data were analysed using discrete time survival modelling. A total of 81 (76%) farmers responded to the questionnaire including 29 of 41 (71%) farmers with flocks positive for severe footrot. Factors that increased the risk of a flock becoming positive for severe footrot in the final multivariable survival model were sheep that trespassed boundary fences and came into contact with a flock positive for severe footrot (odds ratio 11.5, 95% confidence interval 4.1–32.2) and at least one flock with severe footrot within 0–1 km radius of a farm (odds ratio 8.6, 95% confidence interval 2.3–32.6). This study highlights the importance of upgrading and maintaining boundary fences and encouraging farmers to avoid direct and indirect contact between nearby flocks

Sykdomspulsen One Health - A real time surveillance system in an infrastructure coping with half a million analysis a day

Sykdomspulsen is a real time surveillance system developed by the Norwegian Institute of Public Health (NIPH) for One Health surveillance and the surveillance of other infectious diseases in humans like respiratory diseases and lately covid-19.The One Health surveillance comprise of Campylobacter data from humans and chicken farms and also includes diagnosis codes from doctor appointments and weather data with analysis forecasting outbreaks in Norway. It is a joint project between the Norwegian Institute of Public Health (NIPH) and the Norwegian Veterinary Institute (NVI), under the framework of the OHEJP NOVA (Novel approaches for design and evaluation of cost-effective surveillance across the food chain) and MATRIX (Connecting dimensions in One-Health surveillance) projects.The system relies on two pillars, the first being an analytics infrastructure which in real time retrieves data from tens of sources, cleans and harmonizes it, then runs over half a million analyses each day and produces over 20 000 000 rows of results to be used every day. The analytics infrastructure is based on R. Results are notably being used by NIPH for the monitoring of covid-19 development and the surveillance of other transmittable diseases such as influenza and gastro-intestinal illness. The analytics framework also generates hundreds of reports every day, directed at dissemination to municipal health authorities. This framework is not currently publicly available, but an open-source release is expected by the end of 2021.The second pilar is an interactive R Shiny dashboard platform, which is used for communicating the data and the model results to partner organisations. It allows for the easy creation of a website where public and animal health researchers and food safety experts can view real time analyses. This dashboard combines the powerful data visualisation and analysis strength of R with the accessibility, flexibility, structure and interactivity of web-based platforms.The result is a real time interactive surveillance system, that is supported by a solid infrastructure and streamlined data flow, and shared with actors through a beautiful and user-friendly website, based entirely on R

Immigrant screening for latent tuberculosis infection: numbers needed to test and treat, a Norwegian population-based cohort study

Objectives: To estimate the number needed to screen (NNS) and the number needed to treat (NNT) to prevent one tuberculosis (TB) case in the Norwegian immigrant latent tuberculosis infection (LTBI) screening programme and to explore the effect of delay of LTBI treatment initiation. Methods: We obtained aggregated data on immigration to Norway in 2008–2011 and used data from the Norwegian Surveillance System for Infectious Diseases to assess the number of TB cases arising in this cohort within 5 years after arrival. We calculated the average NNS and NNT for immigrants from the top 10 source countries for TB in Norway and by estimated TB incidence rates in source countries. We explored the sensitivity of these estimates with regard to test performance, treatment efficacy and treatment adherence using an extreme value approach, and assessed the effects of emigration, time to TB diagnosis (to define incident TB) and intervention timing. Results: NNS and NNT were overall high, with substantial variation. NNT showed numerically stronger negative correlation with TB notification rate in Norway (−0.75 [95% CI −1.00 to −0.44]) than with the WHO incidence rate (IR) (−0.32 [95% CI −0.93 to 0.29]). NNT was affected substantially by emigration and the definition of incident TB. Estimates were lowest for Somali (NNS 99 [70–150], NNT 27 [19–41]) and highest for Thai immigrants (NNS 585 [413–887], NNT 111 [79–116]). Implementing LTBI treatment in immigrants sooner after arrival may improve the effectiveness of the programme. Conclusion: Using TB notifications in Norway, rather than IR in source countries, would improve targeting of immigrants for LTBI management. However, the overall high NNT is a concern and challenges the scale-up of preventive LTBI treatment for significant public health impact. Better data are urgently needed to monitor and evaluate NNS and NNT in countries implementing LTBI screening

Immigrant screening for latent tuberculosis infection: numbers needed to test and treat, a Norwegian population-based cohort study

Objectives: To estimate the number needed to screen (NNS) and the number needed to treat (NNT) to prevent one tuberculosis (TB) case in the Norwegian immigrant latent tuberculosis infection (LTBI) screening programme and to explore the effect of delay of LTBI treatment initiation. Methods: We obtained aggregated data on immigration to Norway in 2008–2011 and used data from the Norwegian Surveillance System for Infectious Diseases to assess the number of TB cases arising in this cohort within 5 years after arrival. We calculated the average NNS and NNT for immigrants from the top 10 source countries for TB in Norway and by estimated TB incidence rates in source countries. We explored the sensitivity of these estimates with regard to test performance, treatment efficacy and treatment adherence using an extreme value approach, and assessed the effects of emigration, time to TB diagnosis (to define incident TB) and intervention timing. Results: NNS and NNT were overall high, with substantial variation. NNT showed numerically stronger negative correlation with TB notification rate in Norway (−0.75 [95% CI −1.00 to −0.44]) than with the WHO incidence rate (IR) (−0.32 [95% CI −0.93 to 0.29]). NNT was affected substantially by emigration and the definition of incident TB. Estimates were lowest for Somali (NNS 99 [70–150], NNT 27 [19–41]) and highest for Thai immigrants (NNS 585 [413–887], NNT 111 [79–116]). Implementing LTBI treatment in immigrants sooner after arrival may improve the effectiveness of the programme. Conclusion: Using TB notifications in Norway, rather than IR in source countries, would improve targeting of immigrants for LTBI management. However, the overall high NNT is a concern and challenges the scale-up of preventive LTBI treatment for significant public health impact. Better data are urgently needed to monitor and evaluate NNS and NNT in countries implementing LTBI screening

No indication of <it>Coxiella burnetii</it> infection in Norwegian farmed ruminants

Abstract Background Infection with Coxiella burnetii, the cause of Q-fever, has never been detected in Norwegian animals. Recognising the increasing prevalence of the infection in neighbouring countries, the aim of the study was to perform a survey of Norwegian farmed ruminants for the prevalence of C. burnetii infection. Results Milk and blood samples from more than 3450 Norwegian dairy cattle herds, 55 beef cattle herds, 348 dairy goat herds and 118 sheep flocks were serologically examined for antibodies against C. burnetii. All samples were negative for antibodies against C. burnetii. The estimated prevalences of infected herds were 0 (95% confidence interval: 0% - 0.12%), 0 (0% - 12%), 0 (0% - 1.2%) and 0 (0% - 10%) for dairy cattle herds, beef cattle herds, goat herds and sheep flocks, respectively. Conclusions The study indicates that the prevalence of C. burnetii infection in farmed Norwegian ruminants is low, and it cannot be excluded that Norway is free of the infection. It would be beneficial if Norway was able to maintain the current situation. Therefore, preventive measures should be continued.</p