Estimation of the prevalence and contagiousness of undocumented novel coronavirus [severe acute respiratory syndrome–coronavirus 2 (SARS-CoV-2)] infections is critical for understanding the overall prevalence and pandemic potential of this disease. Here, we use observations of reported infection within China, in conjunction with mobility data, a networked dynamic metapopulation model, and Bayesian inference, to infer critical epidemiological characteristics associated with SARS-CoV-2, including the fraction of undocumented infections and their contagiousness. We estimate that 86% of all infections were undocumented [95% credible interval (CI): 82–90%] before the 23 January 2020 travel restrictions. The transmission rate of undocumented infections per person was 55% the transmission rate of documented infections (95% CI: 46–62%), yet, because of their greater numbers, undocumented infections were the source of 79% of the documented cases. These findings explain the rapid geographic spread of SARS-CoV-2 and indicate that containment of this virus will be particularly challenging.

BackgroundCurrent knowledge about elder mistreatment is mainly derived from studies done in Western countries, which indicate that this problem is related to risk factors such as a shared living situation, social isolation, disease burden, and caregiver strain. We know little about prevalence and risk factors for elder mistreatment and mistreatment subtypes in rural China where the elder population is the most vulnerable.MethodsIn 2010, we conducted a cross-sectional survey among older adults aged 60 or older in three rural communities in Macheng, a city in Hubei province, China. Of 2245 people initially identified, 2039 were available for interview and this was completed in 2000. A structured questionnaire was used to collect data regarding mistreatment and covariates. Logistic regression analysis was used to identify factors related to elder mistreatment and subtypes of mistreatment.ResultsElder mistreatment was reported by 36.2% (95% CI: 34.1%–38.3%) of the participants. Prevalence rates of psychological mistreatment, caregiver neglect, physical mistreatment, and financial mistreatment were 27.3% (95% CI: 25.3%–29.2%), 15.8% (95% CI: 14.2%–17.4%), 4.9% (95% CI: 3.9%–5.8%) and 2.0% (95% CI: 1.3%–2.6%), respectively. The multivariate logistic regression analysis revealed that depression, being widowed/divorced/single/separated, having a physical disability, having a labor intensive job, depending solely on self-made income, and living alone were risk factors for elder mistreatment. Different types of elder mistreatment were associated with different risk factors, and depression was the consistent risk factor for the three most common mistreatment subtypes.ConclusionOlder adults in rural China self-report a higher rate of mistreatment than their counterparts in Western countries. Depression is a main risk factor associated with most subtypes of mistreatment. Our findings suggest that prevention and management of elder mistreatment is a challenge facing a rapidly aging Chinese population.

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BackgroundAccelerated population ageing brings about unprecedented challenges to the health system in China. This study aimed to measure the prevalence and the income-related inequality of depressive symptoms, and also identify the determinants of depressive symptom inequality among the elderly in China.MethodsData were drawn from the second wave of the China Health and Retirement Longitudinal Study (CHARLS). Depressive symptoms were assessed with a 10-item Center for Epidemiologic Studies–Depression Scale (CES-D), which was preselected in CHARLS. The concentration index was used to measure the magnitude of income-related inequality in depressive symptoms. A decomposition analysis, based on the logit model, was employed to quantify the contribution of each determinant to total inequality.ResultsMore than 32.55% of the elderly in China had depressive symptoms. Women had a higher prevalence of depressive symptoms than men. The overall concentration index of depressive symptoms was -0.0645 among the elderly, indicating that depressive symptoms are more concentrated among the elderly who lived in economically disadvantaged situations, favoring the rich. Income was found to have the largest percentage of contribution to overall inequality, followed by residents’ location and educational attainment.ConclusionThe prevalence of depressive symptoms in the elderly was considerably high in China. There was also a pro-rich inequality in depressive symptoms amongst elderly Chinese. It is suggested that some form of policy and intervention strategies, such as establishing the urban-rural integrated medical insurance scheme, enhancing the medical assistance system, and promoting health education programs, is required to alleviate inequitable distribution of depressive symptoms.Electronic supplementary materialThe online version of this article (doi:10.1186/s12889-016-3876-1) contains supplementary material, which is available to authorized users.

Hand, foot and mouth disease (HFMD) has recently been recognized as a critical challenge to disease control and public health response in China. This study aimed to quantify the association between temperature and HFMD in Chengdu. Daily HFMD cases and meteorological variables in Chengdu between January 2010 and December 2013 were obtained to construct the time series. A distributed lag non-linear model was performed to investigate the temporal lagged association of daily temperature with age- and gender-specific HFMD. A total of 76,403 HFMD cases aged 0–14 years were reported in Chengdu during the study period, and a bimodal seasonal pattern was observed. The temperature-HFMD relationships were non-linear in all age and gender groups, with the first peak at 14.0–14.1 °C and the second peak at 23.1–23.2 °C. The high temperatures had acute and short-term effects and declined quickly over time, while the effects in low temperature ranges were persistent over longer lag periods. Males and children aged <1 year were more vulnerable to temperature variations. Temperature played an important role in HFMD incidence with non-linear and delayed effects. The success of HFMD intervention strategies could benefit from giving more consideration to local climatic conditions.

ObjectivesChina has experienced a sharply increasing rate of human brucellosis in recent years. Effective spatial monitoring of human brucellosis incidence is very important for successful implementation of control and prevention programmes. The purpose of this paper is to apply exploratory spatial data analysis (ESDA) methods and the empirical Bayes (EB) smoothing technique to monitor county-level incidence rates for human brucellosis in mainland China from 2004 to 2010 by examining spatial patterns.MethodsESDA methods were used to characterise spatial patterns of EB smoothed incidence rates for human brucellosis based on county-level data obtained from the China Information System for Disease Control and Prevention (CISDCP) in mainland China from 2004 to 2010.ResultsEB smoothed incidence rates for human brucellosis were spatially dependent during 2004–2010. The local Moran test identified significantly high-risk clusters of human brucellosis (all p values <0.01), which persisted during the 7-year study period. High-risk counties were centred in the Inner Mongolia Autonomous Region and other Northern provinces (ie, Hebei, Shanxi, Jilin and Heilongjiang provinces) around the border with the Inner Mongolia Autonomous Region where animal husbandry was highly developed. The number of high-risk counties increased from 25 in 2004 to 54 in 2010.ConclusionsESDA methods and the EB smoothing technique can assist public health officials in identifying high-risk areas. Allocating more resources to high-risk areas is an effective way to reduce human brucellosis incidence.

Bacillary dysentery (BD) remains a big public health problem in China. Effective spatio-temporal monitoring of BD incidence is important for successful implementation of control and prevention measures. This study aimed to examine the spatio-temporal pattern of BD and analyze socio-economic factors that may affect BD incidence in Sichuan province, China. Firstly, we used space-time scan statistic to detect the high risk spatio-temporal clusters in each year. Then, bivariate spatial correlation and Bayesian spatio-temporal model were utilized to examine the associations between the socio-economic factors and BD incidence. Spatio-temporal clusters of BD were mainly located in the northern-southern belt of the midwest area of Sichuan province. The proportion of primary industry, the proportion of rural population and the rates of BD incidence show statistically significant positive correlation. The proportion of secondary industry, proportion of tertiary Industry, number of beds in hospitals per thousand persons, medical and technical personnel per thousand persons, per capital GDP and the rate of BD incidence show statistically significant negative correlation. The best fitting spatio-temporal model showed that medical and technical personnel per thousand persons and per capital GDP were significantly negative related to the risk of BD.

Dietary supplementation of d-psicose could slow down fat accumulation in rats by regulating lipid metabolism related genes.