Evaluating the Impact and Capacity of SILAB in Animal Disease Surveillance and Data Quality Assessment in Namibia

This abstract has been accepted at the 2024 DHIS2 Annual Conference

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session link: Animal Surveillance And Response - DHIS2 For Zoonoses

Evaluating the Impact and Capacity of SILAB in Animal Disease Surveillance and Data Quality Assessment in Namibia

Namibia faces a range of animal infectious diseases, prompting the implementation of SILAB for diagnostic and epidemiological surveillance support in 2010. The study assessed Central Veterinary Laboratory (CVL) capacity, the quality of generated data and the epidemiological potential of SILAB (Laboratory Information Management System) in surveillance. All laboratory data from 2020 was retrieved for quality assessment, whilst rabies reports spanning 2018 to 2020 were pulled for statistical and spatial scan analysis using Stata and SatScan software, and DHIS2 for output visualisation. CVL exhibited extensive testing, predominantly for brucellosis screening in healthy animals and sampling related to food safety, reflecting strong capacity, biased towards infectious diseases with economic and human health impact. For rabies, increased laboratory activity and rising positive rates over time, notably in dogs in populous northern areas and kudus in the south, were documented. The odds of disease increased by each year, peaking in rainy and cold dry seasons, and in the north, across all species. This study showcases CVL’s pivotal role in generating health data and SILAB’s value in surveillance and outbreak investigation. Trends and spatial clusters were effectively identified through statistical methods and displayed by DHIS2. SILAB proved an effective tool for managing large national datasets and its epidemiological value was enhanced by integration with statistical and visualisation software. This research project has laid the groundwork for a multisectoral collaboration, including the potential of human and animal data integration through DHIS2, and its rollout in all African and Asian SILAB-user countries could bolster countries’ responses to public health threats.

Primary Author: Ercole Del Negro

SILAB, Africa, Asia, America, Veterinary, Data Integration, Epidemiology, Public Health, Statistical Analysis, Health Data Visualization