Global Health Epidemiology and Genomics最新文献

Host genetic factors are known to modify the susceptibility, severity, and outcomes of COVID-19 and vary across populations. However, continental Africans are yet to be adequately represented in such studies despite the importance of genetic factors in understanding Africa's response to the pandemic. We describe the development of a research resource for coronavirus host genomics studies in South Africa known as COVIGen-SA-a multicollaborator strategic partnership designed to provide harmonised demographic, clinical, and genetic information specific to Black South Africans with COVID-19. Over 2,000 participants have been recruited to date. Preliminary results on 1,354 SARS-CoV-2 positive participants from four participating studies showed that 64.7% were female, 333 had severe disease, and 329 were people living with HIV. Through this resource, we aim to provide insights into host genetic factors relevant to African-ancestry populations, using both genome-wide association testing and targeted sequencing of important genomic loci. This project will promote and enhance partnerships, build skills, and develop resources needed to address the COVID-19 burden and associated risk factors in South African communities.

This cross-sectional study was designed to investigate the prevalence, knowledge, attitude, and predictors of waterpipe (WP) smoking among intermediate and secondary school adolescents in the Kingdom of Saudi Arabia (KSA). A self-administered anonymous questionnaire was used to collect data on demography, WP smoking status and patterns, the Arabic version of the Global Youth Tobacco Survey tool, and instruments to assess knowledge and attitude towards WP smoking. The Patient Health Questionnaire (PHQ-9) was also used. Descriptive and inferential statistical techniques were used. Modeling of WP smoking behavior was conducted using logistic regression. A total of 639 male students participated in this study. The prevalence of current WP and cigarette smokers were 17.7% and 14.6%, respectively. Out of the total population, 47.8% of students have the misconception that WP smoking is less harmful than cigarettes. A significant association (P < 0.05) of some demographic factors (age, school stage, residence, and parents' educational level) on WP smoking status was observed. Pleasure, socializing, and happiness represented the primary motives for initiating WP smoking. The majority of students had misconceptions about WP's health effects. More than 50% believed that smoking WP could ease anxiety, cause less harm, and has less addictive properties compared to cigarettes. Modeling suggested that the most significant predictors of WP smoking were cigarette smoking, depression, and the attitude index. Current findings warrant further research and official health programs to promote educational initiatives regarding WP smoking.

Rapid identification and tracking of emerging SARS-CoV-2 variants are critical for understanding the transmission dynamics and developing strategies for interrupting the transmission chain. Next-Generation Sequencing (NGS) is an exceptional tool for whole-genome analysis and deciphering new mutations. The technique has been instrumental in identifying the variants of concern (VOC) and tracking this pandemic. However, NGS is complex and expensive for large-scale adoption, and epidemiological monitoring with NGS alone could be unattainable in limited-resource settings. In this study, we explored the application of RT-qPCR-based detection of the variant identified by NGS. We analyzed a total of 78 deidentified samples that screened positive for SARS-CoV-2 from two timeframes, August 2020 and July 2021. All 78 samples were classified into WHO lineages by whole-genome sequencing and then compared with two commercially available RT-qPCR assays for spike protein mutation(s). The data showed good concordance between RT-qPCR and NGS analysis for specific SARS-CoV-2 lineages and characteristic mutations. RT-qPCR assays are quick and cost-effective and thus can be implemented in synergy with NGS for screening NGS-identified mutations of SARS-CoV-2 for clinical and epidemiological interest. Strategic use of NGS and RT-qPCR can offer several COVID-19 epidemiological advantages.

Background: A novel coronavirus, a virus that causes coronavirus disease (COVID-19), was first identified in Wuhan, China, on December 2019. The virus affects the respiratory system and it is highly contagious, spreading from person to person. Healthcare workers are more at risk due to the nature of their work, which is caring for both COVID-19-affected and nonaffected patients. Lack of knowledge about the disease directly affects early diagnosis and treatment, which may result in the rapid spread of the infection in the community. Having enough knowledge about a disease can always affect an individual's attitudes and practices. However, there is limited evidence on the knowledge, attitude, practice of prevention, and control measures of COVID-19 and associated factors among healthcare workers (HCWs) in resource-limited countries, including Ethiopia.

Methods: A facility-based cross-sectional study design was used among 334 samples of health workers who were selected using a stratified two-stage sampling technique, from health facilities of the Horo Guduru Wollega Zone from May to June 2021. A structured self-administered questionnaire was used to collect the data from the HCWs. The information collected was entered to EpiData version 3.1 and exported to SPSS version 21 software for further analyses. Bivariable and multivariable binary logistic regression analyses were used to identify factors associated with the KA practice of the HCWs. Those variables with a p value <05 with a 95% confidence interval (CI) were considered as statistically significantly associated with the outcome variable.

Result: Among the participating HCWs, 208 (64%; 95% CI: (58.8%, 69.2%)) of them had good practices of prevention and control measures of COVID-19 with the mean (±SD) practice score was 7.63 ± 2.45. Multivariable binary logistic regression revealed that being a health center worker (AOR = 0.34, 95% CI: (0.19, 0.60)), being trained (AOR = 0.41, 95% CI: (0.21, 0 .82)), and having sufficient knowledge (AOR = 2.73, 95% CI: (1.35, 5.53)) were significantly associated with good preventive practice.

Conclusion: The overall magnitude of practice of prevention and control measures of COVID-19 was not sufficient. Therefore, strategies for enhancing the capacity of healthcare workers to exercise practices of prevention and control measures of COVID-19 are needed.

The 2019 coronavirus disease (COVID-19) pandemic has demonstrated the importance of predicting, identifying, and tracking mutations throughout a pandemic event. As the COVID-19 global pandemic surpassed one year, several variants had emerged resulting in increased severity and transmissibility. Here, we used PCR as a surrogate for viral load and consequent severity to evaluate the real-world capabilities of a genome-based clinical severity predictive algorithm. Using a previously published algorithm, we compared the viral genome-based severity predictions to clinically derived PCR-based viral load of 716 viral genomes. For those samples predicted to be "severe" (probability of severe illness >0.5), we observed an average cycle threshold (Ct) of 18.3, whereas those in in the "mild" category (severity probability <0.5) had an average Ct of 20.4 (P=0.0017). We also found a nontrivial correlation between predicted severity probability and cycle threshold (r = -0.199). Finally, when divided into severity probability quartiles, the group most likely to experience severe illness (≥75% probability) had a Ct of 16.6 (n = 10), whereas the group least likely to experience severe illness (<25% probability) had a Ct of 21.4 (n = 350) (P=0.0045). Taken together, our results suggest that the severity predicted by a genome-based algorithm can be related to clinical diagnostic tests and that relative severity may be inferred from diagnostic values.

Since the zoonotic event from which SARS-CoV-2 started infecting humans late in 2019, the virus has caused more than 5 million deaths and has infected over 500 million people around the world. The pandemic has had a severe impact on social and economic activities, with greater repercussions in low-income countries. South America, with almost 5% of the world's population, has reckoned with almost a fifth of the total people infected and more than 26% (>1/4) of the deceased. Fortunately, the full genome structure and sequence of SARS-CoV-2 have been rapidly obtained and studied thanks to all the scientific efforts and data sharing around the world. Such molecular analysis of SARS-CoV-2 dynamics showed that rates of mutation, similar to other members of the Coronaviridae family, along with natural selection forces, could result in the emergence of new variants; few of them might be of high consequence. However, this is a serious threat to controlling the pandemic and, of course, enduring the process of returning to normalization with the implicit monetary cost of such a contingency. The lack of updated knowledge in South America justifies the need to develop a structured genomic surveillance program of current and emerging SARS-CoV-2 variants. The modeling of the molecular events and microevolution of the virus will contribute to making better decisions on public health management of the pandemic and developing accurate treatments and more efficient vaccines.

Since December 2019, the novel severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has spread rapidly from Wuhan (China) across the globe, affecting more than 200 countries by mid-2021, with over 190 M reported cases and around 4 M fatalities. During the first year of the pandemic, affected countries implemented a variety of nonpharmaceutical interventions to control virus transmission. In December 2020, countries started administering several authorised vaccines under a limited supply scenario. In this context, the aim of this study was to develop a SEIR-type continuous-time deterministic disease model, to determine the impact of interaction between different vaccination scenarios and levels of protection measures on disease incidence. For this, the model incorporates (i) a protection measure including low (self-protection), medium (mobility limitation), high (closure of indoor facilities), and very high (lockdown) protection levels, (ii) quarantine for confirmed cases, and (iii) vaccination rate and efficacy of four types of vaccines (Pfizer, Moderna, Astra Zeneca, and Janssen). The model was verified and evaluated using the response timeline and vaccination strategies and rates in the Basque Country (N. Spain). Once the model performance was validated, different initial phase (when 30% of the population is vaccinated) vaccination scenarios were simulated, including (i) a realistic vaccine limited supply scenario and (ii) four potential full vaccine supply scenarios where a unique vaccine type is administered. Significant differences in disease prevalence and cumulative mortality were found between vaccination scenarios for low and medium-level protection measures. For high-level protection measures, any vaccine scenario is effective at limiting the virus transmission and disease mortality. The results obtained here may vary in further studies since there may be some unpredictable factors/covariates. With this in mind, the model here could be easily applied to other regions or countries, modifying the strategies implemented and initial conditions.

Background: The coronavirus disease 2019 (COVID-19) pandemic has presented as a therapeutic challenge for clinicians worldwide due to its rapid spread along with evolving evidence and understanding of the disease. Internationally, recommendations to guide the management of COVID-19 have been created and updated continuously by the WHO and CDC, which have been locally adapted by different countries. Similarly, Pakistan's National Command Operation Center (NCOC), in its national COVID-19 management strategy, generated guidelines for national implementation. Keeping the guidelines updated has proved challenging globally and locally. Here, we present a summary of the process to assess the evidence, including a time-restricted systematic review based on NCOC Clinical Management Guidelines for COVID-19 Infections v4 published on 11^th December 2020 version, correlating it with current recommendations and with input one of the guidelines authors, particularly noting the methodological challenges.

Methods: We conducted a systematic review synthesizing global research on treatment options for COVID-19 hospitalized patients, limiting it to pharmacological interventions for hospitalized COVID-19 patients included in Pakistan's NCOC's national guidelines v4 published on 11^th December 2020. Each treatment recommendation's strength and quality of evidence was assessed based on the grading of recommendations assessment, development, and evaluation (GRADE) methodology. These were then compared to the most current living WHO COVID-19 pharmacological treatment guidelines v7.1. One of the authors of the NCOC guidelines reviewed and commented on the findings as well.

Results: We note that the data from our systematic review strongly supports corticosteroids use in treating severe and critically ill COVID-19 hospitalized patients correlating with WHO v7.1 guidelines 24 September 2021. However, evidence from our review and WHO v7.1 for the use of tocilizumab had some conflicting evidence, with data from our review until December 2020 supporting only a weak recommendation for its use, compared to the strong recommendation by the WHO for the use of tocilizumab in patients with severe or critical COVID-19 infection. Regarding the use of antibiotics and ivermectin use in treating COVID-19 hospitalized patients, data from our review and WHO v 7.1 recommend against their use.

Conclusion: Research data about the efficacy and safety of pharmacological interventions to treat hospitalized patients with COVID-19 are rapidly evolving, and based on it, the evidence for or against recommendations changes accordingly. Our study illustrates the challenges of keeping up with the evidence; the recommendations were based on studies up till December 2021, and we have compared our recommendations with the WHO v7.1, which showed some significant changes in the use of pharmacologica

Background: The Human Health and Heredity (H3Africa) Consortium continues to generate large amounts of genomic data leading to new insights into health and disease among African populations. This has however generated debate among stakeholders involved in developing, implementing, and applying ethical standards and policies for the return of individual genetic research results. The key questions are about when results must, should, may, or must not be returned and by whom. This study aimed to explore the views on the feedback of individual pertinent and incidental genetic research results of researchers, ethics committee members, and policymakers in Botswana.

Methods: In-depth interviews were conducted with 16 key stakeholders from academic, research institutions, and regulatory bodies in Botswana. An analysis of the coded data was done through an iterative process of analytic induction to document and interpret themes and patterns.

Results: Overall, the study indicated that researchers have at least a partial obligation to return individual genetic research results to research participants. Respondents placed emphasis on the ethical principle of autonomy. They felt that it was inappropriate for researchers to make decisions about the return of results on participants' behalf except in situations of avoiding participant self-harm or harm to society.

Conclusion: Findings helped to highlight the importance of considering participants' autonomy in the development of sustainable and credible guidelines for feedback of findings from genomics research in Botswana, which can be explained during community engagement and consent processes. Such guidelines would ultimately be used to develop policies, guide African genomics research, and promote participant autonomy, transparency, and possibly participant trust in research.

Aim: The current study aimed to investigate the trend changes of stomach cancer incidence amongst African countries and identify the main patterns.

Methods: The annual reports of stomach cancer incidence rate (per 100,000 people) for males and females in 53 African countries from 1990 to 2016 were maintained from the World Health Organization archive. The growth mixture model was used for fitting the models in Mplus 7.4. The estimated linear trend in each pattern was characterized by intercept (the rate at 1990) and slope (the observed biennial trend changes), and finally, each country was grouped into a cluster with the most similar pattern.

Results: Three main patterns for males and two main patterns for females were determined. For males, the first cluster, containing Cape Verde, Central African Republic, and Mauritius, showed a sharp fall, while countries in the second pattern including Algeria, Côte d'Ivoire, Egypt, Gambia, Libya, Malawi, Morocco, Namibia, Nigeria, and Tunisia were categorized in a pattern with a slight decrease, and other 43 countries were in the third pattern with a moderate falling trend. For females, 19 countries including Angola, Botswana, Burundi, Cape Verde, Central African Republic, Congo Republic, Equatorial Guinea, Ethiopia, Gabon, Kenya, Mali, Mauritius, Rwanda, Sao Tome and Principe, Sudan, Swaziland, Uganda, Zambia, and Zimbabwe were categorized in the moderate-to-high falling pattern, but the other 34 countries had a gentle downward pattern.

Conclusion: Although most of the observed trends of stomach cancer were falling, only a few countries had experienced a favorable decreasing trend (three countries in male incidence and nineteen countries in female incidence). Therefore, taking effective actions to accelerate the observed falling trends seems necessary.