| Title |
Individual-Based Simulation Models of HIV Transmission: Reporting Quality and Recommendations
|
|---|---|
| Published in |
PLOS ONE, September 2013
|
| DOI | 10.1371/journal.pone.0075624 |
| Pubmed ID | |
| Authors |
Nadia N. Abuelezam, Kathryn Rough, George R. Seage |
| Abstract |
Individual-based modeling is a growing technique in the HIV transmission and prevention literature, but insufficient attention has been paid to formally evaluate the quality of reporting in this field. We present reporting recommendations for individual-based models for HIV treatment and prevention, assess the quality of reporting in the existing literature, and comment on the contribution of this model type to HIV policy and prediction. |
X Demographics
The data shown below were collected from the profiles of 5 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 2 | 40% |
| Colombia | 1 | 20% |
| Unknown | 2 | 40% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 3 | 60% |
| Scientists | 1 | 20% |
| Science communicators (journalists, bloggers, editors) | 1 | 20% |
Mendeley readers
The data shown below were compiled from readership statistics for 72 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 72 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 16 | 22% |
| Researcher | 16 | 22% |
| Student > Master | 9 | 13% |
| Student > Bachelor | 6 | 8% |
| Student > Doctoral Student | 4 | 6% |
| Other | 9 | 13% |
| Unknown | 12 | 17% |
| Readers by discipline | Count | As % |
|---|---|---|
| Medicine and Dentistry | 12 | 17% |
| Mathematics | 10 | 14% |
| Nursing and Health Professions | 7 | 10% |
| Social Sciences | 6 | 8% |
| Agricultural and Biological Sciences | 4 | 6% |
| Other | 14 | 19% |
| Unknown | 19 | 26% |