ENHanCE Position Paper #1 – Quantitative and Qualitative Approaches to the Prioritisation of Diseases Introduction The prioritisation of diseases is an important process for international, national and regional agencies charged with disease surveillance and implementation of disease management and control, given limited resources. It is also important for funders of research; so that they can identify the most important areas for investment. However, the application of risk analysis as a prioritisation tool often involves evaluating a large number of hazards where it is not feasible to conduct an in-depth assessment of all pathogens. Ranking of communicable diseases and zoonoses into prioritisation lists can be undertaken using several different approaches: qualitative (Valenciano et al., 2001), semi- quantitative (Krause et al., 2007, McKenzie et al., 2007, Cardoen S. et al. 2009) and quantitative (Fosse et al., 2008). In qualitative studies, estimation of parameters and risks is done using words (relatively high, low…), whereas in quantitative work, numbers or probabilities are used. Semi- quantitative studies lie somewhere in the middle, using a mix of qualitative terms and/or signs and numbers. Qualitative and semi-quantitative approaches are criticised due to their potential subjectivity and the large amount of resources they use, respectively. However, most quantitative methods require some input of expert opinion, giving them a degree of subjectivity too. The objective of this position paper was to illustrate and review existing methodologies for prioritisation of diseases in order that attendees to the ENHanCE project agency meeting would be able to identify the approaches most useful to them for future planning. Our aim within the ENHanCE project itself is to build a repeatable and transparent future approach to prioritisation of diseases using a simple but robust algorithm. The results presented were obtained from a literature and web search using keywords such as prioritisation, animal disease, zoonoses and human disease. As work within the Discontools project, http://www.discontools.eu/home/index (IFAH, Europe 2009) had already scanned worldwide for existing methodologies of prioritisation, this review starts by presenting its work and has extracted its table of comparison of the methodologies for the summary and extended it by adding eight more articles and reports. Whilst reading the position paper, the agencies were asked to think about the questions below. Which approach to disease prioritisation is most useful to your agency: qualitative, semi- quantitative and quantitative? Is examination of endemic or exotic pathogens or perhaps both most useful to you? Are you most interested in pathogens at high risk (of change) or which have a high impact (on society)? Would independent prioritisation by us, use of another prioritisation tool, or aggregation of other prioritisation tools thus creating a generic tool be most useful to you? Do you prefer the use of weighting or scoring by expert opinion or objective measures only?
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ENHanCE Position Paper #1 – Quantitative and Qualitative Approaches to the Prioritisation of Diseases
Introduction
The prioritisation of diseases is an important process for international, national and regional agencies
charged with disease surveillance and implementation of disease management and control, given
limited resources. It is also important for funders of research; so that they can identify the most
important areas for investment. However, the application of risk analysis as a prioritisation tool often
involves evaluating a large number of hazards where it is not feasible to conduct an in-depth
assessment of all pathogens. Ranking of communicable diseases and zoonoses into prioritisation lists
can be undertaken using several different approaches: qualitative (Valenciano et al., 2001), semi-
quantitative (Krause et al., 2007, McKenzie et al., 2007, Cardoen S. et al. 2009) and quantitative
(Fosse et al., 2008). In qualitative studies, estimation of parameters and risks is done using words
(relatively high, low…), whereas in quantitative work, numbers or probabilities are used. Semi-
quantitative studies lie somewhere in the middle, using a mix of qualitative terms and/or signs and
numbers. Qualitative and semi-quantitative approaches are criticised due to their potential
subjectivity and the large amount of resources they use, respectively. However, most quantitative
methods require some input of expert opinion, giving them a degree of subjectivity too.
The objective of this position paper was to illustrate and review existing methodologies for
prioritisation of diseases in order that attendees to the ENHanCE project agency meeting would be
able to identify the approaches most useful to them for future planning. Our aim within the ENHanCE
project itself is to build a repeatable and transparent future approach to prioritisation of diseases
using a simple but robust algorithm. The results presented were obtained from a literature and web
search using keywords such as prioritisation, animal disease, zoonoses and human disease.
As work within the Discontools project, http://www.discontools.eu/home/index (IFAH, Europe 2009)
had already scanned worldwide for existing methodologies of prioritisation, this review starts by
presenting its work and has extracted its table of comparison of the methodologies for the summary
and extended it by adding eight more articles and reports.
Whilst reading the position paper, the agencies were asked to think about the questions below.
Which approach to disease prioritisation is most useful to your agency: qualitative, semi-
quantitative and quantitative?
Is examination of endemic or exotic pathogens or perhaps both most useful to you?
Are you most interested in pathogens at high risk (of change) or which have a high impact
(on society)?
Would independent prioritisation by us, use of another prioritisation tool, or aggregation of
other prioritisation tools thus creating a generic tool be most useful to you?
Do you prefer the use of weighting or scoring by expert opinion or objective measures only?
Table 2. The eight prioritisation methodologies added for the ENHanCE project
Diseases or pathogens
RIV
M (
2006
)
McK
enzi
e et
al. (
2007
)
FAO
/OIE
(20
04)
Doh
erty
(20
00)
WH
O (
2006
)
Duf
our
et a
l.
(200
6)
Eger
et
al.
(200
9)
InV
S (2
001)
Card
oen
et a
l.
(200
9)
Perk
ins
et a
l.
(200
7)
Dix
it &
Ana
nd
(200
4)
Foss
e et
al.
(200
7)
Acute flaccid para lys is IAdenovirus IAfrican Horse s ickness I IAlveolar hydatid (echinococcus multilocularis ) I IAnthrax I I IASF IBatrachochytrium dendrobatidis IBluetongue IBrucella dephini, Brucella mani IBrucel los is (B. melitensis ) I I I I IBSE agent/ Creutzfeld Jacob disease I I ICampylobacter spp I I I ICBPP* ICetacean morbillivirus IChickenpox ICholera I IClamydia psittaci IClostridium botulinum I I ICrimean Congo Hemorrhagic fever ICryptosporidium parvum I ICSF ICyclosporias is ICysticercos isdiphteria I IDuck plague IDuck vi rus hepati tis IE. Coli STEC IE. Coli VTEC I IEpizootic haematopoietic necros is Ifasciola hepatica IFMD* IFoodborne diseases IFurunculos is IGenita l clamydia IGiardia intestinalis I IGonorrhea Igroup B streptococcal disease in neonates IHantavirus pulmonary syndrome Ihepati tis A I IHepati tis B I Ihepati tis C I IHerpes vi rus IHIV/AIDS I IHPAI I I IInfluenza I I IInvas ive group A streptococcal IInvas ive meningococcal disease I IInvas ive pneumococcal disease IJapanese encephal i tis I I ILeprosy I ILeptospira interrogans australis ILeptospiros is I I I IListeria monocytogenes I I ILyme disease IMalaria I Imeas les I IMumps IMycobacterium spp I I I INew world screwworm INewcastle disease INipah vi rus INorovirus IOld world screwworm IPacheco's disease IParamyxoviruses - bats IPasteurella multocida serogroup A IPasteurel los is Ipertuss is I IPlague I I Ipol iomyel i tis I IPPR IPsittacine circovirus IPs i ttacine pox IPs i ttacos is IQfever I IRabies I I I I I
Diseases or pathogens (cont.)
RIV
M (
2006
)
McK
enzi
e et
al. (
2007
)
FAO
/OIE
(20
04)
Doh
erty
(20
00)
WH
O (
2006
)
Duf
our
et a
l.
(200
6)
Eger
et
al.
(200
9)
InV
S (2
001)
Card
oen
et a
l.
(200
9)
Perk
ins
et a
l.
(200
7)
Dix
it &
Ana
nd
(200
4)
Foss
e et
al.
(200
7)
Rinderpest - Stomati tis/enetri ti s IRoss River Fever IRotavirus I Irubel la I IRVF* I ISalmonella spp I I I I I ISheep pox*/goat pox* IShigel los is I ISindbis vi rus IStaphylococcus aureus ISteptococcus spp ISyphi l i s I ITetanus I IToxoplasmosis (Toxoplasma gondii ) I I I ITularémia ITyphoid I IUni locular hydatid (echinococcus granulosus ) I IVenezuelan Equine Encephalomyel i ti s IVira l haemorrhagic septicemia IVisceral leishmanios is IWest Ni le Virus I I I IYel low fever I IYersinia enterolitica I I
* diseases for which trend analys is and predictions wi l l be emphas ized
Table 3. A summary of the outputs of previous disease prioritisation exercises.
Perkins et al. (2007)
a. Criteria for inclusion of diseases
An initial list of candidate diseases was compiled through a combination of literature review, web
searching and through contacts with a variety of individuals who had been involved in animal health
activities in Indonesia over a number of years. The criteria for inclusion in this initial list included:
- zoonotic disease
- measurable impact on both livestock and humans
- either evidence or suspicion that the disease was present in Indonesia
From a list of 13 diseases, six were identified as high priority. These did not include diseases for
which insufficient data or information was available to estimate whether the disease was present or
to attempt to assess their impact, or diseases assessed as being unlikely to have any adverse impact
on livestock health or production.
b. Ranking method
Three impact assessment methods were used to rank the list of diseases:
- modified ILRI scoring system (see Box 1), with two different results: socio-
economic impacts that aimed to assess the impact on livestock, and an
adjusted zoonotic score that aimed to assess the impact of diseases on
human health
- DALY: Disability Adjusted Life-Year
- Economic losses
The overall rank was derived from the arithmetic average of the ranks of the four component
assessments and assumed equal weighting of these four methods.
Box 1. The ILRI approach (Described in Perry et al. (2002))
Specific criteria are developed for measuring impacts and each criterion is scored on a scale of 0-5 with 5
representing the most severe type of impact. Scores are then combined to produce a single composite index.
The criterion specific scores (7) are then combined using weighting to produce an overall socio-economic
impact score. This can be used as an un-adjusted estimate of the relative importance of the different diseases
for smallholders.
For the zoonotic score, public health impacts are assessed based on the incidence of disease in livestock, the
human population at risk and the severity of the disease in affected individuals (two criteria). In some cases
scores can be adjusted using weighting.
Dixit & Anand (2004)
a. Criteria for inclusion of diseases and method
Data from 1998-2002 were obtained from the Directorate of Health, Govt. of Rajasthan and analysed
year by year, comparing incidence scenario and DALYs.
Conclusion to semi-quantitative approaches
Many of the semi-quantitative approaches used are hardly comparable. Perkins (2007) and Dixit &
Anand (2004) used similar approaches and settings. Cardoen et al. (2009), however, followed a multi-
criteria decision model with a semi-quantitative approach. They suggested that this circumvents the
problems usually encountered in quantitative methods, such as a lack of data and in qualitative
methods such as subjectivity and unreliability (Cox et al., 2005). Their approach is novel, because it
includes the effect of the policy priorities of risk managers within the final ranking, rather than only
the scientific expertise of risk evaluators (scientific experts).
2. Quantitative approaches
Fosse et al. (2008)
a. Criteria for inclusion of pathogens
Based on a large literature review, biological hazards potentially transmitted to pork consumers were
sorted according to analytical, geographical and historical criteria, in order to identify currently
established biological hazards for European consumers of pork.
b. Ranking method
The hierarchy of hazards could be calculated according to risk scores (see Box 2), considered as cross
functions of the incidence of human cases attributed to pork consumption and the calculated
severity scores of these cases. A ratio for non-control of hazards during and after meat inspection
(the mean incidence of human cases attributable to pork consumption divided by the mean
prevalence of hazards on pork carcasses) was calculated, and comparison between non-control ratio
and risk scores was made to identify the hazards for which new meat control methods should be
considered a priority.
Box 2. The calculation of the risk scores
Risk score: Rλ=Ipork*Sλ where:
Pcar: mean rate of prevalence on pork carcasses
H: rate of hospitalisation: number of hospitalised people among sick people
L: lethality of human clinical cases due to biological hazards: number of deceased people among sick people
Sλ: clinical severity of symptoms induced in humans=H+λL, with λ term to strengthen the epidemiological
weighting of hazards which may be lethal.
Ipork: mean incidence rate=I*PAP
PAP: pork attributable proportion= npork/ntotal with npork and ntotal for one given hazard the number of human
cases due to pork consumption and the total number of human cases due to food consumption
Conclusion to quantitative approaches
This single study used purely a quantitative approach. Interestingly, the results were very similar in
terms of the ranking of the pathogens to that of Cardoen et al. (2009), which used a semi-
quantitative methodology. Other attempts at quantitative analyses may perhaps not have been
made because such analyses are very data rich.
References
Cardoen, S., Van Huffel, X. et al. (2009). Foodborne Pathogens and Disease, 6(9): pp1083-1096.
Cox, L.A. & Babayer, D. (2005). Risk Analysis, 25(3): pp651-662.
Defra (2006). Approaches to the prioritisation of resources: a brief review of selected public sector organisations in the UK
and abroad. (www.defra.gov.uk/foodfarm/farmanimal/diseases/vetsurveillance/documents/prioritisation-resources.pdf).
Discontools (2009). Approaches to the prioritization of diseases: a worldwide review of existing methodologies for health
Perkins, N., Patrick, I., Patel, M. & Fenwick, S. (2007). Assessment of zoonotic diseases in Indonesia. Australian Centre for
International Agricultural research. (http://www.aciar.gov.au/publication/FR2008-01).
Valenciano M. et al. Definition des priorités dans le domaine des zoonoses non alimentaires 2000-2001. Rapport de l’InVS, AFSSA, ENVN, La direction générale de la santé, le centre hospitalier universitaire Cochin et la cellule interregionale d’epidemiologie EST. (http://www.invs.sante.fr/publications/2002/def_priorite_zoonoses/index.html).
Which approach to disease prioritisation is most useful to your agency: qualitative/semi- quantitative/quantitative?
Is examination of endemic or exotic pathogens, or both, more useful to you?
Are you most interested in pathogens at high risk (of change) or those which have a high impact (on society)?
Would independent prioritisation by us, use of another prioritisation tools or aggregation of other prioritisation tools to create a generic tool be most useful to you?
Do you prefer the use of weighting or scoring by expert opinion or objective measures only?
Answers
All approaches; different for specific questions - 22%
Endemic and exotic - 88% High impact on society - 55% Independent prioritization by ENHanCE - 58%
Objective measures - 38%
Semi- quantitative - 22% Exotic - 12% High risk of change and high impact on society - 33%
Don’t mind - 14% Both useful when using different prioritization tools - 24%
Start with large list & qualitative approach, then tailor further using semi-quantitative & quantitative with smaller lists - 22%
High risk of change - 12%
Don’t mind – would prefer a choice of several, comparing diseases from different perspectives - 14%
Weighting/scoring by an expert - 38%
Qualitative - 12%
Independent assessment by more than one group can be helpful, but only if consensus is reached - 14%