Validation of Application SuperDuplicates (AS) enumeration tool for free-roaming dogs (FRD) in urban settings of Panchkula Munic
Free-roaming dogs (FRD) are a serious public health problem in most urban societies of the developing world (1–3) and play an important role in the spread of dog-bite related rabies in countries where the disease is endemic (4). Local governments apply several strategies, including fertility control programmes (5), garbage management and relocation to animal shelters, to limit the size of the FRD population. However, due to infrequent and/or sporadic implementation, these methods have had little impact on the population size of FRD (6). Mass vaccination of FRD against rabies has been advocated as a practical and effective intervention to prevent dog-bite related rabies in countries where it is endemic (4, 7, 8). However, mass vaccination campaigns require 70% coverage to develop critical herd immunity against the virus in the target FRD population (6, 9, 10). Therefore, a lack of information about the true population size of FRD leads to uncertainty if a mass vaccination campaign successfully achieves the necessary level of population coverage (11).
The significance of reliably estimating the FRD population size is important to: assess the impacts of rabies control interventions, dog population management and effect on dog welfare; and to reduce the threat to wildlife (12–15). Enumeration of the FRD population, however, is a time and labor intensive exercise. An accurate estimate of the number of FRD at any given time depends on a number of factors, such as socio-economic status, cultural and social beliefs of the human population and characteristics of the habitat that influence the dynamics of the FRD population (16–18). Many enumeration methods have been employed by researchers to estimate the FRD population in different parts of the world, although the accuracy of such estimates can be questionable (15, 19). In the absence of a gold standard, population estimation methods used for wildlife that are based on the maximum likelihood estimates (MLE) using photographic sight-resight surveys have found acceptance for enumeration of FRD (20). However, these methods require multiple surveys to obtain robust estimates. A methodology that can provide a reliable estimate of the FRD population in an area using a minimum of resources is better suited to the effective implementation of a mass vaccination programme against canine rabies (21).
In an earlier study, Tiwari et al. (21) compared eight methods to enumerate FRD and found that the methods that do not take into account the individual heterogeneity of the dogs potentially underestimate the population size. The Huggin's heterogeneity models (Mh or Mth) with suitable estimators (Jackknife/Chao) were shown to yield robust estimates depending upon if the surveys had reached saturation or not. The number of enumeration surveys conducted is central to the robustness of the estimates, with at least five surveys required to obtain an estimate close to the true population [(22), 69]. However, conducting surveys for 5–6 occasions is not only challenging and resource intensive but may also result in bias from surveyor fatigue (23). To overcome these challenges, an online tool based on the Good-Turing formula to assess species richness, called Application SuperDuplicates (AS), has been shown to provide a robust estimate that is equal to or >70% of the FRD population size with only two consecutive surveys (24). Tiwari et al. (21) concluded that the AS tool (https://Chao.shinyapps.io/SuperDuplicates/), a freely accessible web based calculator could be used to estimate the minimum target FRD population requiring vaccinating with minimal resource implications to control dog-bite related rabies. However, that study only assessed the AS tool in a single rural location. In this study, we test if the AS tool is as effective in urban areas where there are more complex environments and higher dog densities. Assuming that the MLE using heterogeneity models with suitable estimators provides an estimate closest to the true population size, we compare this method with the AS tool to estimate the FRD population size in the urban sectors of the Municipal Corporation of Panchkula in northern India.