911今日黑料

Ebola. The word alone implies a death sentence, and for 11,310 people in West Africa between March 2014 and April 2016 that is exactly what it was. In 2014 the world wasn鈥檛 ready: previous outbreaks, such as in DR Congo in 2012, had caused a maximum of 36 deaths. Being unprepared was part of the problem, but the sheer scale of the disaster means that 911今日黑料 scientists are more determined than ever to make sure the lessons are learned.

One of those at the very forefront of the battle, both then and now, is clinical research fellow in the Department of Medicine, Dr Nathalie MacDermott. She travelled to Liberia in early July 2014 with one of the first disaster response teams, through the charity Samaritan鈥檚 Purse.

鈥淎t that time no-one in the international community was really concerned,鈥� she remembers.

鈥淭he World Health Organisation (WHO) and other experts were still saying it would burn itself out. But when we got there, M茅decins Sans Fronti猫res were already overwhelmed, and asked us to take over the treatment centres in Liberia.鈥�

Those treatment centres had not been designed for an epidemic. 鈥淲e were lying patients on the floor. It was dire. We had to knock through the partition wall of the treatment centre in Monrovia 鈥� ELWA 2 鈥� to add beds. While we were doing that four patients died in two hours.

"Ebola is a horrific, febrile illness transmitted by direct contact with the bodily fluids of infected people. There is diarrhoea and vomiting. Some people bleed from multiple sites and die from that, others have high fevers or seizures before they die.

鈥淏y the end of July the epidemic was out of control 鈥� every day people were coming from a new area, so we could see it spreading throughout the whole country. Our morgue was overflowing.鈥�

At that point two of MacDermott鈥檚 American colleagues contracted Ebola and, subsequently, the whole team was evacuated.

Analysing data in real time

At the same time, Professor Neil Ferguson of the School of Public Health volunteered the services of 911今日黑料鈥檚 MRC (Medical Research Council) Centre for Outbreak Analysis and Modelling to the WHO. In 2019 Professor Ferguson became the first Director of J-IDEA, the Abdul Latif Jameel Institute for Disease and Emergency Analytics. The J-IDEA team is expanding on the MRC Centre鈥檚 work on epidemics to include analysis of other health threats, such as those caused by conflict, natural disasters and climate change. The largest of its kind in the world, the centre analyses data in real time during disease outbreaks to help inform policy at a strategic level, working with governments, the military and NGOs .

鈥淥ur aim was to analyse how rapidly Ebola was spreading across each country and what the variations were within,鈥� explains Ferguson, 鈥渋n order to assess the incubation period, for example, and to answer specific questions such as how many beds were needed in treatment centres. The problem was, the data was incomplete, so trying to analyse the case-to-fatality ratio, for example, gave wildly diverging estimates.鈥�

That is the problem of a disease outbreak in countries without adequate healthcare systems or accurate data recording. MacDermott describes the 鈥榩erfect storm鈥� that allowed Ebola to spread so rapidly throughout Liberia, Sierra Leone and Guinea.

鈥淭he three countries border each other to the north of Liberia, and people travel across those borders all the time 鈥� for trade, for medical treatment or to visit family. There was no contact-tracing in place, nor proper burial facilities, and corpses are highly infectious.

鈥淭his part of the world had never seen Ebola before so health workers weren鈥檛 trained, and in any case there鈥檚 a lack of health infrastructure in these countries, still reeling from civil wars. Some of the areas were urban, which meant disease spread quickly.鈥�

ELWA 2, for example, received patients from the West Point slum, with its high population density and Point slum, with its high population density and limited hygiene, such as communal latrines.

Then there were the beliefs and behaviour of the local population. 鈥淧eople were rioting outside the compound,鈥� explains MacDermott.

鈥淭hey were afraid. They didn鈥檛 want the treatment centre there, because it would mean sick people coming. There was also a widespread belief that Ebola didn鈥檛 really exist, that it was a hoax by the government to gain aid money, or that people were being taken to treatment centres for organ harvesting. In West Point, families were taking sick relatives away from the holding centre on infected mattresses.鈥�

Ferguson says one the biggest lessons learned by the MRC centre from the outbreak is the 鈥渋mportance of the behaviour of individuals in stopping the spread of a disease. Where you have distrust of authority and government, for example, imposing control can be counter-productive.鈥� The centre, he says, has since brought social scientists into its work, to try and model behaviour. 鈥淲e can鈥檛 yet do it reliably,鈥� he says. 鈥淵ou can count cases of hospitalisation, but quantifying behaviour is much more difficult.鈥�

Since the Ebola outbreak, he says, the centre has also developed more sophisticated data processing tools.

鈥淭he data [in 2014] was so noisy and full of errors that it took time to clean up. We are developing open-source tools that can do it more efficiently. Silicon Valley software engineers are also working on this in their spare time.鈥� And his team is developing better criteria for resource allocation.

鈥淭he World Bank鈥檚 new pandemic emergency funding facility, backed by insurance policies, aims to improve the way money is allocated to tackle these types of epidemics. We鈥檝e helped develop the quantitative criteria for pay-outs used by that scheme.鈥�

Comprising around 130 staff, the centre had previously worked on SARS, swine flu and MERS (Middle Eastern respiratory syndrome) coronavirus outbreaks, but Ferguson says Ebola took them, like everybody else, by surprise. 鈥淲e hadn鈥檛 done significant research on Ebola prior to 2014,鈥� he says.

鈥淚t didn鈥檛 cause much concern. It was lethal but outbreaks had always been contained; no-one thought it would cause a large epidemic. That is one lesson: don鈥檛 dismiss a pathogen because you think you know it.鈥�