scholarly journals Predictive accuracy of a hierarchical logistic model of cumulative SARS-CoV-2 case growth until May 2020

2020 ◽  
Vol 20 (1) ◽  
Author(s):  
Levente Kriston
Keyword(s):  
Disease Transmission ◽  
Logistic Model ◽  
Predictive Accuracy ◽  
Future Research ◽  
Cumulative Number ◽  
Epidemiological Models ◽  
First Case ◽  
Distribution Of Resources ◽  
The One ◽  
Models Of Disease

Abstract Background Infectious disease predictions models, including virtually all epidemiological models describing the spread of the SARS-CoV-2 pandemic, are rarely evaluated empirically. The aim of the present study was to investigate the predictive accuracy of a prognostic model for forecasting the development of the cumulative number of reported SARS-CoV-2 cases in countries and administrative regions worldwide until the end of May 2020. Methods The cumulative number of reported SARS-CoV-2 cases was forecasted in 251 regions with a horizon of two weeks, one month, and two months using a hierarchical logistic model at the end of March 2020. Forecasts were compared to actual observations by using a series of evaluation metrics. Results On average, predictive accuracy was very high in nearly all regions at the two weeks forecast, high in most regions at the one month forecast, and notable in the majority of the regions at the two months forecast. Higher accuracy was associated with the availability of more data for estimation and with a more pronounced cumulative case growth from the first case to the date of estimation. In some strongly affected regions, cumulative case counts were considerably underestimated. Conclusions With keeping its limitations in mind, the investigated model may be used for the preparation and distribution of resources during the initial phase of epidemics. Future research should primarily address the model’s assumptions and its scope of applicability. In addition, establishing a relationship with known mechanisms and traditional epidemiological models of disease transmission would be desirable.

scholarly journals Predictive Accuracy of a Hierarchical Logistic Model of Cumulative SARS-CoV-2 Case Growth

2020 ◽  
Author(s):  
Levente Kriston
Keyword(s):  
Disease Transmission ◽  
Logistic Model ◽  
Predictive Accuracy ◽  
Future Research ◽  
Cumulative Number ◽  
Epidemiological Models ◽  
First Case ◽  
Distribution Of Resources ◽  
The One ◽  
Models Of Disease

ABSTRACTBackgroundInfectious disease predictions models, including virtually all epidemiological models describing the spread of the SARS-CoV-2 pandemic up to June 2020, are rarely evaluated. The aim of the present study was to investigate the predictive accuracy of a prognostic model for forecasting the development of the cumulative number of reported SARS-CoV-2 cases in countries and administrative regions worldwide.MethodsThe cumulative number of reported SARS-CoV-2 cases was forecasted in 251 regions with a horizon of two weeks, one month, and two months using a previously described hierarchical logistic model at the end of March 2020. Forecasts were compared to actual observations by using a series of evaluation metrics.ResultsOn average, predictive accuracy was very high in nearly all regions at the two weeks forecast, high in most regions at the one month forecast, and notable in the majority of the regions at the two months forecast. Higher accuracy was associated with the availability of more data for estimation and with a more pronounced cumulative case growth from the first case to the date of estimation. In some strongly affected regions, cumulative case counts were considerably underestimated.ConclusionsWith keeping its limitations in mind, the investigated model can be used for the preparation and distribution of resources during the SARS-CoV-2 pandemic. Future research should primarily address the model’s assumptions and its scope of applicability. In addition, establishing a relationship with known mechanisms and traditional epidemiological models of disease transmission would be desirable.

scholarly journals From plague to coronavirus: vessel trajectory data from ship automatic identification systems for epidemic modeling

2020 ◽  
Vol 27 (6) ◽  
Author(s):  
Katherine E Hoffmann Pham ◽  
Miguel Luengo-Oroz
Keyword(s):  
Disease Transmission ◽  
Air Traffic ◽  
Automatic Identification ◽  
Traffic Data ◽  
Epidemiological Models ◽  
Trajectory Data ◽  
Epidemic Modeling ◽  
Models Of Disease

In addition to moving people and goods, ships can spread disease. Vessel trajectory data from ship Automatic Identification Systems (AIS) is available online and can be extracted and analyzed, as we illustrate in the case of the current coronavirus epidemic. This data should be included in epidemiological models of disease transmission to complement air traffic data and inform operational responses.

scholarly journals Climate change and the rising infectiousness of dengue

2019 ◽  
Vol 3 (2) ◽  
pp. 133-142 ◽  
Author(s):  
Joacim Rocklöv ◽  
Yesim Tozan
Keyword(s):  
Climate Change ◽  
Disease Transmission ◽  
Disease Burden ◽  
Climatic Conditions ◽  
Future Research ◽  
Research Directions ◽  
Core Concepts ◽  
Future Research Directions ◽  
Models Of Disease ◽  
Dengue Vectors

Abstract The disease burden of dengue has been steadily rising over the last half-century due to a multitude of factors, including global trade and travel, urbanization, population growth, and climate variability and change, that facilitate conductive conditions for the proliferation of dengue vectors and viruses. This review describes how climate, specifically temperature, affects the vectors’ ability to cause and sustain outbreaks, and how the infectiousness of dengue is influenced by climatic change. The review is focused on the core concepts and frameworks derived in the area of epidemiology of mosquito-borne diseases and outlines the sensitivity of vectorial capacity and vector-to-human transmission on climatic conditions. It further reviews studies linking mathematical or statistical models of disease transmission to scenarios of projected climate change and provides recommendations for future research directions.

scholarly journals Comparative Analysis and Forecasting on the Death Rate of COVID-19 Patients in Nigeria Using Random Forest and Multinomial Bayesian Epidemiological Models

2021 ◽  
pp. 1-7
Author(s):  
Ozioma Collins Oguine ◽  
◽  
Munachimso Blessing Oguine ◽  
Keyword(s):  
Random Forest ◽  
Death Rate ◽  
Predictive Accuracy ◽  
Learning Approach ◽  
Cumulative Number ◽  
The Novel ◽  
Epidemiological Models ◽  
Random Forest Algorithm ◽  
Bayesian Algorithm ◽  
The World

The novel COVID-19 (SARS-COV-2) is a disease currently ravaging the world, bringing unprecedented health and economic challenges to several nations. There are presently close to 175,000 reported cases in Nigeria with fatalities numbering over 2,163 persons. The main objective of this paper is to compare the analysis and predictive accuracy between the Random Forest and the Multinomial Bayesian Epidemiological model for a cumulative number of deaths for COVID-19 cases in Nigeria by identifying the underlying factors which may propagate future occurrences. It is worthy to note that the Random Forest algorithm is an ensemble learning approach for classification, regression, and other tasks that works by training a large number of decision trees G(t) while the Multinomial Bayesian algorithm provides an excellent theoretical framework for analyzing experimental data and the highlight of its success relies on its ability to integrate prior knowledge about the parameters of interest as a distribution function p(Ck|d).

Aspects of the Evolution of the Romanian Tourists’ Preferences Concerning the Domestic Tourist Destinations

2019 ◽  
Vol 10 (1) ◽  
pp. 21-28
Author(s):  
Aniela Bălăcescu ◽  
Radu Șerban Zaharia
Keyword(s):  
Logistic Model ◽  
Local Level ◽  
Medium Term ◽  
Tourist Destinations ◽  
Tourism Management ◽  
Production And Consumption ◽  
On Line ◽  
The One ◽  
Long Term Studies

Abstract Tourist services represent a category of services in which the inseparability of production and consumption, the inability to be storable, the immateriality, and last but not least non-durability, induces in tourism management a number of peculiarities and difficulties. Under these circumstances the development of medium-term strategies involves long-term studies regarding on the one hand the developments and characteristics of the demand, and on the other hand the tourist potential analysis at regional and local level. Although in the past 20 years there has been tremendous growth of on-line booking made by household users, the tour operators agencies as well as those with sales activity continue to offer the specific services for a large number of tourists, that number, in the case of domestic tourism, increased by 1.6 times in case of the tour operators and by 4.44 times in case of the agencies with sales activity. At the same time, there have been changes in the preferences of tourists regarding their holiday destinations in Romania. Started on these considerations, paper based on a logistic model, examines the evolution of the probabilities and scores corresponding to the way the Romanian tourists spend their holidays on the types of tourism agencies, actions and tourist areas in Romania.

A Review of Drug Side Effect Identification Methods

2020 ◽  
Vol 26 (26) ◽  
pp. 3096-3104 ◽  
Author(s):  
Shuai Deng ◽  
Yige Sun ◽  
Tianyi Zhao ◽  
Yang Hu ◽  
Tianyi Zang
Keyword(s):  
Side Effects ◽  
Future Research ◽  
Drug Side Effects ◽  
Important Indicator ◽  
Advantages And Disadvantages ◽  
Key Points ◽  
Network Methods ◽  
Future Research Directions ◽  
The One ◽  
Approved Drugs

Drug side effects have become an important indicator for evaluating the safety of drugs. There are two main factors in the frequent occurrence of drug safety problems; on the one hand, the clinical understanding of drug side effects is insufficient, leading to frequent adverse drug reactions, while on the other hand, due to the long-term period and complexity of clinical trials, side effects of approved drugs on the market cannot be reported in a timely manner. Therefore, many researchers have focused on developing methods to identify drug side effects. In this review, we summarize the methods of identifying drug side effects and common databases in this field. We classified methods of identifying side effects into four categories: biological experimental, machine learning, text mining and network methods. We point out the key points of each kind of method. In addition, we also explain the advantages and disadvantages of each method. Finally, we propose future research directions.

Novel Coronavirus Disease (COVID-19): A Narrative Review Based on Current Status

2020 ◽  
Vol 18 ◽  
Author(s):  
Rina Das ◽  
Dinesh Kumar Mehta ◽  
Meenakshi Dhanawat
Keyword(s):  
Severe Acute Respiratory Syndrome ◽  
Clinical Symptoms ◽  
Virus Disease ◽  
Relevant Literature ◽  
World Health ◽  
Current Status ◽  
Future Research ◽  
Treatment And Prevention ◽  
First Case ◽  
Novel Coronavirus

Abstract:: A novel virus, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), appeared and expanded globally by the end of year in 2019 from Wuhan, China, causing severe acute respiratory syndrome. During its initial stage, the disease was called the novel coronavirus (2019-nCoV). It was named COVID-19 by the World Health Organization (WHO) on 11 February 2020. The WHO declared worldwide the SARS-CoV-2 virus a pandemic on March 2020. On 30 January 2020 the first case of Corona Virus Disease 2019 (COVID-19) was reported in India. Now in current situation the virus is floating in almost every part of the province and rest of the globe. -: On the basis of novel published evidences, we efficiently summarized the reported work with reference to COVID-19 epidemiology, pathogen, clinical symptoms, treatment and prevention. Using several worldwide electronic scientific databases such as Pubmed, Medline, Embase, Science direct, Scopus, etc were utilized for extensive investigation of relevant literature. -: This review is written in the hope of encouraging the people successfully with the key learning points from the underway efforts to perceive and manage SARS-CoV-2, suggesting sailent points for expanding future research.

scholarly journals An Online Reputation Analysis of the Tourism Industry in Marbella: A Preliminary Study on Open Innovation

2021 ◽  
Vol 7 (2) ◽  
pp. 111
Author(s):  
María Jesús Carrasco-Santos ◽  
Antonio Manuel Ciruela-Lorenzo ◽  
Juan Gabriel Méndez Pavón ◽  
Carmen Cristófol Rodríguez
Keyword(s):  
Quantitative Research ◽  
Tourism Industry ◽  
Future Research ◽  
Full Data ◽  
Tourist Destination ◽  
Specific Advice ◽  
Sociodemographic Profile ◽  
The One ◽  
Online Reputation ◽  
The City

This research analyzed the online reputation of Marbella as a tourist destination and the profiles of the reviewers according to sociodemographic characteristics. A correlational, quantitative research technique was used in this study based on the manual extraction of more than 4000 reviews generated on TripAdvisor. The data used in this study were collected from the TripAdvisor website, taking, as a sample, tourists who had visited the city in the last three years. Ratings that did not provide full data on the variables were excluded. The findings show that Marbella is considered a luxury shopping destination. The preliminary conclusions allow us to generalize about the sociodemographic profile of its tourists. The findings of the study will provide valuable information for Marbella’s Destination Management Organization (DMO). On the one hand, this study highlights the importance of ranking the attractions of the city to create better communication strategies and enhance the appeal of those attractions that receive the best ratings, establishing the true vocation of Marbella as a tourist destination. On the other hand, it provides information on what tourists perceive to be negative elements, allowing the administration to create an improvement plan. The novelty of this research paper is that it delves into Marbella’s online reputation through an analysis of specific attractions’ ratings. Areas that require further attention in future research have been highlighted, along with specific advice on each attraction that contributes to the tourist offerings of the city.

scholarly journals Understanding mosquito host-choice behaviour: a new and low-cost method of identifying the sex of human hosts from mosquito blood meals

2021 ◽  
Vol 14 (1) ◽  
Author(s):  
Fiona Teltscher ◽  
Sophie Bouvaine ◽  
Gabriella Gibson ◽  
Paul Dyer ◽  
Jennifer Guest ◽  
...  
Keyword(s):  
Blood Meal ◽  
Host Species ◽  
Disease Transmission ◽  
Low Cost ◽  
Host Choice ◽  
Epidemiological Models ◽  
Choice Behaviour ◽  
Vector Borne ◽  
Transmission Models ◽  
Blood Meals

Abstract Background Mosquito-borne diseases are a global health problem, causing hundreds of thousands of deaths per year. Pathogens are transmitted by mosquitoes feeding on the blood of an infected host and then feeding on a new host. Monitoring mosquito host-choice behaviour can help in many aspects of vector-borne disease control. Currently, it is possible to determine the host species and an individual human host from the blood meal of a mosquito by using genotyping to match the blood profile of local inhabitants. Epidemiological models generally assume that mosquito biting behaviour is random; however, numerous studies have shown that certain characteristics, e.g. genetic makeup and skin microbiota, make some individuals more attractive to mosquitoes than others. Analysing blood meals and illuminating host-choice behaviour will help re-evaluate and optimise disease transmission models. Methods We describe a new blood meal assay that identifies the sex of the person that a mosquito has bitten. The amelogenin locus (AMEL), a sex marker located on both X and Y chromosomes, was amplified by polymerase chain reaction in DNA extracted from blood-fed Aedes aegypti and Anopheles coluzzii. Results AMEL could be successfully amplified up to 24 h after a blood meal in 100% of An. coluzzii and 96.6% of Ae. aegypti, revealing the sex of humans that were fed on by individual mosquitoes. Conclusions The method described here, developed using mosquitoes fed on volunteers, can be applied to field-caught mosquitoes to determine the host species and the biological sex of human hosts on which they have blood fed. Two important vector species were tested successfully in our laboratory experiments, demonstrating the potential of this technique to improve epidemiological models of vector-borne diseases. This viable and low-cost approach has the capacity to improve our understanding of vector-borne disease transmission, specifically gender differences in exposure and attractiveness to mosquitoes. The data gathered from field studies using our method can be used to shape new transmission models and aid in the implementation of more effective and targeted vector control strategies by enabling a better understanding of the drivers of vector-host interactions.

scholarly journals Exploring International and Inter-Sector Differences of Social Enterprises in the UK and India

2021 ◽  
Vol 13 (11) ◽  
pp. 5870
Author(s):  
Philipp Kruse
Keyword(s):  
Social Entrepreneurship ◽  
Social Enterprise ◽  
Social Enterprises ◽  
Future Research ◽  
Shape Features ◽  
Qualitative And Quantitative ◽  
Clear Cut ◽  
The One ◽  
Definition Of ◽  
The Uk

Social Entrepreneurship (SE) describes a new entrepreneurial form combining the generation of financial and social value. In recent years, research interest in SE increased in various disciplines with a particular focus on the characteristics of social enterprises. Whereas a clear-cut definition of SE is yet to be found, there is evidence that culture and economy affect and shape features of SE activity. In addition, sector-dependent differences are supposed. Building on Institutional Theory and employing a mixed qualitative and quantitative approach, this study sheds light on the existence of international and inter-sector differences by examining 161 UK and Indian social enterprises. A content analysis and analyses of variance were employed and yielded similarities as well as several significant differences on an international and inter-sector level, e.g., regarding innovativeness and the generation of revenue. The current study contributes to a more nuanced picture of the SE landscape by comparing social enterprise characteristics in a developed and a developing country on the one hand and different sectors on the other hand. Furthermore, I highlight the benefits of jointly applying qualitative and quantitative methodologies. Future research should pay more attention to the innate heterogeneity among social enterprises and further consolidate and extend these findings.

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