Modelling the challenges of managing free-ranging dog populations

Abstract

Free-ranging domestic dogs (FRD) are not only vectors of zoonoses of public health concern, but also pose direct threats to humans, livestock, and endangered wildlife. Many developing countries have struggled to control FRD, despite using both lethal and non-lethal methods. India has amongst the highest FRD populations globally and the highest incidences of dog-mediated human rabies, but only deploys Catch-Neuter-Vaccinate-Release (CNVR) for FRD control as a humane alternative to lethal methods, without evidence of it working successfully. Here, we use an agent-based dog population dynamics model to examine the time, effort, financial resources, and conditions needed to successfully control FRD in a typical urban setting. We simulate several scenarios, from an "ideal world" closed population with easily accessible dogs, to a more realistic open population with heterogeneity in catchability of dogs. In only one "best-case" scenario, CNVR resulted in a significant and lasting reduction in FRD, but with vaccination rates peaking only at 35%, which is half the WHO-recommended coverage. The customisable and portable modelling tool that we have developed allows managers to simulate real world processes and understand the expected effort needed to reduce regional dog populations, and assess methods for achieving effective anti-rabies vaccination coverage.

Figure 1

Sequence of events during each step of DogPopDy.

Figure 2

DogPopDy evaluation using a ‘business as usual’ scenario (no population control intervention). Model dog population was projected over a 30 year period. (A) Dog abundance (pre-breeding season, month = September), and (B) Annual recruitment of juveniles into the adult age class, summarized for 100 DogPopDy iterations. The four assessment intervals are indicated by dashed lines (blue).

Figure 3

DogPopDy evaluation using a ‘best case’ scenario (closed population, all dogs in the population are equally and easily catchable) with a 5 year ABC program (1 ABC center =  ~ 250 ABC surgeries per month). (A) Dog abundance (pre-breeding season, month = September), and (B) Annual recruitment of juveniles into the adult age class, summarized for 100 DogPopDy iterations. The four assessment intervals are indicated by dashed lines (blue).

Figure 4

DogPopDy assessment of a moderate intensity ABC effort using a ‘best case’ scenario (closed population, all dogs in the population are equally and easily catchable). Two ABC centers (~ 500 ABC surgeries per month) represented moderate intensity ABC effort. (A) Dog abundance (pre-breeding season, month = September), and (B) Annual recruitment of juveniles into the adult age class, summarized for 100 DogPopDy iterations. The four assessment intervals are indicated by dashed lines (blue).

Figure 5

DogPopDy assessment of a high intensity ABC effort using a ‘best case’ scenario (closed population, all dogs in the population are equally and easily catchable). Three ABC centers (~ 750 ABC surgeries per month) represented high intensity ABC effort. (A) Dog abundance (pre-breeding season, month = September), and (B) Annual recruitment of juveniles into the adult age class, summarized for 100 DogPopDy iterations. The four assessment intervals are indicated by dashed lines (blue).

Figure 6

DogPopDy assessment of a high intensity ABC effort using a ‘real world’ scenario (open population, capture heterogeneity, 5% dogs inaccessible for population management interventions). The actual number of ABC surgeries performed in a month is influenced by the catchability of the intact dogs in the population. Furthermore, inaccessible dogs and immigration also influence the population dynamics. (A) Dog abundance (pre-breeding season, month = September), and (B) Annual recruitment of juveniles into the adult age class, summarized for 100 DogPopDy iterations. The four assessment intervals are indicated by dashed lines (blue).