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. 2015 May 26;2:150019. doi: 10.1038/sdata.2015.19

A review of epidemiological parameters from Ebola outbreaks to inform early public health decision-making

Maria D Van Kerkhove 1,2,a, Ana I Bento 1, Harriet L Mills 1, Neil M Ferguson 1, Christl A Donnelly 1
PMCID: PMC4443880  PMID: 26029377

Abstract

The unprecedented scale of the Ebola outbreak in West Africa has, as of 29 April 2015, resulted in more than 10,884 deaths among 26,277 cases. Prior to the ongoing outbreak, Ebola virus disease (EVD) caused relatively small outbreaks (maximum outbreak size 425 in Gulu, Uganda) in isolated populations in central Africa. Here, we have compiled a comprehensive database of estimates of epidemiological parameters based on data from past outbreaks, including the incubation period distribution, case fatality rate, basic reproduction number (R0), effective reproduction number (Rt) and delay distributions. We have compared these to parameter estimates from the ongoing outbreak in West Africa. The ongoing outbreak, because of its size, provides a unique opportunity to better understand transmission patterns of EVD. We have not performed a meta-analysis of the data, but rather summarize the estimates by virus from comprehensive investigations of EVD and Marburg outbreaks over the past 40 years. These estimates can be used to parameterize transmission models to improve understanding of initial spread of EVD outbreaks and to inform surveillance and control guidelines.

Subject terms: Epidemiology, Ebola virus, Viral epidemiology, Viral infection

Background & Summary

Ebola virus disease (EVD), formerly known as Ebola hemorrhagic fever, is caused by a zoonotic virus first discovered in 1976 in remote villages of Democratic Republic of Congo (DRC, formerly Zaire) and Sudan1–4. The virus was again identified in the mid-1990s, when it re-emerged in Gabon and Kikwit, DRC5,6. Since then, there have been sporadic outbreaks in human and non-human-primate populations, primarily in remote areas in central Africa (Table 1)7–9. There are five Ebola viruses: Zaire ebolavirus, Sudan ebolavirus, Bundibugyo ebolavirus, Tai Forest ebolavirus and Reston ebolavirus. The most lethal is the Ebola Zaire virus. Ebola Reston is unique among the five Ebola viruses in that it is not known to cause disease in humans10 and Ebola Tai Forest has only been reported in 1 human case11. Together with Marburg virus, Ebola forms the Filoviridae family (filovirus)8.

Table 1. Human Outbreaks of Ebola Zaire, Ebola Sudan and Ebola Bundibugyo from 1976 to present.

Outbreak Year Ebola virus Number of confirmed, probable and suspected cases
Outbreaks with more than 1 case are included in the table.
     
DRC=Democratic Republic of Congo; The outbreak in West Africa includes cases from the following countries: Guinea, Liberia, Mali, Nigeria, Senegal and Sierra Leone, Spain, United Kingdom, and United States.
     
Yambuku, DRC2 1976 Zaire 318
South Sudan1 1976 Sudan 284
Nzara, Sudan24 1979 Sudan 34
Gabon6 1994–1995 Zaire 49
Kikwit, DRC5 1995 Zaire 315
Maybout, Gabon* 1996 Zaire 37
Booue, Gabon6 1996–1997 Zaire 60
South Africa74 1996 Zaire 2
Gulu, Uganda45,52,53 2000–2001 Sudan 425
Republic of Congo and Gabon75 2001–2002 Zaire 65 in Gabon, 59 in Congo
Republic of Congo25,72 2002–2003 Zaire 143
Mbomo, Republic of Congo25 2003 Zaire 35
Yambio, South Sudan 2004 Sudan 17
Etoumbi, Republic of Congo25 2005 Zaire 12
Kasai Occidental Province, DRC23 2007 Zaire 264
Bundibugyo District, Uganda47 2007–2008 Bundibugyo 116
Kasai Occidental Province, DRC 2008–2009 Zaire 32
Orientale Province, DRC§ 2012 Bundibugyo 77
Kibaale District, Uganda|| 2012 Sudan 24
Luwero District, Uganda 2012–2013 Sudan 7
Équateur province, DRC49 2014 Zaire 69
West Africa# 2014–2015 Zaire >26,000

*Reference: WHO 26 April 1996 Disease Outbreak News. 1996- Ebola haemorrhagic fever in Gabon- Update3: www.who.int/csr/don/1996_04_26b/en/.

Reference: WHO 7 August 2004: WHO announces end of Ebola Outbreak in Southern Sudan: www.who.int/csr/don/2004_08_07/en/.

Reference: WHO Disease Outbreak News: www.who.int/csr/don/2009_02_17/en/.

||Reference: WHO Disease Outbreak News: www.who.int/csr/don/2012_09_03/en/.

Reference: WHO Disease Outbreak News: www.who.int/csr/don/2012_11_30_ebola/en/.

#Outbreak is ongoing in Guinea, Liberia and Sierra Leone. Case count reflects cases reported as of 29 April 2015.

The primary reservoir of the Ebola virus is believed to be fruit bats12,13. However, non-human primates, including chimpanzees, gorillas, and cynomolgus monkeys, and forest antelopes have been reported as possible vectors in transmission to humans14, and EVD has caused devastating mortality in non-human-primate populations15. Once infected, the symptoms of human EVD are non-specific and typically include fever, headache, joint or muscle pain, sore throat, vomiting, and/or diarrhea15–17. More severe cases involve hemorrhagic manifestations, shock and other neurological symptoms14,16–21.

While it has been difficult to trace the source of human outbreaks, it is believed that EVD outbreaks usually start from a zoonotic source with subsequent human-to-human transmission22,23. Transmission between humans occurs through exposure to infectious bodily fluids, typically from close contact with infectious individuals when caring for EVD patients (e.g., sharing of contaminated needles, family home care, insufficient protective measures among health care workers in health care settings6,24,25) or with fatal EVD patients in preparation for burial19,20. Control measures for EVD are well documented and include identification, isolation and care of suspected patients, strict infection prevention and control among those caring for patients and safe burials26,27.

At the start of an infectious disease outbreak, it is critical to understand the transmission dynamics of the pathogen and to determine those at highest risk for infection or severe outcomes in the population(s) affected28,29. This information is needed to develop interventions to reduce the spread of disease and to reduce morbidity and mortality in the affected populations. Real-time analysis of any ongoing outbreak by analyzing detailed information collected on the confirmed, probable and suspected cases and deaths provides an opportunity to determine the stages of disease and areas where control measures can be applied. For example, knowledge of the incubation period distribution of the pathogen will inform the duration of time required to follow up the contacts of cases to evaluate whether or not they become secondary cases. Additionally, information on the timing of symptom onset, isolation, hospitalization and outcome (either death or recovery) are important to understand EVD progression. Mathematical models which make use of available data early in an outbreak to estimate the outbreak’s potential impact are increasingly used by public health policy makers to inform decision making around emerging and re-emerging pathogens28–30.

The purpose of this review was to collect all published epidemiological parameter estimates (reprinted in detailed tables containing estimates, and corresponding confidence intervals) estimated from past EVD outbreaks. Our aim was not to perform a meta-analysis, but rather to compile and document the available parameter estimates based on data from EVD outbreaks over the past 40 years. In order to estimate any of the parameters referenced in our manuscript, we would need detailed case data of each of the cohorts studied in the original papers, which we do not have. We also reprint parameter estimates from past Marburg outbreaks and the ongoing outbreak in West Africa for comparison. This information is valuable for public health organizations that need to quickly evaluate the early behavior of a new outbreak and estimate the potential impact, in terms of morbidity, mortality and geographic spread. We highlight how the parameter estimates we have examined improve our understanding of EVD epidemiology. Our results help to put the ongoing EVD outbreak in West Africa into context and to assess the likely effects of ongoing and novel interventions.

Methods

Data collection

All searches using the following search terms (Ebola, Marburg, EHF, EVD, MHF, EBOV, Ebola Zaire, Ebola Sudan, Ebola Reston, Ebola Bundibugyo, outbreak, model, parameterization, incubation period, case fatality rate, case fatality rate (CFR), risk factors, basic reproduction number, R0, effective reproduction number, serial interval, delay distributions, generation time) were carried out on 1 August 2014, 15 September 2014 and again in February 2015 using the following databases: ScienceDirect, ResearchGate, Google, GoogleScholar, BioOne, Web of Science and PubMed. Our searches aimed to find primary reports describing and analyzing data collected from investigations of EVD and Marburg outbreaks since the virus was identified in 1976. The criteria for inclusion were: sample size of EVD cases described in the study ≥5, studies of human outbreaks, studies which evaluated potential risk factors had to report prevalence proportion ratios, odds ratios or relative risks. Reviews, commentaries, case reports on individual cases, and policy pieces were excluded. Additionally, literature evaluating non-human outbreaks or the potential for international (human) spread of EVD outside of an outbreak zone was excluded.

Using these search terms, a total of 49 papers were determined eligible for inclusion. In addition, for context we included additional published information on EVD including the final outbreak sizes as reported by the World Health Organization (WHO) Disease Outbreak News following declaration that each outbreak was over.

From the relevant EVD and Marburg literature, we extracted the following details for all parameter estimates (as provided): point estimates, confidence intervals, ranges, sample size used to estimate the parameter (total numbers of cases encompassing confirmed, suspected, and retrospectively diagnosed cases, depending on the study), EVD virus, and inferential methods. We then compiled the parameter estimate database into tables. Table 1 and Data Citation 1 list the human outbreaks of Ebola Zaire, Ebola Sudan and Ebola Bundibugyo that have occurred in Africa from 1976 to present. We have not provided detailed information on the outbreaks as these have been previously described9. Table 2 (available online only) summarizes the literature we used in this review.

Table 2. List of studies used in the review and the estimated parameters.

Estimated Parameters
             
Study Virus Year ofoutbreak Incubation PeriodDistribution R0 Rt Serial Interval*Distribution GenerationTime Distribution Delay Distributions CFR RFI
CFR refers to case fatality rate.
                   
RFI refers to risk factor for infection.
                   
International Commission2 EBOV Zaire 1976 x x x
Camacho et al. 38 EBOV Zaire 1976 x x x x
WHO International Study Team1 EBOV Sudan 1976 x x
Baron et al. 24 EBOV Sudan 1979 x x x
Dowell et al. 39 EBOV Zaire 1995 x x x x
Bwaka et al. 37 EBOV Zaire 1995 x x
Chowell et al. 44 EBOV Zaire and Sudan 1995; 2000–2001 x x x x
Lekone & Finkenstädt42 EBOV Zaire 1995 x x
Eichner et al. 40 EBOV Zaire 1995 x
Ndambi et al. 43 EBOV Zaire 1995 x x
Khan et al. 5 EBOV Zaire 1995 x x x
Muyembe & Kipasa70 EBOV Zaire 1995 x x
Legrand et al. 59 EBOV Zaire and Sudan 1995; 2000–2001 x
Ferrari et al. 58 EBOV Zaire 1995 x
Sadek et al. 50 EBOV Zaire 1995 x x x
Rowe et al. 20 EBOV Zaire 1995 x
Bertherat et al. 71 EBOV Zaire 1995 x
Ndanguza et al. 35 EBOV Zaire 1995 x x
White & Pagano60 EBOV Zaire 1995 x x
Georges et al. 6 EBOV Zaire 1996 x x
Okware et al. 53 EBOV Sudan 2000–2001 x x x x
Borchert et al. 51 EBOV Sudan 2000 x x
Lamunu et al. 52 EBOV Sudan 2000–2001 x x
Francesconi et al. 45 EBOV Sudan 2000–2001 x x
Nkoghe et al. 25 EBOV Zaire 2005 x x
MacNeil et al. 46 EBOV Bundibugyo 2007 x x
Wamala et al. 47 EBOV Bundibugyo 2007 x x x x
Roddy et al. 19 EBOV Bundibugyo 2007 x x
Althaus36 EBOV Zaire 2014–2015 x x
Gomes et al. 62 EBOV Zaire 2014–2015 x
Fisman et al. 30 EBOV Zaire 2014–2015 x x
Nishiura & Chowell65 EBOV Zaire 2014–2015 x
WHO Ebola Response Team16 EBOV Zaire 2014–2015 x x x x x x
WHO Ebola Response Team17 EBOV Zaire 2014–2015 x x x x x
Althaus et al. 61 EBOV Zaire 2014–2015 x x x x
Fasina et al. 54 EBOV Zaire 2014–2015 x x x
Faye et al. 41 EBOV Zaire 2014–2015 x x x x x
Lewnard et al. 64 EBOV Zaire 2014–2015 x
Towers et al. 66 EBOV Zaire 2014–2015 x
Maganga et al. 49 EBOV Zaire 2014 x x x x
Webb et al. 68 EBOV Zaire 2014–2015 x
White et al. 69 EBOV Zaire 2014–2015 x
Yamin et al. 76 EBOV Zaire 2014–2015 x
Rivers et al. 48 EBOV Zaire 2014–2015 x x x x
Colebunders et al. 57 Marburg 1998 x x
Bausch et al. 56 Marburg 1998 x
Ajelli & Merler55 Marburg 2005 x x x x

*Some of the studies refer to this parameter estimate as generation time but actually estimate serial interval.

Our manuscript and tables include estimates, confidence intervals and ranges obtained from the referenced publications (Table 2 (available online only) and Data Citation 2).

Definition of key parameters recorded

The incubation period is the interval between exposure to a pathogen and initial occurrence of symptoms and signs28,29. The incubation period distribution is usually characterized using the mean or the median incubation period.

The CFR is the proportion of cases (infected symptomatic individuals) within a designated population who die as a result of their infection. For past EVD and Marburg outbreaks, we report on the CFR estimated after the outbreak was declared over (estimated at least 42 days after the last case experienced symptom onset) by taking the number of deaths among cases divided by the total number of cases recorded during the outbreak. However, during outbreaks, the CFR is often estimated before all cases have been identified and before some cases have either recovered or died.

Risk factors for infection include demographic factors, medical conditions and behavioral exposures or practices that are associated with an individual’s risk of becoming infected with Ebola.

The basic reproduction number (R0) is used to measure the transmission potential of a disease. It is the average number of secondary infections produced by an infected case in a susceptible population31. If R0 >1, then once established the outbreak will continue, whereas if R0<1, then the outbreak will die out.

The effective reproduction number (Rt) is similar to R0 but relates to a particular calendar time t (after the start of the outbreak). Like R0, if Rt>1, then the outbreak will continue, whereas if Rt<1, then the outbreak will die out. Rt can be reduced through the use of successful control measures (e.g., by limiting contacts between susceptible and infectious individuals). Rt can also be reduced due to the depletion of susceptible individuals whether through extensive transmission or through the immunization of susceptible individuals32.

The serial interval is the interval between symptom onset in an index case and symptom onset in a secondary case infected by that index case33.

The generation time is the interval between infection of an index case and infection of a secondary case infected by that index case. The serial interval is more frequently estimated than the generation time and is often assumed to be the same duration as the generation time34.

Delay distributions

  1. Symptom onset to hospitalization (also referred to as onset to clinical assessment): The interval between symptom onset and hospitalization.

  2. Hospital admission to day of first blood sample: The interval between admission to hospital or medical facility for treatment of EVD and when a biological sample is collected for diagnosis.

  3. Symptom onset to recovery/discharge: The interval between symptom onset and recovery or hospital discharge.

  4. Symptom onset to death: The interval between symptom onset and death.

  5. Duration of admission (survivors)—hospitalization to discharge: The interval between admission to a hospital or medical facility for treatment of EVD and discharge from the facility.

  6. Duration of admission (fatal cases)—hospitalization to death: The interval between admission to a hospital or medical facility for treatment of EVD and death.

Data Records

The data from this analysis are summarized in two types of data format. Four data tables detail the methods and parameter estimates from each study included in our review. Our data tables:

  1. Table S1: Human Outbreaks of Ebola Zaire, Ebola Sudan and Ebola Bundibugyo from 1976 presents compiled data on the year and location of the each human outbreak, the Ebola Virus causing the outbreak and number of cases reported (Data Citation 1).

  2. Table S2: Parameter Estimates by Outbreak presents a comprehensive list of parameter estimates, including incubation period distribution, reproduction number, serial interval distribution, generation time distribution, delay distributions, and CFR by Ebola virus and study (Data Citation 2).

  3. Table S3: Parameter estimates for the ongoing EVD outbreak in West Africa presents published estimates of delay distributions and CFR for the ongoing outbreak in West Africa (Data Citation 3).

  4. Table S4: Risk factors for EVD and Marburg infection presents published results from outbreak (Data Citation 4).

Using these four tables, we then summarized the parameter database in six tables and two figures presented in this article. The parameters estimated for Ebola Zaire, Ebola Sudan and Ebola Bundibugyo outbreaks, including the incubation period distribution, serial interval distribution, R0, delay distributions and CFR, are shown in Tables 3 (available online only), 4 (available online only), 5, respectively. Parameter estimates for the ongoing outbreak in West Africa are summarized in Table 6 (available online only) and for Marburg outbreaks are presented in a single table (Table 7). Risk factors for Ebola and Marburg infection are summarized in Table 8 (available online only). Estimates of the incubation period distribution and CFR are presented in Figs 1 and 2, respectively.

Table 3. Parameter Estimates for Ebola Zaire excluding the ongoing outbreak in West Africa.

Parameter Estimate
Med=median; s.d.=standard deviation.
 
Incubation Period Distribution (range of central estimates, (range)) * 5.3–12.7 (1–21) days
Serial interval Distribution (range of mean estimates) 10–16.1 days
Khan et al. (mean) 5 14 days
Muyembe & Kipasa (approximation) 70 10 days
Dowell et al. (median, (range)) 39 Med=17 days (9–25)
White & Pagano (mean, (IQR)) 60 5.82 days (5.43–7.60)
Maganga et al. (median, (range), mean, s.d.) 49 Med=16 days (3–27), 16.1 days, 4.4
R 0 (range of estimates) 1.36–4.71
Chowell et al. (estimate, s.d.) 44 1.83, 0.06
Ferrari et al. (estimate, (95% CI) 58 3.65 (3.05, 4.33)
Legrand et al. (estimate, (95% CI)) 59 2.7 (1.9, 2.8)
Lekone & Finkenstädt (estimate, s.d.) 42 1.36, 0.13
Ndanguza et al. (estimate, (95% CI)) 35 2.22 (1.90, 2.73)
White & Pagano (estimate, (IQR)) 60 1.93 (1.74–2.78)
Camacho et al. (estimate, (95% CI)) 38 4.71 (3.92, 5.66)
R t (range of estimates) 0.84–1.29
Maganga et al. (estimate, (95% CI) 49) 1.29 (−4.72, 7.29)0.84 (−0.38, 2.06)
Delay Distributions (days)
 
 Infectious period
 
  Chowell et al. (mean, s.d.) 44 5.61,0.19
 Symptom onset to…
  … hospitalization (range of mean and median estimates) 4–5; Med=3–4
   Khan et al. (mean, median, (range), n) 5 5, Med=4 (0–19), n=219
   Rowe et al. (mean, s.d., median, (range)) 20 4, 3.3, Med=3 (0–14)
   Camacho et al. (median, (95% CI)) 38 Med=3.00 (2.81, 3.20)
  … death (range of mean estimates) 6–10.1
   Camacho et al. (median, (95% CI)) 38 Med=7.49 (7.30, 7.69)
   Bwaka et al. (mean, (range), n) 37 10.1 (3–21), n=86
   Dowell et al. (median) 39 Med=10
   Khan et al. (mean, median, (range), n) 5 9.6, Med=9 (0–34), n=224
   Nkoghe et al. (mean, (range), n) 25 6.2 (3–13), n=12
Med=6 (<15 years old)
Med=9 (15–29 years old)
   Sadek et al. (median, n) 50 Med=10 (30–44 years old)
Med=8 (45–59 years old)
Med=9.5 (>59 years old), overall n=226
   Georges et al. (range) 6 12–18
   Maganga et al. (median, (range), mean, s.d.) 49 11 (1–30), 11.3, 6.8
  … recovery 10
   Camacho et al. (median, (95% CI)) 38 10.00 (9.80, 10.19)
 Hospitalization to…
  … discharge 17
   Khan et al. (mean, median, (range), n) 5 17, Med=14 (0–56), n=34
  … death 4.6
   Khan et al. (mean, median, (range), n) 5 4.6, Med=4 (0–20), n=185
 Death to burial
  Camacho et al. (median, (95% CI)) 38 Med=0.99 (0.8, 1.18)
Overall Case Fatality Rate (range of estimates)α 0.69–0.88
International Commission (estimate, n, year of outbreak) 2 0.88, n=318, 1976
Muyembe & Kipasa (estimate, n, year of outbreak) 70 0.74, n=136, 1995
Ndambi et al. (estimate, n, year of outbreak) 43 0.78, n=23, 1995
Khan et al. (estimate, n, year of outbreak) 5 0.81, n=315, 1995
Overall: 0.807, n=310, 1995
0.778 (<15 years old)
Sadek et al. (estimate, n, year of outbreak) 50 0.69 (15–29 years old)
0.796 (30–44 years old)
0.89 (45–59 years old)
0.957 (>59 years old)
Chowell et al. (estimate, n, year of outbreak) 44 0.81, n=315, 1995
Nkoghe et al. (estimate, n, year of outbreak) 25 0.83, n=12, 2005
Camacho et al. (estimate, n, year of outbreak) 38 0.88, n=262, 1976
Maganga et al. (estimate, n, year of outbreak) 49 0.74, n=69, 2014

*See Fig. 1 for individual estimates; extreme outlier estimate from Ndanguza et al. 35 not included.

generation time estimated as serial interval.

No methodology provided.

α*See Fig. 2 for CFR estimates.

Table 4. Parameter Estimates for Ebola Sudan .

Parameter Estimate
Med=Median; s.d.=standard deviation.
 
Incubation Period Distribution (range of central estimates, (range)) * 3.35–14 (2–21) days
R 0 (range of estimates) 1.34–2.7
Chowell et al. (estimate, s.d.)44 1.34, 0.03
Legrand et al. (estimate, (95% CI)) 59 2.7 (2.5, 4.1)
Ferrari et al. (estimate, (95% CI)) 58 1.79 (1.52, 2.30)
Delay Distributions (days)
 
 Infectious period…
 
  Chowell et al. (mean, s.d.) 44 3.50,0.67
 Symptom onset to…
 
 … hospitalization 2
  Borchert et al. (mean, (range), n) 51 2 (0–8), n=26
 … death 9
  Baron et al. (median, (range), n) 24 Med=9 (5–15), n=22
 … discharge 12
  Okware et al. (mean, (range), median) 53 12, (2–35), 13
 Hospitalization to…
 
 … discharge (range of mean estimates) 8–10
  Borchert et al. (mean, (range), n) 51 8.0 (2–11) n=8
  Okware et al. (mean, (range)) 53 10 (1–29)
 … death 6.1
  Borchert et al. (mean, (range), n) 51 6.1 (2–13) n=18
Case Fatality Rate (range of estimates) 0.53–0.69
WHO International Study Team (estimate, n, year of outbreak) 1 0.53, n=284, 1976
Baron et al. (estimate, n, year of outbreak) 24 0.65, n=34, 1979
Okware et al. (estimate, n, year of outbreak) 53 0.53, n=425, 2000–2001
Lamunu et al. (estimate, n, year of outbreak) 52 0.53, n=425, 2000–2001
Chowell et al. (estimate, n, year of outbreak) 44 0.53, n=425, 2000–2001
Borchert et al. (estimate, n, year of outbreak) 51 0.69, n=26, 2000

*See Fig. 1 for individual estimates.

See Fig. 2 for CFR estimates.

Table 5. Parameter Estimates for Ebola Bundibugyo .

Parameter Estimate Estimate
Med=median; (NP)=Not Provided.
 
Incubation Period Distribution (days) (mean, (95% CI), median, (range)) * 6.3 (5.2, 7.3), Med=7 (2–20)
Delay Distributions (days)
 
 Symptom onset to…
 
 … hospitalization 3.5
  Roddy et al. (median, (range), n) 19 Med=3.5 (0–8), n=26
 … death (range of medians) 9–10
  Roddy et al. (median, (range), n) 19 Med=9 (3–20), n=11
  Wamala et al. (median, (range), n) 47 Med=10 (3–21), n=(NP)
 …recovery 10
  Wamala et al. (median, (range), n) 47 Med=10 (2–26), n=(NP)
Case Fatality Rate (range of estimates) 0.34–0.42
MacNeil et al. (estimate, n, year of outbreak) 46 0.40, n=43, 2007
Wamala et al. (estimate, n, year of outbreak) 47 0.34, n=116, 2007
Roddy et al. (estimate, n, year of outbreak) 19 0.42, n=26 (hospitalized confirmed), 2007–08

*See Fig. 1 for individual estimates.

See Fig. 2 for CFR estimates.

Confirmed cases only.

Table 6. Parameter estimates for the ongoing outbreak in West Africa.

Parameter All countries * Guinea Liberia Nigeria Sierra Leone References
Rt refers to effective reproduction number.
           
μ=mean; Med=median; s.d.=standard deviation.
           
WHO ERT is the World Health Organization Ebola Response Team16,17.
           
Incubation Period Distribution (days)
           
 Multi-day exposures, observed (mean) 11.4, n=155 10.9, n=20 11.7, n=79 10.8, n=48 16
 Single-day exposures, observed, (median (IQR)) 9 (5–13) 17
 Fitted single-day exposures (mean, (95% CI)) 10.3 (9.9, 10.7) 17
 Fitted values (mean) 12 10 48
Serial interval Distribution (days)
           
WHO ERT 2014 (gamma fit mean, s.d., n) 15.3, 9.3, n=92) 19.0, 11.2, n=40) 13.1, 7.8, n=26) 11.6, 6.3, n=25) 16
WHO ERT 2015 (gamma fit mean, (95% CI), n) 14.2 (13.1, 15.3), n=305 17
Fisman et al. 30 15 days (derived) 30
Faye et al. 2014 (mean, (range), s.d., (95% CI for s.d.)) 14.2 (13.1–15.5), 7.1 (6.2, 8.2) 41
R0 (estimate, (95% CI))
           
 With estimated serial interval 15.3 d 1.71 (1.44, 2.01) 1.83 (1.72, 1.94) 2.02 (1.79, 2.26) 16
 With fixed incubation period 5.3 d 1.51 (1.50, 1.52) 1.59 (1.57, 1.60) 9.0 (5.2, 15.6) 2.53 (2.41, 2.67) 36,61
 Overall, data driven 1.8 (1.5, 2.0) 62
 SEIR model 2.1 (1.9, 2.4) 62
 Community using Legrand et al. 59 model 0.8 (0.3, 0.9) 62
 Hospital using Legrand et al. 59 model 0.4 (0.2, 1.4) 62
 Funeral using Legrand et al. 59 model 0.6 (0.2, 1.0) 62
 Assumed fixed generation time of 15d 1.78 2.46 1.72 8.33 30
 Estimated mean serial interval 15.3d 1.71 (1.44, 2.01) 1.83 (1.72, 1.94) 1.2 (0.67, 1.96) 2.02 (1.79, 2.26) 16
 Overall (Conakry) 1.7 (1.2, 2.3) 41
 Community (Conakry) 1.0 (0.6, 1.5) 41
 Hospital (Conakry) 0.4 (0.2, 0.7) 41
 Funeral (Conakry) 0.3 (0.1, 0.6) 41
 Montserrado only 2.49 (2.38, 2.60) 64
Webb et al. 2015 1.54 1.26 68
Rivers et al. 48 (overall) 2.22 1.78 48
Rivers et al. 48 (community) 1,35 1.11 48
Rivers et al. 48 (hospitals) 0.35 0.24 48
Rivers et al. 48 (funerals) 0.53 0.43 48
Khan et al. 63 (raw data) 1.76 1.49 63
Khan et al. 63 (corrected for underreporting) 1.9 1.37 63
Rt (estimate, (95% CI))
           
 Estimated mean serial interval 15.3 d 1.81 (1.60, 2.03) 1.51 (1.41, 1.60) <1† 1.38 (1.27, 1.51) 16,36
 Estimated mean generation time 12 d 1 1.7 1.4 65
 Sierra Leone (56 days of data) 1.1 (0.95, 1.24) 69
 Montserrado only 1.73 (1.66, 1.83) 76
 Survivors Montserrado only 0.66 (0.10, 1.69) 76
 Non-survivors Montserrado only 2.36 (1.72, 2.80) 76
Observed Delay Distributions (days)
           
Symptom onset to…
           
  … hospitalization
           
   WHO ERT 2014 (mean, s.d., n) 5.0, 4.7, n=1135 5.3, 4.3, n=484 4.9, 5.1, n=245 4.1, 1.4, n=11 4.6, 5.1, n=395 16
   WHO ERT 2015 (mean, (95% CI), n) 5.0 (4.9, 5.1), n=5616 17
   Faye et al. 2014 (mean, s.d., n) 5.0, 3.9, n=152
   Rivers et al. 48 (mean) 3.24 4.12 48
  ... hospital discharge
           
   WHO ERT 2014 (mean, s.d., n) 16.4, 6.5, n=267 16.3, 6.1, n=152 15.4, 8.2, n=41 17.2, 6.2, n=70 16
   WHO ERT 2015 (mean, (95% CI)) 15.1 (14.6, 15.6) 17
  … death
           
   WHO ERT 2014 (mean, s.d., n) 7.5, 6.8, n=594 6.4, 5.3, n=248 7.9, 8, n=212 8.6, 6.9, n=128 16
   WHO ERT 2015 (mean, (95% CI)) 8.2 (7.9, 8.4) 17
   Faye et al. 2014 (mean, s.d., n) 8.9, 4.0, n=82) 41
   Althaus et al. 61 (mean, range) 7.41 (4–17), n=17 61
  … WHO notification 6.1, 8.5, n=2185 7.5, 10.4, n=743 6, 8.7, n=797 4.5, 5, n=634 16
WHO notification to…
           
… hospital discharge (mean, s.d., n) 11.8, 7.2, n=312 11.1, 5.8, n=164 11, 8, n=41 12.7, 8.4, n=102 16
  … death (mean, s.d., n) -3.0, 13.8, n=584 -4.4, 14.4, n=300 -1.8, 13.6, n=221 -1.6, 9.2, n=58 16
Hospitalization to…
           
… discharge
           
  WHO ERT 2014 (mean, s.d., n) 11.8, 6.1, n=290 11, 5.4, n=159 12.8, 8.1, n=40 12.4, 5.8, n=86 16
  WHO ERT 2015 (mean, (95% CI)) 11.2 (10.8, 11.7) 17
  Rivers et al. 48 (recovery) (mean) 15.88 15.88 48
… death
           
  WHO ERT 2014 (mean, s.d., n) 4.2, 6.4, n=121 2.5, 3.4, n=36 4.5, 6, n=63 4.4, 6, n=17 16
  WHO ERT 2015 (mean, (95% CI)) 4.3 (4.1, 4.5) 17
  Rivers et al. 48 (mean) 10.07 6.26 48
Infectious period
           
Rivers et al. 48 (mean) 15.00 18.00 48
Infection to death
           
Rivers et al. 48 (mean) 13.31 10.38 48
Case Fatality Rate (estimate, (95% CI), n)
           
WHO ERT 2014 (based on current status) 37.7 (36.1, 39.2), n=3747 57.5 (53.7, 61.1), n=677 34.7 (32.4, 37.1), n=1616 40.0 (19.8–64.3), n=15 31.6 (29.3, 34.1), n=1439 16
Althaus 36 (based on reported deaths) 74 (72, 75), n=607 71 (69, 74), n=1082 48 (47, 50), n=910 36
All cases (based on definitive outcome)
           
WHO ERT 2014 70.8 (68.6, 72.8), n=1737 70.7 (66.7, 74.3), n=542 72.3 (68.9, 75.4), n=739 45.5 (21.3, 72), n=11 69.0 (64.5, 73.1), n=445 16
WHO ERT 2015 70.4 (69.2, 71.6), n=5616 17
Althaus et al. 61 39 (14, 71), n=20 61
Fasina et al. 54 40 (22, 61), n=20 54
All hospitalized cases
           
WHO ERT 2014 (based on definitive outcome) 63.5 (60.5, 66.3), n=1100 63.4 (58.6, 67.9), n=434 66.6 (61.3, 71.6), n=338 100 (2.5, 100), n=1 61 (55.4, 66.4), n=318 16
WHO ERT 2015 (based on definitive outcome) 60.7 (59.2, 62.3), n=3839 17
Rivers et al. 48 0.500 0.750 48
Subset of Cases
           
Faye et al. 2014 (Conakry) 54 (49, 63), n=152 41

*here all countries refer to Guinea, Liberia and Sierra Leone.

R0 of the index case arriving by air travel from Liberia; Rt estimated to be below 1 within 15 days (95% CI 11–21 days) after arrival of the index case from Liberia36

Authors refer to generation time, but have estimated the serial interval and assumed serial interval is the same as generation time.

Table 7. Parameter Estimates for Marburg.

Parameter Estimate
Med=median; s.d.=standard deviation; (NP)=Not Provided.
 
Generation Time Distribution (days) (mean, 95% CI, s.d., n) * 55 9 (8.2, 10), 5.4, n=374
R 0 (estimate, 95% CI) 1.59 (1.53, 1.66)
Delay Distributions (days)
 
 Symptom onset to death (range of medians) 7–8
  Ajelli & Merler (median, range, n) 55 Med=7 (5–9), n=329
  Colebunders et al. (median, range, n) 57 Med=8 (2–16), n=40
Case Fatality Rate (range of estimates) 0.78–0.88
Ajelli & Merler (estimate, 95% CI, n, year of outbreak) 55 0.88 (0.84–0.91), n=374, 2005
Bausch et al. (estimate, n, year of outbreak) 56 0.83, n=(NP), 1998
Colebunders et al. (estimate, n, year of outbreak) 57 0.78, n=77, 1998

*Authors refer to generation time, but have estimated the serial interval and assumed serial interval is the same as generation time.

See Fig. 2 for CFR estimates.

Table 8. Risk factors for human-to-human transmission for infection with EVD.

Risk Factors for infection OR, PPR, or RR 95% CI Virus References
PPR=Prevalence Proportion Ratio; RR=Risk Ratio; OR=Odds Ratio.        
Physical Contact
       
 Sharing bed with a patient during their late stage of illness RR=2.2 1.2, 4.2 Zaire 39
 Slept in the same hut on the same mat PPR=2.78 1.15, 6.70 Sudan 45
 Touch cadaver RR=2.1 1.1, 4.2 Zaire 39
 Touch body of deceased person PPR=1.95 0.91, 4.17 Sudan 45
 Contact with known suspected case OR=2.7 1.35, 5.24 Bundibugyo 47
 Contact with confirmed case RR=3.21 1.53, 6.75 Zaire 71
 Intimate contact: nursing care OR=5.1 1.31, 15.48 Sudan 24
 Receiving injections OR=7.4 1.6, 33.2 Marburg 56
 Caring for patients at early stage of illness PPR=6.0 1.32, 27.10 Sudan 45
 Cared for the patient until the patient’s death at hospital PPR=8.57 1.95, 37.66 Sudan 45
 Cared for the patient until the patient’s death at home PPR=13.33 3.20, 55.59 Sudan 45
 Contact with body fluids PPR=5.3 2.14, 13.14 Sudan 45
 Direct physical contact with a sick person PPR=3.53 0.52, 24.11 Sudan 45
Non-Physical Contact
       
 Age (>18 years old) RR=3.6 1.3, 10.1 Zaire 39
 Sharing a meal with a patient during their late stage of illness RR=2.2 1.2, 4.0 Zaire 39
 Conversation with a patient during their late stage of illness RR=3.9 1.2, 12.2 Zaire 39
 Shared meals with a sick person PPR=1.94 0.89, 4.22 Sudan 45
 Washed clothes of a sick person PPR=1.68 0.78, 3.60 Sudan 45
 Slept in the same hut PPR=2.16 0.90, 5.19 Sudan 45
 Profession- Miner OR=13.9 3.1, 62.1 Marburg 56
 Travelled before illness OR=2.1 1.0, 4.5 Bundibugyo 47
 Hospitalized or visited hospital OR=2.6 1.4, 4.9 Bundibugyo 47
 Consulted traditional healer OR=0.2 0.01, 1.5 Bundibugyo 47
Funeral-associated contact
       
 Ritual hand washing during funeral PPR=2.25 1.08, 4.72 Sudan 45
 Communal meal during funeral PPR=2.84 1.35, 5.98 Sudan 45
Funeral rites participation OR=4.22 2.2, 8.2 Bundibugyo 47

Figure 1. Estimates of the incubation period distribution by virus, year of outbreak and study.

Figure 1

The dots represent the mean or median estimate and the lines illustrate the range, for all studies, with the exception of MacNeil et al. 46 and WHO Ebola Response Team (ERT) 201517 (fitted) where the line represents the 95% CI for the estimate. Chowell et al. 44, Eichner et al. 40, WHO ERT 2014 (multi-day observed)16 and Lekone and Finkenstädt42 provide standard deviation (s.d.).

Figure 2. Overall case fatality rate (CFR) for Ebola by virus and Marburg virus; we include only those outbreaks that have been declared over.

Figure 2

Outbreaks with fewer than 10 fatal patients were excluded from this figure. For each outbreak, the bars represent the rate of fatal (dark color) and recovered (light color) patients. For country specific information see Table 1. The source of each estimate is denoted by the reference number at the top of each bar.

Technical Validation

Incubation period distribution

The incubation period distribution of EVD has been estimated for past EVD outbreaks (Fig. 1 and Tables 3 (available online only), 4 (available online only), 5; minimum sample size n=5, maximum sample size n=1,798). The mean (or median) incubation period (Fig. 1), for the different Ebola viruses ranged from 3.35 to 12.7 days (range 1–21 days), excluding an extreme outlier35. Central estimates for the incubation period distribution were between 5.3–12.7 days (range 1–21 days) for Ebola Zaire 5,6,16,17,36–43, 3.35–12 days (range 1–16 days) for Ebola Sudan 1,44,45, and 6.3–7 days (range 2–20 days) for Ebola Bundibugyo 46,47.

The mean incubation period for the ongoing Ebola outbreak in West Africa has been estimated to be between 9–12 days (Table 6 (available online only))16,17,41,48. The range of incubation periods observed in past EVD outbreaks supports the policy of contact tracing for 21 days following contact with an EVD patient. An outbreak is officially declared over after no new cases are identified 42 days (2 times the 21-day maximum incubation period) after the last EVD case is found.

Case fatality rate (CFR)

In Fig. 2 and Tables 3 (available online only), 4 (available online only), 5, we reprint the estimated CFR for each Ebola outbreak (by virus) and for Marburg virus. The Ebola Zaire virus is the most lethal with an overall estimated CFR ranging from 69 to 88%2,5,25,38,43,49,50 (Table 3 (available online only)). The CFR of outbreaks due to Ebola Sudan virus ranged from 53 to 69%1,24,51–53 (Table 4 (available online only)), and the CFR of outbreaks due to Ebola Bundibugyo ranged from 34 to 42%19,46,47 (Table 5). For the ongoing outbreak in West Africa due to Ebola Zaire, the estimated CFR, as measured among confirmed and probable cases with definitive outcome (recovered or fatal), is approximately 70%, and varies little among the three most affected countries (Guinea, Liberia and Sierra Leone; Table 6 (available online only) and Data Citation 2)38. The CFR among EVD cases reported by Nigeria (n=20) was 40%54). A second, unrelated EVD outbreak occurred in Équateur province, DRC between July and October 2014 resulting in 69 confirmed and probable cases with a CFR of 74%49. The CFR for Marburg is approximately 80%55–57).

R0 and Rt

Looking at past outbreaks, estimates of R0 for Ebola Zaire ranged from 1.4-4.735,42,44,58–60) (Table 3 (available online only) and Data Citation 2), and for Ebola Sudan ranged from 1.3-2.744,58–60 (Table 4 (available online only)). R0 has not been estimated for Ebola Bundibugyo.

In the ongoing outbreak in West Africa, estimates of R0 and Rt have been estimated for all countries combined, as well as separately for Guinea, Liberia, Nigeria and Sierra Leone16,30,36,41,48,54,61–69. All estimates of Rt are provided in Table 6 (available online only) and Data Citation 2 and Data Citation 3. Gomes et al. 62 reported several all-country R0 estimates (means ranging 1.8–2.1), depending on model choice and assumptions. Fisman et al. 30 reported all-country and country-specific R0 estimates depending on assumptions including action taken to mitigate infection. For the most part, R0 estimates for Guinea, Liberia, and Sierra Leone ranged from 1.2 to 2.5 with the striking exception of the Fisman et al. 30 R0 estimate of 8.3 for Sierra Leone. Nishiura and Chowell65 estimated Rt fluctuating around 1 for Guinea, 1.7 for Liberia and 1.4 for Sierra Leone. The WHO Ebola Response Team16 estimated Rt for Guinea (ranging from 1.6 to 2.0), for Liberia (ranging from 1.4 to 1.6) and for Sierra Leone (ranging from 1.3 to 1.5).

Several groups have also estimated R0 for specific geographic areas within the region (full details in Table 6 (available online only) and Data Citation 2). For example, Faye et al. estimated R0 for cases occurring in Conakry, Guinea at the start of the outbreak (n=193)41 as 1.7 (95% CI 1.2, 2.3); whereas Lewnard et al. 64 estimated R0 for EVD cases in Montserrado, Liberia as of October 2014 (R0=2.5 (2.4, 2.6)).

Serial interval distribution

The serial interval, defined as the time interval between symptom onset in an index case and symptom onset in a secondary case infected by that index case, has been infrequently estimated due to the paucity of data on epidemiologically linked pairs of index and secondary cases. For Ebola Zaire (Table 3 (available online only)), the mean serial interval was estimated to be 10–16.1 days5,49,60,70. In the ongoing outbreak in West Africa, the mean serial interval has been estimated to be approximately 14–15 days16,17,30,41 (Table 6 (available online only)).

Generation time distribution

Closely related to the serial interval, the generation time is defined as the time interval between infection of an index case and infection of a secondary case infected by that index case. As such, the generation time distribution nearly always needs to be inferred indirectly from serial interval observations and knowledge of the incubation period distribution. We found one such estimate of the mean generation time for Marburg of 9 days (95% CI 8.2, 10.0)55.

Delay distributions

For Ebola Zaire, including the ongoing outbreak, the mean time from symptom onset to hospitalization (Table 3 (available online only) and Table 6 (available online only)), ranged from 3.2 to 5.3 days5,16,17,20,38,41,48, whereas the mean time from symptom onset to death ranged from 6 to 10.1 days5,17,25,37–39,41,49,61. For Ebola Sudan (Table 4 (available online only)), the mean time from symptom onset to hospitalization was 2 days (range 0–8)51 and the median time from symptom onset to death was 9 days (range 5–15)24, respectively. The mean time from hospitalization to discharge for Ebola Sudan ranged from 8 to 10 days51,53 whereas the mean time from hospitalization to death was 6.1 days (range 2–13)51. For Ebola Bundibugyo (Table 5), the median time from symptom onset to hospitalization was 3.5 days (range 0–8)19 and the median time from symptom onset to death was 9–10 days (range 3–21 days)19,47.

Risk for developing EVD

Risk factors for human-to-human transmission of EVD or Marburg were evaluated from comparison of the exposures, behaviors and practices in cases compared to controls (including unaffected controls, defined to be suspected cases but negative serologic test results) and were described using a prevalence proportion ratio, an odds ratio or a relative risk (and the corresponding confidence interval). Significant risk factors associated with developing EVD are reported in Table 8 (available online only) and Data Citation 4 and include direct physical contact (sharing a bed, touching a cadaver or funeral preparations for an EVD patient, nursing care and contact with bodily fluids) and non-physical contact (sharing a meal, contact with a hospital where EVD patients were treated)24,39,45,47,56,71.

Usage Notes

The data presented in this review summarize estimates of the epidemiological parameters of EVD and Marburg. These results can facilitate parameterization and sensitivity analysis of transmission models examining surveillance, control and treatment strategies. The results can also inform epidemiological studies investigating human-to-human transmission during Ebola and Marburg outbreaks, deepening our understanding of the transmission process.

The number of parameters estimated for each outbreak has generally increased with time (Table 2 (available online only)). While the incubation period distribution was consistently assessed, R0 has increasingly been estimated, most notably with the ongoing outbreak in West Africa (Table 6 (available online only) and Data Citation 2). Fig. 1 shows the central estimates and ranges for the different studies that estimated the incubation period distribution for EVD outbreaks. While there are small differences in the central estimates of the incubation period distribution of the four Ebola viruses, the ranges around the mean or median are consistent, with a maximum of ≤21 days. Current EVD guidance states that EVD has an incubation period of 2–21 days, which is the basis for the recommended duration of contact tracing of 21 days26,27. This is supported by the findings in our review.

Figure 2 shows CFR for different Ebola Zaire, Ebola Sudan, Ebola Bundibugyo and Marburg outbreaks. While the CFR for Ebola and Marburg are high (compared to other infectious diseases), outbreaks caused by Ebola Zaire and Ebola Sudan have experienced the highest CFR amongst these three Ebola viruses causing outbreaks in humans1,2,5,19,24,25,38,43,46,47,50–53,72–76. The estimated CFR for the ongoing outbreak in West Africa, due to Ebola Zaire, is approximately 70%16,17,36, which falls within the range of CFRs for past outbreaks due to this virus2,5,25,38,43,50.

Figure 2 also illustrates that recent CFR estimates for Ebola Zaire remain comparable to those observed in the 1970s. While there are ongoing efforts to develop medical treatments for EVD, treatment remains mainly supportive. The massive scale of the ongoing outbreak has highlighted the urgent need to develop new treatments and to fast track the use of experimental medical interventions77.

The transmission potential, as measured by R0, is fairly consistent among the three Ebola viruses, ranging from approximately >1 to 4 (also mentioned in ref. 78). Previously, EVD typically affected villages in remote areas of central Africa35,38,42,44,58,59, and while devastating in these areas, the populations that are at risk are generally limited in number. The ongoing EVD outbreak had circulated for at least three months prior to discovery22,79 which allowed spread of the virus to go unchecked while it infected people in an area of Guinea that shares borders with Sierra Leone and Liberia. Recent experience in Nigeria, has shown that an Ebola virus with R0>1, even in a population of over 20 million, can be controlled with vigorous application of control methods49,54.

Differences in estimates of R0 and Rt are likely, at least in part, to be the result of the quality of data available and the inferential method. The focus on R0 estimation together with serial interval estimates may reflect a shift from data collection purely for surveillance to recognition of the epidemiological value of such data.

The specific factors that result in an EVD outbreak have been under investigation since the emergence of this virus and include examination of human and susceptible non-human populations living in close proximity with each other in remote areas of central Africa. Recent investigations into the first cases of the ongoing outbreak found that the outbreak may have begun in Meliandou, Guinea in a village where the inhabitants frequently came in contact with fruit bats in a hollowed out tree80. Although the current focus is on limiting human-to-human transmission and treating the infected, the challenging underlying factors that led to this large outbreak in West Africa will require long-term investments to improve both health care and surveillance for infectious diseases.

Our dataset is the most complete collection of published epidemiological parameter estimates from EVD outbreaks available at the time of writing and provides an evidence-based foundation for both retrospective analyses and responses to future outbreaks.

Additional Information

How to cite this article: Van Kerkhove, M. D. et al. A review of epidemiological parameters from Ebola outbreaks to inform early public health decision-making. Sci. Data 2:150019 doi: 10.1038/sdata.2015.19 (2015).

Supplementary Material

sdata201519-isa1.zip (7.5KB, zip)

Acknowledgments

The authors would like to acknowledge the Medical Research Council, the Bill and Melinda Gates Foundation, the Wellcome Trust, the Health Protection Research Units of the National Institute for Health Research, and the European Union Seventh Framework Programme [FP7/2007–2013] under agreement Grant Agreement nu278433-PREDEMICS for funding.

Footnotes

The authors declare no competing financial interests.

Data Citations

  1. Van Kerkhove M., Bento A. I., Mills H. L., Ferguson N. M., Donnelly C. A. 2015. figshare. http://dx.doi.org/10.6084/m9.figshare.1381874 [DOI] [PMC free article] [PubMed]
  2. Van Kerkhove M., Bento A. I., Mills H. L., Ferguson N. M., Donnelly C. A. 2015. Figshare. http://dx.doi.org/10.6084/m9.figshare.1381876 [DOI] [PMC free article] [PubMed]
  3. Van Kerkhove M., Bento A. I., Mills H. L., Ferguson N. M., Donnelly C. A. 2015. Figshare. http://dx.doi.org/10.6084/m9.figshare.1381877 [DOI] [PMC free article] [PubMed]
  4. Van Kerkhove M., Bento A. I., Mills H. L., Ferguson N. M., Donnelly C. A. 2015. Figshare. http://dx.doi.org/10.6084/m9.figshare.1381875 [DOI] [PMC free article] [PubMed]

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Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Data Citations

  1. Van Kerkhove M., Bento A. I., Mills H. L., Ferguson N. M., Donnelly C. A. 2015. figshare. http://dx.doi.org/10.6084/m9.figshare.1381874 [DOI] [PMC free article] [PubMed]
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Supplementary Materials

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