scholarly journals Let's End HepC: Modelling Public Health Epidemiological Policies Applied to Hepatitis C in Spain

2022 ◽  
Vol 9 ◽  
Author(s):  
Henrique Lopes ◽  
Ricardo Baptista-Leite ◽  
Diogo Franco ◽  
Miguel A. Serra ◽  
Amparo Escudero ◽  
...  
Keyword(s):  
Public Health ◽  
Hepatitis C ◽  
Total Population ◽  
Policy Outcomes ◽  
Public Health Policies ◽  
Number Of Patients ◽  
If Current ◽  
Elimination Goal ◽  
Adaptive Conjoint Analysis ◽  
The Impact

Background: The WHO has defined international targets toward the elimination of hepatitis C by 2030. Most countries cannot be on track to achieve this goal unless many challenges are surpassed. The Let's End HepC (LEHC) tool aims to contribute to the control of hepatitis C. The innovation of this tool combines the modelling of public health policies (PHP) focused on hepatitis C with epidemiological modelling of the disease, obtaining a unique result that allows to forecast the impact of policy outcomes. The model was applied to several countries, including Spain.Methods: To address the stated objective, we applied the “Adaptive Conjoint Analysis” for PHP decision-making and Markov Chains in the LEHC modelling tool. The tool also aims to be used as an element of health literacy for patient advocacy through gamification mechanisms and country comparability. The LEHC project has been conducted in several countries, including Spain. The population segments comprised in the project are: People Who Inject Drugs (PWID), prisoners, blood products, remnant population.Results: A total of 24 PHP related to hepatitis C were included in the LEHC project. It was identified that Spain had fully implemented 14 of those policies to control hepatitis C. According to LEHC's model forecast, the WHO's Hepatitis C elimination goal on reducing the number of patients living with Hepatitis C to 10% can be achieved in Spain by 2026 if current policies are maintained. The model estimates that the total population in Spain, by 2026, is expected to comprise 26,367 individuals living with hepatitis C. Moreover, if the 24 PHP considered for this study are fully implemented in Spain, the elimination goal may be achieved in 2024, with 29,615 individuals living with hepatitis C by that year.Conclusion: The findings corroborate the view that Spain has set great efforts in directing PHP toward Hepatitis C Virus (HCV) elimination by 2030. However, there is still room for improvement, namely in further implementing 10 of the 24 PHP considered for the LEHC project. By maintaining the 14 PHP in force, the LEHC model estimates the HCV elimination in the country by 2026, and by 2024 if further measures are employed to control the disease.

scholarly journals Integrating public health policies in the epidemiological modeling of hepatitis C with LEHC tool: application in Austria

2020 ◽  
Author(s):  
Henrique Lopes ◽  
Ricardo Baptista-Leite ◽  
Diogo Franco ◽  
Roxana Pirker ◽  
Michael Gschwantler
Keyword(s):  
Public Health ◽  
Hepatitis C ◽  
People Who Inject Drugs ◽  
Health Policies ◽  
Epidemiological Modeling ◽  
Public Health Policies ◽  
Elimination Goal ◽  
Adaptive Conjoint Analysis ◽  
The Impact ◽  
Adequate Management

Summary Background Eliminating hepatitis C requires addressing issues other than medicines or therapies. Public health policies focused on the hepatitis C virus (HCV) must be emphasized and worked to know the impacts on its epidemiologic dynamics. This research aims to provide a tool to evaluate and simulate alternatives by redefining policies meeting specific needs in each country towards the HCV elimination target by 2030. Methods The development of a gamified model with 24 public health policies focused on HCV was conducted to evaluate the impact of measures in the disease epidemiologic dynamics. The Let’s End HepC (LEHC) project encompassed key populations (people who inject drugs [PWID], prisoners, blood products and remnant population) in Austria and other countries, presenting prospects for every year from 2019 to 2030. The LEHC epidemiological model comprised an integrated solution for HCV, with adaptive conjoint analysis (ACA) and Markov chains constituting its main processes. Results Despite Austria’s efforts towards achieving the HCV elimination goal by 2030, the LEHC model forecast quantitative analysis predicts that it is still not enough to meet the target; however, prospects are very optimistic if public health policies are adapted to the country’s needs, being possible to achieve the goal as early as 2026. Conclusion In Austria, the LEHC tool allowed to forecast the HCV elimination year anticipation to 2026, instead of being achieved after 2030. This target will only be valid if adequate management of the 24 public health policies focused on this pathology is further implemented.

scholarly journals Modeling the Puzzle of Hepatitis C Epidemiology in Romania: A Pathway to Control

2020 ◽  
Author(s):  
Henrique Lopes ◽  
Ricardo Baptista-Leite ◽  
Diogo Franco ◽  
Irina Eclemea ◽  
Eugenia C Bratu ◽  
...  
Keyword(s):  
Public Health ◽  
Hepatitis C ◽  
People Who Inject Drugs ◽  
Public Policies ◽  
Risk Groups ◽  
Health Policies ◽  
Blood Products ◽  
Public Health Policies ◽  
If Current ◽  
Adaptive Conjoint Analysis

Background and Aims: To combat hepatitis C virus (HCV) and achieve its elimination by 2030, the emphasis should be on public health policies. In this study, we investigated the dynamics of epidemiology of HCV in Romanian risk groups that are characterized by higher occurrence densities with the aid of The Let’s End HepC (LEHC) project. Methods: The LEHC project addressed the modelling of HCV epidemiology, being applied in several countries, one of which is Romania. The model comprised an integrated solution of public health policies focused on the disease, using Adaptive Conjoint Analysis and Markov chains systems. This tool allowed the quantitative evaluation of public health policies‘ impact, for every year until 2030, in five population groups: people who inject drugs (PWID), prisoners, individuals who have received blood products, children at risk for vertical transmission, and the remnant population. Results: It appears that Romania was already making great efforts in the context of public policies, allowing the achievement of HCV elimination by 2028 if current policies were maintained. Through additional work and greater efforts in further implementing public policies, the LEHC model estimated the possibility of anticipating this outcome to 2026. Conclusion: The LEHC model estimated an anticipation of the HCV elimination year in Romania to be 2026 if the twenty-four health policies in the study are fully implemented and consistently maintained over the years.

scholarly journals Using Unstated Cases to Correct for COVID-19 Pandemic Outbreak and Its Impact on Easing the Intervention for Qatar

Biology ◽  
2021 ◽  
Vol 10 (6) ◽  
pp. 463
Author(s):  
Narjiss Sallahi ◽  
Heesoo Park ◽  
Fedwa El Mellouhi ◽  
Mustapha Rachdi ◽  
Idir Ouassou ◽  
...  
Keyword(s):  
Public Health ◽  
A Priori ◽  
Epidemiological Models ◽  
Sir Epidemic Model ◽  
Gulf Region ◽  
Epidemiological Modeling ◽  
Public Health Policies ◽  
Sir Epidemic ◽  
The Impact ◽  
Case Data

Epidemiological Modeling supports the evaluation of various disease management activities. The value of epidemiological models lies in their ability to study various scenarios and to provide governments with a priori knowledge of the consequence of disease incursions and the impact of preventive strategies. A prevalent method of modeling the spread of pandemics is to categorize individuals in the population as belonging to one of several distinct compartments, which represents their health status with regard to the pandemic. In this work, a modified SIR epidemic model is proposed and analyzed with respect to the identification of its parameters and initial values based on stated or recorded case data from public health sources to estimate the unreported cases and the effectiveness of public health policies such as social distancing in slowing the spread of the epidemic. The analysis aims to highlight the importance of unreported cases for correcting the underestimated basic reproduction number. In many epidemic outbreaks, the number of reported infections is likely much lower than the actual number of infections which can be calculated from the model’s parameters derived from reported case data. The analysis is applied to the COVID-19 pandemic for several countries in the Gulf region and Europe.

scholarly journals Public Health Policies in the Akyem Abuakwa of Ghana (1850-1957)

2020 ◽  
Vol 20 (2) ◽  
pp. 129-157
Author(s):  
Samuel Adu Gyamfi ◽  
Phinehas Asiamah ◽  
Benjamin Dompreh Darkwa ◽  
Lucky Tomdi
Keyword(s):  
Public Health ◽  
Academic Research ◽  
Health Policies ◽  
Historical Study ◽  
Colonial Era ◽  
Public Health Policies ◽  
Health History ◽  
Documentary Sources ◽  
The People ◽  
The Impact

Abstract Akyem Abuakwa is one of the largest states of the Akan ethnic group in Ghana. Notwithstanding its size and important contribution to Ghana’s development, historians have paid little attention in doing academic research on the health history of the people. Using a qualitative method of research, this paper does a historical study on public health policies in Akyem Abuakwa from the 1850s to 1957. We utilised documentary and non-documentary sources to discuss the various public health policies implemented in Akyem Abuakwa from the pre-colonial era to the colonial era. We examined the impact of the policies on the people of Akyem Abuakwa and the various challenges faced by the British colonial administration in their quest to implement public health policies.

scholarly journals Integrated Resistance Analysis of CERTAIN-1 and CERTAIN-2 Studies in Hepatitis C Virus-Infected Patients Receiving Glecaprevir and Pibrentasvir in Japan

2017 ◽  
Vol 62 (2) ◽  
Author(s):  
Preethi Krishnan ◽  
Gretja Schnell ◽  
Rakesh Tripathi ◽  
Jill Beyer ◽  
Thomas Reisch ◽  
...  
Keyword(s):  
Hepatitis C Virus ◽  
Hepatitis C ◽  
Virologic Failure ◽  
Virologic Response ◽  
Fixed Dose ◽  
Resistance Testing ◽  
Combination Regimen ◽  
Resistance Analysis ◽  
Number Of Patients ◽  
The Impact

ABSTRACT Glecaprevir and pibrentasvir are hepatitis C virus (HCV) pangenotypic inhibitors targeting NS3/4A protease and NS5A, respectively. This once-daily, fixed-dose combination regimen demonstrated high sustained virologic response 12 weeks postdosing (SVR12) rates in CERTAIN-1 and CERTAIN-2 studies in Japanese HCV-infected patients, with a low virologic failure rate (1.2%). There were no virologic failures among direct-acting antiviral (DAA)-treatment-naive genotype 1a (GT1a) (n = 4)-, GT1b (n = 128)-, and GT2 (n = 97)-infected noncirrhotic patients treated for 8 weeks or among GT1b (n = 38)- or GT2 (n = 20)-infected patients with compensated cirrhosis treated for 12 weeks. Two of 33 DAA-experienced and 2 of 12 GT3-infected patients treated for 12 weeks experienced virologic failure. Pooled resistance analysis, grouped by HCV subtype, treatment duration, prior treatment experience, and cirrhosis status, was conducted. Among DAA-naive GT1b-infected patients, the baseline prevalence of NS3-D168E was 1.2%, that of NS5A-L31M was 3.6%, and that of NS5A-Y93H was 17.6%. Baseline polymorphisms in NS3 or NS5A were less prevalent in GT2, with the exception of the common L/M31 polymorphism in NS5A. Among DAA-experienced GT1b-infected patients (30/32 daclatasvir plus asunaprevir-experienced patients), the baseline prevalence of NS3-D168E/T/V was 48.4%, that of NS5A-L31F/I/M/V was 81.3%, that of the NS5A P32deletion was 6.3%, and that of NS5A-Y93H was 59.4%. Common baseline polymorphisms in NS3 and/or NS5A had no impact on treatment outcomes in GT1- and GT2-infected patients; the impact on GT3-infected patients could not be assessed due to the enrollment of patients infected with diverse subtypes and the limited number of patients. The glecaprevir-pibrentasvir combination regimen allows a simplified treatment option without the need for HCV subtyping or baseline resistance testing for DAA-naive GT1- or GT2-infected patients. (The CERTAIN-1 and CERTAIN-2 studies have been registered at ClinicalTrials.gov under identifiers NCT02707952 and NCT02723084, respectively.)

scholarly journals Teledescante nº1: polyphony in time of plague

2021 ◽  
Vol 9 (2) ◽  
pp. 1-43
Author(s):  
Maurício De Bonis ◽  
Fábio Scucuglia
Keyword(s):  
Public Health ◽  
Social Isolation ◽  
Health Policies ◽  
Humanitarian Crisis ◽  
Public Health Policies ◽  
Guiding Principle ◽  
Music Making ◽  
The Impact

This report contemplates an instrumental composition as a project for audiovisual production in social isolation, during the Covid-19 pandemic. Based on the problematization of the impact of the pandemic in music making, solutions were sought that were not only viable as an artistic result but that could also be projected in a purposeful and prospective way in times of humanitarian crisis, of dismal symmetry between capitalist neoliberalism and programmed neglect in public health policies. After a description of the research on the use of art in past pandemics as a guiding principle in the choice of materials, the audiovisual production is detailed. The piece was written in April 2020 as a result of the analysis of a Renaissance motet, which, in turn, was conceived as a tribute to a composer who had perished from the plague and as a palliative against the disease.

scholarly journals Worldwide prevalence, genotype distribution and management of hepatitis C

2021 ◽  
Vol 84 (4) ◽  
pp. 633-652
Author(s):  
P Guntipalli ◽  
R Pakala ◽  
S Kumari Gara ◽  
F Ahmed ◽  
A Bhatnagar ◽  
...  
Keyword(s):  
Public Health ◽  
Hepatitis C ◽  
Geographic Origin ◽  
Global Strategy ◽  
Hcv Infection ◽  
Transmission Risk ◽  
World Health ◽  
Risk Category ◽  
Genotype Distribution ◽  
The Impact

Hepatitis C virus (HCV) is one of the leading causes of chronic liver disease, cirrhosis, and hepatocellular carcinoma, resulting in major global public health concerns. The HCV infection is unevenly distributed worldwide, with variations in prevalence across and within countries. The studies on molecular epidemiology conducted in several countries provide an essential supplement for a comprehensive knowledge of HCV epidemiology, genotypes, and subtypes, along with providing information on the impact of current and earlier migratory flows. HCV is phylogenetically classified into 8 major genotypes and 57 subtypes. HCV genotype and subtype distribution differ according to geographic origin and transmission risk category. Unless people with HCV infection are detected and treated appropriately, the number of deaths due to the disease will continue to increase. In 2015, 1.75 million new viral infections were mostly due to unsafe healthcare procedures and drug use injections. In the same year, access to direct-acting antivirals was challenging and varied in developing and developed countries, affecting HCV cure rates based on their availability. The World Health Assembly, in 2016, approved a global strategy to achieve the elimination of the HCV public health threat by 2030 (by reducing new infections by 90% and deaths by 65%). Globally, countries are implementing policies and measures to eliminate HCV risk based on their distribution of genotypes and prevalence.

scholarly journals Assessing the impact of adherence to Non-pharmaceutical interventions and indirect transmission on the dynamics of COVID-19: a mathematical modelling study

2021 ◽  
Author(s):  
Sarafa A. Iyaniwura ◽  
Musa Rabiu ◽  
Jummy F. David ◽  
Jude D. Kong
Keyword(s):  
Public Health ◽  
Reproduction Number ◽  
Health Policies ◽  
Public Health Policies ◽  
Indirect Transmission ◽  
Epidemic Size ◽  
Final Epidemic Size ◽  
The Impact ◽  
Size Relation ◽  
Pharmaceutical Interventions

AbstractAdherence to public health policies such as the non-pharmaceutical interventions implemented against COVID-19 plays a major role in reducing infections and controlling the spread of the diseases. In addition, understanding the transmission dynamics of the disease is also important in order to make and implement efficient public health policies. In this paper, we developed an SEIR-type compartmental model to assess the impact of adherence to COVID-19 non-pharmaceutical interventions and indirect transmission on the dynamics of the disease. Our model considers both direct and indirect transmission routes and stratifies the population into two groups: those that adhere to COVID-19 non-pharmaceutical interventions (NPIs) and those that do not adhere to the NPIs. We compute the control reproduction number and the final epidemic size relation for our model and study the effect of different parameters of the model on these quantities. Our results show that direct transmission has more effect on the reproduction number and final epidemic size, relative to indirect transmission. In addition, we showed that there is a significant benefit in adhering to the COVID-19 NPIs.

scholarly journals COVID-19: A Comparison of Time Series Methods to Forecast Percentage of Active Cases per Population

2020 ◽  
Vol 10 (11) ◽  
pp. 3880 ◽  
Author(s):  
Vasilis Papastefanopoulos ◽  
Pantelis Linardatos ◽  
Sotiris Kotsiantis
Keyword(s):  
Public Health ◽  
Machine Learning ◽  
Time Series ◽  
Health System ◽  
Total Population ◽  
Outbreak Detection ◽  
Time Series Modeling ◽  
Learning Time ◽  
Raising Awareness ◽  
The Impact

The ongoing COVID-19 pandemic has caused worldwide socioeconomic unrest, forcing governments to introduce extreme measures to reduce its spread. Being able to accurately forecast when the outbreak will hit its peak would significantly diminish the impact of the disease, as it would allow governments to alter their policy accordingly and plan ahead for the preventive steps needed such as public health messaging, raising awareness of citizens and increasing the capacity of the health system. This study investigated the accuracy of a variety of time series modeling approaches for coronavirus outbreak detection in ten different countries with the highest number of confirmed cases as of 4 May 2020. For each of these countries, six different time series approaches were developed and compared using two publicly available datasets regarding the progression of the virus in each country and the population of each country, respectively. The results demonstrate that, given data produced using actual testing for a small portion of the population, machine learning time series methods can learn and scale to accurately estimate the percentage of the total population that will become affected in the future.

Sign in / Sign up

Export Citation Format

Share Document