Abstract
The complex biological relationships underlying malaria transmission make it difficult to predict the impact of interventions. Mathematical models simplify these relationships and capture essential components of malaria transmission and epidemiology. Models designed to predict the impact of control programs generally infer a relationship between transmission intensity and human infectiousness to the mosquito, requiring assumptions about how infectiousness varies between individuals. A lack of understanding of human infectiousness precludes a standard approach to this inference, however, and field data reveal no obvious correlation between transmission intensity and human population infectiousness. We argue that model assumptions will have important consequences for predicting the impact of control programs.
| Original language | English (US) |
|---|---|
| Pages (from-to) | 270-275 |
| Number of pages | 6 |
| Journal | Trends in Parasitology |
| Volume | 29 |
| Issue number | 6 |
| DOIs | |
| State | Published - Jun 2013 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
-
SDG 3 Good Health and Well-being
All Science Journal Classification (ASJC) codes
- Parasitology
- Infectious Diseases
Fingerprint
Dive into the research topics of 'Modeling the human infectious reservoir for malaria control: Does heterogeneity matter?'. Together they form a unique fingerprint.Cite this
- APA
- Author
- BIBTEX
- Harvard
- Standard
- RIS
- Vancouver