Peiping Zhou
Biographic Data
| ID | 9022805 |
|---|---|
| NAME | Peiping Zhou |
| GIVEN NAMES | Peiping |
| FAMILY NAME | Zhou |
| SIGNATURE | ZHOU P |
| AFFILIATIONS | Xinxiang Medical University |
| ORCID | 0009-0009-2369-0319 |
| VERIFIED | Yes |
| TOTAL WORKS | 3 |
| TOTAL CITATIONS | 0 |
| AUTHOR COUNT | 3 |
| EDITOR COUNT | 0 |
| FIRST PUBLICATION YEAR | 2025 |
| LATEST PUBLICATION YEAR | 2025 |
| H-INDEX | 0 |
Forecasting tuberculosis epidemics using an autoregressive fractionally integrated moving average model: A 17-year time series analysis
Background: Multimorbidity is increasingly prevalent among older adults and poses significant challenges to health and well-being. This study applied a health ecological model to investigate the prevalence, determinants, and common disease patterns of multimorbidity, as well as the factors associated with quality of life (QoL) among older adults in southern China. Methods: A cross-sectional survey was conducted among 2404 individuals aged 60 year…
Forecasting tuberculosis epidemics using an autoregressive fractionally integrated moving average model: A 17-year time series analysis
Background: Tuberculosis (TB) remains a significant public health challenge in Henan, China, requiring accurate forecasting to guide prevention and control efforts. While traditional models like autoregressive integrated moving average (ARIMA) are commonly used, they may not fully capture long-term dependencies in the data. This study evaluates the autoregressive fractionally integrated moving average (ARFIMA) model, which incorporates fractional…
Long-term impact of Covid-19-related nonpharmaceutical interventions on tuberculosis: An interrupted time series analysis using Bayesian method
Background: The implementation of non-pharmaceutical interventions (NPIs) during the COVID-19 pandemic may inadvertently influence the epidemiology of tuberculosis (TB). (TB). However, few studies have explored how NPIs impact the long-term epidemiological trends of TB. We aimed to estimate the impact of NPIs implemented against COVID-19 on the medium- and long-term TB epidemics and to forecast the epidemiological trend of TB in Henan. Methods: W…
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Forecasting tuberculosis epidemics using an autoregressive fractionally integrated moving average model: A 17-year time series analysis
Background: Multimorbidity is increasingly prevalent among older adults and poses significant challenges to health and well-being. This study applied a health ecological model to investigate the prevalence, determinants, and common disease patterns of multimorbidity, as well as the factors associated with quality of life (QoL) among older adults in southern China. Methods: A cross-sectional survey was conducted among 2404 individuals aged 60 year…
Forecasting tuberculosis epidemics using an autoregressive fractionally integrated moving average model: A 17-year time series analysis
Background: Tuberculosis (TB) remains a significant public health challenge in Henan, China, requiring accurate forecasting to guide prevention and control efforts. While traditional models like autoregressive integrated moving average (ARIMA) are commonly used, they may not fully capture long-term dependencies in the data. This study evaluates the autoregressive fractionally integrated moving average (ARFIMA) model, which incorporates fractional…
Long-term impact of Covid-19-related nonpharmaceutical interventions on tuberculosis: An interrupted time series analysis using Bayesian method
Background: The implementation of non-pharmaceutical interventions (NPIs) during the COVID-19 pandemic may inadvertently influence the epidemiology of tuberculosis (TB). (TB). However, few studies have explored how NPIs impact the long-term epidemiological trends of TB. We aimed to estimate the impact of NPIs implemented against COVID-19 on the medium- and long-term TB epidemics and to forecast the epidemiological trend of TB in Henan. Methods: W…
Time series (3 works) · Tuberculosis (3 works) · Tuberculosis Research and Epidemiology (3 works) · Autoregressive integrated moving average (2 works) · Autoregressive model (2 works) · Biology (2 works) · Computer Science (2 works) · Mathematics (2 works) · Medicine (2 works) · Statistics (2 works)