'Estimating the contribution of human-to-human transmission to Lassa fever', presented by Gianni Lo Iacono, of the Dynamic drivers of Disease in Africa Consortium, at EWDA 2014

1. Dynamic Drivers of Disease in Africa
Integrating our understandings of zoonoses, ecosystems and wellbeing
Estimating the contribution of human-to-human
transmission to Lassa fever
Gianni Lo Iacono, University of Cambridge

2. Background
False-colour transmission electron
micrograph of the Lassa fever virus. Photo
from Science Photo Library
Viral hemorrhagic fever
caused by Arenavirus Lassa

3. Background
Mastomys Nataliensis. Photo from Lina
Moses
Viral hemorrhagic fever
caused by Arenavirus Lassa
Vector and reservoir:
Mastomys Natalensis

4. Background
Map of the Mano River Union countries
(Sierra Leone, Guinea, and Liberia). The
approximate known endemic area for Lassa
fever is shown by the dotted oval.
From Khan et al (2008)
Viral hemorrhagic fever
caused by Arenavirus Lassa
Vector and reservoir:
Mastomys Natalensis
Endemic in West Africa

5. Background
Viral hemorrhagic fever
caused by Arenavirus Lassa
Vector and reservoir:
Mastomys Natalensis
Endemic in West Africa
Unclear routes of
transmission (contaminated
excreta, aerosol..)

6. Background
Viral hemorrhagic fever
caused by Arenavirus Lassa
Vector and reservoir:
Mastomys Natalensis
Endemic in West Africa
Unclear routes of
transmission (contaminated
excreta, aerosol..)
Unclear role of human-to-human
transmission

7. Background
Viral hemorrhagic fever
caused by Arenavirus Lassa
Vector and reservoir:
Mastomys Natalensis
Endemic in West Africa
Unclear routes of
transmission (contaminated
excreta, aerosol..)
Unclear role of human-to-human
transmission

8. Existing Data
Nosocomial Outbreak in Jos, Nigeria
From Carey et al (1972)

9. Existing Data

10. Existing Data

11. Existing Data:
Kenema Governament Hospital (KGH).
The Kenema Government Hospital Laboratory. From Khan et al. (2008)

12. Kenema Governament Hospital (KGH)
Shaffer et al (2014)
12
9
6
3
0
01/04/08 01/10/08 01/04/09 01/10/09 01/04/10 01/10/10 01/04/11 01/10/11
Date of admission
No of Cases

13. Kenema Governament Hospital (KGH)
Shaffer et al (2014)
Zoonotic origin
Human origin
9
6
3
0
01/04/08 01/10/08 01/04/09 01/10/09 01/04/10 01/10/10 01/04/11 01/10/11
Date of admission
No of Cases

14. Methods: How to disentangle the two
contributions?
Zoonotic origin
Human origin
9
6
3
0
01/04/08 01/10/08 01/04/09 01/10/09 01/04/10 01/10/10 01/04/11 01/10/11
Date of admission
No of Cases
• First, we identified Lassa fever outbreaks known to be due to human-to-
human chains of transmission (Jos situation)
• Then, we looked at people hospitalized with the disease in KGH, who
could have been infected either by rodents or humans.

15. • We asked, what should the proportion of patients be who get
infected by humans, assuming the statistical patterns observed in
the human-to-human chains are the same in both instances?
=
Zoonotic origin
Human origin
9
6
3
0
01/04/08 01/10/08 01/04/09 01/10/09 01/04/10 01/10/10 01/04/11 01/10/11
Date of admission
No of Cases
Methods: How to disentangle the two
contributions?

16. Effective Reproductive Number for
nosocomial cases
From www.cmaj.ca
Average Number of
secondary cases arising
from the primary case

17. Effective Reproductive Number for
nosocomial cases
The relative likelihood that case i has been infected by case j
proportional on the time of exposure (based on Wallinga &
Teunis (2004))

18. Human-to-human transmission
From Carey et al (1972)
Diagrammatic representation
Sister in law of SI
Wife of Case HR2. Cared for child
Ward Cleaner
Visited the ward
Not located
Hospital staff
Cared for child
Friend of HR. Visited the ward
Scrub nurse
Ward cleaner
Not clear if she visited the ward
Mother of LM
On ward for other illness. Wife of TI, aunt of EE,EE2,SE
Cared for TS
On ward for other illness. Daughter of YB
Husband of HR
Not located
Not located
Nephew of FT and TI, brother of EE2, SE
Husband of FT
Sister of EE2
Brother of EE2
TS
HR
KD
DG
L
PI
RA
GD
AK
MA
AA
AH
YB
FT
SI
LM
HR2
HY
HA
EE
TI
EE2
SE
0 25 50 75 100
No of days from onset

19. Human-to-human transmission
From Carey et al (1972)
Sister in law of SI
Diagrammatic representation
Wife of Case HR2. Cared for child
Ward Cleaner
Visited the ward
Not located
Hospital staff
Cared for child
Friend of HR. Visited the ward
Scrub nurse
Ward cleaner
Not clear if she visited the ward
Mother of LM
On ward for other illness. Wife of TI, aunt of EE,EE2,SE
Cared for TS
On ward for other illness. Daughter of YB
Husband of HR
Not located
Not located
Nephew of FT and TI, brother of EE2, SE
Husband of FT
Sister of EE2
Brother of EE2
TS
HR
KD
DG
L
PI
RA
GD
AK
MA
AA
AH
YB
FT
SI
LM
HR2
HY
HA
EE
TI
EE2
SE
0 25 50 75 100
No of days from onset

20. Effective Reproductive number for
nosocomial cases
●
●
●
●
●●
●●●●
●
●
●●
●●
●●●
●
12
9
6
3
0
TS
HR
KD
DG
PI
RA
GD
AK
MA
AA
AH
YB
FT
SI
LM
HR2
HY
HA
EE
TI
EE2
SE
NA
Case ID
Reff

21. Generation Time
0.10
0.05
0.00
0 10 20 30
Generation time (days)
Density

22. Effective Reproductive number for data
from KGH(Based on Wallinga & Teunis (2004) )
12
9
6
3
0
01/04/08 01/10/08 01/04/09 01/10/09 01/04/10 01/10/10 01/04/11 01/10/11
Date of admission
No of Cases

23. Effective Reproductive number for data
from KGH(Based on Wallinga & Teunis (2004) )
12
9
6
3
0
01/04/08 01/10/08 01/04/09 01/10/09 01/04/10 01/10/10 01/04/11 01/10/11
Date of admission
No of Cases

24. Effective Reproductive number for data
from KGH(Based on Wallinga & Teunis (2004) )
12
9
6
3
0
01/04/08 01/10/08 01/04/09 01/10/09 01/04/10 01/10/10 01/04/11 01/10/11
Date of admission
No of Cases

25. Effective Reproductive number for data
from KGH(Based on Wallinga & Teunis (2004) )

26. Effective Reproductive number for data
from KGH(Based on Wallinga & Teunis (2004) )
Human origin
Zoonotic origin
9
6
3
0
01/04/08 01/10/08 01/04/09 01/10/09 01/04/10 01/10/10 01/04/11 01/10/11
Date of admission
No of Cases

27. Effective Reproductive number for data
from KGH(Based on Wallinga & Teunis (2004) )
Reproductive Number from
human−to−human transmission
for all Sierra Leonean cases
based on admission to KGH hospital
0.4
0.3
0.2
0.1
0.0
0
25
50
75
100
Proportion of cases due to human−to−human transmission
R

28. Effective Reproductive number for data
from KGH(Based on Wallinga & Teunis (2004) )
Reproductive Number for nosocomial cases (Jos and Zorzor)
Reproductive Number from
human−to−human transmission
for all Sierra Leonean cases
based on admission to KGH hospital
0.4
0.3
0.2
0.1
0.0
0
25
50
75
100
Proportion of cases due to human−to−human transmission
R

29. Effective Reproductive number for data
from KGH(Based on Wallinga & Teunis (2004) )
Reproductive Number for nosocomial cases (Jos and Zorzor)
Reproductive Number from
human−to−human transmission
for all Sierra Leonean cases
based on admission to KGH hospital
Reproductive Number for extra−nosocomial
cases (family from Jos)
0.4
0.3
0.2
0.1
0.0
0
25
50
75
100
Proportion of cases due to human−to−human transmission
R

30. Effective Reproductive number for data
from KGH(Based on Wallinga & Teunis (2004) )
Reproductive Number for nosocomial cases (Jos and Zorzor)
Reproductive Number from
human−to−human transmission
for all Sierra Leonean cases
based on admission to KGH hospital
Reproductive Number for extra−nosocomial
cases (family from Jos)
Proportion when the two
Reproductive Numbers
are equal
0.4
0.3
0.2
0.1
0.0
0.0
21.8
50.0
75.0
100.0
Proportion of cases due to human−to−human transmission
R

31. Super-spreading
An illustration of Typhoid Mary (Mary Mallon) that
appeared in the New York American article of
June 20, 1909.

32. Effective Reproductive number for
nosocomial cases
10
5
1 5 10
Reff
Density
Hospital
Zorzor
Jos

33. Conclusions
• If we regard the extra-nosocomial cases observed
in the Jos outbreak as representative of disease
transmission in an endemic area, then a significant
proportion of LF cases arise from human-to-human
transmission.
• A significant proportion of these secondary cases,
however, are attributable to a few events with
disproportionately large effective reproduction
numbers
• Reconciliation of two opposing paradigms

34. Acknowledgments
Andrew A. Cunningham2, Elisabeth Fichet-Calvet 3, Robert F. Garry 4, Donald S. Grant 7, Sheik
Humarr Khan 7, Melissa Leach 8, Lina M. Moses 4, John S. Schieffelin 10, Jeffrey G. Shaffer 11,
Colleen Webb 12, James L. N. Wood 1
1 Department of Veterinary Medicine, Disease Dynamics Unit, University of Cambridge, Cambridge, United Kingdom.
2 Institute of Zoology, Zoological Society of London. United Kingdom
3 Bernhard-Nocht Institute of Tropical Medicine. Hamburg, Germany
4 Department of Microbiology and Immunology, Tulane University, New Orleans, Louisiana, USA 5 Broad Institute, Cambridge, Massachusetts, USA
7 Lassa Fever Program, Kenema Government Hospital, Kenema, Sierra Leone
8 Institute of Development Studies, University of Sussex. Brighton, United Kingdom.
10 Sections of Infectious Disease, Departments of Pediatrics and Internal Medicine, School of Medicine, Tulane University, New Orleans, LA, USA
11 Department of Biostatistics and Bioinformatics, Tulane School of Public Health and Tropical Medicine, New Orleans, LA, USA
12 Department of Biology, Colorado State University, Fort Collins, USA
This work for the Dynamic Drivers of Disease in Africa Consortium was
funded with support from the Ecosystem Services for Poverty Alleviation
(ESPA) programme. The ESPA programme is funded by the Department for
International Development (DFID), the Economic and Social Research
Council (ESRC) and the Natural Environment Research Council (NERC). See
more at www.espa.ac.uk

35. In memoriam of Dr. Sheik Humarr Khan, who has
recently died from Ebola virus. Dr Khan was a leading
doctor on the front lines fighting the Ebola outbreak in
Sierra Leone. Dr Khan was called a "national hero" for
his "tremendous sacrifice" in working to save the lives
of more than 100 infected patients

36. The ‘20-80’ rule

37. The ‘20-80’ rule

38. The ‘20-80’ rule

39. The ‘20-80’ rule

40. Existing Data:
Kenema Governament Hospital (KGH).

41. Existing Data:
Kenema Governament Hospital (KGH).

42. Existing Data:
Kenema Governament Hospital (KGH).