Impact of interventions and the incidence of ebola virus disease in Liberia—implications for future epidemics

Datos Bibliográficos

ID11490849
AutoresThomas D Kirsch (0000-0001-5190-9829, Johns Hopkins University), Heidi Moseson (0000-0002-2488-2429, Department of Epidemiology & Biostatistics, University of California, San Francisco, San Francisco, CA, USA), Moses Massaquoi (0000-0001-6732-5422, Liberian Ministry of Health, Tubman Blvd, Monrovia, Liberia and), Tolbert Nyenswah (University of Liberia), Tolbert G Nyenswah (Liberian Ministry of Health, Tubman Blvd, Monrovia, Liberia and), Rachel Goodermote (0009-0005-8351-393X, Johns Hopkins University), Isabel Rodriguez-Barraquer (0000-0001-6784-1021, Johns Hopkins University), Justin Lessler (0000-0002-9741-8109, Johns Hopkins University), Derek A T Cumings (Johns Hopkins University), David H Peters (0000-0001-8377-3444, Johns Hopkins University)
Año2017
Volumen32
Número2
Páginas205-214
Fecha de publicación2017-03-01
Peer ReviewedSí
Open AccessSí
TipoARTICLE
RevistaHealth Policy and Planning (JOURNAL)
Identificadores de la revistaISSN: 0268-1080 • E-ISSN: 1460-2237
EditorialOxford University Press (PUBLISHER • GB)
DOI10.1093/heapol/czw113
PMID28207062
OpenAlexW2541599508
IdiomaEN
Citas recibidas10
Referencias citadas5

To better understand the impact of national and global efforts to contain the Ebola virus disease epidemic of 2014–15 in Liberia, we provide a detailed timeline of the major interventions and relate them to the epidemic curve. In addition to personal experience in the response, we systematically reviewed situation reports from the Liberian government, UN, CDC, WHO, UNICEF, IFRC, USAID, and local and international news reports to create the timeline. We extracted data on the timing and nature of activities and compared them to the timeline of the epidemic curve using the reproduction number—the estimate of the average number of new cases caused by a single case. Interventions were organized around five major strategies, with the majority of resources directed to the creation of treatment beds. We conclude that no single intervention stopped the epidemic; rather, the interventions likely had reinforcing effects, and some were less likely than others to have made a major impact. We find that the epidemic’s turning coincided with a reorganization of the response in August–September 2014, the emergence of community leadership in control efforts, and changing beliefs and practices in the population. Ebola Treatment Units were important for Ebola treatment, but the vast majority of these treatment centre beds became available after the epidemic curve began declining. Similarly, the United Nations Mission for Ebola Emergency Response was launched after the epidemic curve had already turned. These findings have significant policy implications for future epidemics and suggest that much of the decline in the epidemic curve was driven by critical behaviour changes within local communities, rather than by international efforts that came after the epidemic had turned. Future global interventions in epidemic response should focus on building community capabilities, strengthening local ownership, and dramatically reducing delays in the response

Ebola virus · Economic growth · Economics · Environmental health · Geography · Government (linguistics) · Intervention (counseling) · Outbreak · Political science · Population · Psychological intervention · Sociology · Timeline · COVID-19 epidemiological studies · Demography · Disaster Response and Management · Medicine · Viral Infections and Outbreaks Research · Virology