scholarly journals Intelligent Software-Aided Contact Tracing Framework: Towards Real-Time Model-Driven Prediction of Covid-19 Cases in Nigeria

2021 ◽  
Vol 7 (1) ◽  
pp. 67-76
Author(s):  
Edward N. Udo ◽  
◽  
Etebong B. Isong ◽  
Emmanuel E. Nyoho ◽  
◽  
...  
Keyword(s):  
Real Time ◽  
Routing Algorithm ◽  
Principal Component ◽  
World Health ◽  
Contact Tracing ◽  
Android Application ◽  
Time Model ◽  
Model Driven ◽  
Intelligent Software ◽  
Health Organization

As many countries around the world are trying to live with the deadly coronavirus by adhering to the safety measures put in place by their government as regulated by World Health Organization (WHO), it becomes very vital to continuously trace patients with COVID-19 symptoms for isolation, quarantine and treatment. In this work, an intelligent software-aided contact tracing for real-time model-driven prediction of COVID-19 cases is proposed utilizing COVID-19 dataset from kaggle.com. The dataset is preprocessed using One-Hot encoding and Principal Component Analysis. Isolation Forest algorithm is used to train and predict COVID-19 cases. The performance of the model is evaluated using Accuracy, Precision, Recall and F1-Score. The intelligent software-aided contact tracing framework has four layers: symptoms, modeling/prediction, cloud storage/contact routing and contact tracers. The contact tracing system is an android application that receives symptom values, predict it and automatically send the prediction result together with user’s contact and location details to the closest contact tracer via the Firebase real-time database. The closest contact tracer is determined by employing a dynamic routing algorithm (contact routing algorithm) that uses Open Shortest Path First (OSPF) protocol to compute the distance between two geographic locations (user and contact tracer) and chooses a contact tracer with shortest distance to the patient utilizing a unicast routing technique (routing a patient to a contact tracer in a one-to-one relationship). The predictive model along with the android application for software-aided contact tracing is implemented using the python, and Java programming language on Pycharm and Android Studio IDE respectively. This Framework is capable of predicting COVID-19 patients, notifying contact tracers of positive cases for proper follow-up which can subsequently curtail the spread of the virus.

Perancangan Sistem Informasi “DIAMONS” (Diabetes Monitoring System) Berbasis Internet of Things (IoT)

2019 ◽  
Vol 6 (1) ◽  
pp. 39-51
Author(s):  
Endang Sri Rahayu ◽  
Nurul Amalia
Keyword(s):  
Internet Of Things ◽  
World Health Organization ◽  
Real Time ◽  
Monitoring System ◽  
World Health ◽  
Health Organization ◽  
Diabetes Monitoring

Diabetes merupakan penyakit “silent killer” yang ditandai dengan peningkatan kadar glukosa darahdan kegagalan sekresi insulin. World Health Organization (WHO) pada tahun 2016 menyatakanbahwa diabetes menduduki urutan ke-6 sebagai penyakit mematikan di Indonesia. Sehingga upayapencegahan dan penanganan diabetes perlu mendapat perhatian yang serius. Internet of Things (IoT)dapat dijadikan sarana penunjang dalam penanganan penyakit diabetes. Inovasi ini memungkinkanperangkat perawatan kesehatan terhubung dengan jaringan internet, sehingga data pasien dapatdiperbaharui dan diakses secara real-time. Selain mempermudah akses, penggunaan IoT juga akanmemberikan nilai tambah pada efisiensi biaya pelayanan kesehatan. Penelitian ini bertujuan untukmerancang software sistem monitoring gula darah berbasis web yang terintegrasi dengan IoT,sehingga pasien dapat melakukan pemeriksaan, konsultasi dengan dokter dan melihat data rekammedis dari jarak jauh. Data hasil pemeriksaan akan disimpan didalam cloud dan ditampilkan secaraonline. Penelitian ini menggunakan Node MCU ESP8266 sebagai mikrokontroller yang telahdilengkapi dengan modul WiFi, Thingspeak sebagai cloud, aplikasi online dengan “Diamons” sebagaidashboard yang mampu menampilkan presentasi data grafis, dibangun dengan bahasa HypertextPreprocessor (PHP) sebagai bahasa pemogramannya. Penelitian ini akan melibatkan pihak medisdalam pengambilan keputusan. Umpan balik yang diberikan kepada pasien berupa anjuran sepertiresep obat, pola makan, dan kegiatan fisik yang harus dilakukan oleh pasien.

scholarly journals An analysis of heavy metals contamination and estimating the daily intakes of vegetables from Uganda

2021 ◽  
Vol 5 ◽  
pp. 239784732098525
Author(s):  
Keneth Iceland Kasozi ◽  
Eric Oloya Otim ◽  
Herbert Izo Ninsiima ◽  
Gerald Zirintunda ◽  
Andrew Tamale ◽  
...  
Keyword(s):  
Heavy Metals ◽  
Daily Intake ◽  
Principal Component ◽  
Absorption Spectrometry ◽  
Cross Sectional Study ◽  
Essential Elements ◽  
World Health ◽  
Cross Sectional ◽  
Health Organization ◽  
Daily Intakes

Background: Environmental contamination with elevated levels of copper (Cu), cobalt (Co), iron (Fe), zinc (Zn), lead (Pb), chromium (Cr6+), cadmium (Cd), and nickel (Ni)—all states of which are found in Uganda—raises health risk to the public. Pb, Cr6+, Cd, and Ni for instance are generally considered nonessential to cellular functions, notwithstanding the importance of the oxidative state of the metals in bioavailability. As such, we aimed in this study (i) to evaluate heavy metal concentrations in four vegetables from a typical open-air market in Uganda, (ii) to assess the safety of consuming these vegetables against the World Health Organization (WHO) recommended limits of heavy metals consumption, and (iii) to formulate a model of estimated daily intake (EDI) among consumers in the country. Methods: This was a cross-sectional study conducted in five georeferenced markets of Bushenyi district in January 2020. Amaranthus, cabbages, scarlet eggplants, and tomatoes were collected from open markets, processed, and analyzed by atomic absorption spectrometry. Modeled EDI, principal component (PCA) and cluster analysis (CA) were conducted to identify relationships in the samples. Results: The levels of essential elements in the four vegetables were found to fall from Co > Cu > Fe > Zn. Those of non-essential metals were significantly higher and followed the pattern Cd > Cr > Pb > Ni. The highest EDI values were those of Cu in scarlet eggplants, Zn in amaranthus, Fe in amaranthus, Co in amaranthus, Pb in cabbages, total Cr in scarlet eggplant, Cd in cabbages and tomatoes, and Ni in cabbages. In comparison to international limits, EDIs for Zn, Cu, Co and Fe were low while Ni in cabbages were high. PCA showed high variations in scarlet eggplant and amaranthus. The study vegetables were found to be related with each other, not according to the location of the markets from where they were obtained, but according to their species by CA. Conclusion: The presence of non-essential elements above WHO limits raises policy challenges for the consumption and marketing of vegetables in the study area. Furthermore, low EDIs of essential elements in the vegetables create demand for nutritious foods to promote healthy communities.

scholarly journals Examination of Surface Water Along River-Rima Floodplain in Wamakko, Sokoto State, Nigeria.

2020 ◽  
Vol 2 (3) ◽  
Author(s):  
Abdulqadir Abubakar Usman ◽  
Murtala Abubakar Gada ◽  
Aminu Muhammad Bayawa ◽  
Ibrahim Mustapha Dankani ◽  
Saadu Umar Wali
Keyword(s):  
Drinking Water ◽  
Surface Water ◽  
Principal Component ◽  
Hierarchical Cluster ◽  
World Health ◽  
Coliform Bacteria ◽  
Municipal Sewage ◽  
Bacteria Growth ◽  
Anthropogenic Inputs ◽  
Health Organization

This study examined the hydrochemistry of surface water along the River-Rima floodplain area. Five sampling locations were purposively selected, and, in each point, three samples were taken from surface water (river). The sampling was repeated after 20 days. Thus, a total of 30 samples were collected. Water samples obtained were subjected to laboratory tests. Results revealed that BOD, TDS, Mg2+, and Fe3+ are above the World Health Organization (WHO) and Standard Organization of Nigeria (SON) reference guidelines for drinking water quality. Isolates detected from the coliform bacteriological analysis include Enterobacter aerogene, Escherichia coli, and Citrobacter freundii with most of the samples showing coliform bacteria growth above the SON standard for drinking water. Hence, the water in the River-Rima floodplain of the Wamakko area is of low quality and unsafe for drinking. Results of principal component analysis (PCA) revealed external influences such as pollutant wash off and rock weathering as controls on hydrochemistry of surface water. There is some indication of anthropogenic inputs (Cl-, NO3-, and PO42-) based on hierarchical cluster analysis. Elements including Cl-, NO3-, and PO42- are increasingly added into surface water from human activities, mainly agriculture, and municipal sewage.

scholarly journals Spatial Distribution of Fluoride in Drinking Water in Dhamar City, Yemen

2021 ◽  
Vol 10 (1) ◽  
pp. 49-63
Author(s):  
Hefdhallah Al Aizari ◽  
Rachida Fegrouche ◽  
Ali Al Aizari ◽  
Saeed S. Albaseer
Keyword(s):  
Drinking Water ◽  
Anthropogenic Activities ◽  
Groundwater Resources ◽  
Principal Component ◽  
World Health ◽  
Residential Areas ◽  
Central Plateau ◽  
The World ◽  
Pca Method ◽  
Health Organization

The fact that groundwater is the only source of drinking water in Yemen mandates strict monitoring of its quality. The aim of this study was to measure the levels of fluoride in the groundwater resources of Dhamar city. Dhamar city is the capital of Dhamar governorate located in the central plateau of Yemen. For this purpose, fluoride content in the groundwater from 16 wells located around Dhamar city was measured. The results showed that 75% of the investigated wells contain fluoride at or below the permissible level set by the World Health Organization (0.5 – 1.5 mg/L), whereas 25% of the wells have relatively higher fluoride concentrations (1.59 – 184 mg/L). The high levels of fluoride have been attributed to the anthropogenic activities in the residential areas near the contaminated wells. Interestingly, some wells contain very low fluoride concentrations (0.30 – 0.50 mg/L).  Data were statistically treated using the principal component analysis (PCA) method to investigate any possible correlations between various factors. PCA shows a high correlation between well depth and its content of fluoride. On the other hand, health problems dominating in the study area necessitate further studies to investigate any correlation with imbalanced fluoride intake.

scholarly journals Investigating the effectiveness of re-opening policies before vaccination during a pandemic: SD modelling research based on COVID-19 in Wuhan

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Ying Qian ◽  
Wei Xie ◽  
Jidi Zhao ◽  
Ming Xue ◽  
Shiyong Liu ◽  
...  
Keyword(s):  
Model Simulation ◽  
Control Measures ◽  
World Health ◽  
Contact Tracing ◽  
Infection Prevention And Control ◽  
Real World Data ◽  
Medical Resources ◽  
Health Organization ◽  
The Impact ◽  
Different Levels

Abstract Background Lockdown policies were widely adopted during the coronavirus disease 2019 (COVID-19) pandemic to control the spread of the virus before vaccines became available. These policies had significant economic impacts and caused social disruptions. Early re-opening is preferable, but it introduces the risk of a resurgence of the epidemic. Although the World Health Organization has outlined criteria for re-opening, decisions on re-opening are mainly based on epidemiologic criteria. To date, the effectiveness of re-opening policies remains unclear. Methods A system dynamics COVID-19 model, SEIHR(Q), was constructed by integrating infection prevention and control measures implemented in Wuhan into the classic SEIR epidemiological model and was validated with real-world data. The input data were obtained from official websites and the published literature. Results The simulation results showed that track-and-trace measures had significant effects on the level of risk associated with re-opening. In the case of Wuhan, where comprehensive contact tracing was implemented, there would have been almost no risk associated with re-opening. With partial contact tracing, re-opening would have led to a minor second wave of the epidemic. However, if only limited contact tracing had been implemented, a more severe second outbreak of the epidemic would have occurred, overwhelming the available medical resources. If the ability to implement a track-trace-quarantine policy is fixed, the epidemiological criteria need to be further taken into account. The model simulation revealed different levels of risk associated with re-opening under different levels of track-and-trace ability and various epidemiological criteria. A matrix was developed to evaluate the effectiveness of the re-opening policies. Conclusions The SEIHR(Q) model designed in this study can quantify the impact of various re-opening policies on the spread of COVID-19. Integrating epidemiologic criteria, the contact tracing policy, and medical resources, the model simulation predicts whether the re-opening policy is likely to lead to a further outbreak of the epidemic and provides evidence-based support for decisions regarding safe re-opening during an ongoing epidemic. Keyords COVID-19; Risk of re-opening; Effectiveness of re-opening policies; IPC measures; SD modelling.

Robson Classification and quality audit

2021 ◽  
Vol 16 (1) ◽  
Author(s):  
Gehanath Baral
Keyword(s):  
Cesarean Section ◽  
World Health Organization ◽  
Real Time ◽  
Perinatal Outcome ◽  
World Health ◽  
Related Factors ◽  
Quality Audit ◽  
Robson Classification ◽  
Health Organization

World Health Organization has recommended Robson Classification from baseline obstetric characters to assess, monitor and compare Cesarean Section rates by the quantity analysis. Incorporation of real time labor related factors requires quality audit for both maternal and perinatal outcome.

scholarly journals Groundwater quality assessment of Shahdadkot, Qubo Saeed Khan and Sijawal Junejo Talukas of District Qambar Shahdadkot, Sindh

2019 ◽  
Vol 10 (1) ◽  
Author(s):  
Muhammad Farooque Lanjwani ◽  
Muhammad Yar Khuhawar ◽  
Taj Muhammad Jahangir Khuhawar
Keyword(s):  
Water Quality ◽  
Principal Component ◽  
Quality Parameters ◽  
World Health ◽  
Coefficient Of Determination ◽  
High Concentration ◽  
Permissible Limits ◽  
Groundwater Samples ◽  
Health Organization

AbstractThe study examines the water quality of Shahdadkot, Qubo Saeed Khan and Sijawal Junejo talukas of Qambar Shahdadkot District, less affected by industrial contamination. A total of 38 groundwater samples were collected and analysed for 28 parameters. The results indicated that 57.89% samples were not suitable for drinking purpose with total dissolved solids above than maximum permissible limit of World Health Organization (WHO) (1000 mg/L). The pH, total phosphate, orthophosphate and nitrite were within WHO limits. The concentration of essential metals more than half samples, fluoride in 60.52% and heavy metals 0–50% were contaminated higher than permissible limits of WHO. The statistical analysis of water quality parameters was also carried out to evaluate coefficient of determination among the parameters, cluster analysis and principal component analysis. Water quality determined for irrigation based on Kelly index (KI), sodium percentage (Na%), chloride–sulphate ratio, sodium adsorption ratio, permeability index (PI), chloroalkaline indices 1 (CAI-1), residual sodium carbonate and chloride bicarbonate ratio indicated that samples (55 to 100%) could be used for irrigation purposes. The consumption of water with high concentration of salts and fluoride above the permissible limits may be a cause of a number of diseases in the area.

scholarly journals Modelling and Simulating the Novel Coronavirus with Implications of Asymptomatic Carriers

2020 ◽  
Vol 2020 ◽  
pp. 1-9
Author(s):  
Ghassane Benrhmach ◽  
Khalil Namir ◽  
Jamal Bouyaghroumni
Keyword(s):  
Control Strategies ◽  
World Health ◽  
Contact Tracing ◽  
Effective Control ◽  
Public Authorities ◽  
Asymptomatic Carriers ◽  
Social Distancing ◽  
Infected People ◽  
Novel Coronavirus ◽  
Health Organization

The World Health Organization declared that the total number of confirmed cases tested positive for SARS‐CoV‐2, affecting 210 countries, exceeded 3 million on 29 April 2020, with more than 207,973 deaths. In order to end the global COVID‐19 pandemic, public authorities have put in place multiple strategies like testing, contact tracing, and social distancing. Predictive mathematical models for epidemics are fundamental to understand the development of the epidemic and to plan effective control strategies. Some hosts may carry SARS‐CoV‐2 and transmit it to others, yet display no symptoms themselves. We propose applying a model (SELIAHRD) taking in consideration the number of asymptomatic infected people. The SELIAHRD model consists of eight stages: Susceptible, Exposed, Latent, Symptomatic Infected, Asymptomatic Infected, Hospitalized, Recovered, and Dead. The asymptomatic carriers contribute to the spread of disease, but go largely undetected and can therefore undermine efforts to control transmission. The simulation of possible scenarios of the implementation of social distancing shows that if we rigorously follow the social distancing rule then the healthcare system will not be overloaded.

scholarly journals Predicting the Epidemiological Outbreak of the Coronavirus Disease 2019 (COVID-19) in Saudi Arabia

2020 ◽  
Vol 17 (12) ◽  
pp. 4568 ◽  
Author(s):  
Dabiah Alboaneen ◽  
Bernardi Pranggono ◽  
Dhahi Alshammari ◽  
Nourah Alqahtani ◽  
Raja Alyaffer
Keyword(s):  
Saudi Arabia ◽  
Real Time ◽  
World Health ◽  
Logistic Growth ◽  
Final Phase ◽  
Time Data ◽  
Local Prediction ◽  
The World ◽  
Real Time Data ◽  
Health Organization

The coronavirus diseases 2019 (COVID-19) outbreak continues to spread rapidly across the world and has been declared as pandemic by World Health Organization (WHO). Saudi Arabia was among the countries that was affected by the deadly and contagious virus. Using a real-time data from 2 March 2020 to 15 May 2020 collected from Saudi Ministry of Health, we aimed to give a local prediction of the epidemic in Saudi Arabia. We used two models: the Logistic Growth and the Susceptible-Infected-Recovered for real-time forecasting the confirmed cases of COVID-19 across Saudi Arabia. Our models predicted that the epidemics of COVID-19 will have total cases of 69,000 to 79,000 cases. The simulations also predicted that the outbreak will entering the final-phase by end of June 2020.

Multi-camera tele-immersion system with real-time model driven data compression

2009 ◽  
Vol 26 (1) ◽  
pp. 3-15 ◽  
Author(s):  
Jyh-Ming Lien ◽  
Gregorij Kurillo ◽  
Ruzena Bajcsy
Keyword(s):  
Data Compression ◽  
Real Time ◽  
Time Model ◽  
Model Driven
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