Seroepidemiological Investigation of Lyme Disease and Human Granulocytic Anaplasmosis among People Living in Forest Areas of Eight Provinces in China

Objective Lyme disease and Human granulocytic anaplasmosis are tick-borne diseases caused by Borrelia burgdorferi and Anoplasrna phagocytophilum respectively. We have investigated infection and co-infection of the two diseases in the population of forest areas of eight provinces in China by measuring seroprevalence of antibodies against B. burgdorferi and A. phagocytophilum. Methods Forest areas in 8 provinces were chosen for investigation using whole sampling and questionnaire survey methods. 3 669 serum samples from people in the forest areas were tested for the presence of antibodies by indirect immunofluorescent assay （IFA）. Results Seroprevalence against B. burgdorferi was 3% to 15% and against A. phagocytophilum was 2% to 18% in the study sites in the 8 provinces in China. We also found co-infection of B. burgdorferi and A. phagocytophilum in 7 of the 8 provinces （the exception being the Miyun area in Beijing）. The seroprevalence for both B. burgdorferi and A. phagocytophilum was significantly higher among people exposed to ticks than among people who were not exposed to ticks. Conclusion We conclude that both pathogens are endemic in the forest areas in the eight provinces, but the prevalence of B. burgdorferi and A. phagocytophilum differs between the provinces.

A diagnostic prediction model for hypertension in Han and Yugur population from the China National Health Survey (CNHS)

Background:The prevalence of hypertension is high among Chinese adults,thus,identifying non-hypertensive individuals at high risk for intervention will help to improve the efficiency of primary prevention strategies.Methods:The cross-sectional data on 9699 participants aged 20 to 80 years were collected from the China National Health Survey in Gansu and Hebei provinces in 2016 to 2017,and they were nonrandomly split into the training set and validation set based on location.Multivariable logistic regression analysis was performed to develop the diagnostic prediction model,which was presented as a nomogram and a website with risk classification.Predictive performances of the model were evaluated using discrimination and calibration,and were further compared with a previously published model.Decision curve analysis was used to calculate the standardized net benefit for assessing the clinical usefulness of the model.Results:The Lasso regression analysis identified the significant predictors of hypertension in the training set,and a diagnostic model was developed using logistic regression.A nomogram with risk classification was constructed to visualize the model,and a website(https://chris-yu.shinyapps.io/hypertension_risk_prediction/)was developed to calculate the exact probabilities of hypertension.The model showed good discrimination and calibration,with the C-index of 0.789(95%confidence interval[CI]:0.768,0.810)through internal validation and 0.829(95%CI:0.816,0.842)through external validation.Decision curve analysis demonstrated that the model was clinically useful.The model had a higher area under receiver operating characteristic curves in training and validation sets compared with a previously published diagnostic model based on Northern China population.Conclusion:This study developed and validated a diagnostic model for hypertension prediction in Gansu Province.A nomogram and a website were developed to make the model conveniently used to facilitate the individualized prediction of hypertension in the general population of Han and Yugur.