Imperial College London
Alternate

ProfessorMartaBlangiardo

Faculty of Medicine, School of Public Health

Chair in Biostatistics
 
 
 
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Contact

 

m.blangiardo Website

 
 
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Location

 

705School of Public HealthWhite City Campus

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Summary

 

Publications

Citation

BibTex format

@article{Manica:2019:10.1111/1365-2664.13454,
author = {Manica, M and Caputo, B and Screti, A and Filipponi, F and Rosa, R and Solimini, A and Della, Torre A and Blangiardo, M},
doi = {10.1111/1365-2664.13454},
journal = {Journal of Applied Ecology},
pages = {2225--2235},
title = {Applying the Nmixture model approach to estimate mosquito population absolute abundance from monitoring data},
url = {http://dx.doi.org/10.1111/1365-2664.13454},
volume = {56},
year = {2019}
}
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RIS format (EndNote, RefMan)

TY  - JOUR
AB  - 1. Estimating population abundance is a key objective of surveillance programmes, particularly for vector species of public health interest. For mosquitos, which are vectors of human pathogens, established methods to measure absolute population abundance such as markreleaserecapture are difficult to implement and usually spatially limited. Typically, regional monitoring schemes assess species relative abundance (counting captured individuals) to prioritize control efforts and study species distribution. However, assessing absolute abundance is crucial when the focus is on pathogen transmission by contacts between vectors and hosts. Here, we applied the Nmixture model approach to estimate mosquito abundance from standard monitoring data.2. We extended the Nmixture model approach in a Bayesian framework by considering a betabinomial distribution for the detection process. We ran a simulation study to explore model performance under a low detection probability, a timevarying population and different sets of independent variables.3. When informative priors were used and the model was well specified, estimates by Nmixture model well correlated (>0.9) with synthetic data and had a mean absolute deviation of about 20%. Correlation decreased and biased increased with uninformative priors or model misspecification.4. When fed with field monitoring data to estimate the absolute abundance of the mosquito arbovirus vector Aedes albopictus within the metropolitan city of Rome (Italy), the Nmixture model showed higher population size in residential neighbourhoods than in large green areas and revealed that traps located adjacent to vegetated sites have a higher probability of capturing mosquitoes.5. Synthesis and applications. Our results show that, if supported by a good knowledge of the target species biology and by informative priors (e.g. from previous studies of capture rates), the Nmixture model represents a valuable tool to exploit field monitoring data to esti
AU  - Manica,M
AU  - Caputo,B
AU  - Screti,A
AU  - Filipponi,F
AU  - Rosa,R
AU  - Solimini,A
AU  - Della,Torre A
AU  - Blangiardo,M
DO  - 10.1111/1365-2664.13454
EP  - 2235
PY  - 2019///
SN  - 0021-8901
SP  - 2225
TI  - Applying the Nmixture model approach to estimate mosquito population absolute abundance from monitoring data
T2  - Journal of Applied Ecology
UR  - http://dx.doi.org/10.1111/1365-2664.13454
UR  - http://hdl.handle.net/10044/1/70324
VL  - 56
ER  -
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