Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
. 2021 Jun 18;11(1):12898.
doi: 10.1038/s41598-021-92308-7.

Predictors of free-roaming domestic dogs' contact network centrality and their relevance for rabies control

Charlotte Warembourg  1 , Guillaume Fournié  2 , Mahamat Fayiz Abakar  3 , Danilo Alvarez  4 , Monica Berger-González  4   5 , Terence Odoch  6 , Ewaldus Wera  7 , Grace Alobo  6 , Elfrida Triasny Ludvina Carvallo  8 , Valentin Dingamnayal Bal  3 , Alexis Leonel López Hernandez  4 , Enos Madaye  3 , Filipe Maximiano Sousa  9 , Abakar Naminou  3 , Pablo Roquel  4 , Sonja Hartnack  10 , Jakob Zinsstag  5 , Salome Dürr  9
Affiliations

Predictors of free-roaming domestic dogs' contact network centrality and their relevance for rabies control

Charlotte Warembourg et al. Sci Rep. .

Abstract

Free roaming domestic dogs (FRDD) are the main vectors for rabies transmission to humans worldwide. To eradicate rabies from a dog population, current recommendations focus on random vaccination with at least 70% coverage. Studies suggest that targeting high-risk subpopulations could reduce the required vaccination coverage, and increase the likelihood of success of elimination campaigns. The centrality of a dog in a contact network can be used as a measure of its potential contribution to disease transmission. Our objectives were to investigate social networks of FRDD in eleven study sites in Chad, Guatemala, Indonesia and Uganda, and to identify characteristics of dogs, and their owners, associated with their centrality in the networks. In all study sites, networks had small-world properties and right-skewed degree distributions, suggesting that vaccinating highly connected dogs would be more effective than random vaccination. Dogs were more connected in rural than urban settings, and the likelihood of contacts was negatively correlated with the distance between dogs' households. While heterogeneity in dog's connectedness was observed in all networks, factors predicting centrality and likelihood of contacts varied across networks and countries. We therefore hypothesize that the investigated dog and owner characteristics resulted in different contact patterns depending on the social, cultural and economic context. We suggest to invest into understanding of the sociocultural structures impacting dog ownership and thus driving dog ecology, a requirement to assess the potential of targeted vaccination in dog populations.

PubMed Disclaimer

Conflict of interest statement

The authors declare no competing interests.

Figures

Figure 1
Figure 1
Undirected and unweighted dog contact networks. Nodes represent dogs and edges contacts between two dogs. Within these example networks it can be seen that some dogs are more connected than others. (A) Chad—rural 2 (network size = 24), (B) Guatemala—rural 2 (n = 121), (C) Indonesia—rural 2 (n = 61), (D) Uganda—urban/semi-urban (n = 82).
Figure 2
Figure 2
(A) Relative degree and (B) normalized betweenness distributions of ten dog contact networks in Chad, Guatemala, Indonesia and Uganda. Significance codes: 0.001 = ***, 0.01 = **, 0.05 = *, 0.1 = .
Figure 3
Figure 3
Permutation-based linear model (PBLM) results with degree as response variable. (A) Significance and direction of coefficients of the dog-level networks. (B) Proportion of deviance of the PBLM explained by each variable in the dog-level networks. (C) Significance and direction of coefficients of the household-level networks. (D) Proportion of deviance explained by each variable in the household-level networks. Empty field denote variables that were not explored or were not selected for the best models by the PBLM (see methods). Details on the values of the coefficients and p values are presented in the Supplementary Tables S10–S21. Dog-level factors (see also Supplementary Table S3) are: dog's sex (Sex—0: male (baseline), 1: female); body condition score (BCS) of 2 and lower (Low BCS), BCS of 4 and higher (High BCS) with the baseline of BCS = 3; being a guardian dog (Guardian, dummy variable), hunting dog (Hunting, dummy variable), shepherd dog (Shepherd, dummy variable) or raised for meat (Source of meat, dummy variable); free-roaming time (FRT—range from 0 to 10); number of dogs collared per household (NDC, contiguous variable); and distance per 100 m from dogs home to the centroid of the study site (Distance, continuous variable). Household-level factors (see also Supplementary Table S4) are: wealth category based on the Multiple Factor Analysis or the income when available (Wealth, with the lowest level (i.e. poorest) being the baseline); owner finalizing primary school (Primary school), finalizing secondary school (Secondary school), finalizing professional training or university (Higher Education), with absence of formal education being the baseline; owner belonging to the main local ethnicity (Ethnicity, dummy variable), being catholic (Catholic, dummy variable), being evangelic (Evangelic, dummy variable); number of dogs collared per household (NDC, contiguous variable); and distance per 100 m from household to the centroid of the study area (Distance, continuous variable).
Figure 4
Figure 4
Odds ratios derived from the multiple regression quadratic assignment procedure (MRQAP) between dogs (A) or households (B) having the same level per variable investigated and being in contact. Positive association: OR > 1, negative association: OR < 1. Empty field denote variables that were not explored or were not selected for the best models by the MRQAP (see methods). Details on the values of the coefficients and p values are presented in the Supplementary Tables S24–S27. Dog-level factors (see also Supplementary Table S22) are: sex (male versus female), age category (more or less than two years old), BCS category (more or less than 2), reason for keeping the dog (guardian, hunting, shepherd, source of meat), free-roaming time (FRT, always free-roaming, free-roaming by day, by night, a few hours per day or never), and distance per 100 m between the households (Distance, continuous variable). Household-level factors (see also Supplementary Table S23) are: wealth category (Wealth, cluster 1 to 4), education level (Education: no formal education, primary education, secondary education, higher education), ethnicity (Ethnicity, various levels depending on the study site), religion (Religion, various levels depending on the study site) and distance per 100 m between the households (Distance, continuous variable).
See this image and copyright information in PMC

Similar articles

See all similar articles

Cited by

See all "Cited by" articles

References

    1. Bouli FPNO, Awah-Ndukum J, Mingoas KJP, Tejiokem MC, Tchoumboue J. Dog demographics and husbandry practices related with rabies in Cameroon. Trop. Anim. Health Prod. 2020;52:979–987. doi: 10.1007/s11250-019-02085-9. - DOI - PubMed
    1. Van Kesteren F, et al. Dog ownership, dog behaviour and transmission of Echinococcus spp. in the Alay Valley, southern Kyrgyzstan. Parasitology. 2013;140:1674–1684. doi: 10.1017/S0031182013001182. - DOI - PMC - PubMed
    1. Pulczer AS, Jones-Bitton A, Waltner-Toews D, Dewey CE. Owned dog demography in Todos Santos Cuchumatán, Guatemala. Prev. Vet. Med. 2013;108:209–217. doi: 10.1016/j.prevetmed.2012.07.012. - DOI - PubMed
    1. Czupryna AM, et al. Ecology and demography of free-roaming domestic dogs in rural villages near serengeti national park in Tanzania. PLoS ONE. 2016;11:1–24. doi: 10.1371/journal.pone.0167092. - DOI - PMC - PubMed
    1. Ratsitorahina M, et al. Dog ecology and demography in Antananarivo, 2007. BMC Vet. Res. 2009;5:1–7. doi: 10.1186/1746-6148-5-21. - DOI - PMC - PubMed

Publication types