Copyright Oxford University Press CHAPTER 4 Summary Numerous zoonotic diseases cause morbidity, mortality and productivity losses in both humans and animal populations. Recent studies suggest that these diseases can produce large societal impacts in endemic areas. Estimates of monetary impact and dis- ease burden provide essential, evidence-based data for conducting cost-benefit and cost-utility analyses that can contribute to secur- ing political will and financial and technical resources. To evaluate burden, monetary and non-monetary impacts of zoonoses on human health, agriculture and society should be comprehensively considered. This chapter reviews the framework used to assess the health impact and burden of zoonoses and the data needed to esti- mate the extent of the problem for societies. Case studies are pre- sented to illustrate the use of burden of disease assessment for the zoonotic diseases cystic echinococcosis, Taenia solium cysticerco- sis, brucellosis and rabies. Introduction Numerous zoonotic infections result in ill health and economic losses in humans and animals. The challenge in assessing the burden of a zoonotic infection is that most approaches will esti- mate the impact of the infection in one species at a time. In addi- tion, some approaches are only applicable to measuring human health impact, and are not applicable to animal health impact. To overcome this challenge, a number of large-scale initiatives and individual researchers have endeavoured to assess the burden of these infections in both non-monetary and monetary terms. Non- monetary assessment can include measures of mortality, morbidity (which often includes reduction in productivity in animals), and health adjusted life year (HALY) measures which include the qual- ity adjusted life year (QALY) and the disability adjusted life year (DALY). Monetary assessment of these conditions should include both direct and indirect costs associated with disease in both human and animal hosts. Measuring burden Mortality as a measure of burden Mortality has traditionally been used to measure and compare the health status of populations (Hyder and Morrow 2001). For humans, vital statistics data have been shown to be available from only 115 out of 192 member states of the World Health Organization (WHO) (Mathers et al. 2005). Of those 115 member states, death registration was considered complete in only 64 (33 %). In addi- tion, among 106 countries with recent data at least 50 % complete, the quality of the data on classification of the causes of death was considered as high, medium and poor in 23, 55 and 28 countries, respectively. These data underline the difficulty of measuring burden across states even using what is usually considered an objective and reliable measure, death. There is no systematic data collection on causes of animal deaths, except in the case of the occurrence of an outbreak. In livestock, slaughterhouse data, when available, may be used to estimate the prevalence of infections (see later), but do not reflect causes of death nor natural (non-slaughter) death rates. There is no vital sta- tistics system for pet animals. Therefore, while there is a way to compare human death rates across countries, even if they are not completely accurate, such measures are not available for animal populations. Morbidity as a measure of burden Causes of death data may accurately measure the impact of deadly diseases, but ignore those diseases that may be chronic and disa- bling, but not or rarely fatal. In humans, such data can be estimated from clinical records systems, health insurance claims databases or notifiable disease or cancer registries. Medical records systems will only reflect the incidence rates of diseases among people seeking medical care, even in countries with universal health coverage. Notifiable disease surveillance data are known to underestimate the true frequency of infectious diseases, but are helpful to detect outbreaks and analyse temporal and spatial trends (Trottier et al. 2006; Giesecke 2002; Chorba 2001; Nelson and Sifakis 2007). In addition, models have been developed for some diseases, such as measles, to adjust for under-reporting (Fine and Clarkson 1982). The reliability of the classification of diseases from medical records is often poor (De Coster et al. 2006). Finally, availability of medical record data is limited to only a few developed countries. In animals, data from slaughterhouses or official carcass inspections in markets can be used, where available, to estimate the frequency of diseases in animals. Such data are only useful in coun- tries where home slaughter is uncommon and where the majority Health impact assessment and burden of zoonotic diseases Christine M. Budke, Hélène Carabin and Paul R. Torgerson