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| Content Provider | Springer Nature : BioMed Central |
|---|---|
| Author | Yuan, Lei Tian, Shiyin Zhao, Zhe Liu, Pei Liu, Lijuan Sun, Jinhai |
| Abstract | Background Since the first case of HIV infection was reported in China in 1985, the incidence and mortality of AIDS have been increasing rapidly, which has caused serious damage to the life and health of people in China and all over the world. Therefore, it is of great significance to study the technique for predicting AIDS morbidity and mortality. The purpose of this research is to explore the applicability of the mean generation function model (MGFM) in the early warning of AIDS morbidity and mortality, to predict its prevalence trend, to enrich the prediction techniques and methods of AIDS research and to provide suggestions for AIDS transmission control. Methods In this research, the MGFM was applied to predict the incidence and mortality of AIDS in China. AIDS incidence and mortality data in China from 2008 to 2019 were used to construct the prediction model. Results The MGFM can predict the annual incidence and mortality of AIDS. The model constructed in this research predicted that the incidence and mortality of AIDS in China will continue to increase from 2020 to 2023. Conclusion The mean birth function model was an effective method to monitor and predict the changing trend of AIDS incidence and mortality in China. |
| Related Links | https://bmcmedinformdecismak.biomedcentral.com/counter/pdf/10.1186/s12911-022-01825-6.pdf |
| Ending Page | 10 |
| Page Count | 10 |
| Starting Page | 1 |
| File Format | HTM / HTML |
| ISSN | 14726947 |
| DOI | 10.1186/s12911-022-01825-6 |
| Journal | BMC Medical Informatics and Decision Making |
| Issue Number | 1 |
| Volume Number | 22 |
| Language | English |
| Publisher | BioMed Central |
| Publisher Date | 2022-04-16 |
| Access Restriction | Open |
| Subject Keyword | Health Informatics Information Systems and Communication Service Management of Computing and Information Systems AIDS Incidence Mortality Mean generation function model Forecast China |
| Content Type | Text |
| Resource Type | Article |
| Subject | Health Informatics Computer Science Applications Health Policy |
| Journal Impact Factor | 3.3/2023 |
| 5-Year Journal Impact Factor | 3.9/2023 |
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