jueves, 13 de noviembre de 2014

Computer Models Can Help Guide Ebola Response - NIH Research Matters - National Institutes of Health (NIH)

Computer Models Can Help Guide Ebola Response - NIH Research Matters - National Institutes of Health (NIH)

National Institutes of Health (NIH) - Turning Discovery Into Health

Contact Us

Mailing Address:
NIH Research Matters
Bldg. 31, Rm. 5B64A, MSC 2094
Bethesda, MD 20892-2094

About NIH Research Matters

Editor: Harrison Wein, Ph.D.
Assistant Editors: Vicki Contie, Carol Torgan, Ph.D.
NIH Research Matters is a weekly update of NIH research highlights from the Office of Communications and Public Liaison, Office of the Director, National Institutes of Health.
ISSN 2375-9593

Computer Models Can Help Guide Ebola Response

At a Glance

  • Computer model projections provide insight into the dynamics of the Ebola outbreak.
  • Such computational models can help predict the potential course of the outbreak and guide more effective control efforts and preparedness strategies.
The 2014 Ebola outbreak in West Africa is the largest such outbreak in history. By the end of October, nearly 14,000 cases were reported in 8 countries, and about 5,000 deaths.
Staff in West Africa enter data to help get Ebola under control. Image courtesy of CDC.
The Ebola virus can spread through direct contact with the blood or secretions of an infected person. Symptoms usually appear 2 to 21 days after exposure. Infection can cause fever, headache, body aches, weakness, stomach pain, and lack of appetite. Later symptoms include vomiting, diarrhea, and in some cases, internal and external bleeding (hemorrhage). There are no approved drugs, but early care can improve survival.
The best way to limit the international spread of Ebola and minimize the death toll is to control the disease at its source. Recent advances in computational and mathematical research are now helping scientists track and predict the potential course of the current outbreak. One research team from Yale University, Oregon State University, and the Ministry of Health and Social Welfare in Liberia developed a computer model of Ebola transmission in the current outbreak to assess containment strategies.
The team modeled Ebola transmission within and between communities, hospitals, and funerals. They combined demographic data with data from the current outbreak in Liberia—including Ebola cases, deaths, health care worker infections, and hospitalizations. To calculate the risk posed by funeral attendance, they used data collected during a previous Ebola outbreak in the Democratic Republic of the Congo.
To calibrate the model, the researchers used data from before August 8, 2014, when Liberia first established checkpoints to restrict movement from affected regions. Data from the period between August 8 and September 20 when assistance from the international community was deployed, served to validate the model projections. The team, led by Dr. Alison P. Galvani of Yale, was supported by NIH’s National Institute of General Medical Sciences (NIGMS). Results appeared online on October 30, 2014, in Science.
The model suggests that a combination of interventions will be needed to curtail the outbreak over the next few months. These include isolating infectious patients, providing protection for healthcare workers, and contact tracing in the community. Funeral procedures are also an important driver of Ebola transmission. Traditional West African funeral practices may involve washing, touching, and kissing the body. Sanitary funeral processes can thus play a large role in reversing the outbreak. The model suggests however, that the recent cordon sanitaire (placing a barrier around the infected area to contain it) and curfews have had little benefit.
“It is imperative that funeral transmission be stopped, and also that we take other aggressive steps to isolate cases and better protect health care workers,” says study co-author Dr. Jan Medlock of Oregon State University.
The study suggests that the current outbreak can be best contained with immediate action using a combination of strategies. This and other computer models are helping officials to understand the dynamics of the outbreak and develop more effective strategies to slow it.
—by Harrison Wein, Ph.D.


Reference: Science DOI: 10.1126/science.1260612.
Funding: NIH’s National Institute of General Medical Sciences (NIGMS) and the Notsew Orm Sands Foundation.

No hay comentarios:

Publicar un comentario