Spatial Distribution and Population Estimation of Dogs in Thailand: Implications for Rabies Prevention and Control.

Weerapong Thanapongtharm,Marius Gilbert,Suwicha Kasemsuwan,Tanu Pinyopummintr,Khemmapat Boonyo,Kansuda Leelahapongsathon,Vilaiporn Wongphruksasoong,Anuwat Wiratsudakul

doi:10.3389/fvets.2021.790701

Abstract

Poor management of dog populations causes many problems in different countries, including rabies. To strategically design a dog population management, certain sets of data are required, such as the population size and spatial distribution of dogs. However, these data are rarely available or incomplete. Hence, this study aimed to describe the characteristics of dog populations in Thailand, explore their spatial distribution and relevant factors, and estimate the number of dogs in the whole country. First, four districts were selected as representatives of each region. Each district was partitioned into grids with a 300-m resolution. The selected grids were then surveyed, and the number of dogs and related data were collected. Random forest models with a two-part approach were used to quantify the association between the surveyed dog population and predictor variables. The spatial distribution of dog populations was then predicted. A total of 1,750 grids were surveyed (945 grids with dog presence and 805 grids with dog absence). Among the surveyed dogs, 86.6% (12,027/13,895) were owned. Of these, 51% were classified as independent, followed by confined (25%), semi-independent (21%), and unidentified dogs (3%). Seventy-two percent (1,348/1,868) of the ownerless dogs were feral, and the rest were community dogs. The spatial pattern of the dog populations was highly distributed in big cities such as Bangkok and its suburbs. In owned dogs, it was linked to household demographics, whereas it was related to community factors in ownerless dogs. The number of estimated dogs in the entire country was 12.8 million heads including 11.2 million owned dogs (21.7 heads/km2) and 1.6 million ownerless dogs (3.2 heads/km2). The methods developed here are extrapolatable to a larger area and use much less budget and manpower compared to the present practices. Our results are helpful for canine rabies prevention and control programs, such as dog population management and control and rabies vaccine allocation.

Highlights

The poor management of dog populations, especially stray dogs, may result in different problems that exist in many countries
Previous reports have shown that stray dogs have become a serious public administration problem in many Asian countries, such as China [10], India [11], Bangladesh [12], Indonesia [13], and Cambodia [14]
We evaluated the predictive power of the models using two statistical metrics, the correlation coefficient (COR), and the root mean square error (RMSE) to quantify the goodness of fit (GOF) between the observed values of the model sets and predicted values

Summary

Introduction

The poor management of dog populations, especially stray dogs, may result in different problems that exist in many countries. These problems are complexly related to human and animal health, welfare, socio-economics, politics, and religion. Stray dogs are associated with the transmission of a number of zoonotic pathogens, dog bite injuries, and road traffic accidents [2]. Many of these dogs may be packed and claim a street, which they beg for food, and are a general nuisance to local people and tourists [3]. These dogs cannot be vaccinated or sterilized, and are responsible for sustaining endemic rabies

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Conclusion