Surveillance system assessment in Guinea: Training needed to strengthen data quality and analysis, 2016

The 2014–2016 Ebola virus disease outbreak revealed the fragility of the Guinean public health infrastructure. As a result, the Guinean Ministry of Health is collaborating with international partners to improve compliance with the International Health Regulations and work toward the Global Health Security Agenda goals, including enhanced case- and community-based disease surveillance. We assessed the case-based disease surveillance system during October 1, 2015–March 31, 2016, in the Boffa prefecture of Guinea. We conducted onsite interviews with public health staff at the peripheral (health center), middle (prefectural), and central (Ministry of Health) levels of the public health system to document leadership structure; methods for maintaining case registers and submitting weekly case reports; disease surveillance feedback; data analysis; and baseline surveillance information on four epidemic-prone diseases (cholera, meningococcal meningitis, measles, and yellow fever). The surveillance system was simple and paper-based at health centers and computer spreadsheet–based at the prefectural and central levels. Surveillance feedback to stakeholders at all levels was infrequent. Data analysis activities were minimal at the peripheral levels and progressively more robust at the prefectural and central levels. Reviewing the surveillance reports from Boffa during the study period, we observed zero reported cases of the four epidemic-prone diseases in the weekly reporting from the peripheral to the central level. Similarly, the national District Health Information System 2 had no reported cases of the four diseases in Boffa but did indicate reported cases among all four neighboring prefectures. Based on the assessment findings, which suggest low sensitivity of the case-based disease surveillance system in Boffa, we recommend additional training and support to improve surveillance data quality and enhance Guinean public health workforce capacity to use these data.