FIGURE 1: Scheme showing how misperceptions about dog ecology and rabies epidemiology have negative consequences for rabies control; and identifying the types of research studies that can generate the evidence-base needed for effective control.

Here we review the most recent evidence from rabies epidemiology studies that address these misperceptions, highlighting how new approaches and analytical techniques are being applied and illustrating how the results are constantly reinforcing the evidence base as to the feasibility of canine rabies elimination in Africa.

The most recent estimates of rabies burden incorporate more detailed country-level data, including updated information on human PEP use. These analyses, part of the global burden of disease studies coordinated by the Partners for Rabies Prevention, have also included consideration of economic losses as a result of premature deaths. Overall, using the probability model, global estimates of human rabies deaths are similar to previous studies, with an estimated 61 000 human rabies deaths per year occurring globally (95% CI, 52 200–70 700) and 23 800 in Africa (95% CI, 21 000–28 000) (WHO 2013). However, the apparent consistency in estimates masks substantial local variation, most notably the decline in human rabies deaths in several countries in Asia because of increased availability of rabies PEP and, in some areas, dog rabies control. Whilst any decline in human rabies deaths is to be celebrated, this progress has come at a high cost, with PEP costs in Asia estimated at around US$1.5 billion. These contribute substantially to the estimated global annual cost of rabies of US$6bn (95% CI, 4.6–7.3), which also includes productivity losses of US$2bn as a result of premature deaths (WHO 2013).

Empirical data to both parameterise and validate estimates of human rabies deaths have been generated from community surveys (Hossain et al. 2012), large-scale verbal autopsy surveys (Suraweera et al. 2012) and active surveillance and contact tracing (Hampson et al. 2008). Nonetheless, it is clear that these data are still very scarce and that any figures based on models that incorporate incomplete and imprecise data are likely to have a high degree of uncertainty.

Despite these uncertainties, clinical studies in Malawi have demonstrated that rabies is a more common cause of childhood encephalitis than recognised previously and can be misdiagnosed easily as malaria, even by experienced clinicians (Mallewa et al. 2007). This may seem surprising, given that rabies exhibits several distinct clinical features in humans, such as aerophobia and hydrophobia, but serves to highlight the importance of improving awareness amongst clinicians and submitting samples for laboratory diagnosis to ensure that the rabies disease burden is not masked by high levels of misdiagnosis, particularly in malaria-endemic areas of Africa.

Although rabies does not have the pandemic potential that characterises the emerging zoonoses of greatest concern to high-income countries (Figure 2), its burden and impact cannot be considered negligible. The physical, psychological and economic consequences of rabies are borne by the poorest communities in the world and the continued suffering caused by the disease is entirely preventable and remains a conspicuous failure of the veterinary and medical professions to deliver on existing solutions.

FIGURE 2: Scheme showing how misperceptions about dog ecology and rabies epidemiology have negative consequences for rabies control; and identifying the types of research studies that can generate the evidence-base needed for effective control.

Whilst much effort has focused on understanding the epidemiology and control of rabies in endemic settings, attention is now turning toward prospects for the elimination of canine rabies. The feasibility of canine rabies elimination has been supported by a strong body of evidence from epidemiological field studies, phylogenetic analyses and epidemiological modelling (summarised in Lembo et al. 2010). A key finding has been the low value of R₀, which consistently falls between 1.0 and 2.0 for canine rabies in dog populations across the world, despite wide variation in dog densities and demographic characteristics in urban and rural communities in different countries (Hampson et al. 2009). The lack of density-dependence in rabies transmission was evidenced again with an R₀ estimate of 1.2 for the 2008–2010 rabies outbreak in Bali, Indonesia in communities with very high dog densities (Townsend et al. 2013).

These findings have two major implications for rabies control and elimination: firstly, that elimination of canine rabies through vaccination of ~70% dogs is epidemiologically feasible in most settings, including high-density populations; and secondly, that tackling rabies through dog density reduction (e.g. mass culling) is likely to be ineffective (Morters et al. 2013). These conclusions are also supported by previous experience. For example, despite substantial reductions in the dog population of Flores, Indonesia as part of a culling program to control a rabies outbreak in 1996, the disease remains endemic (Windiyaningsih et al. 2004). Similarly, culling failed to control canine rabies in Korea, Israel, and Bali, whereas subsequent mass dog vaccination programmes have resulted in control of the disease (Knobel et al. 2013). In addition to having no demonstrable beneficial impact on the control of rabies, indiscriminate culling of dogs also has substantial ethical and welfare implications and no evidence exists to support its use in rabies control strategies. However, misperceptions remain widespread (presumably because conclusions from research studies run counter to many intuitive assumptions) and culling is still considered a feasible policy option by many veterinary services in Africa. Engaging with policy-makers therefore remains a high priority to ensure uptake of research findings and to instill confidence as to the feasibility of rabies control and elimination through mass dog vaccination.

Epidemiological models also provide critical support for the development and design of elimination strategies in terms of understanding elimination dynamics; designing the most cost-effective strategies for disease control and surveillance at national, regional and global levels; and providing guidance for policymakers about expected times to elimination. A spatially-explicit stochastic simulation model of rabies in Bali, Indonesia, for example, has indicated that time to elimination of rabies is critically dependent on high levels of contiguous vaccination coverage and that even small pockets of low coverage (e.g. involving < 0.5% of the dog population) can cause a significant delay in progress (Townsend et al. 2013). In contrast, the probability of rabies elimination is only slightly affected by the timing of campaigns (e.g. intensive synchronised versus more prolonged dog vaccination campaigns), so campaigns can be tailored to optimise logistic efficiency and resource availability in order to achieve the high vaccination coverage required.

Several questions therefore remain as to the optimum control strategies that should be adopted in the face of low case-detection probabilities, as well as regarding the duration and level of surveillance efforts that are needed in order to provide confidence that rabies has truly been eliminated. Although definitions for freedom from canine rabies have been proposed (WHO 2013), current international guidelines lack quantitative definitions about the level of surveillance that would be required by an effective surveillance system for the purpose of declaring freedom from rabies (OIE 2011). Recent modelling work provides useful insights, for example, in the use of outbreak simulation techniques to explore the effectiveness of control and elimination strategies. In relatively isolated areas that are not subject to frequent reintroductions (e.g. islands), but which have realistic levels of rabies surveillance (i.e. case-detection probabilities < 10%), mass dog vaccination is more effective at controlling rabies (and is no more costly) than vaccinating only in response to detected outbreaks. These models further indicate that surveillance measures need to be able to detect at least 5% of rabies cases in order to be confident that rabies has been eliminated under the current guidelines for declaration of freedom (Townsend et al. 2012).

These models were developed initially for populations without repeat introductions but, in reality, high levels of legal and illegal dog movements remain a concern for maintaining rabies-free status in areas where the disease has been eliminated. Informal movement of dogs through road and water-based transport can represent a considerable challenge in many areas and, whilst cross-boundary coordination and effective rabies control over large geographic regions should mitigate the risk of new introductions, effective surveillance will still be needed in order to detect and respond to new incursions. Maintaining surveillance levels is also important so as to detect outbreaks that may be triggered by rare spill-over transmission from other reservoir hosts, such as bats, and to contain outbreaks that might otherwise have the potential to establish new epidemic cycles.

With recognition of the critical importance of strengthening rabies surveillance, much effort is therefore being directed at improvements in detection, reporting and laboratory diagnosis of rabies. Examples include the application of mobile phone technologies to enhance reporting of human rabies exposures at bite treatment centres in Tanzania (Mtema 2013). Mobile phone systems also allow for rapid communication between human and animal health sectors to ensure follow up of animal cases; reminder texts to be sent to patients to complete the full course of PEP; and improved distribution of vaccine stocks to avoid the vaccine shortages that occur frequently in many of the more remote parts of Africa (Mtema 2013).

The advent of new diagnostic techniques is also helping to overcome some of the logistic, technical and cultural barriers associated with submitting human and animal samples for centralised laboratory diagnosis using conventional fluorescence techniques. These include (1) new diagnostic tests that use light microscopy rather than fluorescence microscopy and can therefore be carried out at local facilities with very high specificity and sensitivity (Dürr et al. 2008; Lembo et al. 2006); (2) field-based lateral flow devices, that may provide a useful tool for generating surveillance data (Markotter et al. 2009) and for empowering and incentivising field workers to engage with rabies surveillance (Halliday et al. 2012); (3) new techniques for intra vitam diagnosis of human rabies cases (Dacheux et al. 2008; Fooks et al. 2009); and (4) culturally-acceptable methods for post-mortem sampling of brain material for human rabies diagnosis (Mallewa et al. 2007).

Although these techniques are improving capacity for laboratory-confirmed diagnosis in Africa, attention also needs to be given to improving the reporting of clinical cases, which provides the entry point for building an effective rabies surveillance system. Whilst laboratory diagnosis provides robust confirmation of rabies and is important for effective administration of PEP, clinical case reporting also needs strengthening as the central pillar of rabies surveillance. For example, surveillance in the smallpox eradication programme was underpinned by clinical case reporting from health centres (Henderson & Klepac 2013) and during the rinderpest eradication campaigns in Africa, participatory surveillance based on the engagement of local communities was the primary surveillance tool in the final stages of eradication (Roeder, Mariner & Kock 2012).

Given the distinctive nature of dog rabies, recognition amongst local communities in Africa can be high (e.g. 74% of cases reported as suspect rabid animals in rural Tanzania were confirmed positive on laboratory diagnosis; Lembo et al. 2008). Whilst clinical surveillance is clearly neither 100% specific nor sensitive, these cases can contribute valuable epidemiological data for the comparative analysis of trends, initiating follow-up investigations and, most critically, providing a stimulus for disease control measures. Indeed, the lack of feedback or beneficial response to mitigate disease problems is arguably the greatest barrier to the reporting of zoonoses, particularly within resource-poor systems, and this chronic lack of response (or capacity to respond) is disempowering and demotivating at the grassroots level for healthcare and veterinary workers alike (Halliday et al. 2012). Therefore, whilst there is no doubt that laboratory diagnostic capacity needs strengthening throughout most of Africa, the lack of capacity should not act as a deterrent to initiating rabies control measures. Rather, effective rabies control measures should be integrated within responsive surveillance systems and should provide motivation to field staff to improve case reporting and submission of samples.

However, the relationship between dog rabies incidence and human PEP demand, which is a critical determinant of cost-effectiveness, is likely to vary considerably across different socioeconomic settings. In northern Tanzania, for example, the incidence of bite injuries reported at health clinics declines rapidly as the incidence of rabies falls (Cleaveland et al. 2003) and can decline to zero in areas where canine rabies has been eliminated (Lembo et al. 2010). This suggests that people in these communities seek PEP only when they recognise the risk of rabies – they would not seek treatment for bite injuries from non-rabies suspect animals, a situation which presumably reflects both a high level of rabies recognition and the high private costs associated with PEP in comparison with household incomes in Africa (Knobel et al. 2005). In contrast, in many higher-income settings or where rabies occurs more sporadically, the scale of PEP use may be driven both by health-seeking behaviour of more affluent and knowledgeable members of the community as well as clinician decision making. In these situations, pressures and uncertainties faced by clinicians regarding the genuine need for PEP means that PEP use can remain very high even when the incidence of animal rabies cases and risk of exposure to rabies is extremely low (Lardon et al. 2010), with important implications for the cost-effectiveness of human rabies prevention through rabies control in the animal reservoir.

Research findings have also contributed important information for practical field operations, including fundamental questions relating to dog population ecology and ownership patterns, which are central to the design of rabies control measures.

A key finding from dog ecology studies is that, although most dogs in Africa are free-roaming, the number of ownerless dogs or those inaccessible for vaccination remains very low. For example, only 1%, 8% and 11% of dogs respectively were unowned in three study sites in N’Djamena (Kayali et al. 2003). In Zimbabwe, all dogs on communal lands were owned (Butler & Bingham 2000) and in Tanzania, < 1% of dogs were unowned in an urban site that was specifically targeted for dog ecology studies on the basis of reports of a large population of ‘stray’ dogs (Gsell et al. 2012). Although precise estimates of ownerless dogs are difficult to obtain, a robust conclusion remains that the level of dog ownership and dog accessibility is sufficiently high in all these communities to be able to control dog rabies through mass dog vaccination of owned dogs.

Estimating the size of dog populations has been considered a key operational requirement for mass dog vaccination campaigns. However, although several approaches to determining the dog population size have been described (summarised in the Canine Rabies Blueprint [Global Alliance for Rabies Control 2013]), difficulties still remain.

For owned dogs, knowledge of the human:dog ratio (HDR) combined with human population data can provide useful preliminary estimates. Dog ecology studies from across Africa indicate relatively consistent HDR values in rural settings (Davlin & Vonville 2012; Knobel et al. 2008), but the HDR can vary widely, particularly in urban settings. Furthermore, human population figures are generally obtained from census data, which may only be collected every 10 years, and projections from these data are usually generated from average population growth rates. However, with rapid changes in human demographics, including high rates of urbanisation in Africa (UN Habitat 2008), population growth rates at a local level can vary widely, leading to uncertainties in projected population sizes and, hence, dog population estimates. Therefore, whilst an initial crude estimate of the dog population size can be generated using the projected human population sizes and ‘average’ or ‘typical’ HDRs for planning of first campaigns, these figures should be refined progressively as campaigns are implemented.

An important point in designing household dog population surveys is that estimates of HDR need to explicitly include pups, because pups are not always considered as ‘dogs’ in answer to the question about the number of dogs in a household. It is also important to note that young pups (less than 3 months of age) need to be included for rabies vaccination during annual campaigns (a point that is often not well recognised by either the owners of puppies or veterinary officers). Determining vaccination coverage levels for puppies separately from adults can be useful in order to identify whether low coverage in pups is a problem that needs to be addressed.

Despite uncertainties in most approaches to estimating dog population sizes, it is clear that extremely precise data may not be critical at the initial stages of implementing national strategies and more precise data can be generated as campaigns are rolled out. For procurement purposes, estimates should over-estimate rather than underestimate dog population sizes; provision of excess vaccines at the start of a rabies control programme is generally not problematic, provided the shelf life allows for vaccine to be used in successive campaigns.

In addition to planning campaigns, knowledge of the dog population size is also important in order to determine vaccination coverage, a critical parameter for monitoring vaccination campaigns. During campaigns, vaccination coverage is often determined from the number of dogs vaccinated during a campaign (or vaccine doses used) divided by the estimated dog population size, but given the uncertainties in dog population sizes, these figures are also likely to be unreliable. It should also be noted that, during recurrent campaigns, using vaccine doses to estimate coverage would only provide a conservative estimate, as dogs vaccinated in the previous year(s) and not during the current campaign would not be included in coverage estimates. However, if using vaccines with 2–3 years’ duration of immunity (as is the case for most commercial vaccines), some of these dogs may still be protected against rabies and contributing to population immunity. Because of the critical importance of monitoring vaccination coverage during national control programmes, alternative methods should be adopted to generate more precise values at the community level. Household surveys generate accurate and useful data and it is feasible to include them in vaccination campaigns that adopt ‘house-to-house’ strategies. However, logistic and resource constraints may preclude sampling other communities and, as the ‘even-ness’ of coverage is likely to be an important measure (Townsend et al. 2013), greater emphasis may need to be given to developing relatively cheap and simple population- and community-based survey tools that could be applied more broadly in all vaccinated communities. Other forms of post-vaccination survey include mark-resight surveys, which capture coverage in free-roaming dogs (e.g. Kaare et al. 2009; Kayali et al. 2003; Matter et al. 2000) and could be encouraged as standard methodology for campaigns which are conducted using centralised vaccination stations and in areas with a high proportion of free-roaming dogs. These methods have, in addition, been used to estimate the size of the ownerless dog population (e.g. Gsell et al. 2012).

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