Dog population estimates and rabies vaccination optimization using the High-Resolution Settlement Layer (HRSL) – a proof of principle for the Oshana region, Namibia

Author:

Freuling Conrad M.ORCID,Czaja Eva-Maria,Wysocki Patrick,Athingo Rauna,Tenzin Tenzin,Müller Thomas

Abstract

AbstractDespite being vaccine preventable, dog-mediated rabies continues unabated in low-resourced countries in Africa and Asia. For interventions into dog rabies control, an estimate of the dog population is a prerequisite. Here we used a High-Resolution Settlement Layer (HRSL) with an unprecedented resolution of 30m grid length that is Open Source for dog populations estimates and studies on vaccination coverages, with the Oshana region of Namibia as an example. Our analyses show that the average dog density per km2is 8.15 but ranges between 0 and 40 per constituency, with individual densities being as high as 551.Spatial analyses for different settings of static vaccination points indicate that the previously used vaccination points during the pilot phase and cattle crush-pens are insufficient for reaching a 70% vaccination level in the Oshana region. Based on cost calculations, between US$5.29 and US$7.77 are needed to parenterally vaccinate dogs in this region, suggesting that oral rabies vaccination may be a cost-effective supplement or even replacement. The high-resolution spatial analyses are exemplified for rabies, but any other One Health intervention, particularly for Neglected tropical diseases in highly heterogenous and remote areas could use our approach as a template.Author SummaryHere, we used high-resolution geospatial data for demonstrating and validating its utility to assist veterinary authorities in their fight against dog-mediated rabies on the example of the Oshana region in Namibia. With such detailed data it is possible estimate the dog population and to analyse and optimize vaccination strategies in dog rabies endemic areas. Such analyses are exemplified for rabies, but any other One Health intervention, particularly for Neglected tropical diseases in highly heterogenous and remote areas could use our approach as a template.

Publisher

Cold Spring Harbor Laboratory

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