New research from Arizona State University and the University of Tokyo that analyzes transmission rates of Ebola in West African countries shows how rapidly the disease is spreading. The findings, published this month in the journal Eurosurveillance, could prove to be an invaluable resource for public health officials working to combat the unprecedented outbreak.
The new study, led by Dr. Gerardo Chowell of the ASU School of Human Evolution and Social Change and Dr. Hiroshi Nishiura of the University of Tokyo, utilized the principles of epidemic theory to provide a real-time analysis of data from the ongoing Ebola outbreak. The researchers found that transmission rates for each existing case of Ebola consistently showed at least one new (secondary) case of the disease being transmitted. Country-specific analysis of transmission dynamics in Liberia and Sierra Leone showed on average between one and two secondary cases for every existing case.
“Our analysis of the reproduction numbers of Ebola cases shows continuous growth from June to August 2014 that signaled a major epidemic,” Dr. Nishiura said. “Uncontrolled cross-border transmission could fuel a major epidemic to take off in new geographical areas as was seen in Liberia.”
The current outbreak of Ebola, which began in Guinea as early as December 2013, is already the largest outbreak on record and shows no signs of slowing down any time soon. The deadly virus has now spread to five West African nations, resulting in at least 2,400 deaths as of Friday — more than all previous Ebola outbreaks combined. Despite major scale-ups in the public health response, efforts to contain the outbreak are falling short, experts warn. With the number of cases increasing exponentially, some recent estimates indicate that as many as 10,000 people could be infected by the end of September, and potentially hundreds of thousands before the outbreak is contained.
Understanding the dynamics of disease transmission that underlie the outbreak is vital to planning an effective response. Two key parameters describing the spread of an infection are the basic and the effective reproduction number (also called reproductive rates or reproduction ratios), both of which provide a measure of the transmission potential of a disease.
Reproductive rates and disease transmission
Basic reproductive rate
The basic reproductive rate (R0) is thought of as the number of secondary infections produced by a typical case of an infection in a population that is totally susceptible (i.e., every member of the population is at risk). It can therefore be measured by counting the number of secondary cases following the introduction of an infection into a totally susceptible population. For example, if the R0 for influenza in a population is 15, then we would expect it to spread rapidly because each new case of influenza would produce 15 new secondary cases. R0 excludes new cases produced by the secondary cases, etc.
The basic reproductive rate is affected by several factors:
- The rate of contacts in the host population
- The probability of infection being transmitted during contact
- The duration of infectiousness
In general, when R0 < 1 the infection will die out in the long run. But if R0 > 1 the infection will be able to spread in a population, as the number of cases is increasing. The larger the value of R0, the harder it is to control the epidemic.
In many circumstances not all contacts will be susceptible to infection. That is, some contacts will be immune, for example due to prior infection which has conferred lifelong immunity, or as a result of previous immunization. Therefore, not all contacts will become infected and the average number of secondary cases per infectious case will decrease.
This is measured by the effective reproductive rate (Rt)
Effective reproductive rate (Rt)
A population will rarely be totally susceptible to an infection in the real world. The effective reproductive rate (Rt) estimates the average number of secondary cases per infectious case in a population made up of both susceptible and non-susceptible hosts. It can be thought of as the number of secondary infections produced by a typical infective.
Rt = R0x
It is calculated as the basic reproductive rate discounted by the fraction of the host population that is susceptible (x).
For example, if R0 for influenza is 12 in a population where half of the population is immune, the effective reproductive rate for influenza is 12 x 0.5 = 6. Therefore, under these circumstances, a single case of influenza would produce an average of 6 new secondary cases.
The metrics for Rt and R0 are identical: Values of Rt<1 indicate that the epidemic is in a downward trend. By contrast, an epidemic is in an increasing trend if Rt>1. If Rt= 0, then each primary case will replace itself with one secondary case and the disease will continue to persist endemically in the population.
The reproductive rate for a particular disease is a vital piece of information when dealing with infectious pathogens. The metric not only provides an indication of transmission dynamics, but can also help researchers determine the amount of effort which is necessary either to prevent an epidemic or to eliminate an infection from a population. Additionally, comparing reproductive numbers from different points in time during the same outbreak, or from different outbreaks of the same disease, can provide crucial insights into how the pathogen has evolved.
To stop Ebola outbreak, reproductive rate needs to be halved
In the new study, researchers estimated the reproductive rate for Ebola in real time in order to assess the current status of the evolving outbreak across affected countries. The team also compared estimates of the reproductive number for the current outbreak with those previously published for the largest outbreaks in Central Africa. According to the article, the mean reproductive number for Ebola has been estimated at 1.83 for an outbreak in Congo in 1995 and 1.34 in Uganda in 2000.
The team analyzed daily, weekly, and monthly case counts from the World Health Organization; analyses were based on the number of cases as of Aug. 26, 2014. Two groups of data were used: confirmed and probable cases; and the total number of reported cases (confirmed, probable and suspected cases).
The researchers found that the effective reproductive rate was consistently and significantly above 1.0 for the duration of the study period. While it reached as high as 2.0, the average country-specific reproductive number ranged from 1.4 to 1.7 during June and July. In other words, for each existing case of Ebola in July, an average of 1.4 to 1.7 secondary cases were produced.
These rates are consistent with the rate of disease spread from prior outbreaks in Central Africa, the team found. Importantly, however, rates from the previous outbreaks were calculated before any infection control measures were put in place, while the rate for the 2014 outbreak reflects transmission dynamics after the implementation of public health controls. It is likely that the reproductive number would be far higher in the absence of response measures, the researchers note.
After factoring in other relevant parameters, including population dynamics and time- and country-specific trends, the team calculated that the reproductive number needs to be cut at least in half in order to contain the current outbreak.
“Our findings suggest that control of the Ebola epidemic that has taken so many lives could be attained by preventing more than half of the secondary transmissions for each primary case. This could be attained by isolating those with Ebola and tracing each case to its source,” says Dr. Chowell. “Characterizing the distribution of secondary cases from a single case can help healthcare workers and officials understand Ebola transmission dynamics over time in affected countries and gauge the effect of interventions to control spread of the disease.”
The current epidemic is not only the largest on record, but also the first regional outbreak of Ebola in West Africa. The outbreak was not recognized until March 2014, three months after it began, which facilitated the spread to Sierra Leone, Liberia, Nigeria, and now Senegal. The World Health Organization declared the epidemic a Public Health Emergency of International Concern in August.
If the reproductive rate remains constant (ranging from 1.4 to 1.7) for the remainder of the year, as many as 300,000 additional cases would occur within 2014, the team reports.
Drs. Chowell and Nishiura hope the new findings will be used to inform better response measures. By reassessing the reproductive rate after the implementation of new infection controls, public health officials can gain invaluable real-time feedback on the effectiveness of various interventions, allowing them to determine the most effective approach(es) to combat the outbreak. “Close monitoring of this evolving epidemic should continue in order to assess the status of the outbreak in real time and guide control interventions in the region,” adds Dr. Chowell.
To learn more about the innovative techniques used by scientists studying the Ebola outbreak, check out the following PublicHealthWatch article:
- Disease Model Shows ‘1 in 5 Chance’ That Ebola Will Spread To U.S. By The End Of September (publichealthwatch.wordpress.com)
- Mathematical Tool Based On Evolutionary Game Theory Could Improve Public Health Response To Ebola, Future Pandemics (publichealthwatch.wordpress.com)
- New Study Uncovers Startling Finding: Ebola Virus Is Rapidly Mutating As It Spreads Across West Africa (publichealthwatch.wordpress.com)
- How A Computer Algorithm Predicted West Africa’s Ebola Outbreak Before It Was Announced (publichealthwatch.wordpress.com)