Estimating the extrinsic incubation period of malaria using a mechanistic model of sporogony.
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 malar...
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Public Library of Science (PLoS)
2021-02-01
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| Series: | PLoS Computational Biology |
| Online Access: | https://journals.plos.org/ploscompbiol/article/file?id=10.1371/journal.pcbi.1008658&type=printable |
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| author | Isaac J Stopard Thomas S Churcher Ben Lambert |
| author_facet | Isaac J Stopard Thomas S Churcher Ben Lambert |
| author_sort | Isaac J Stopard |
| collection | DOAJ |
| description | 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. |
| format | Article |
| id | doaj-art-68bbe09354d54c3bb4174b91b5b3d115 |
| institution | OA Journals |
| issn | 1553-734X 1553-7358 |
| language | English |
| publishDate | 2021-02-01 |
| publisher | Public Library of Science (PLoS) |
| record_format | Article |
| series | PLoS Computational Biology |
| spelling | doaj-art-68bbe09354d54c3bb4174b91b5b3d1152025-08-20T02:22:24ZengPublic Library of Science (PLoS)PLoS Computational Biology1553-734X1553-73582021-02-01172e100865810.1371/journal.pcbi.1008658Estimating the extrinsic incubation period of malaria using a mechanistic model of sporogony.Isaac J StopardThomas S ChurcherBen LambertDuring 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.https://journals.plos.org/ploscompbiol/article/file?id=10.1371/journal.pcbi.1008658&type=printable |
| spellingShingle | Isaac J Stopard Thomas S Churcher Ben Lambert Estimating the extrinsic incubation period of malaria using a mechanistic model of sporogony. PLoS Computational Biology |
| title | Estimating the extrinsic incubation period of malaria using a mechanistic model of sporogony. |
| title_full | Estimating the extrinsic incubation period of malaria using a mechanistic model of sporogony. |
| title_fullStr | Estimating the extrinsic incubation period of malaria using a mechanistic model of sporogony. |
| title_full_unstemmed | Estimating the extrinsic incubation period of malaria using a mechanistic model of sporogony. |
| title_short | Estimating the extrinsic incubation period of malaria using a mechanistic model of sporogony. |
| title_sort | estimating the extrinsic incubation period of malaria using a mechanistic model of sporogony |
| url | https://journals.plos.org/ploscompbiol/article/file?id=10.1371/journal.pcbi.1008658&type=printable |
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