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   2021| December  | Volume 14 | Issue 12  
    Online since December 29, 2021

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Intention of healthcare workers to accept COVID-19 vaccination and related factors: A systematic review and meta-analysis
Petros Galanis, Irene Vraka, Despoina Fragkou, Angeliki Bilali, Daphne Kaitelidou
December 2021, 14(12):543-554
Considering medical and economic burden of coronavirus disease 2019 (COVID-19), a high COVID-19 vaccination coverage among healthcare workers (HCWs) is an urgent need. The aim of this systematic review and meta-analysis was to evaluate the intention of HCWs to accept COVID-19 vaccination and to identify related factors. We searched PubMed, MEDLINE, Scopus, Web of Science, ProQuest, CINAHL and medRxiv until July 14, 2021. The heterogeneity between results was very high; thus, we applied a random effects model to estimate pooled effects. We performed subgroup and meta-regression analysis to identify possible resources of heterogeneity. Twenty four studies, including 50 940 HCWs, met the inclusion criteria. The overall proportion of HCWs that intend to accept COVID-19 vaccination was 63.5% (95% confidence interval: 56.5%-70.2%) with a wide range among studies from 27.7% to 90.1%. The following factors were associated with increased HCWs' willingness to get vaccinated against COVID-19: male gender, older age, white HCWs, physician profession, higher education level, comorbidity among HCWs, vaccination against flu during previous season, stronger vaccine confidence, positive attitude towards a COVID-19 vaccine, fear about COVID-19, individual perceived risk about COVID-19, and contact with suspected or confirmed COVID-19 patients. The reluctance of HCWs to vaccinate against COVID-19 could diminish the trust of individuals and trigger a ripple effect in the general public. Since vaccination is a complex behavior, understanding the way that HCWs take the decision to accept or refuse COVID-19 vaccination will give us the opportunity to develop the appropriate interventions to increase COVID-19 vaccination uptake.
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Methods and parameters of melting curve analysis for identification of Leishmania species: A scoping review
Juliana J G Ferreira, Fernanda S Nascimento, Gláucia E B Marcon, Eros A de Almeida, Sandra C B Costa
December 2021, 14(12):528-542
Leishmaniasis is a set of diseases with a worldwide distribution that affects mainly economically underprivileged populations in developing countries. It has a major impact on public health, with a global cost of billions of dollars per year. The treatment and control of leishmaniasis vary according to the Leishmania species involved, which require reliable methods for species identification. Since most of the currently used methods have limitations, there is a need for assays that allow rapid, precise identification of the offending species. Real-time polymerase chain reactions in conjunction with dissociation curve analysis have been used to detect differences in the DNA composition of selected genes of Leishmania spp. Kinetoplast DNA is the main molecular target used because of its high copy number per parasite, but other targets have also been studied. As part of an effort to establish melting temperature standards for each target gene, we have reviewed the pertinent literature available in public databases, including PubMed, Web of Science, SciELO and LILACS, using the keywords “Leishmania”, “leishmaniasis”, “real-time PCR”, “melting temperature”, and “melting curve”, alone or in combination. After applying eligibility criteria, 27 articles were selected for analysis. A considerable variation in the methodologies analyzed was found regarding molecular targets, standardization of the methods, reproducibility and specificity. Because of this, statistical analysis was not performed. In most cases, the methods were able to differentiate the parasite at the subgenus level or few species regardless of the target chosen.
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Dissemination of scientific information to fight against COVID-19: Academic journals' role
Qiao Zhang, Yin Pan
December 2021, 14(12):525-527
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Socio-ecological determinants of dengue prevention practices: A cross-sectional study among wet market traders in a selected district in Perak, Malaysia
N. I.K. Kamaruddin, Salmiah bt Md Said, H Kadir Shahar, PY Lim
December 2021, 14(12):555-563
Objective: To determine the level of dengue prevention practices among wet market traders in a Malaysian district and their associated socio-ecological factors including individual, relationships, community and societal factors. Methods: A cross-sectional study involving 246 wet market traders was conducted in a district in Perak state in northwest Malaysia between September 2018 to June 2019. Participants were selected through stratified sampling from four wet markets in Hilir Perak district. Data on dengue prevention practices and associated socio-ecological characteristics were collected using a validated interview-based questionnaire. The data were analyzed using SPSS version 25. Multiple logistic regression was performed to identify socio-ecological determinants of dengue prevention practices among wet market traders in Hilir Perak District. Results: From the total number of respondents, 78% had high dengue prevention practices. Higher dengue prevention practices were associated with owners of wet market shoplots compared to employed workers (adjusted OR 4.18, 95% CI 1.78, 9.85), high perceived susceptibility (adjusted OR 6.93, 95% CI 3.02, 15.92), high familial support (adjusted OR 3.65, 95% CI 1.25, 10.64), and high perceived dengue prevention and control laws and regulations (adjusted OR 3.24, 95% CI 1.44, 7.32). Conclusions: Dengue prevention practices were associated not only with individual determinants but also with other determinants from relationships to societal level which must be considered in planning or evaluating current dengue control programs.
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Predicting COVID-19 fatality rate based on age group using LSTM
Zahra Ramezani, Seyed Abbas Mousavi, Ghasem Oveis, Mohammad Reza Parsai, Fatemeh Abdollahi, Jamshid Yazdani Charati
December 2021, 14(12):564-574
Objective: To predict the daily incidence and fatality rates based on long short-term memory (LSTM) in 4 age groups of COVID-19 patients in Mazandaran Province, Iran. Methods: To predict the daily incidence and fatality rates by age groups, this epidemiological study was conducted based on the LSTM model. All data of COVID-19 disease were collected daily for training the LSTM model from February 22, 2020 to April 10, 2021 in the Mazandaran University of Medical Sciences. We defined 4 age groups, i.e., patients under 29, between 30 and 49, between 50 and 59, and over 60 years old. Then, LSTM models were applied to predict the trend of daily incidence and fatality rates from 14 to 40 days in different age groups. The results of different methods were compared with each other. Results: This study evaluated 5 0826 patients and 5 109 deaths with COVID-19 daily in 20 cities of Mazandaran Province. Among the patients, 25 240 were females (49.7%), and 25 586 were males (50.3%). The predicted daily incidence rates on April 11, 2021 were 91.76, 155.84, 150.03, and 325.99 per 100 000 people, respectively; for the fourteenth day April 24, 2021, the predicted daily incidence rates were 35.91, 92.90, 83.74, and 225.68 in each group per 100 000 people. Furthermore, the predicted average daily incidence rates in 40 days for the 4 age groups were 34.25, 95.68, 76.43, and 210.80 per 100 000 people, and the daily fatality rates were 8.38, 4.18, 3.40, 22.53 per 100 000 people according to the established LSTM model. The findings demonstrated the daily incidence and fatality rates of 417.16 and 38.49 per 100 000 people for all age groups over the next 40 days. Conclusions: The results highlighted the proper performance of the LSTM model for predicting the daily incidence and fatality rates. It can clarify the path of spread or decline of the COVID-19 outbreak and the priority of vaccination in age groups.
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