Predicting Urban Medical Services Demand in China: An Improved Grey Markov Chain Model by Taylor Approximation

The sharp increase of the aging population has raised the pressure on the current limited medical resources in China. To better allocate resources, a more accurate prediction on medical service demand is very urgently needed. This study aims to improve the prediction on medical services demand in China. To achieve this aim, the study combines Taylor Approximation into the Grey Markov Chain model, and develops a new model named Taylor-Markov Chain GM (1,1) (T-MCGM (1,1)). The new model has been tested by adopting the historical data, which includes the medical service on treatment of diabetes, heart disease, and cerebrovascular disease from 1997 to 2015 in China. The model provides a predication on medical service demand of these three types of disease up to 2022. The results reveal an enormous growth of urban medical service demand in the future. The findings provide practical implications for the Health Administrative Department to allocate medical resources, and help hospitals to manage investments on medical facilities

The dynamics of urban population developments: projection model of urban-rural growth differences

ABSTRACT The study aimed at projecting urban growth from 2010 to 2050 using United Nations, World Urbanization Prospects data. The result is compared to UN prediction on urban growth for the same period. As an alternative to the second order polynomial tested in previous research, a third order polynomial was used to model urban-rural growth difference from 1950 to 2005 country by country, then projections were drawn to 2050. The model was tested over the 1990-2005 period using the 1950-1990 data, giving very good results (mean percentage error of only 1.15%). Using the third order polynomial model, the world urban population is projected at 52.8% by 2050 and 54.2% without China while the UN predicts 67.9%. For the same year (2050), the third order polynomial model foresees that 48.8% of the population in the less developed countries will be living in urban areas while the UN predicts 64.7%. The projection of urban growth in least developed countries is estimated at 35.2% and 55.5% using respectively the third order polynomial model and the UN predictions. The findings suggest that UN predictions are excessively high mostly for less developed countries. The second order polynomial model fitted on the same data gives the same results

Estimation of COVID-19 spread curves integrating global data and borrowing information

Currently, novel coronavirus disease 2019 (COVID-19) is a big threat to global health. The rapid spread of the virus has created pandemic, and countries all over the world are struggling with a surge in COVID-19 infected cases. There are no drugs or other therapeutics approved by the US Food and Drug Administration to prevent or treat COVID-19: information on the disease is very limited and scattered even if it exists. This motivates the use of data integration, combining data from diverse sources and eliciting useful information with a unified view of them. In this paper, we propose a Bayesian hierarchical model that integrates global data for real-time prediction of infection trajectory for multiple countries. Because the proposed model takes advantage of borrowing information across multiple countries, it outperforms an existing individual country-based model. As fully Bayesian way has been adopted, the model provides a powerful predictive tool endowed with uncertainty quantification. Additionally, a joint variable selection technique has been integrated into the proposed modeling scheme, which aimed to identify possible country-level risk factors for severe disease due to COVID-19

The future impact of population growth and aging on coronary heart disease in China: projections from the Coronary Heart Disease Policy Model-China

Background: China will experience an overall growth and aging of its adult population in coming decades. We used a computer model to forecast the future impact of these demographic changes on coronary heart disease (CHD) in China. Methods: The CHD Policy Model is a validated state-transition, computer simulation of CHD on a national scale. China-specific CHD risk factor, incidence, case-fatality, and prevalence data were incorporated, and a CHD prediction model was generated from a Chinese cohort study and calibrated to age-specific Chinese mortality rates. Disability-adjusted life years (DALYs) due to CHD were calculated using standard methods. The projected population of China aged 35–84 years was entered, and CHD events, deaths, and DALYs were simulated over 2000–2029. CHD risk factors other than age and case-fatality were held at year 2000 levels. Sensitivity analyses tested uncertainty regarding CHD mortality coding, the proportion of total deaths attributable to CHD, and case-fatality. Results: We predicted 7.8 million excess CHD events (a 69% increase) and 3.4 million excess CHD deaths (a 64% increase) in the decade 2020–2029 compared with 2000–2009. For 2030, we predicted 71% of almost one million annual CHD deaths will occur in persons ≥ 65 years old, while 67% of the growing annual burden of CHD death and disability will weigh on adults < 65 years old. Substituting alternate CHD mortality assumptions led to 17–20% more predicted CHD deaths over 2000–2029, though the pattern of increases in CHD events and deaths over time remained. Conclusion: We forecast that absolute numbers of CHD events and deaths will increase dramatically in China over 2010–2029, due to a growing and aging population alone. Recent data suggest CHD risk factor levels are increasing, so our projections may underestimate the extent of the potential CHD epidemic in China

Predicting the potential geographical distribution of the harlequin ladybird, Harmonia axyridis, using the CLIMEX model - BioControl

Harmonia axyridis (Pallas, 1773) (Coleoptera: Coccinellidae) is a ladybird beetle native to temperate and subtropical parts of Asia. Since 1916 populations of this species have been introduced throughout the world, either deliberately, or by accident through international transport. Harmonia axyridis was originally released as a classical biological control agent of aphid and coccid pests in orchards and forests, but since 1994 it is also available as a commercial product for augmentative control in field and greenhouse crops. It is a very voracious and effective natural enemy of aphids, psyllids and coccids in various agricultural and horticultural habitats and forests. During the past 20 years, however, it has successfully invaded non-target habitats in North America (since 1988), Europe (1999) and South America (2001) respectively in a short period of time, attacking a wide range of non-pest species in different insect orders. Becoming part of the agricultural commercial pathway, it is prone to being introduced into large areas across the world by accident. We use the CLIMEX programme (v2) to predict the potential geographical distribution of H. axyridis by means of matching the climate of its region of origin with other regions in the world and taking in account biological characteristics of the species. Establishment and spread seem likely in many regions across the world, including those areas which H. axyridis has already invaded (temperate Europe, North America). Based on the CLIMEX prediction a large part of Mediterranean Europe, South America, Africa, Australia and New Zealand seem highly suitable for long-term survival of H. axyridis as well. In addition we evaluate CLIMEX as a strategic tool for estimating establishment potential as part of an environmental risk assessment procedure for biological control agents we discuss biological and ecological aspects necessary to fine-tune its establishment and spread in areas after it has been introduce