Imperial College London
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ProfessorThomasChurcher

Faculty of Medicine, School of Public Health

Professor of Infectious Disease Dynamics
 
 
 
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Contact

 

thomas.churcher

 
 
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Location

 

G35Medical SchoolSt Mary's Campus

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Summary

 

Publications

Citation

BibTex format

@article{Stopard:2021:10.1371/journal.pcbi.1008658,
author = {Stopard, IJ and Churcher, TS and Lambert, B},
doi = {10.1371/journal.pcbi.1008658},
journal = {PLoS Computational Biology},
title = {Estimating the extrinsic incubation period of malaria using a mechanistic model of sporogony},
url = {http://dx.doi.org/10.1371/journal.pcbi.1008658},
volume = {17},
year = {2021}
}
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RIS format (EndNote, RefMan)

TY  - JOUR
AB  - During sporogony, malaria-causing parasites infect a mosquito, reproduce and migrate to the mosquito salivary glands where they can be transmitted the next time blood feeding occurs. The time required for sporogony, known as the extrinsic incubation period (EIP), is an important determinant of malaria transmission intensity. The EIP is typically estimated as the time for a given percentile, x, of infected mosquitoes to develop salivary gland sporozoites (the infectious parasite life stage), which is denoted by EIPx. Many mechanisms, however, affect the observed sporozoite prevalence including the human-to-mosquito transmission probability and possibly differences in mosquito mortality according to infection status. To account for these various mechanisms, we present a mechanistic mathematical model, which explicitly models key processes at the parasite, mosquito and observational scales. Fitting this model to experimental data, we find greater variation in the EIP than previously thought: we estimated the range between EIP10 and EIP90 (at 27°C) as 4.5 days compared to 0.9 days using existing statistical methods. This pattern holds over the range of study temperatures included in the dataset. Increasing temperature from 21°C to 34°C decreased the EIP50 from 16.1 to 8.8 days. Our work highlights the importance of mechanistic modelling of sporogony to (1) improve estimates of malaria transmission under different environmental conditions or disease control programs and (2) evaluate novel interventions that target the mosquito life stages of the parasite.
AU  - Stopard,IJ
AU  - Churcher,TS
AU  - Lambert,B
DO  - 10.1371/journal.pcbi.1008658
PY  - 2021///
SN  - 1553-734X
TI  - Estimating the extrinsic incubation period of malaria using a mechanistic model of sporogony
T2  - PLoS Computational Biology
UR  - http://dx.doi.org/10.1371/journal.pcbi.1008658
UR  - https://www.ncbi.nlm.nih.gov/pubmed/33591963
UR  - http://hdl.handle.net/10044/1/86441
VL  - 17
ER  -
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