Qunzheng Mu
Biographic Data
| ID | 7780874 |
|---|---|
| NAME | Qunzheng Mu |
| GIVEN NAMES | Qunzheng |
| FAMILY NAME | Mu |
| SIGNATURE | MU Q |
| AFFILIATIONS | Sichuan University |
| VERIFIED | No |
| TOTAL WORKS | 3 |
| TOTAL CITATIONS | 0 |
| WORKS AS AUTHOR | 3 |
| WORKS AS EDITOR | 0 |
| FIRST PUBLICATION YEAR | 2023 |
| LATEST PUBLICATION YEAR | 2026 |
| H-INDEX | 0 |
Spatiotemporal patterns, associated factors, and forecasting of pulmonary tuberculosis
Pulmonary tuberculosis (PTB) remains a significant public health challenge in underdeveloped regions of western China. A critical, yet underutilized, approach to strengthening grassroots control lies in township-level Perspective. This study takes Zigong City, a prototypical prefectural-level city in Southwestern China, as a case study to elucidate the fine-scale spatiotemporal patterns, potential influencing factors, and future trends of PTB. Th…
Predicting the potential distribution areas of Leptotrombidium rubellum under current and future climate change
Background: a confirmed vector of scrub typhus, was historically restricted to southeastern coastal China but has recently been detected in southwestern regions. Species distribution modeling was applied to predict its current and future potential distribution areas under multiple climate scenarios, identify high-priority surveillance areas, and determine key environmental drivers. The results may facilitate a transition from passive to proactive…
Predicting global potential distribution of Peromyscopsylla hesperomys and Orchopeas sexdentatus and risk assessment for invading China under climate change
Background: are regarded to be representative plague vectors in the United States. The incidence of plague is rising globally, possibly due to climate change and environmental damage. Environmental factors such as temperature and precipitation have a significant impact on the temporal and spatial distribution of plague vectors. Methods: Maximum entropy models (MaxEnt) were utilized to predict the distributions of these two fleas and their trends …
No prominent works on this page.
Predicting global potential distribution of Peromyscopsylla hesperomys and Orchopeas sexdentatus and risk assessment for invading China under climate change
Background: are regarded to be representative plague vectors in the United States. The incidence of plague is rising globally, possibly due to climate change and environmental damage. Environmental factors such as temperature and precipitation have a significant impact on the temporal and spatial distribution of plague vectors. Methods: Maximum entropy models (MaxEnt) were utilized to predict the distributions of these two fleas and their trends …
Predicting the potential distribution areas of Leptotrombidium rubellum under current and future climate change
Background: a confirmed vector of scrub typhus, was historically restricted to southeastern coastal China but has recently been detected in southwestern regions. Species distribution modeling was applied to predict its current and future potential distribution areas under multiple climate scenarios, identify high-priority surveillance areas, and determine key environmental drivers. The results may facilitate a transition from passive to proactive…
Spatiotemporal patterns, associated factors, and forecasting of pulmonary tuberculosis
Pulmonary tuberculosis (PTB) remains a significant public health challenge in underdeveloped regions of western China. A critical, yet underutilized, approach to strengthening grassroots control lies in township-level Perspective. This study takes Zigong City, a prototypical prefectural-level city in Southwestern China, as a case study to elucidate the fine-scale spatiotemporal patterns, potential influencing factors, and future trends of PTB. Th…
Biology (2 works) · China (2 works) · Climate change (2 works) · Climatology (2 works) · Ecology (2 works) · Environmental Science (2 works) · Mathematics (2 works) · Mosquito-borne diseases and control (2 works) · Animal Ecology and Behavior Studies (1 work) · Climate Change and Health Impacts (1 work)