Hostname: page-component-cd9895bd7-lnqnp Total loading time: 0 Render date: 2024-12-23T06:18:08.609Z Has data issue: false hasContentIssue false

Economics of zoonoses surveillance in a ‘One Health’ context: an assessment of Campylobacter surveillance in Switzerland

Published online by Cambridge University Press:  23 January 2017

S. BABO MARTINS*
Affiliation:
Department of Production and Population Health, Veterinary Epidemiology, Economics and Public Health Group, Royal Veterinary College, Hatfield, UK SAFOSO AG, Bern-Liebefeld, Switzerland
J. RUSHTON
Affiliation:
Department of Production and Population Health, Veterinary Epidemiology, Economics and Public Health Group, Royal Veterinary College, Hatfield, UK
K. D. C. STÄRK
Affiliation:
Department of Production and Population Health, Veterinary Epidemiology, Economics and Public Health Group, Royal Veterinary College, Hatfield, UK SAFOSO AG, Bern-Liebefeld, Switzerland
*
*Author for correspondence: S. Babo Martins, Department of Production and Population Health, Veterinary Epidemiology, Economics and Public Health Group, Royal Veterinary College, Hawkshead Lane, Hatfield, AL9 7TA, UK. (Email: [email protected])
Rights & Permissions [Opens in a new window]

Summary

Cross-sectorial surveillance and general collaboration between the animal and the public health sectors are increasingly recognized as needed to better manage the impacts of zoonoses. From 2009, the Swiss established a Campylobacter mitigation system that includes human and poultry surveillance data-sharing within a multi-sectorial platform, in a ‘One Health’ approach. The objective of this study was to explore the economics of this cross-sectorial approach, including surveillance and triggered interventions. Costs and benefits of the One Health and of the uni-sectorial approach to Campylobacter surveillance were identified using an economic assessment framework developed earlier. Cost information of surveillance activities and interventions was gathered and disability-adjusted life years (DALYs) associated with the disease estimated for 2008 and 2013. In the first 5 years of this One Health approach to Campylobacter mitigation, surveillance contributed with information mainly used to perform risk assessments, monitor trends and shape research efforts on Campylobacter. There was an increase in costs associated with the mitigation activities following integration, due mainly to the allocation of additional resources to research and implementation of poultry surveillance. The overall burden of campylobacteriosis increased by 3·4–8·8% to 1751–2852 DALYs in 2013. In the timing of the analysis, added value associated with this cross-sectorial approach to surveillance of Campylobacter in the country was likely generated through non-measurable benefits such as intellectual capital and social capital.

Type
Original Papers
Copyright
Copyright © Cambridge University Press 2017 

INTRODUCTION

Campylobacter poses an important public health threat, and it is currently identified as the most important zoonotic infectious agent in Europe [1]. In Switzerland, human campylobacteriosis has been a notifiable disease since 1988 and the most frequently recorded zoonotic infection since 1995. Overall, an increasing trend of the disease in humans has been observed, with a peak of notified cases of 105 reports per 100000 inhabitants in 2012 [Reference Baumgartner, Felleisen and Gut2, Reference Schmutz3]. Its impact in the country in terms of healthcare costs of laboratory-confirmed campylobacteriosis patients has been recently estimated as €8·3 million [Reference Schmutz4]. There is a distinct two-peak seasonality of reported human cases in the country: a summer peak, likely to be connected to a higher infection rate in poultry flocks, higher frequency of exposure via barbecue activities and foreign travel, and a winter peak mainly related to consumption of chicken meat in the traditional festive dish Fondue Chinoise [Reference Bless5Reference Wei, Schüpbach and Held7]. The chicken reservoir has been identified as the main source for human campylobacteriosis in Switzerland, with 71% of human cases attributed to chicken based on the comparison of isolates from humans and animals [Reference Kittl8]. In poultry, the prevalence of Campylobacter in cloacal swabs ranged from 33% to 38%, from 2010 to 2013 [6].

In response to the observed increasing trend in human campylobacteriosis cases, the animal and the human health authorities enhanced collaborative disease surveillance and intervention efforts with the intention of improving disease management. A stakeholder group composed of the poultry industry, researchers and public health and animal health national and cantonal authorities – the Campylobacter platform – was formed with the aim of exchanging information, coordinating and evaluating control measures, and identifying gaps of knowledge and funding of research [Reference Baumgartner, Felleisen and Gut2]. A regular surveillance system in broiler chicken was also implemented. This constituted a shift from the previously instituted system, which was essentially based on the monitoring of human cases.

Such change, from a uni-sectorial to a multi-sectorial approach to Campylobacter mitigation, is also in line with increased recognition at the international level of the need for collaboration between the animal and the public health sectors as a means of improving the management of zoonotic threats. The One Health movement is based on the principles that collaborative or integrated efforts across multiple disciplines can result in a decrease of the burden of zoonotic disease and generate a better health status, and that a multi-sectorial approach best captures the interrelationships of health of different species [Reference Zinsstag, Waltner-Toews, Tanner, Zinsstag, Schelling, Waltner-Toews, Whittaker and Tanner9, 10]. This includes strengthened integrated surveillance systems for zoonotic pathogens and sharing of information, currently seen as key to an effective health system [Reference Halliday11Reference Gubernot, Boyer and Moses14].

The need to identify better ways to mitigate the impact of campylobacteriosis has triggered research work into the cost-effectiveness of control options for Campylobacter at different levels of the food chain in different countries [Reference Lake15Reference Gellynck17]. However, similar to economic assessments of other zoonotic diseases, the focus of these assessments is largely on the economics of disease control, with no specific focus on the costs and benefits of efforts for surveillance or collaborative mitigation activities for Campylobacter. Surveillance activities require resource spending that may be significant and information on the extent of expenditure associated with these activities is needed to inform prevention, surveillance and control strategy decisions. Furthermore, from an economic perspective, it is of interest to consider whether overall resources are used more efficiently by integrated, One Health surveillance, than by a surveillance system with disconnected, sector-specific components. Such increased efficiency in resource use can be attained either through cost savings and/or by added benefits associated with a reduced impact at the societal level of zoonotic threats [Reference Babo Martins, Rushton and Stärk18].

It has been shown in previous work that the economic assessment of surveillance activities needs to be underpinned by the understanding of how the surveillance activities link to interventions and to the broader mitigation process [Reference Häsler, Howe and Stärk19]. An assessment of the overall mitigation approach including surveillance and intervention is therefore needed when exploring the economics of surveillance. In the case of One Health surveillance, this extends to the understanding of how surveillance information is used and how it triggers health consequences and benefit streams across different sectors [Reference Babo Martins, Rushton and Stärk18].

In this study, we explored the cross-sectorial costs and benefits associated with the sharing of surveillance information on Campylobacter in Switzerland during the period 2009–2013. The objective is to provide information on the economics of this cross-sectorial approach to Campylobacter mitigation and to test the practical implementation of an assessment framework previously developed.

METHODS

General approach

The One Health approach to Campylobacter mitigation was considered as the system in place since 2009 to 2013 (in this study). In this period information generated by surveillance activities in the poultry population and in the human population was shared in the Campylobacter platform and fed into cross-sectorial policy discussions, triggering public health and animal health targeted interventions. The collaborative nature of the analysis of information generated by the animal and human surveillance streams in the Campylobacter platform fits into the concept of ‘One Health surveillance’, as currently described [Reference Stärk20, Reference Berezowski21]. This One Health approach was compared with the system in place prior to establishment of the Campylobacter platform, the 5-year period from 2004 to 2008. The mitigation activities during this period were predominantly public-health-based, with a monitoring system centred on mandatory notification of human cases, triggering public health messaging activities.

As mentioned before, costs and benefits of surveillance are intrinsically linked to the interventions triggered by the information generated. Taking this into consideration, and to guide our assessment, we applied a framework previously developed [Reference Babo Martins, Rushton and Stärk18] to identify surveillance activities across the two sectors, their links to public health and animal health decision-making and triggered interventions in the two time periods. The framework entails an initial step that involves a conceptualization of the links between surveillance and triggered interventions, followed by the identification of costs and benefits and their valuation. An overview of the steps taken in this analysis is provided in Figure 1.

Fig. 1. Overview of the steps taken in the economic assessment of Campylobacter surveillance in Switzerland in a One Health perspective following the conceptual framework used in this study [Reference Babo Martins, Rushton and Stärk18].

Only official surveillance systems and interventions were considered in this assessment and industry-borne costs and benefits were not incorporated in the analysis.

Initial framing and identification of cost and benefit items associated with Campylobacter surveillance

The initial framing for the analysis entailed the conceptualization of the links between the surveillance streams for Campylobacter and the triggered interventions across sectors. Information on the type of surveillance activities, integration mechanisms and interventions prompted by the information generated in both the animal and human health sectors were identified for the One Health and uni-sectorial systems, based on discussion with experts involved in the surveillance activities and in the Campylobacter platform and literature review [Reference Baumgartner, Felleisen and Gut2]. The information was mapped enabling the identification of the costs items and potential benefit streams of the mitigation systems (Fig. 2).

Fig. 2. Conceptual representation of the links between Campylobacter surveillance and triggered activities across the public health and the animal health sectors and the benefit streams generated, in 2009–2013.

Valuing costs and estimating the break-even point

Data used to parameterize the cost estimation model were collected for the two periods in analysis from the Swiss Federal Food Safety and Veterinary Office (FVO) and Federal Office of Public Health (FOPH). Labour costs and expenses accrued by planning and preparation tasks of the surveillance systems, sampling and test costs, including analysis and transport of materials and samples were included where appropriate, as well as labour costs and expenses related to data analysis and interpretation, and information dissemination. Running costs of the Campylobacter platform as well as costs associated with interventions that were triggered by surveillance information were also estimated. For the human monitoring system, only labour and expenses associated with the notification of cases upstream of the laboratory diagnosis were considered, as all costs downstream to that point could not be directly allocated to the monitoring system. Intangible costs were not included in the analysis. Table 1 summarizes the inputs considered for the cost estimate.

Table 1. Inputs considered for the cost analysis per system component

Labour costs for scientific and administrative level staff were calculated considering the wage table established by the Swiss Confederation for 2014 and using an average variation of 1·2% [22] to establish the corresponding wages for the years in analysis. A working month of 182·7 hours was used as a basis for the calculation of the hourly cost associated with the Campylobacter mitigation activities.

The break-even point for the system, i.e. the point at which cost or expenses and benefits are equal and the system would recover its costs, was calculated in terms of the number of disability-adjusted life years (DALYs) – the metric used to assess marginal benefits of the system – that would have to be averted. To compare a monetary metric for costs [Swiss Francs (CHF)] with a non-monetary metric, break-even points were calculated using three point estimates of health burden and associated cost-of-illness (converted into CHF, using the yearly average exchange rate of 2013) available in the literature: 8437 CHF/DALY [23], 61 362 CHF/DALY [Reference Toljander24] (considering the average DALY estimate) and 21 534 CHF/DALY [Reference Mangen25].

Valuing benefits

From the benefit streams identified (Fig. 2), we explored in more detail potential changes regarding the impact of disease in the human population. The potential benefits of Campylobacter mitigation in the poultry population, in terms of direct impact, were not assessed considering the relatively minor role of Campylobacter as a pathogen for poultry [Reference Wagenaar and Singer26]. Similarly, potential benefits in terms of mitigation of potential indirect impacts (e.g. effects on market access and trade) were not assessed.

Burden of disease was calculated using DALYs, applying the methodology developed by Murray & Lopez [Reference Murray and Lopez27] and building upon the model recently used in Denmark for the estimation of the burden of foodborne disease [Reference Pires28]. The estimates of burden for 2013 (5 years after the start of the approach) were compared to the estimated burden of disease in 2008 (the year prior to the implementation of the Campylobacter platform).

Table 2 summarizes the inputs used to parameterize the DALY model. To correct for underdiagnoses and underreporting and to estimate the total incidence of disease in the community, multiplication factors of 3·4 [23] and of 9·3 [Reference Tam29] as a best- and worst-case scenario, respectively, were used in the 2 years estimated – 2008 and 2013. Underreporting and underdiagnoses were considered as constant in 2008 and 2013 as there were no changes to the human monitoring system. Health outcomes associated with Campylobacter infection considered were gastroenteritis (GE), reactive arthritis (RA), irritable bowel syndrome (IBS), inflammatory bowel disease (IBD) and Guillain–Barré syndrome (GBS). Data pertaining to these health outcomes were sourced from national data whenever possible and from data available in the literature from elsewhere and recently reviewed in [Reference Pires28]. Disability weights (DWs) used were based on the Global Burden of Disease 2010 study [Reference Salomon30]. When the DW for a specific health outcome was not available, a DW from an outcome with similar health effects was used. When DWs for specific health outcomes differentiated between multiple degrees of severity, an overall DW was calculated on the basis of the estimate of the proportion of cases with those severity levels in Switzerland. Life expectancy estimates were obtained from the Swiss population statistics for 2013 [31]. Age weighting and discounting were not applied.

Table 2. Input parameters for DALY calculation and data sources

DALY, Disability-adjusted life year; FOPH, Federal Office of Public Health; GE, Gastroenteritis; RA, reactive arthritis; IBS: irritable bowel syndrome; IBD, irritable bowel disease; GBS, Guillian–Barré syndrome.

Total years of life lost to disability (YLD), to mortality (YLL), and overall DALYs for the years under analysis were calculated by applying a stochastic model using the DALY Calculator interface developed in R [Reference Devleesschauwer38]. In addition to the estimate of best- and worst-case scenarios to explore the uncertainty resulting from data limitations in the incidence of campylobacteriosis, sensitivity analysis using a linear regression-based analysis was conducted with the same software to explore the contribution of each stochastic variable in model input parameters to the overall uncertainty of the end result.

RESULTS

From 2009 to 2013, the information generated by surveillance in the animal population and by human case monitoring shared in the Campylobacter platform, triggered activities concerning biosecurity messaging in poultry farms and public health messaging on hygienic measures for chicken meat handling and prevention of cross-contamination. Integration of surveillance information was also used to perform cross-sectorial risk assessments and to identify gaps in the knowledge base for Campylobacter infection in the country and research needs. The links between information generated by the animal health sector and triggered interventions in the public health sector through the integration of this information in a One Health approach are presented in Figure 2.

Through its links to public health messaging, surveillance of Campylobacter in poultry and integration of information has the potential to generate a reduction in the direct and indirect impact of the disease in the human population, namely on the burden of disease or cost-of-illness. Equally, through its links to biosecurity messaging at the farm level, it has the potential to reduce the direct and indirect impact of disease in the animal population, ultimately contributing to a reduction in human infection.

Intermediate or intangible benefits were identified, related to enhanced knowledge, performance of risk assessments and triggering of research, such as intellectual capital, and to social capital, generated through the intrinsic value of multi-sectorial collaboration and networking.

The overall mitigation activities surrounding Campylobacter in Switzerland in the period 2009–2013 had an associated cost of ~1·85 million CHF, corresponding to a yearly average expenditure of ~ 370 000 CHF. This figure does not include mitigation costs borne by industry as these were not available but known to be >0. The overall marginal cost of such an enhanced effort was of 1·2 million CHF (over 5 years) in relation to the 5-year period 2004–2008 when the activities were mainly public-health based. Almost half (48%) of the total expenditure in 2009–2013 was absorbed by commissioned research on Campylobacter in Switzerland, followed by the surveillance and monitoring activities in poultry and humans, respectively. Table 3 shows the cost analysis results by system component for the One Health approach.

Table 3. Estimated cumulative cost of the One Health mitigation system per component, in the period 2009–2013 (in CHF)

The average total burden of disease of campylobacteriosis was estimated to be 1751 [95% confidence interval (CI) 1478–2069] to 2852 (95% CI 2520–3227) DALYs in 2013, in the best- and worst-case scenarios, respectively. This represents a 3·4–8·8% increase since 2008 when the estimated burden of disease was of 1609 (95% CI 1330–1947) DALYs to 2756 (95% CI 2412–3140) (undiscounted). From the total results, 746–802 to 820–942 of the DALYs were related to GE in 2008 and 2013, respectively, with the remaining burden allocated to disease sequelae. The total DALYs correspond to 20·19–34·59 and to 21·96–35·08 DALYs/100 000 inhabitants in 2008 and 2013, respectively. Table 4 shows these results in more detail.

Table 4. Estimated total DALYs, YLD and YLL associated with campylobacteriosis in Switzerland in 2008 and 2013 in two scenarios of estimated total incidence

DALY, Disability-adjusted life year; YLD, total years of life lost to disability; YLL, total years of life lost to mortality; BCS, best-case scenario; WCS, worst-case scenario.

The results are expressed in mean and 95% confidence intervals.

The One Health mitigation approach would recover its costs if 6–43·8 DALYs were averted per year, depending on the cost-of-illness to DALY match estimate used in the break-even point calculations.

Figure 3 summarizes the results of the cost analysis and burden calculation by showing the evolution of costs per activity in the 10 years of the analysis and the campylobacteriosis burden estimate from 2008 to 2013.

Fig. 3. Costs of Campylobacter mitigation activities in Switzerland per activity undertaken, from 2004 to 2013 (CHF) and estimates of overall campylobacteriosis burden of disease (DALYs) for 2008 and 2013 (best- and worst-case scenarios for estimated true incidence).

In addition to the impact of the estimated true incidence input parameter shown above, the sensitivity analysis indicated that, from the stochastic inputs to the model, changes in the duration of symptoms of GE had the highest impact on the model outcome. One standard deviation change in duration of GE symptoms would lead to a difference of 34·2 DALYs in the overall DALY estimate.

DISCUSSION

We assessed the costs and benefits associated with Campylobacter surveillance in Switzerland from a One Health perspective.

Our results suggest that, in the first 5 years of the system, the level of the expenditure increased with a cross-sectorial approach to surveillance and intervention for Campylobacter in the country, particularly in research funding and surveillance activities in poultry. In the period of this work, integrated surveillance information contributed mainly to the assessment of trends, to perform risk assessments and to inform discussion on gaps and information needs regarding Campylobacter in the country, thus contributing to the shaping of research efforts and strengthening of the knowledge base regarding the disease. Consequently, in these initial 5 years, the nature of benefits was intangible, including the generation of intellectual capital. The latter relates to the intangible value (information, intellectual property, experience) in the knowledge and relationships of employees, management staff, and other stakeholders of a company or institution, that can be used, in the future, to generate wealth. In the public sector context, measurement of intellectual capital and knowledge assets has been carried out by universities and research funding institutions [Reference Fazlagic39].

Such intellectual capital created by surveillance can later generate measurable value when it is translated into control measures that mitigate the impact of the disease. In fact, from 2014, the Campylobacter mitigation system in Switzerland shifted from a main focus on assessment and knowledge-generation to the implementation of interventions targeting the food chain. New national regulations in place from January 2014 require that poultry liver from Campylobacter-positive herds can only be sold frozen and that pre-packed fresh poultry meat and meat preparations should be labelled with information on the need to thoroughly cook the products before consumption and on hygiene rules [6].

The timing of our analysis is therefore particularly relevant for the benefits assessment. A time delay between initiating research and implementing interventions with possible health effects can be expected. Furthermore, it can be expected that the power of an integrated surveillance system increases with time as information is gathered and trends and sources are more accurately identified. This has been shown with other integrated surveillance approaches such as the Danish Integrated Antimicrobial Resistance Monitoring Programme [Reference Hammerum40].

The estimated burden of disease increased from 1609–2756 in 2008 to 1751–2852 DALYs in 2013. The increase of overall burden of disease in Switzerland of 96–142 DALYs from 2008 to 2013 reflects not only an increase in overall incidence of disease, but also a shift in the age structure of cases, with a steady increase of case reports in the elderly aged >65 years, where the Campylobacter-associated mortality rate is higher, from 49/100 000 inhabitants in 2004 to 100/100 000 in 2013 [6]. Simultaneously, an increase in chicken meat consumption from 10·88 to 11·42 kg per capita has been observed in the country over the same period (Proviande data). Such increase needs to also be interpreted considering that in the period of this analysis there was no direct control interventions implemented in the food chain, and therefore a direct health effect and measurable benefit of surveillance in this time-frame would not be expected. Additional economic analysis further in time could allow to understand if measurable benefits were generated by the intervention measures implemented from 2014 described above. Such benefits could be quantified by assessing the effect of the interventions and by comparing it with baseline scenarios as described in studies estimating the cost-effectiveness of interventions targeting Campylobacter along the food chain (reviewed in [23]). Increasing the time-frame would allow the capture of possible measurable health effects and the estimation of cost-effectiveness of the One Health approach compared to uni-sectorial approaches.

The break-even point analysis for the One Health approach suggests that a return on investment can be achieved with a small reduction in cases reported. Although this information provides a perspective on how intervention costs can be recouped, it does not provide evidence on how this system compares in terms of costs per DALY avoided with other mitigation system designs. For Campylobacter in particular, a reduction in cases does not seem to be easily achievable [Reference Wagenaar, French and Havelaar41] as shown by the increasing trends on disease incidence until 2012 in most countries facing this challenge. Interventions in the poultry meat production chain, such as biosecurity alone, have limited effect and the most effective interventions such as freezing are costly and face consumer acceptance constraints [Reference Wagenaar, French and Havelaar41].

Some limitations to our estimates should be considered. The cost analysis and results for marginal cost increase associated with the cross-sectorial mitigation efforts for Campylobacter in this study focused on official surveillance programmes and interventions reliant on public spending. Yet, in addition to the official surveillance and control activities, the poultry industry has also been carrying out mitigation activities to tackle Campylobacter at pre-harvest and post-harvest levels. Since our estimates do not account for the costs of such activities, our results are likely an underestimation of the societal efforts in terms of expenditure in Campylobacter surveillance and mitigation. In the same way, we did not exhaustively assess all benefit streams potentially linked to surveillance integration. Fluctuations in terms of consumption and production due to trade at the country level and potential alleviation effects on changes in consumer perception and loss of sales could have implications in the overall benefits assessment from a societal perspective. Benefits could therefore also be undervalued in this study.

Our DALY estimates of 21·98–35/100 000 inhabitants in 2013 are in agreement with results recently observed elsewhere in Europe. For other countries, the most recent estimates point to a burden of campylobacteriosis of 19·8 DALYs/100 000 in The Netherlands [Reference Havelaar33] and of 28·4 DALYs/100 000 in Denmark [Reference Pires28]. However, the burden of disease estimation in this study was limited by the fact that many parameters in the DALY model relied on assumptions and data sourced from literature of studies developed elsewhere. Particularly, the underreporting factor used to estimate the true incidence of Campylobacter-associated disease in the human population may be influential. In our estimation, we used a multiplier factor available in the literature for Switzerland [23] as a best-case scenario. That value was calculated using relative risks for Swedish travellers as a proxy for relative incidence in local residents. There are many caveats surrounding such calculations, namely underdiagnoses of travel-related cases, late expression of symptoms and inability to attribute cases to countries, absence of information on the nature and duration of travel and immunity in the resident population [42]. Preferably, the construction of national disease surveillance pyramids should be informed by country-specific information collected as part of multiplier studies [42] and involving data such as care-seeking behaviour, probabilities of stool sample submission, positive laboratory results reporting and testing for a specific pathogen and the sensitivity of the laboratory tests [Reference Pires28]. Since multiplier studies are not available for Switzerland, and the reported factor was inferior to all other recent estimates of multiplier factors in Europe (reviewed in [Reference Pires28]), we also used a multiplier factor calculated for the UK to model a worst-case scenario. Similarly, the use of a multiplier factor from another country can be disputed as differences in healthcare systems may lead to bias [42]. The reliance on scenarios and data sourced from studies conducted elsewhere, suggests that the human case-monitoring system based upon case reporting was not generating sufficient information to be able to determine more accurately the burden of disease in the country. Future burden of disease or cost-of-illness estimations would greatly benefit from information on the parameters that seem impact the model results most, notably human incidence and prevalence data.

Gains in information and knowledge have been recognized as benefits from One Health approaches [Reference Häsler43, Reference Häsler44]. However, the lack of ability to measure the final outputs in tangible indicators means that it is infrequent to have such benefits incorporated into economic assessments. The same situation is observable in overall economic assessment of disease control [Reference Wilson, Ward and Garner45]. We believe that to accurately understand the added value of One Health and surveillance integration for decision making, the assessment of these assets needs to be an integral part of the analysis. This is particularly relevant for the surveillance systems that are at a similar maturity stage, i.e. mainly informing assessment and producing knowledge, as the Campylobacter mitigation system in Switzerland in the period 2009–2013. Further work on the importance of these intangible assets generated by surveillance integration would enrichen our understanding of the economic aspects of zoonoses surveillance and policy making.

Overall, the framework used as the basis for economic assessment allowed the identification of cross-sectorial cost items and benefits streams, associated with Campylobacter in Switzerland in the period in analysis, through the conceptualization of its links to intervention. By providing information on the economics of cross-sectorial surveillance of Campylobacter as well as the tools for this assessment, the results of this work can be directly applicable and can inform planning of effective and efficient future surveillance programmes for zoonoses. Such assessments require an understanding of how information generated by surveillance is part of the zoonoses mitigation process, and availability of data on costs of activities conducted and on the impacts of such activities in terms of intangible and tangible benefits. The latter set of benefits can only be accurately assessed if adequate surveillance information allows capturing changes in disease dynamics in the populations.

ACKNOWLEDGEMENTS

The authors acknowledge Silke Bruhn (FVO) and Marianne Jost (FOPH) for their assistance in data collection of costs of surveillance and triggered activities. Thanks are also due to Sara Monteiro Pires for her guidance on the burden-of-disease estimation.

This work was supported by the Swiss Federal Food Safety and Veterinary Office and the Royal Veterinary College.

DECLARATION OF INTEREST

None.

References

REFERENCES

1. European Food Safety Authority and European Centre for Disease Prevention and Control. The European Union Summary Report on trends and sources of zoonotic agents and food borne outbreaks in 2011. 2013.Google Scholar
2. Baumgartner, A, Felleisen, R, Gut, C. Campylobacter in Switzerland. Risk factors and measures for dealing with the problem (http://www.blv.admin.ch/themen/04678/04711/04777/05277/index.html?lang=en&download=NHzLpZeg7t,lnp6I0NTU042l2Z6ln1ad1IZn4Z2qZpnO2Yuq2Z6gpJCFfYF6fGym162epYbg2c_JjKbNoKSn6A--). Accessed 4 November 2014.Google Scholar
3. Schmutz, C, et al. Inverse trends of Campylobacter and Salmonella in Swiss surveillance data, 1988–2013. Eurosurveillance 2016, 21: pii = 30130.CrossRefGoogle ScholarPubMed
4. Schmutz, C, et al. Estimating healthcare costs of acute gastroenteritis and human campylobacteriosis in Switzerland. Epidemiology and Infection. Published online: 12 August 2016. doi:http://dx.doi.org/10.1017/S0950268816001618.Google ScholarPubMed
5. Bless, PJ, et al. A tradition and an epidemic: determinants of the campylobacteriosis winter peak in Switzerland. European Journal of Epidemiology 2014; 29: 527537.Google Scholar
6. European Food Safety Authority. Switzerland, the report referred to in Article 9 of Directive 2003/99/EC, Trends and sources of zoonoses and zoonotic agents in humans, foostuffs, animals and in feedingstuffs. 2013.Google Scholar
7. Wei, W, Schüpbach, G, Held, L. Time-series analysis of Campylobacter incidence in Switzerland. Epidemiology and Infection 2014; 143: 19821989.Google Scholar
8. Kittl, S, et al. Source attribution of human Campylobacter isolates by MLST and fla-typing and association of genotypes with quinolone resistance. PLoS ONE 2013, 8: e81796.Google Scholar
9. Zinsstag, J, Waltner-Toews, D, Tanner, M. Theoretical issues of one health. In: Zinsstag, J, Schelling, E, Waltner-Toews, D, Whittaker, M, Tanner, M, eds. One Health - The Theory and Practice of Integrated Health Approaches. Wallingford, UK: CABI, 2015, pp. 1626.CrossRefGoogle Scholar
10. World Bank. People, pathogens and our planet, volume 1: towards a one health approach for controlling zoonotic diseases, Report No. 50833-GLB. 2010.Google Scholar
11. Halliday, J, et al. Bringing together emerging and endemic zoonoses surveillance: shared challenges and a common solution. Philosophical Transactions of the Royal Society of London, Series B: Biological Sciences 2012; 367: 28722880.CrossRefGoogle Scholar
12. Rabinowitz, P, Scotch, M, Conti, L. Human and animal sentinels for shared health risks. Veterinaria Italiana 2009; 45: 2324.Google ScholarPubMed
13. Scotch, M, Odofin, L, Rabinowitz, P. Linkages between animal and human health sentinel data. BMC Veterinary Research 2009; 5: 15.CrossRefGoogle ScholarPubMed
14. Gubernot, DM, Boyer, BL, Moses, MS. Animals as early detectors of bioevents: veterinary tools and a framework for animal-human integrated zoonotic disease surveillance. Public Health Reports 2008; 123: 300315.Google Scholar
15. Lake, RJ, et al. Cost-effectiveness of interventions to control Campylobacter in the New Zealand poultry meat food supply. Journal of Food Protection 2013; 76: 11611167.CrossRefGoogle ScholarPubMed
16. Elliott, J, et al. Analysis of the costs and benefits of setting certain control measures for reduction of Campylobacter in broiler meat at different stages of the food chain – Final Report (http://ec.europa.eu/food/food/biosafety/salmonella/docs/campylobacter_cost_benefit_analysis_en.pdf). Accessed 21 November 2014.Google Scholar
17. Gellynck, X et al. Economics of reducing Campylobacter at different levels within the Belgian poultry meat chain. Journal of Food Protection 2008; 71: 479485.Google Scholar
18. Babo Martins, S, Rushton, J, Stärk, KDC. Economic assessment of zoonoses surveillance in a ‘One Health’ context: a conceptual framework. Zoonoses and Public Health 2015; 63: 386395.Google Scholar
19. Häsler, B, Howe, KS, Stärk, KD. Conceptualising the technical relationship of animal disease surveillance to intervention and mitigation as a basis for economic analysis. BMC Health Services Research 2011; 11: 225.CrossRefGoogle ScholarPubMed
20. Stärk, KDC, et al. One Health Surveillance – more than a buzz word? Preventive Veterinary Medicine 2015; 20: 124130.Google Scholar
21. Berezowski, J, et al. Do we need One Health surveillance? One Health Newsletter (http://media.news.health.ufl.edu/misc/egh/OneHealthNewsletter/OHNL_Volume8_Issue1.pdf). Accessed 24 March 2016.Google Scholar
22. Swiss Federal Statistical Office. Wages and income from employment – detailed data Wage evolution (http://www.bfs.admin.ch/bfs/portal/en/index/themen/03/04/blank/data/02.html). Accessed 15 September 2014.Google Scholar
23. European Food Safety Authority. Scientific Opinion on Campylobacter in broiler meat production: control options and performance objectives and/or targets at different stages of the food chain. EFSA Journal 2011; 9: 1141.Google Scholar
24. Toljander, J, et al. Public health burden due to infections by verocytotoxin-producing Escherichia coli (VTEC) and Campylobacter spp. as estimated by cost of illness and different approaches to model disability-adjusted life years. Scandinavian Journal of Public Health 2012; 40: 294302.CrossRefGoogle ScholarPubMed
25. Mangen, MJJ, et al. The costs of human Campylobacter infections and sequelae in the Netherlands: a DALY and cost-of-illness approach. Acta Agriculturae Scandinavica, Section C – Food Economics 2005; 2: 3551.Google Scholar
26. Wagenaar, JA, et al. Campylobacter: animal reservoirs, human infections and options for control. In: Singer, A, ed. Zoonoses – Infections Affecting Humans and Animals: Focus on Public Health Aspects, pp. 159177. Dordrecht, The Netherlands: Springer, 2014.Google Scholar
27. Murray, CJL, Lopez, AD (eds). Global Burden of Disease: A Comprehensive Assessment of Mortality and Disability from Diseases, Injuries and Risk Factors in 1990 and Projected to 2020. Cambridge, MA: Harvard University Press, 1996.Google Scholar
28. Pires, SM. Burden of disease of foodborne pathogens in Denmark – Technical Report (http://www.food.dtu.dk/english/~/media/Institutter/Foedevareinstituttet/Publikationer/Pub-2014/Burden-of-Disease-of-Foodborne-Pathogens-in-Denmark.ashx?la=da). Accessed 3 March 2015.Google Scholar
29. Tam, CC, et al. Longitudinal study of infectious intestinal disease in the UK (IID2 study): incidence in the community and presenting to general practice. Gut 2012; 61: 6977.Google Scholar
30. Salomon, JA, et al. Common values in assessing health outcomes from disease and injury: disability weights measurement study for the Global Burden of Disease Study 2010. Lancet 2012; 380: 21292143.CrossRefGoogle ScholarPubMed
31. Swiss Federal Statistical Office. Components of population change – data, indicators, life expectancy (http://www.bfs.admin.ch/bfs/portal/en/index/themen/01/06/blank/key/04/04.html). Accessed 10 October 2014.Google Scholar
32. Helms, M, et al. Short and long term mortality associated with foodborne bacterial gastrointestinal infections: registry based study. British Medical Journal 2003; 326: 357.CrossRefGoogle Scholar
33. Havelaar, AH, et al. Disease burden of foodborne pathogens in the Netherlands, 2009. International Journal of Food Microbiology 2012; 156: 231238.CrossRefGoogle ScholarPubMed
34. Haagsma, JA, et al. Disease burden of post-infectious irritable bowel syndrome in The Netherlands. Epidemiology and Infection 2010; 138: 16501656.CrossRefGoogle ScholarPubMed
35. Havelaar, AH, et al. Health burden in the Netherlands due to infection with thermophilic Campylobacter spp. Epidemiology and Infection 2000; 125: 505522.CrossRefGoogle ScholarPubMed
36. Melse, JM, Kramers, PGN. Calculation of the burden of disease in The Netherlands. Background document to PHSF (Public Health Survey of the Future) 1997, Part III, Chapter 7. Report no. 431 501 028, 1998.Google Scholar
37. Mangen, MJJ, Havelaar, AH, de Wit, G. Campylobacteriosis and sequelae in the Netherlands – estimating the disease burden and the costs-of-illness. RIVM Report 250911004 (http://www.rivm.nl/en/Documents_and_publications/Scientific/Reports/2004/mei/Campylobacteriosis_and_sequelae_in_the_Netherlands_Estimating_the_disease_burden_and_the_costs_of_illness?sp=cml2bXE9ZmFsc2U7c2VhcmNoYmFzZT0yMjc2MDtyaXZtcT1mYWxzZTs=&pagenr=2277). Accessed 14 June 2015.Google Scholar
38. Devleesschauwer, B, et al. DALY calculator – a GUI for stochastic DALY calculation in R. R package version 1.2 (https://cran.r-project.org/web/packages/DALY/index.html). Accessed 9 September 2014.Google Scholar
39. Fazlagic, A. Measuring the intellectual capital of a university (https://www.oecd.org/edu/imhe/35322785.pdf). Accessed 3 October 2015.Google Scholar
40. Hammerum, AM, et al. Danish integrated antimicrobial resistance monitoring and research program. Emerging Infectious Diseases 2007; 13: 16321639.CrossRefGoogle ScholarPubMed
41. Wagenaar, JA, French, NP, Havelaar, AH. Preventing Campylobacter at the source: why is it so difficult?. Clinical Infectious Diseases 2013; 57: 16001606.Google Scholar
42. World Health Organization. The global view of campylobacteriosis: report of an expert consultation, Utrecht, Netherlands, 9–11 July 2012 (http://apps.who.int/iris/bitstream/10665/80751/1/9789241564601_eng.pdf). Accessed 20 October 2014.Google Scholar
43. Häsler, B, et al. The economic value of One Health in relation to the mitigation of zoonotic disease risks. Current Topics in Microbiology and Immunology 2013; 365: 127151.Google Scholar
44. Häsler, B, et al. A review of the metrics for One Health benefits. Scientific and Technical Review of the Office International des Epizooties 2014; 33: 453464.Google Scholar
45. Wilson, SJ, Ward, MP, Garner, MG. A framework for assessing the intangible impacts of emergency animal disease. Preventive Veterinary Medicine 2013; 111: 194199.Google Scholar
Figure 0

Fig. 1. Overview of the steps taken in the economic assessment of Campylobacter surveillance in Switzerland in a One Health perspective following the conceptual framework used in this study [18].

Figure 1

Fig. 2. Conceptual representation of the links between Campylobacter surveillance and triggered activities across the public health and the animal health sectors and the benefit streams generated, in 2009–2013.

Figure 2

Table 1. Inputs considered for the cost analysis per system component

Figure 3

Table 2. Input parameters for DALY calculation and data sources

Figure 4

Table 3. Estimated cumulative cost of the One Health mitigation system per component, in the period 2009–2013 (in CHF)

Figure 5

Table 4. Estimated total DALYs, YLD and YLL associated with campylobacteriosis in Switzerland in 2008 and 2013 in two scenarios of estimated total incidence

Figure 6

Fig. 3. Costs of Campylobacter mitigation activities in Switzerland per activity undertaken, from 2004 to 2013 (CHF) and estimates of overall campylobacteriosis burden of disease (DALYs) for 2008 and 2013 (best- and worst-case scenarios for estimated true incidence).