statistics non communicable diseases

(204535/Z/16/Z). This report provides a summary of the burden of the key NCDs and their risk factors. Oxford University Press is a department of the University of Oxford. More. According to the WHO’s latest Global Health Estimates, which traced statistics between 2000-2019 found that even though people … Here, we present an overview of the approaches developed for spatiotemporal disease surveillance of NCDs. Comparison of two methods for cell count determination in the course of biocide susceptibility testing. © 2016 MoHFW, Government of India, All rights reserved. ... Coronavirus Disease 2019 ADHD Cancer COPD Diabetes Flu (Influenza) Heart Disease Sexually Transmitted Diseases (STDs) Data & Statistics. Welfare schemes for vulnerable sections of the population by the Centre and States and the performance of these schemes. Another is that the Monte Carlo sampling method allows the computation of whatever joint probability statements are required. Later we introduce the computational aspects of the BHM modelling framework for NCD surveillance; then we run a simulation study to evaluate advantages and drawbacks of the approaches presented in detecting areas deviating from the expected trend. Surveillance systems are commonly used to provide early warning detection or to assess an impact of an intervention/policy. Electronic Health Record Standards For India Helpdesk, Yash Respiratory & Medical Disease Centre, Northcentral Liver, Digestive Disease & Endoscopy Centre, Yash Prasutigruh & Women Disease Hospital, Dr. Kamras Urinary & Surgical Diseases Centre, Renew R. P Endoscopic & Enitre Women Diseases Clin, Escorts - Mehta Heart Center & Mehta Institute For Chest & Heart Diseases & Intensive Care Unit, Mehta Institute For Chest & Heart Diseases & I.C.U, Metro Centre For Liver & Digestive Diseases, Surya Clinic & Centre For Life Style Diseases, Jain Hospital And Institute Of Digestive Diseases - Solapur, International Center For Cardio Thoracic & Vascular Diseases(Frontier Life Hosp). Source: Environment and Health Atlas.42. Non-Communicable Diseases. The major NCDs are cardiovascular diseases, cancers, chronic respiratory diseases and diabetes. Syndromic data, such as primary care data, drug prescriptions, nurse calls and home visits, which are indicative of a potential anomaly, may provide an additional level of information leading to a detection event before the data aberration occurs.68 Diggle et al.69,70 analysed NHS non-emergency telephone calls reporting symptoms of gastrointestinal diseases. The global action plan has suggested 9 targets for countries to set. Computationally intensive BHMs benefit from high-performance computing clusters to speed up computation times, but these are not necessarily required. Differences across the competing models were observed in terms of computation time, an important factor in assessing their performance. Integration of NPCDCS with the National Health Mission (NHM) resulted into augmented infrastructure and human resources particularly in the form of frontline workers- the ANM and the ASHA. (‎2018)‎. Leroux BG, Lei X, Breslow N. Estimation of disease rates in small areas: a new mixed model for spatial dependence. Health data contain both a time and a space component. In particular, Abellan et al.42 developed a BHM model (termed STmix) where a mixture of two normal distributions characterized by different variances is specified for the space-time interaction. We also discuss some challenges faced by researchers when dealing with NCD surveillance, including how to account for false detection and the modifiable areal unit problem. A key aspect of surveillance studies concerns how to communicate information to public health researchers and policy makers. To know more about NCDs and National Programme Guidelines-, This question is for preventing automated spam submissions. It was applied to male and female lung cancer38 and later extended to jointly model multiple diseases,30,39 with an application on oral cavity, oesophagus, larynx and lung cancers in males in the 544 districts of Germany from 1986 to 1990. NCDs Non-Communicable Diseases NGOs Non-Governmental Organizations NISR National Institute of Statistics of Rwanda NUR National University of Rwanda OBP Objectives-Based Planning PIH Partners in Health PWDs Persons living with disabilities RBC Rwanda Biomedical Center … Posterior mean and 95% credible intervals for the competing models in the simulation study. The majority of premature NCD deaths are preventable. Following the design initially proposed by Li et al.,43 and later used by Boulierei et al.,47 we used real asthma hospital episode statistics (HES) data to generate 50 simulated datasets. This approach, named BaySTDetect, was applied to detect unusual trends for asthma and chronic obstructive pulmonary disease at Clinical Commissioning Group (CCG) level in England (211 in total) on monthly data between August 2010 and March 2011, across mortality, hospital admissions and general practice drug prescriptions.44, To illustrate the typical output obtained from this model, Figure 2 shows the area-specific time trends of the CCGs which were detected as unusual, plotted against the national trend. The results of the simulation study showed that the standard approach was not able to capture the variability in the spatiotemporal interactions and therefore it was not able to distinguish between common and unusual areas. The authors used ranking of all provinces according to mortality rates to identify high-risk groups. the number of parameters) also impacts on the computational burden, for instance in terms of convergence time when running MCMC simulations. In this paper we carried out a simulation study to formally evaluate the detection performance and compare DM, STmix and FlexDetect (see description of the models in Space-time disease mapping). Surveillance methods need to be able to detect meaningful departures from expectation and exploit dependencies within such data to produce unbiased estimates of risk as well as future forecasts. Part of their popularity lies in the availability of free user-friendly SaTScanTM software []. The same method was suggested in the context of descriptive spatial epidemiology, to obtain areas characterized by a Standardised Mortality Ratio different from 1.51 Even in the Bayesian setting, FDR rules were suggested by many authors.52–56 The mixture model proposed by Li et al. Surveillance methods must be able to capture spatial and temporal patterns in both lifestyle/environmental exposures and health outcomes. age/sex/ethnicity) and social economic status. Non-communicable di… One of the biggest challenges researchers face when analysing large and complex space-time datasets is their computational burden. Also note that mixture models notoriously have problems converging, suffering from issues such as label switching, which lead to multimodal posterior distributions. NCDs are one of the major challenges for public health in the 21st century, not only in terms of human suffering they cause but also the harm they inflict on the socioeconomic development of the country. Find Out Results of the analysis of the data depict that, females dominate those who are suffering from Non-Communicable Diseases. Spiegelhalter DJ, Thomas A, Best NG, Gilks W, Lunn D. BUGS: Bayesian Inference Using Gibbs Sampling. This can be particularly challenging for rare diseases where the numbers of cases at small-area level are very low. According to World Health Organization (WHO) projections, the total annual number of deaths from NCDs will increase to 55 million by 2030, if timely interventions are not done for prevention and control of NCDs. The more spatial variability is present in the data, the more profound the potential impact of the modifiable areal unit (MAUP).74,75 As MAUP depends on the level of aggregation, this issue has been linked to ecological bias,76 and the general suggestion in the scientific literature is to consider the finest spatial scale available. Non-communicable diseases are the diseases that are not transferred from an infected person to another via any means and are mostly caused by factors like improper lifestyle and eating habits. A number of patients living with non-communicable diseases cannot easily access treatment as the services have been scaled down and some of … The standard disease mapping approach has been used informally to detect anomalies (unusual observations) in space and time, i.e. A common choice for capturing temporal dependence is a random walk prior,29 but extensions to incorporate spatiotemporal interactions among neighbouring areas and time points have also been developed.30 This framework can also account for factors known to modify spatial and temporal trends that, in the context of NCDs, will include demographic variables (e.g. Frumkin H, Hess J, Luber G, Malilay J, McGeehin M. Ye Y, Wamukoya M, Ezeh A, Emina JB, Sankoh O. Utazi CE, Sahu SK, Atkinson PM, Tejedor N, Tatem AJ. Non-communicable diseases (NCDs) – conditions that are not caused by an acute infection – are the leading cause of death worldwide, accounting for 68% of total deaths in 2012. general practices in England). There is increasing recognition of the importance of surveillance for NCDs. They contribute to raised blood pressure (hypertension); raised blood sugar (diabetes); raised and abnormal blood lipids (dyslipidaemia); and obesity. In: Handbook of Spatial Statistics, Health and environment information systems for exposure and disease mapping, and risk assessment, SpatialEpiApp: A Shiny web application for the analysis of spatial and spatiotemporal disease data. Test-based methods such as scan statistics can only answer questions related to the deviation from the null hypothesis. Concepts and Techniques in Modern Geography, An integrated framework for the geographic surveillance of chronic disease, Spatial aggregation and the ecological fallacy. This is due to the excessive smoothing following the assumption of a common variance across all the areas and time points. Here, the focus was on efficient, near real-time, computation which was achieved using INLA to perform approximate Bayesian inference. The UK Small Area Health Statistics Unit (SAHSU) is part of the MRC-PHE Centre for Environment and Health, which is supported by the Medical Research Council (MR/L01341X/1) and Public Health England (PHE). Reducing the major risk factors for NCDs is the key focus of MOHFW to prevent deaths from NCDs. This method was further extended to increase its flexibility by accounting for different space-time patterns in the unusual observations, as well as by allowing for longer time series to be analysed. Over the past 40 years there have been significant changes in the disease pattern around the world. Traditionally, the methodological and conceptual frameworks for surveillance have been designed for infectious diseases, but the rising burden of non-communicable diseases (NCDs) worldwide suggests a pressing need for surveillance strategies to detect unusual patterns in the data and to help unveil important risk factors in this setting. For example, if the public health question is whether current risk exceeds an agreed acceptable level in all areas that do, and in no areas that do not, meet a particular criterion such as adherence to a particular advisory policy, the correct predictive probability to attach to this statement can be calculated. Through the exceedance probabilities, these maps give a perception of the uncertainty around the area-level relative risks estimates. Tackling the epidemic of chronic diseases – or non-communicable diseases (NCDs) – is at the heart of this agenda, and it’s a major challenge. Global Influenza Surveillance and Response System (GISRS). We defined TP as the number of true-positives, FP as false-positives, TN as true-negatives and FN as false-negatives, respectively. Another example can be found in Morrison et al.71 who forecasted multiple measures of healthcare use (including physician visits and prescriptions of asthma medication) within British Columbia, Canada, where seasonal wildfires produce high levels of air pollution, significantly affecting population health. Overweight, obesity and their related non-communicable disease … Both the detection methods deal with this through the modelling specification,42 constraining the variance of the modified areas to be larger than that of unmodified areas, or through informative priors on the variances of the two components.43, In this paper we have presented an overview of the main statistical methods for disease surveillance in the context of NCDs, both from a test-based and model-based perspective and with a particular focus on the BHM approach, which provides a flexible framework to allow for complex data dependencies present in surveillance studies. In this section, we first discuss how data availability is one of the key challenges in surveillance studies, before giving a generic overview of test-based approaches for NCD surveillance. Non-communicable diseases are also called non-contagious or non-infectious diseases. to exhibit a risk pattern not deviating from the expected one.43. In later life with high chances of obesity, cardiovascular diseases, diabetes can lead to disability and premature death. Fixing a 0.9 threshold (DM2), FDR decreases, despite still being above the standard threshold of 0.05, while at the same time sensitivity also decreases (0.660) (Table 1). The Non-communicable Disease Unit . Thacker SB, Stroup DF, Parrish RG, Anderson HA. Version 0.5 (version ii). A recent study proposed a Bayesian probabilistic clustering method to evaluate the network representativeness in terms of socioeconomic and environmental variables in sub-Saharan Africa, identifying areas of poor coverage in the existing network and using predictive probability distributions to suggest the best location for new HDSS sites.11. Prevention and management of chronic obstructive pulmonary disease (COPD) and chronic Kidney disease (CKD); and better management of co-morbidities such as diabetes and tuberculosis are also considered under the programme. Also, people within 20 to 34 year group are mostly affected by Non-Communicable Diseases. Wang Y, Pirani M, Hansell AL, Richardson S, Blangiardo M. Yiannakoulias N, Svenson LW, Schopflocher DP. A standard spatiotemporal model27 was first fitted to the real data, and the obtained parameters were selected for the generation of the simulated data. A joint model allows information to be borrowed across the outcomes, thus helping stabilize estimates, particularly when the outcomes are rare. These can be particularly useful for practitioners less skilful in statistical modelling and programming. We then focus on BHMs and describe disease mapping and mixture-based models for anomaly detection. It is a particularly important issue in low-income settings because surveillance studies often need to rely on information from surveys, and the lack of financial resources may make comprehensive coverage of data sources (e.g. This is particularly challenging as the statistical modelling of surveillance data becomes more sophisticated. 1 National public health agencies, such as the US Centers for Disease Control and Prevention (CDC) and Public Health England (PHE), … National HIV Surveillance System (NHSS). Clayton DG. We selected 15 areas to deviate from the overall time trend over the last five time points. Molecular Detection and Phylogenetic Analysis of. The authors specified a spatiotemporal point process on the location and time of the individual calls and modelled the spatial and temporal dependency on the intensity of the process. The two mixture models returned more comparable performances. This will potentially lead to bias in population representativeness due to non-random missingness12 which will need to be addressed using advanced statistical methods, for instance through the integration of data from appropriate surveys/cohorts, as proposed in the context of residual confounding.73, An important issue with surveillance studies is that of the spatial resolution and the type of geographical areas considered; modifying these might lead to different results, as the spatial distribution of the outcome will depend on these choices. uses the specification suggested by Newton et al.,53 later used by Ventrucci et al.57 in order to account for multiple testing. In response to the “WHO Global Action Plan for the Prevention and Control of NCDs 2013-2020”, India is the first country to adopt the National Action Plan with specific national targets and indicators aimed at reducing the number of global premature deaths from NCDs by 25% by 2025. Non-communicable diseases (NCDs) are medical conditions or diseases that are not caused by infectious agents. A non-communicable disease, or NCD, is a medical condition or disease which by definition is non-infectious and cannot be passed from person to person. A log likelihood ratio (LLR)14 is calculated for each interval, and the test statistic is defined as the maximum LLR over all intervals. The degree of complexity of the model (e.g. Tackling the risk factors will therefore not only save lives; it will also provide a huge boost for the economic development of the country. The shared component model,37 originally developed for two diseases, includes a common component (likely to reflect common risk factors) and a disease-specific one, which can point towards specific risk factors otherwise masked in a single disease model. We compared the detection performance of disease mapping (DM1, DM2), the mixture model on the spatiotemporal interaction (STmix1, STmix2) and the mixture model on the spatiotemporal rates (FlexDetect). Non-communicable diseases (NCDs) refer to those diseases which are not transmitted through infected persons or organisms. Some of the reasons for the non-infectious disease are genetics, nutritional deficiency, age and sex of the individual and so on. Recently, it was further extended to jointly model age- and gender-specific diseases.40, An alternative multivariate specification considers spatial and temporal terms explicitly, modelling the correlation among the outcomes in space/time. The results are presented in Table 1 in terms of four different performance measures. According to the World Health Organization (WHO), surveillance is the ‘ongoing systematic data collection, analysis and interpretation and dissemination of information in order for action to be taken’. This has led to the increasing development of a range of space-time methods specifically designed for NCD surveillance. Non-communicable Disease. To know more about NCDs and National Programme Guidelines-  Click here, /,, You would need to login or signup to start a Discussion. Air pollution is also leading risk factor for NCDs in terms of both outdoor air pollution and household air pollution that mainly results from burning solid fuels in the home for cooking and heat. UK Small Area Health Statistics Unit, Department of Epidemiology & Biostatistics, School of Public Health, Imperial College London, Norfolk Place, London W2 1PG, UK. However, there is increased importance of early warning detection, so that unusual behaviour can be detected at the earliest possible time. 1996. (29 August 2019, date last accessed). Examples include cancer, diabetes, and hypertension. India’s National Monitoring Framework for Prevention and Control of NCDs has committed for a 50% relative reduction in household use of solid fuel and a 30% relative reduction in prevalence of current tobacco use by 2025. Piel FB, Parkes BL, Daby H, Hansell AL, Elliott P. Kulldorff M, Heffernan R, Hartman J, Assunçao R, Mostashari F. Sherman RL, Henry KA, Tannenbaum SL, Feaster DJ, Kobetz E, Lee DJ. They are responsible for significant premature disability, morbidity and mortality, and … In-depth information about NCDs, mortality and morbidity has been addressed by the global health observatory (GHO) data of the WHO in the form of a noncommunicable diseases country profile . One of the major challenges of surveillance studies is the availability of suitable data. Here we focus on current and future trends for some of the most prevalent non-communicable diseases. For the latter, a common choice is the predictive probability that the relative risk exceeds a prespecified threshold.32,33 Exceedance probabilities can be used to flag areas and/or time points characterized by increased risk that may then be further investigated.

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