Browsing by Author "Franco, Diogo"
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- Fighting Hepatitis C in a COVID-19 ecosystem. Public health policies are needed more than everPublication . Lopes, Henrique; Baptista-Leite, Ricardo; Franco, Diogo; Kundurzhiev, Todor; Mateva, Lyudmila; Jelev, Dejan; Simonova, Marieta
- Integrating public health policies in the epidemiological modeling of hepatitis C with LEHC tool: application in AustriaPublication . Lopes, Henrique; Baptista-Leite, Ricardo; Franco, Diogo; Pirke, Roxana; Gschwantler, MichaelBackground: 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.
- Let's End HepC: modelling public health epidemiological policies applied to Hepatitis C in SpainPublication . Lopes, Henrique; Baptista-Leite, Ricardo; Franco, Diogo; Serra, Miguel A.; Escudero, Amparo; Martín-Moreno, José M.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.
- Modeling the puzzle of hepatitis C epidemiology in Romania: a pathway to controlPublication . Lopes, Henrique; Baptista-Leite, Ricardo; Franco, Diogo; Eclemea, Irina; Bratu, Eugenia C.; Furtunescu, Florentina L.; Pop, Corina Silvia; Pana, Bogdan C.Background & 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.
- Real-world evidence: the low validity of temperature screening for COVID-19 triagePublication . Pană, Bogdan C.; Lopes, Henrique; Furtunescu, Florentina; Franco, Diogo; Rapcea, Anca; Stanca, Mihai; Tănase, Alina; Coliţă, AncaBackground: The COVID-19 pandemic forced health-related organizations to rapidly launch country-wide procedures that were easy to use and inexpensive. Body temperature measurement with non-contact infrared thermometers (NCITs) is among the most common procedures, both in hospital settings and in many other entities. However, practical hospital experiences have raised great doubts about the procedure's validity. Aim: This study aimed to evaluate the validity of the body temperature measured using NCITs among oncological and transplant patients who took the polymerase chain reaction test for SARS-Cov-2 PCR+ and PCR- in a Romanian Hospital. Methods: Body temperature was measured for 5,231 inpatients using NCITs. The cutoff point for fever was equal to or above 37.3 degrees C. Patients then completed a questionnaire about their symptoms, contact, and travel history. Findings: Fever was detected in five of 53 persons with PCR+, resulting in a sensitivity of 9.43% (95% CI, 3.13-20.66%). No fever was verified in 5,131 of 5,171 persons with PCR-, resulting in a specificity of 99.15% (95% CI, 98.86-99.38%). A defensive vision of NCIT procedure (maximum standard error only in favor) had a sensitivity of 15.09% (95% CI, 6.75-27.59%). Conclusions: The use of NCITs in a triage provides little value for detection of COVID-19. Moreover, it provides a false sense of protection against the disease while possibly discriminating individuals that could present fever due to other reasons, such as oncologic treatments, where fever is a common therapeutical consequence. The consumption of qualified human resources should be considered, especially in the context of the shortage of healthcare professionals worldwide.
- SARS-CoV-2: sir model limitations and predictive constraintsPublication . Telles, Charles Roberto; Lopes, Henrique; Franco, DiogoBackground: The main purpose of this research is to describe the mathematical asymmetric patterns of susceptible, infectious, or recovered (SIR) model equation application in the light of coronavirus disease 2019 (COVID-19) skewness patterns worldwide. Methods: The research mod-eled severe acute respiratory syndrome coronavirus 2 (SARS-COV-2) spreading and dissemination patterns sensitivity by redesigning time series data extraction of daily new cases in terms of deviation consistency concerning variables that sustain COVID-19 transmission. The approach opened a new scenario where seasonality forcing behavior was introduced to understand SARS-COV-2 non-linear dynamics due to heterogeneity and confounding epidemics scenarios. Results: The main research results are the elucidation of three birth-and death-forced seasonality persistence phases that can explain COVID-19 skew patterns worldwide. They are presented in the following order: (1) the environmental variables (Earth seasons and atmospheric conditions); (2) health policies and adult learning education (HPALE) interventions; (3) urban spaces (local indoor and outdoor spaces for transit and social-cultural interactions, public or private, with natural physical features (river, lake, terrain). Conclusions: Three forced seasonality phases (positive to negative skew) phases were pointed out as a theoretical framework to explain uncertainty found in the predictive SIR model equations that might diverge in outcomes expected to express the disease’s behaviour.