Abstract
The global reductions in disease burden and the continued spread of drug and insecticide resistance make malaria elimination both viable and imperative, although this may be more easily achieved in some settings compared to others. Whilst the focus has been on optimal approaches to achieve elimination, less attention has been paid to how to measure the absence of malaria. Measuring the absence of transmission poses a specific challenge in that it involves proving a negative. The concept of freedom from infection, routinely used in veterinary epidemiology, can provide quantitative and reproducible estimates that, if infections were present above a predefined (low) threshold, they would be detected with a known uncertainty. Additionally, these methods are adaptable for both passively and actively collected data as well as combining information when multiple surveillance streams are available. Here we discuss the potential application of this approach to malaria. Evidence-based approaches for informing public health decision-making in the context of disease elimination are currently lacking.Tools developed in veterinary epidemiology can generate quantitative and reproducible estimates for the probability of detecting disease were it present at a pre-specified (low) level.Passive case detection can be augmented with actively collected data to generate an overall estimate of the sensitivity of the surveillance system and corresponding estimates of freedom from infection.Historical data can be incorporated into estimates of freedom with appropriate weighting according to the probability that infection is introduced into the population.For malaria control programs that are reorienting surveillance for elimination certification, freedom from infection estimates provide a potential standardized approach for informing decision-making.
| Original language | English (US) |
|---|---|
| Journal | Trends in Parasitology |
| DOIs | |
| State | Accepted/In press - 2016 |
| Externally published | Yes |
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Keywords
- Active surveillance
- Elimination
- Negative reporting
- Passive surveillance
ASJC Scopus subject areas
- Parasitology
- Infectious Diseases
Cite this
Freedom from Infection : Confirming Interruption of Malaria Transmission. / Stresman, Gillian; Cameron, Angus; Drakeley, Chris.
In: Trends in Parasitology, 2016.Research output: Contribution to journal › Article
}
TY - JOUR
T1 - Freedom from Infection
T2 - Confirming Interruption of Malaria Transmission
AU - Stresman, Gillian
AU - Cameron, Angus
AU - Drakeley, Chris
PY - 2016
Y1 - 2016
N2 - The global reductions in disease burden and the continued spread of drug and insecticide resistance make malaria elimination both viable and imperative, although this may be more easily achieved in some settings compared to others. Whilst the focus has been on optimal approaches to achieve elimination, less attention has been paid to how to measure the absence of malaria. Measuring the absence of transmission poses a specific challenge in that it involves proving a negative. The concept of freedom from infection, routinely used in veterinary epidemiology, can provide quantitative and reproducible estimates that, if infections were present above a predefined (low) threshold, they would be detected with a known uncertainty. Additionally, these methods are adaptable for both passively and actively collected data as well as combining information when multiple surveillance streams are available. Here we discuss the potential application of this approach to malaria. Evidence-based approaches for informing public health decision-making in the context of disease elimination are currently lacking.Tools developed in veterinary epidemiology can generate quantitative and reproducible estimates for the probability of detecting disease were it present at a pre-specified (low) level.Passive case detection can be augmented with actively collected data to generate an overall estimate of the sensitivity of the surveillance system and corresponding estimates of freedom from infection.Historical data can be incorporated into estimates of freedom with appropriate weighting according to the probability that infection is introduced into the population.For malaria control programs that are reorienting surveillance for elimination certification, freedom from infection estimates provide a potential standardized approach for informing decision-making.
AB - The global reductions in disease burden and the continued spread of drug and insecticide resistance make malaria elimination both viable and imperative, although this may be more easily achieved in some settings compared to others. Whilst the focus has been on optimal approaches to achieve elimination, less attention has been paid to how to measure the absence of malaria. Measuring the absence of transmission poses a specific challenge in that it involves proving a negative. The concept of freedom from infection, routinely used in veterinary epidemiology, can provide quantitative and reproducible estimates that, if infections were present above a predefined (low) threshold, they would be detected with a known uncertainty. Additionally, these methods are adaptable for both passively and actively collected data as well as combining information when multiple surveillance streams are available. Here we discuss the potential application of this approach to malaria. Evidence-based approaches for informing public health decision-making in the context of disease elimination are currently lacking.Tools developed in veterinary epidemiology can generate quantitative and reproducible estimates for the probability of detecting disease were it present at a pre-specified (low) level.Passive case detection can be augmented with actively collected data to generate an overall estimate of the sensitivity of the surveillance system and corresponding estimates of freedom from infection.Historical data can be incorporated into estimates of freedom with appropriate weighting according to the probability that infection is introduced into the population.For malaria control programs that are reorienting surveillance for elimination certification, freedom from infection estimates provide a potential standardized approach for informing decision-making.
KW - Active surveillance
KW - Elimination
KW - Negative reporting
KW - Passive surveillance
UR - http://www.scopus.com/inward/record.url?scp=85009820146&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85009820146&partnerID=8YFLogxK
U2 - 10.1016/j.pt.2016.12.005
DO - 10.1016/j.pt.2016.12.005
M3 - Article
C2 - 28108199
AN - SCOPUS:85009820146
JO - Trends in Parasitology
JF - Trends in Parasitology
SN - 1471-4922
ER -