Low-risk Regions Research Articles

Hypofractionated Accelerated Radiation Dose-Painting (HARD) vs. Standard Radiotherapy for Unresected Soft-Tissue Sarcoma

Conventionally fractionated radiotherapy (CFRT) offers modest local control (LC) for unresected soft tissue sarcoma (STS). Although STS has a low α/β (∼2 - 6) that may benefit from a hypofractionated radiotherapy regimen, it is often limited due to the toxicity risk to surrounding organs. A simultaneous integrated boost to gross disease (2.5 - 3 Gy/fraction), with lower doses to the intermediate and low risk target volume, may offer a safe isotoxic dose escalation approach. We hypothesize that this hypofractionated accelerated radiotherapy dose-painting (HARD) will improve local control compared to CFRT. We performed a single institution retrospective analysis of patients who received external beam radiotherapy with definitive intent (≥50 Gy) for unresected STS. CFRT was defined as 1.8 - 2 Gy/fraction (Gy/fx). HARD regimens consisted of 60 - 66 Gy at 3 Gy/fx or 70 Gy at 2.5 Gy/fx to gross disease, with 1.8 - 2.4 Gy/fx to intermediate and low risk regions. All anatomical sites and histologies were included. Local control (LC) was defined from date of current diagnosis, estimated by Kaplan-Meier methods via log-rank tests or Cox regression for univariate analysis (UVA), when appropriate. Cox regression multivariate analysis (MVA) included regimen, biological effective dose (α/β 6; BED6), lesion size, age, and grade. We identified 77 patients with primary and metastatic STS treated with HARD (n = 40) or CFRT (n = 37) between 1990 and 2022, with a median follow up of 24 months in surviving patients. The mean dose for CFRT and HARD are 56.8 Gy (50 - 77.4 Gy) and 64.9 Gy (60 - 70 Gy), respectively. HARD was comprised of 65% for 3 Gy/fx and 35% for 2.5 Gy/fx regimens. At the time of RT, grade 3 (69%) and extremity (39%) tumors were the most common. Tumor histology was very heterogenous across both cohorts, with undifferentiated pleomorphic sarcoma being the most common for HARD (33%) and CFRT (19%). HARD was more often utilized in stage IV patients (55% vs. 19%, p = 0.001) and had a higher mean BED6 (96 vs. 74.2 Gy, p < 0.001) than CFRT, but without differences in age (67 vs. 59 years), tumor size (8 vs. 10 cm), concurrent chemotherapy (35% vs. 30%), Karnofsky performance status (86 vs. 85), follow-up (19 vs. 28 months), and grade (all p > 0.1). On UVA, there was a LC benefit associated with higher BED6 (HR 0.94, 95% CI 0.9 - 0.98, p = 0.002) and the HARD regimen (2-year LC 95% vs. 62%, p < 0.001). On MVA, only HARD (HR 0.07, 95% CI 0.006 - 0.729, p = 0.027) was independently associated with LC. Although the HARD regimen and higher BED6 were both associated with significant improvement in LC, only the HARD regimen independently associated with a local control benefit for unresected STS. These results suggest biologic dose-intensification exploiting the low α/β of STS with an isotoxic hypofractionated regimen may be a favorable strategy for unresectable STS. Future prospective studies are necessary to validate these findings.

Combining Radiotherapy with Chemotherapy and Immunotherapy as First-Line Treatment for De Novo Metastatic Nasopharyngeal Carcinoma: A Dual-Center Retrospective Analysis

Local regional radiotherapy combined with systemic chemotherapy significantly improves the prognosis of patients with metastatic nasopharyngeal carcinoma (NPC). Immunochemotherapy has become the first-line treatment for initial metastatic NPC. This study evaluated the safety and efficacy of local regional radiotherapy combined with immunochemotherapy as the first-line treatment of metastatic NPC. Patients with histologically proven de novo metastatic NPC who received immunotherapy and chemotherapy followed by local-regional radiotherapy were included from 2 cancer centers. Toxicity and treatment response were assessed using CTCAE 5.0 and RECIST 1.1, respectively. Overall survival (OS) and progression free survival (PFS) were analyzed using the Kaplan-Meier method. From 2019 to 2021, a total of 16 patients were retrospectively analyzed. The median age was 44.5-year-old (range 16-76). Patients with ≥3 metastatic lesions accounts for 58.8%. Bone metastasis was the most common metastatic site. The chemotherapy regimens were paclitaxel/gemcitabine and cisplatin. Toripalimab, camrelizumab and sintilimab were used for immunotherapy. All patients completed the local regional radiotherapy with 69.96Gy for primary nasopharyngeal tumor and positive lymph nodes, 60.06Gy for high-risk region and 50ཞ54.45Gy for low-risk region. Seven patients underwent radiotherapy for metastatic lesions. The median follow-up was 20.5 months (range 6-38 months). Two-year OS was 100%. Three patients experienced distant progression. One-year and 2-year PFS rate was 93.8% and 76.7%, respectively. After combination of chemotherapy and immunotherapy, the overall response rate (ORR) was 93.7% with a complete response (CR) of 6.3%. At the end of radiotherapy, the ORR was 100%. Nine patients (56.3%) achieved CR. Radiotherapy related acute severe (grade 3 or higher) toxicity was dermatitis (1/16, 6.3%) and mucositis (2/16, 12.5%). Immunotherapy related hypophysitis and capillary hyperplasia was 6.3% and 6.3%, respectively. No long-term toxicity was observed. Loco-regional radiotherapy provided a promising efficacy with modest toxicity for patients with metastatic nasopharyngeal carcinoma who received immunochemotherapy.

Study on the regional risk classification method for the prevention and control of emerging infectious diseases based on directed graph theory.

Emerging infectious diseases are a class of diseases that are spreading rapidly and are highly contagious. It seriously affects social stability and poses a significant threat to human health, requiring urgent measures to deal with them. Its outbreak will very easily lead to the large-scale spread of the virus, causing social problems such as work stoppages and traffic control, thereby causing social panic and psychological unrest, affecting human activities and social stability, and even endangering lives. It is essential to prevent and control the spread of infectious diseases effectively. We aim to propose an effective method to classify the risk level of a new epidemic region by using graph theory and risk classification methods to provide a theoretical reference for the comprehensive evaluation and determination of epidemic prevention and control, as well as risk level classification. Using the graph theory method, we first define the network structure of social groups and construct the risk transmission network of the new epidemic region. Then, combined with the risk classification method, the classification of high, medium, and low risk levels of the new epidemic region is discussed from two cases with common and looped graph nodes, respectively. Finally, the reasonableness of the classification method is verified by simulation data. The directed weighted scale-free network can better describe the transmission law of an epidemic. Moreover, the proposed method of classifying the risk level of a region by using the correlation function between two regions and the risk value of the regional nodes can effectively evaluate the risk level of different regions in the new epidemic region. The experiments show that the number of medium and high risk nodes shows no increasing trend. The number of high-risk regions is relatively small compared to medium-risk regions, and the number of low-risk regions is the largest. It is necessary to distinguish scientifically between the risk level of the epidemic area and the neighboring regions so that the constructed social network model of the epidemic region's spread risk can better describe the spread of the epidemic risk in the social network relations.

Investigation of the prevalence and risk factors of Helicobacter pylori infection and the value of different gastric cancer screening methods in a low-risk region of gastric cancer in China

Background The aim of this current study was to identify the prevalence and risk factors of H. pylori infection in the low-risk area of gastric cancer in China, and evaluate the value of different gastric cancer screening methods. Methods An epidemiological study was conducted in Yudu County, Jiangxi, China, and participants were followed up for 6 years. All participants completed a questionnaire, laboratory tests and endoscopy. Patients were divided into H. pylori positive and negative groups, and risk factors for H. pylori infection were identified using multivariate logistic regression analysis. Results A total of 1962 residents were included, the prevalence of H. pylori infection was 33.8%. Multivariate analysis showed that annual income ≤20,000 yuan (OR: 1.44, 95% CI: 1.18–1.77, p < 0.001), loss of appetite (OR: 1.71, 95% CI: 1.29-2.26, p < 0.001), PG II >37.23 ng/mL (OR: 2.11, 95% CI: 1.50–2.97, p < 0.001), G-17 > 1.5 and ≤5.7 pmol/L (OR: 2.52, 95% CI: 1.93–3.30, p < 0.001), and G-17 > 5.7 pmol/L (OR: 1.96, 95% CI: 1.48–2.60, p < 0.001) were risk factors of H. pylori infection, while alcohol consumption (OR: 0.70, 95% CI: 0.54–0.91, p = 0.006) was a protective factor. According to the new gastric cancer screening method, the prevalence of low-grade intraepithelial neoplasia in the low-risk group, medium-risk group and high-risk group was 4.4%, 7.7% and 12.5% respectively (p < 0.001). Conclusions In a low-risk area of gastric cancer in China, the infection rate of H. pylori is relatively low. Low income, loss of appetite, high PG II, and high G-17 were risk factors for H. pylori infection, while alcohol consumption was a protective factor. Moreover, the new gastric cancer screening method better predicted low-grade intraepithelial neoplasia than the ABC method and the new ABC method.

Recommendations for statin management in primary prevention: disparities among international risk scores.

Statin recommendations in primary prevention depend upon risk algorithms. Moreover, with intermediate risk, risk enhancers and de-enhancers are advocated to aid decisions. The aim of this study was to compare algorithms used in North America and Europe for the identification of patients warranting statin or consideration of risk enhancers and de-enhancers. A simulated population (n = 7680) equal in males and females, with/without smoking, aged 45-70 years, total cholesterol 3.5-7.0 mmol/L, high-density lipoprotein cholesterol 0.6-2.2 mmol/L, and systolic blood pressure 100-170 mmHg, was evaluated. High, intermediate, and low risks were determined using the Framingham Risk Score (FRS), Pooled Cohort Equation (PCE), four versions of Systematic Coronary Risk Evaluation 2 (SCORE2), and Multi-Ethnic Study of Atherosclerosis (MESA) algorithm (0-1000 Agatston Units). Concordance for the three levels of risk varied from 19% to 85%. Both sexes might be considered to have low, intermediate, or high risk depending on the algorithm applied, even with the same burden of risk factors. Only SCORE2 (High Risk and Very High Risk versions) identified equal proportions of males and females with high risk. Excluding MESA, the proportion with moderate risk was 25% (SCORE2, Very High Risk Region), 32% (FRS), 39% (PCE), and 45% (SCORE2, Low Risk Region). Risk algorithms differ substantially in their estimation of risk, recommendations for statin treatment, and use of ancillary testing, even in identical patients. These results highlight the limitations of currently used risk-based approaches for addressing lipid-specific risk in primary prevention.

Integrating landscape ecological risk into ecosystem service value assessment: A case study of Nanjing City, China

The scientific assessment of ecosystem service value (ESV) and landscape ecological risk (LER) is important for ecological security and sustainable development. However, existing studies often separate ESV and LER for a single evaluation, and the single evaluation is limited in guiding ecological conservation. Therefore, proposing an evaluation framework that integrates ESV and LER is urgent. Taking Nanjing City as an example, this study evaluated LER based on the risk evaluation cell and introduced it into ESV evaluation. Then, the influence of land use/land cover change on LER and ESV from 2000 to 2020 was analyzed. The results showed that built-up land and water body/wetland increased by 881.96 km2 and 41.41 km2, and farmland and forest land decreased by 875.46 km2 and 55.83 km2 from 2000 to 2020. The LER was low in the middle and high in the north and south. From 2000 to 2010, the LER increased from 0.67 to 0.68, and it then decreased to 0.61 in 2020. Medium-low risk regions decreased during 2000–2010, and low-risk regions increased and medium-high risk regions decreased during 2010–2020. The ESV increased by 0.77 billion United States dollars (USD) during 2000–2010 but decreased by 0.40 billion USD during 2010–2020. Under the impact of LER, the ESV per unit area of the farmland, forest land, and water body decreased during 2000–2020. The ESV of the water body dominated the total ESV and had an important influence on the change in total ESV. The ESV in Nanjing City during 2000–2020 mainly showed High-High autocorrelation and a few Low-High autocorrelations. Ecological restoration programs increased ESV during 2000–2010, but rapid urbanization reduced ESV during 2010–2020. Integrating social, economic, and ecological resources is necessary to realize the coordinated development of the economy and ecology. The results can provide an important reference for landscape planning and ecosystem management.

Landslide Classification and Prediction of Debris Flow Using Machine Learning Models

Landslides are unpredictable and destructive calamities that motivated the development of early warning systems to alert people and save their lives and property. A novel two-layer architecture is proposed to classify and predict landslides and types. The research is carried out in the Idukki district, Kerala, India, covering an area of 4358 km2. Layer-1 uses topographical, hydrogeological, and meteorological features collected from various sources. The binary classifier in this layer classifies and predicts the probability of landslide occurrence. Layer-2 classifies landslides into debris flow, rockfall, and surficial slides and predicts debris flow through a multi-class classifier. To achieve better prediction accuracy, the landslide features that significantly influence the landslide occurrence of layer-1 are combined with layer-2. The Synthetic Minority Oversampling Technique is used to balance the database of minority categories. Classification and prediction are achieved using machine learning models such as the support vector machine, decision tree, random forest, and extreme gradient-boosting, and their performances are compared. The feature score for every feature of the model is calculated using the feature importance technique. The machine learning models are validated using the Area Under the Receiver Operating Characteristics curve and F1-score. On comparison, Extreme Gradient-Boost is found to perform well. Based on the prediction probability, the debris flow is classified into high-risk, medium-risk, and low-risk regions. This favored in identifying vulnerable areas and appropriate mitigation measures to reduce life loss and damage to infrastructure.

A multi-dimensional framework for improving flood risk assessment: Application in the Han River Basin, China

Study regionThe Han River Basin, China Study focusAs the water source of the Middle Route Project of the South to North Water Transfer Project, water security in the Han River Basin deeply impacts national water resource allocation. This study constructed a Multi-Dimensional Flood Risk Assessment (MDFRA) framework combining a comprehensive index system, an integrated weight method, and a clustering algorithm to assess flood risk in the Han River Basin. We first constructed a comprehensive index system including eight hazard indexes, four exposure indexes, and eight vulnerability indexes in demographic, economic, ecological, and infrastructural categories to assess flood risk. The index weights were determined by the integrated weight method, which integrated the Shapley value and the Analytic Hierarchy Process method (SAHP). Finally, the possibilistic fuzzy C-means algorithm was employed to identify flood risk levels. New hydrological insights for the regionThe MDFRA framework presents flood risk in the Han River Basin realistically and comprehensively, revealing flood risk composition and providing more detailed risk information. Results show that high-risk regions accounted for 34.51% of the basin area and were mainly concentrated in the mid-lower reaches, while middle-risk (19.13%) and middle-high-risk (23.35%) regions were mainly distributed in the upstream. 4.52%, 5.12%, and 13.37% of the basin area were assigned as very-low, low, and middle-low risk regions respectively, and were mainly adjacent to the Danjiangkou reservoir. Flood-prone natural conditions and dense population and assets were the causes of high flood risk, while reservoir regulation and storage capacity had significantly alleviated flood risk.

Environmental Threat of Soil Erosion in the Gwang Khola Watershed, Chure Region of Nepal

Chure, also known as the foothills of the Himalayas that extends from east to west of Nepal, is an essential region due to the hotspot of biological diversity and various natural resources, including recharge groundwater for the Tarai region of the country. However, the Chure region has a high rate of soil erosion due to human activities and natural processes, a severe issue in the Chure region. This study looked at soil erosion in the Gwang Khola watershed in the Chure region. We used the Revised Universal Soil Loss Equation (RUSLE) model to measure soil loss by soil erosion. The results showed that about 547,992.9 tons of soil were lost annually in the Gwang Khola watershed. The results indicated that 5,259.87 hectares of the land area were in a very low-risk zone for soil erosion. Similarly, 317.79 hectares of land had a moderate risk of soil degradation, while 13.59 hectares of forest area posed a high threat. The extreme-risk erosion area was situated above 1,250 m. In contrast, the moderate and the low-risk regions of soil erosion had a lower elevation range of 950 m to 1,250 m and 650 m to 950 m, respectively. The findings of this study may aid planners and policymakers in preventing soil erosion and protecting the ecosystem in this watershed and those with similar circumstances.

Spatiotemporal dynamics in epidemic models with Lévy flights: A fractional diffusion approach

Recent field and experimental studies show that mobility patterns for humans exhibit scale-free nonlocal dynamics with heavy-tailed distributions characterized by Lévy flights. To study the long-range geographical spread of infectious diseases, in this paper we propose a susceptible-infectious-susceptible epidemic model with Lévy flights in which the dispersal of susceptible and infectious individuals follows a heavy-tailed jump distribution. Owing to the fractional diffusion described by a spectral fractional Neumann Laplacian, the nonlocal diffusion model can be used to address the spatiotemporal dynamics driven by the nonlocal dispersal. The primary focuses are on the existence and stability of disease-free and endemic equilibria and the impact of dispersal rates and fractional powers on the spatial profiles of these equilibria. A variational characterization of the basic reproduction number R0 is obtained and its dependence on dispersal rates and fractional powers is also examined. Then R0 is utilized to investigate the effects of spatial heterogeneity on the transmission dynamics. It is shown that R0 serves as a threshold for determining the existence and nonexistence of an epidemic equilibrium as well as the stability of the disease-free and endemic equilibria. In particular, in low-risk regions both dispersal rates and fractional powers play a critical role and are capable of altering the threshold value. Numerical simulations were performed to illustrate the theoretical results.

A risk-sharing mechanism for multi-region catastrophe insurance with government subsidies

Catastrophe insurance can play an important role in compensating disaster losses and mitigating catastrophe risk, but interest in participating is usually mismatched between insurance companies and disaster-affected regions. High-risk regions are more willing to purchase catastrophe insurance, while insurance companies are reluctant to provide it. In low-risk regions, the situation is reversed. We address this problem by developing a multi-region catastrophe insurance method that disperses risk among high- and low-risk regions, expanding coverage across a broader area and ensuring profitability with greater stability for the insurance company. In this study, we introduce a risk-sharing mechanism that determines participating regions' contributions to the total premium by accounting for their disaster risk profiles and their economic status. Government subsidies are introduced to account for those regions that cannot fully afford their allocated premium. The proposed insurance system's performance is analyzed in practice, using the Yunnan Province as a test case, and the results show that multi-region catastrophe insurance can benefit both disaster-affected regions and the insurance company, and that government subsidies promote the implementation of this system.

Did Depression, Schizophrenia, and Alcohol Use Increase During the COVID-19 Pandemic Even in Low-Risk Regions? An Analysis of the 2017-2020 National Health Insurance Data in Tottori Prefecture.

This study aimed to determine whether the COVID-19 pandemic increased the number of medical consultations for depression, schizophrenia, and alcohol dependence in low-risk regions. National Health Insurance enrolments from March 2017 to March 2021 in Tottori Prefecture, Japan, where there were minimal COVID-19 cases in 2020, were included in this study. The all-cause mortality and proportion of National Health Insurance members with depression, schizophrenia, and alcohol dependence in the financial years (FY) 2017, 2018, 2019, and 2020 were calculated. The proportion in FY 2020 was compared with the average proportion from FY2017 to FY2019 and the proportion in FY2019. The all-cause mortality for men aged 80-99 years and women aged 70-89 years decreased in FY2020. The proportion of men aged 20-29 years with depression increased to 4.1% in FY2020 compared with 3.0% in FY2019, while the proportion of women aged 20-29 years with depression was 4.4% in FY2017, 4.8% in FY2018, 4.8% in FY2019, and 5.5% in FY2020, confirming an increasing trend from before the COVID-19 pandemic. The proportion of men aged 30-39 years and 60-69 years with schizophrenia increased and that of women aged 40-49 years, 60-69 years, and 90-99 years with schizophrenia also increased, even before the pandemic. The proportion of people with alcohol use disorder has not changed significantly since FY2017. The pandemic has led to an increased proportion of men aged 20-29 years with depression, even in low-risk regions.

Mycobacterial infections in cats (Felis catus) as a potential threat to humans – a review 2014–2023

Mycobacteria infections in cats include tuberculosis (caused by Mycobacterium bovis and Mycobacterium microti) and mycobacteriosis caused by non-tuberculous mycobacteria (NTM). The aim of the paper is to present the latest reports on mycobacterial infections in cats and place emphasis on their impact on the health of their owners. The reviewers looked for papers about mycobacterial infections in cats in PubMed and Google Scholar from any date from January 2014 to June 2023. The search used the following keywords: cat, feline, tuberculosis, and mycobacteria. Papers were evaluated for their value to science and their applicability. Papers published in recent years have shown that mycobacterial infections in cats should still be considered in a differential diagnosis when many clinical signs present and they are mainly skin and ocular symptoms. An epidemiological investigation of these infections is highly important because cases were reported also in low-risk regions. Mycobacterial infections pose a risk to humans. The degree of risk depends on many factors, such as the species of mycobacteria, the closeness of animal-owner contact, and the immune status of the owner. The greatest risk are still believed to be M. bovis infections; however, NTM infections should also raise a concern, especially in high-risk groups.

Brain metastases from small cell lung cancer and non-small cell lung cancer: comparison of spatial distribution and identification of metastatic risk regions.

This study aims to investigate the spatial distribution difference of brain metastases (BM) between small-cell lung cancer (SCLC) and non-small-cell lung cancer (NSCLC) and to identify the metastatic risk in brain regions. T1-enhanced MR images of 2997 BM from 728 eligible patients with SCLC and NSCLC were retrospectively reviewed by three independent medical institutions in China. All images were spatially normalised according to the Montreal Neurological Institute space, following BM delineation confirmed by three senior radiologists. The brain regions in the normalised images were identified based on the merged Anatomical Automatic Labeling atlas, and all BM locations were mapped onto these brain regions. Two-tailed proportional hypothesis testing was used to compare the BM observed rate with the expected rate based on the region's volume, and metastatic risk regions were finally identified. In SCLC and NSCLC, BM was mainly present in the deep white matter (22.51% and 17.96%, respectively), cerebellar hemisphere (9.84% and 7.46%, respectively) and middle frontal gyrus (6.72% and 7.97%, respectively). The cerebellar hemisphere was a high-risk brain region in the SCLC. The precentral gyrus, middle frontal gyrus, paracentral lobule and cerebellar hemisphere were high-risk BM in the NSCLC. The inferior frontal gyrus and the temporal pole were a low-risk brain region in the SCLC and NSCLC, respectively. The spatial BM distribution between SCLC and NSCLC is similar. Several critical brain regions had relatively low BM frequency in both SCLC and NSCLC, where a low-dose radiation distribution can be delivered due to adequate preoperative evaluations.

Spatial distribution and temporal trend of drug-related deaths in the Islamic Republic of Iran during 2014-2017.

Research suggests that there is an increasing trend in drug-related deaths worldwide: an estimated 69 000 individuals lose their lives due to substance abuse annually. To determine the geographical pathology of drug-related deaths in the Islamic Republic of Iran and to evaluate incidence trends, with a focus on identifying high- and low-risk regions. For this ecological study, we collected data from the 2 main sources (the Legal Medicine Organization and the Ministry of Health and Medical Education) responsible for registering substance-related deaths during 2014-2017. Data analysis was conducted using Joinpoint regression analysis, Global Moran's I and Anselin Local Moran's I. Of the 12 386 drug-related deaths in 2014-2017, most occurred during the summer months; 7162 of these were among middle-aged individuals. The mean age of children and adolescents who died of substance abuse was 5.2 [standard deviation (SD) 4.6] years. In the young adult group, mean age at death was 20.7 (SD 2.5) years; it was 34.2 (SD 5.4) years for adults and 55.6 (SD 9.8) years for older adults. Changes in mortality rate peaked in 2017 (annual percentage change = 0.52); in the last months of the study period there was a nonsignificant decrease (annual percentage change = -6.99) in the incidence (average annual percentage change = -0.5; 95% confidence interval: -3.2, 2.3). Deaths due to substance abuse will remain a huge public health problem unless policy- and decision-makers determine why this problem continues to increase despite the extensive efforts on regulation and find ways to mitigate it.

A deep spatiotemporal network for forecasting the risk of traffic accidents in low-risk regions

A deep spatiotemporal network for forecasting the risk of traffic accidents in low-risk regions

Insight into Delta variant dominated second wave of COVID-19 in Nepal

ObjectiveTo study the spreading nature of Delta variant (B.1.617.2) dominated COVID-19 in Nepal to help the policymakers assess and manage health care facilities and vaccination programs. MethodsDeterministic mathematical models in the form of systems of ordinary differential equations were developed to describe the COVID-19 transmission in the high- and the low-risk regions of Nepal. The models were validated using the multiple data sets containing daily new cases in the whole country, the high-risk region, the low-risk region, and cases needing medical care, ICU, and ventilator. ResultsWe found the reproduction number of Rt=4.2 at the beginning of the second wave, larger than the first wave (∼1.8 estimated previously), indicating that the transmissibility of Delta variant is higher than the wild-type circulated during the first wave. Model predicts that ∼5% of the COVID-19 cases were reported in Nepal, estimating the seroprevalence of ∼63.9% as of July 2021, consistent with the survey conducted by the Government of Nepal. The seroprevalence was expected to reach 94.46% by April 2022, among which ∼46% would have both infection and vaccination. The expected cases from September 2021 to April 2022 is 111,300, among which 11,890 people might need medical care, 3590 need ICU, and 953 need ventilators. The COVID-19 cases and medical care needs could be significantly reduced with proper implementation of vaccination and social distancing. ConclusionsThe data-driven mathematical models are useful to assess control programs in resource-limited countries. The appropriate combination of vaccination and social distancing are necessary to keep the pandemic under-control and manage the medical care facilities in Nepal.

Prediction of lifetime cardiovascular risk and individual lifetime treatment benefit in four European risk regions: geographic recalibration of the LIFE-CVD model

Abstract Background The life expectancy free of cardiovascular disease (CVD) in individuals without previous CVD can be estimated with the LIFEtime-perspective CardioVascular Disease (LIFE-CVD) model, as recommended by the 2021 ESC CVD prevention guidelines. Our aim was to systematically recalibrate the LIFE-CVD model to four European risk regions using contemporary and representative registry data. Methods and results The LIFE-CVD model was systematically recalibrated to four distinct risk regions within Europe, using representative aggregate data on age- and sex-specific expected CVD and non-CVD mortality incidences and risk factor distributions. For external validation, 1,451,077 individuals without previous CVD were included from seven European cohorts, with 53,721 CVD events and 62,902 non-CVD deaths during follow up. After applying the recalibrated risk prediction models to external validation cohorts, C-indices (figure 1) ranged from 0.670 (95% CI 0.650–0.690) to 0.787 (95% CI 0.785–0.789). Predicted risks matched the observed risks in the CPRD data. With the recalibrated LIFE-CVD model, the estimated gain in CVD-free life expectancy from preventive therapy differed per region, for example a 50-year-old smoking women with a systolic blood pressure of 140mm Hg was estimated to gain 0.4 years of CVD-free life from 10 mm Hg SBP reduction in the low risk region, whereas this would be 1.5 years in the very high risk region (figure 2). Interpretation By taking into account geographical differences in CVD incidence, the recalibrated LIFE-CVD model provides a more accurate tool for the prediction of lifetime risk and CVD-free life expectancy for individuals without previous CVD, facilitating shared decision-making in cardiovascular prevention options as recommended by the 2021 European Prevention Guidelines. Funding Acknowledgement Type of funding sources: None.

Performance of SCORE2 and SCORE2-OP risk algorithms in a Cypriot cohort.

SCORE2 and SCORE2-OP algorithms and associated online calculators provide a new and easy method of estimating the 10-year cardiovascular risk in apparently healthy Europeans. The aim of the study was to determine the performance of these algorithms in terms of discrimination and calibration in the cohort of the Cyprus Epidemiological Study on Atherosclerosis (CESA), not only for the 10-year risk for myocardial infarction (MI), stroke and cardiovascular death, but also for all types of atherosclerotic cardiovascular events (ASCVE). SCORE2 and SCORE2-OP for low-risk regions were calculated in a non-diabetic subset of CESA consisting of 908 people (mean age±SD: 57.8±10.5; range 40-89; 58.8% female) using baseline risk factors. Mean follow-up was 13.2±3.7 years (range 1-17) with 89 primary endpoints (MI, stroke and cardiovascular death) and 136 secondary endpoints (primary endpoints, angina, cardiac failure, coronary revascularization, transient ischemic attack, claudication and critical limb ischemia). The C-statistic for the prediction of the primary endpoint for all ages was 0.76 (95% CI 0.70 to 0.81) and the observed 10-year event rate was similar to the predicted one. However, the observed 10-year rate for secondary events was similar to the estimated one only when the algorithm for high-risk regions was used. SCORE2 and SCORE2-OP moderate risk algorithms perform well in the Cypriot population for predicting the 10-year risk for MI, stroke and fatal cardiovascular disease. However, an estimate of the 10-year risk for all ASCVD events is best calculated from the high-risk algorithm.

Epidemiological characteristics and spatiotemporal patterns of scrub typhus in Fujian province during 2012-2020.

BackgroundScrub typhus has become a serious public health concern in the Asia-Pacific region including China. There were new natural foci continuously recognized and dramatically increased reported cases in mainland China. However, the epidemiological characteristics and spatiotemporal patterns of scrub typhus in Fujian province have yet to be investigated.ObjectiveThis study proposes to explore demographic characteristics and spatiotemporal dynamics of scrub typhus cases in Fujian province, and to detect high-risk regions between January 2012 and December 2020 at county/district scale and thereby help in devising public health strategies to improve scrub typhus prevention and control measures.MethodMonthly cases of scrub typhus reported at the county level in Fujian province during 2012–2020 were collected from the National Notifiable Disease Surveillance System. Time-series analyses, spatial autocorrelation analyses and space-time scan statistics were applied to identify and visualize the spatiotemporal patterns of scrub typhus cases in Fujian province. The demographic differences of scrub typhus cases from high-risk and low-risk counties in Fujian province were also compared.ResultsA total of 11,859 scrub typhus cases reported in 87 counties from Fujian province were analyzed and the incidence showed an increasing trend from 2012 (2.31 per 100,000) to 2020 (3.20 per 100,000) with a peak in 2018 (4.59 per 100,000). There existed two seasonal peaks in June-July and September-October every year in Fujian province. A significant positive spatial autocorrelation of scrub typhus incidence in Fujian province was observed with Moran’s I values ranging from 0.258 to 0.471 (P<0.001). Several distinct spatiotemporal clusters mainly concentrated in north and southern parts of Fujian province. Compared to low-risk regions, a greater proportion of cases were female, farmer, and older residents in high-risk counties.ConclusionsThese results demonstrate a clear spatiotemporal heterogeneity of scrub typhus cases in Fujian province, and provide the evidence in directing future researches on risk factors and effectively assist local health authorities in the refinement of public health interventions against scrub typhus transmission in the high risk regions.