Application of the GARC Data Logger—a custom-developed data collection device—to capture and monitor mass dog vaccination campaigns in Namibia
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Date
Authors
Athingo, Rauna
Tenzin, Tenzin
Coetzer, Andre
Hikufe, Emmanuel H.
Peter, Josephat
Hango, Laina
Haimbodi, Tangeni
Lipinge, Johannes
Haufiku, Frenada
Naunyango, Matias
Journal Title
Journal ISSN
Volume Title
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Public Library of Science
Abstract
Domestic dogs are responsible for 99% of all cases of human rabies and thus, mass dog
vaccination has been demonstrated to be the most effective approach towards the elimination
of dog-mediated human rabies. Namibia demonstrated the feasibility of this approach
by applying government-led strategic rabies vaccination campaigns to reduce both human
and dog rabies incidences in the Northern Communal Areas of Namibia since 2016. The lessons
learnt using paper-based form for data capturing and management of mass dog vaccination
campaign during the pilot and roll out phase of the project (2016–2018) led to the
implementation of a simple and accurate data collection tool in the second phase (2019–
2022) of the rabies elimination program. In this paper, we describe the implementation of
such custom-developed vaccination tracking device, i.e. the Global Alliance for Rabies Control
(GARC) Data Logger (GDL), and the integration of the collected data into a websitebased
rabies surveillance system (Rabies Epidemiological Bulletin—REB) during 2019 and
2020 campaigns. A total of 10,037 dogs and 520 cats were vaccinated during the 2019 campaign and 13,219 dogs and 1,044 cats during the 2020 campaign. The vaccination data
were recorded with the GDL and visualized via REB. Subsequent GIS-analysis using
gridded population data revealed a suboptimal vaccination coverage in the great majority of
grid cells (82%) with a vaccination coverage below 50%. Spatial regression analysis identified
the number of schools, estimated human density, and adult dog population were associated
with the vaccination performance. However, there was an inverse correlation to human
densities. Nonetheless, the use of the GDL improved data capturing and monitoring capacity
of the campaign, enabling the Namibian government to improve strategies for the vaccination
of at-risk areas towards achieving adequate vaccination coverage which would
effectively break the transmission of rabies.
Description
S1 Appendix. Explanation on OLS, spatial regression model and model diagnostics.
S1 Data. Number of dogs vaccinated and estimated vaccination coverage at the 20x20 KM grid cells in the Northern Communal Area of Namibia, 2019–2020.
S1 Table. Results of Ordinary Least Square model, Spatial Lag Model and Spatial Error Model to assess the variables associated with a log-transformed grid level (20 x 20 km) vaccination coverage against rabies in dogs during 2020 mass dog vaccination campaign in NCA regions, Namibia.
S2 Table. Results of Ordinary Least Square model, Spatial Lag Model and Spatial Error Model to assess the variables associated with a log-transformed grid level (20 x 20 km) vaccination coverage against rabies in dogs during 2019 mass dog vaccination campaign in NCA regions, Namibia.
S1 Fig. Map displaying the locations of vaccination points during the vaccination campaign in 2019 (red dots) and in 2020 (black dots) in the four regions (Oshana, Oshikoto, Omusati and Ohangwena) as downloaded from Rabies Epidemiological Bulletin. The REB allows real time online visualization of vaccination points.
S2 Fig. Map displaying the locations of schools in the four regions (Oshana, Oshikoto, Omusati and Ohangwena) of Northern Communal Area, Namibia (data updated as of 25/ 11/2015) and downloaded from the data world [47].
S3 Fig. The bar graph and time distribution of animal vaccination during 2019 (A and B) and 2020 (C and D) vaccination campaigns in the four regions (Oshana, Oshikoto, Omusati and Ohangwena) of Northern Communal Area, Namibia.
S1 Data. Number of dogs vaccinated and estimated vaccination coverage at the 20x20 KM grid cells in the Northern Communal Area of Namibia, 2019–2020.
S1 Table. Results of Ordinary Least Square model, Spatial Lag Model and Spatial Error Model to assess the variables associated with a log-transformed grid level (20 x 20 km) vaccination coverage against rabies in dogs during 2020 mass dog vaccination campaign in NCA regions, Namibia.
S2 Table. Results of Ordinary Least Square model, Spatial Lag Model and Spatial Error Model to assess the variables associated with a log-transformed grid level (20 x 20 km) vaccination coverage against rabies in dogs during 2019 mass dog vaccination campaign in NCA regions, Namibia.
S1 Fig. Map displaying the locations of vaccination points during the vaccination campaign in 2019 (red dots) and in 2020 (black dots) in the four regions (Oshana, Oshikoto, Omusati and Ohangwena) as downloaded from Rabies Epidemiological Bulletin. The REB allows real time online visualization of vaccination points.
S2 Fig. Map displaying the locations of schools in the four regions (Oshana, Oshikoto, Omusati and Ohangwena) of Northern Communal Area, Namibia (data updated as of 25/ 11/2015) and downloaded from the data world [47].
S3 Fig. The bar graph and time distribution of animal vaccination during 2019 (A and B) and 2020 (C and D) vaccination campaigns in the four regions (Oshana, Oshikoto, Omusati and Ohangwena) of Northern Communal Area, Namibia.
Keywords
Domestic dogs, Dogs (Canis familiaris), Namibia, Human rabies, Vaccination, Global Alliance for Rabies Control (GARC), GARC data logger (GDL)
Sustainable Development Goals
Citation
Athingo R, Tenzin T, Coetzer A, Hikufe EH,
Peter J, Hango L, et al. (2020) Application of the
GARC Data Logger—a custom-developed data
collection device—to capture and monitor mass
dog vaccination campaigns in Namibia. Plos Neglected Tropical Diseases 14(12): e0008948. https://DOI.org/10.1371/journal.pntd.0008948.