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Objectives: To review the evidence that migrants from tuberculosis (TB) high-incidence countries migrating to TB low-incidence countries significantly contribute to active TB cases in the counties of destination, primarily through reactivation of latent TB. Methods: This is a narrative review. The different screening programs in the countries of destination are reviewed either based on screening and preventive treatment of latent TB pre or more commonly – post arrival. Results: Screening can be performed using interferon-gamma release assays (IGRA) or tuberculin skin tests (TST). Preventive treatment of latent TB is using either monotherapy with isoniazid, or in combination with rifampicin or rifapentine. We discuss the ethical issues of preventive treatment in asymptomatic individuals and how these are addressed in different screening programs. Conclusion: Screening migrants from TB high endemic countries to TB low endemic countries is beneficial. There is a lack of standardization and agreement on screening protocols, follow up and treatment.

Study region: Northern Metropolitan France. Study focus: Assessing long-term changes in groundwater is crucial for understanding the impacts of climate change on aquifers and for managing water resources.However, long-term groundwater level (GWL) records are often scarce, limiting the understanding of historical trends and variability. In this paper, we present a deep learning approach to reconstruct GWLs up to several decades back in time using recurrent-based neural networks with wavelet pre-processing and climate reanalysis data as inputs. GWLs are reconstructed using two different reanalysis datasets with distinct spatial resolutions (ERA5: 0.25° x 0.25° & ERA20C: 1° x 1°) and monthly time resolution, and the performance of the simulations were evaluated. New insights: Long term GWL timeseries are now available for northern France, corresponding to extended versions of observational timeseries back to early 20th century. All three types of piezometric behaviours could be reconstructed reliably and consistently capture the multi-decadal variability even at coarser resolutions, which is crucial for understanding long-term hydroclimatic trends and cycles. GWLs'multidecadal variability was consistent with the Atlantic multidecadal oscillation. From a synthetic experiment involving a modified long-term observational time series, we highlighted the need for longer training datasets for some low-frequency signals. Nevertheless, our study demonstrated the potential of using DL models together with reanalysis data to extend GWL observations and improve our understanding of groundwater variability and climate interactions.

Abstract Background HCV infection in hemodialysis units is a significant cause of morbidity and mortality. The risk of HCV infection among dialysis patients is higher compared to the general population due to high potential blood exposures in hemodialysis settings. This study aims to assess the national HCV seroprevalence in selected dialysis units and to determine the risk factors for acquiring HCV infection. Methods This cross-sectional study was conducted from 1 January to 31 March 2021. A total of 734 patients from 11 hemodialysis centers in Oman were included. Samples were tested simultaneously for HCV antibodies and HCV RNA. HCV genotyping was determined in all viremic patients. Demographic and hemodialysis center related data were gathered and their association with the positive HCV serology were explored using univariate and multivariate logistic regression analysis. Results Out of 800 patients selected from 11 dialysis units for the study, 734 patients (91.8%) were included. The overall seroprevalence of HCV infection among hemodialysis patients was 5.6%. (41/734). HCV RNA was detected in 31.7% (13/41) of seropositive hemodialysis patients. The most common genotype was subtype 1a, followed by subtype 3. Variables associated with high HCV prevalence were family history of HCV and duration of dialysis. Conclusion The prevalence of infection within hemodialysis patients in Oman has significantly decreased but remained higher than the general population. Continuous monitoring and follow-up, including periodic serosurvey and linkage to care and treatment are recommended. Additionally, practice audits are recommended for identifying gaps and ensuring sustainability of best practices and further improvement.

Hypervirulent Klebsiella pneumoniae (hvKp) is a variant that has been increasingly linked to severe, life-threatening infections including pyogenic liver abscess and bloodstream infections. HvKps belonging to the capsular serotypes K1 and K2 have been reported worldwide, however, very scarce studies are available on their genomics and virulence. In the current study, we report four hypermucoviscous extended-spectrum β-lactamase-producing hvKp clinical strains of capsular serotype K1 and K2 isolated from pus and urine of critically ill patients in tertiary care hospitals in Oman. These strains belong to diverse sequence types (STs), namely ST-23(K1), ST-231(K2), ST-881(K2), and ST-14(K2). To study their virulence, a Galleria mellonella model and resistance to human serum killing were used. The G. mellonella model revealed that the K1/ST-23 isolate was the most virulent, as 50% of the larvae died in the first day, followed by isolate K2/ST-231 and K2/ST-14, for which 75% and 50% of the larvae died in the second day, respectively. Resistance to human serum killing showed there was complete inhibition of bacterial growth of all four isolates by the end of the first hour and up to the third hour. Whole genome sequencing (WGS) revealed that hvKp strains display a unique genetic arrangement of k-loci. Whole-genome single-nucleotide polymorphism-based phylogenetic analysis revealed that these hvKp isolates were phylogenetically distinct, belonging to diverse clades, and belonged to different STs in comparison to global isolates. For ST-23(K1), ST-231(K2), ST-881(K2), and ST-14(K2), there was a gradual decrease in the number of colonies up to the second to third hour, which indicates neutralization of bacterial cells by the serum components. However, this was followed by a sudden increase of bacterial growth, indicating possible resistance of bacteria against human serum bactericidal activity. This is the first report from Oman detailing the WGS of hvKp clinical isolates and assessing their resistance and virulence genomics, which reinforce our understanding of their epidemiology and dissemination in clinical settings.

ABSTRACT Tuberculosis (TB) originating from expatriates that hail from high TB-burden countries is hypothesized to play a role in continued TB transmission in Oman. Here, we used whole-genome sequencing (WGS) to assess national TB transmission dynamics. The annual incidence per 100,000 population per year was calculated for nationals and expatriates. A convenience sample of Mycobacterium tuberculosis (MTB) isolates from 2018 to 2019 was sequenced and analyzed with publicly available TB sequences from Bangladesh, Tanzania, the Philippines, India, and Pakistan. Relatedness was assessed by generating core-genome single nucleotide polymorphism (SNP) distances. The incidence of TB was five cases per 100,000 persons in 2018 and seven cases per 100,000 persons in 2020 (R2 = 0.34, P = 0.60). Incidence among nationals was 3.9 per 100,000 persons in 2018 and 3.5 per 100,000 persons in 2020 (R2 = 0.20, P = 0.70), and incidence among expatriates was 7.2 per 100,000 persons in 2018 and 12.7 per 100,000 persons in 2020 (R2 = 0.74, P = 0.34). Sixty-eight local MTB isolates were sequenced and analyzed with 393 global isolates. Isolates belonged to nine distinct spoligotypes. Two isolates, originating from an expatriate and an Omani national, were grouped into a WGS-based cluster (SNP distance < 12), which was corroborated by an epidemiological investigation. Relatedness of local and global isolates (SNP distance < 100) was also seen. The relatedness between MTB strains in Oman and those in expatriate countries of origin can aid inform TB control policy. Our results provide evidence that WGS can complement epidemiological analysis to achieve the End TB strategy goal in Oman. IMPORTANCE Tuberculosis (TB) incidence in Oman remains above national program control targets. TB transmission originating from expatriates from high TB-burden countries has been hypothesized to play a role. We used whole-genome sequencing (WGS) to assess TB transmission dynamics between expatriates and Omani nationals to inform TB control efforts. Available Mycobacterium tuberculosis isolates from 2018 to 2019 underwent WGS and analysis with publicly available TB sequences from Bangladesh, the Philippines, India, and Pakistan to assess for genetic relatedness. Our analysis revealed evidence of previously unrecognized transmission between an expatriate and an Omani national, which was corroborated by epidemiological investigation. Analysis of local and global isolates revealed evidence of distant relatedness between local and global isolates. Our results provide evidence that WGS can complement classic public health surveillance to inform targeted interventions to achieve the End TB strategy goal in Oman.

Streptococcus agalactiae is known to cause invasive infections in risk groups such as pregnant women, newborns, and immunosuppressed patients but it is uncommon in older children. We describe a case of recurrent infective endocarditis due to S. agalactiae in an 11-year-old boy with Loeys-Dietz syndrome who was successfully treated with long-term antimicrobial therapy for one year.

Background and objective: The presence of carbapenemase enzymes among Enterobacterales is the main mechanism to reduce susceptibility to a wide range of antibiotics. Carbapenemase enzymes such as the Klebsiella pneumoniae carbapenemase (KPC) hydrolyse beta-lactam antibiotics group, which includes carbapenem, leads to fewer treatment options. We aim to describe the first report of carbapenem-resistant K. pneumoniae (CRKP) sequence type (ST) 11 harbouring KPC in Oman. Material and methods: Five confirmed CRKP isolates were isolated from clinical samples during the period of January 2019 till December 2019. Strains were genotyped by pulse field gel electrophoresis (PFGE) for genetic relatedness. Whole genome sequencing (WGS) was performed to observe relationships with global strains using multilocus sequence typing (MLST). Antimicrobial genes, capsular loci-K-types, plasmids types and virulence genes were also identified using whole genome sequence data. Results: All five CRKP were determined to have blaKPC-2 with or without blaOX-A48 and blaNDM-2. The molecular genotyping by PFGE showed 100% similarity among the five isolates. The MLST allelic profile analysis clonally clustered our strains with SL-258, CG-11 and ST11 mainly reported from South Asia. Further molecular characterization of the capsular K-locus and O-locus genes, revealed the strains to belong to KL-47 type and OL101 type respectively. The core genome typing suggests that our strains were clonally related to Chinese strains with less than five chromosomal nucleotides differences. Conclusion: Epidemiological and molecular analyses confirmed that these KPC-producing K. pneumoniae strains are from a single clone that caused multiple nosocomial infections in one health institution. This finding highlights the importance to sustain the surveillance and infection prevention efforts and to step up active screening to prevent the spread of nosocomial infection.

Background: A surge in COVID-19-associated mucormycosis cases has been observed during the second wave of COVID-19 in summer of 2021. Most cases were reported from India. The Delta variant (B.1.617.2) was the most common variant circulating at that time. Mucormycosis is an opportunistic angioinvasive fungal infection with high morbidity and mortality. Methods: We present 10 cases of COVID-19-associated rhino-orbital and rhino-orbital-cerebral mucormycosis managed in a secondary hospital in Oman. Results: The median time for developing mucormycosis was two weeks after COVID-19 diagnosis. All patients were newly diagnosed or already known to have poorly controlled diabetes mellitus. Five patients received corticosteroid therapy for COVID-19. Three patients had severe COVID-19 and died of severe acute respiratory distress syndrome and septic shock. Another three patients died of advanced mucormycosis and cerebral involvement. Despite aggressive medical and surgical intervention, the mortality rate was 60% (6/10). Conclusion: Mucormycosis is an aggressive opportunistic infection with high morbidity and mortality that requires prompt recognition and urgent intervention.Uncontrolled blood sugar, the use of corticosteroids, and immune dysfunction due to COVID-19 are all important risk factors for development of mucormycosis. Worse outcomes are associated with poor glycemic control despite aggressive medical and surgical interventions.

ABSTRACT: Objectives: Mycobacterium tuberculosis (MTB) is a global public health issue. Although Oman reduced the burden of tuberculosis (TB) by 85% in under 25 years, the annual incidence rate remains stagnant. Whole genome sequencing (WGS) is used to investigate the transmission dynamics of MTB complex. This study aimed to resolve traditional genotype clusters and exploring the geospatial distribution to understand the epidemiology of TB in Oman. Methods: Confirmed cases with spoligotyping clusters were randomly selected. WGS of 70 isolates were selected for final analysis. Correlation of epidemiological and geospatial data was conducted. Results: A total of 233 cases were registered in 2021; 169 had confirmed growth, with an incidence rate of 5.2/100,000 population for 2021. A total of 70 genomes were analyzed, and five large clusters and three medium clusters were identified. The lineages L1, L2, L3, and L4 and several sublineages belonging to the Indo-Oceanic family and East African Indian family were identified as predominant in Oman. There were no multidrug-resistant cases identified. Conclusion: There is a considerable genetic variation among the strains in Oman. This predominance could be linked with the high percentage of non-national population, which represents different countries and frequent traveling to high TB burden countries. WGS combined with geospatial investigations of MTB are required to better understand the disease transmission in Oman, which will support TB elimination efforts.

The dynamic movement of electronic government (e-government) needs a clear pathway on the adoption level of stakeholders within the public sector organization. This research has identified gaps in the movement of the adoption. The respondents comprised 237 public sector managers at the ministry level who conduct e-government services in the Sultanate of Oman. A questionnaire was designed to tap into the manager's perception of the Internet's Perceived Usefulness, Perceived Credibility of technology, Intention to use the technology, and adoption of the Internet itself. Seven hypothesized relationships were tested in the structural model. An advanced quantitative data analysis using multivariate data analysis was employed. The data were analyzed using structural equation modeling (SEM) to test the causal and mediating effects of latent variables. Based on the research, the hypothesized model fit fails to be supported (p

Leclercia adecarboxylata is a recently acknowledged emerging pathogen. It is a member of the Enterobacterals family, formerly thought to be a member of the genus Escherichia. Isolation was reported from various animal and environmental specimens. However, it rarely causes infection in humans, and the true frequency is unknown or underestimated. Leclercia adecarboxylata showed an ascending resistance grade from pan-sensitive to Carbapenem-resistant due to its ability to produce and harbour hydrolysing enzymes that challenge daily clinical practices. In our report, the isolate was misidentified as Citrobacter koseri by Analytical Profile Index for Enterobacterals (API E), and as Pantoea species by Vitek 2 but confirmed by matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) and 16S ribosomal RNA analysis as Leclercia adecarboxylata. Conventional PCR revealed the presence of two populations of resistance genes, VIM-1 and OXA-48. Herein, a report of the first clinical emergence of Leclercia adecarboxylata producing VIM-1 in a rectal swab of a 63-year-old non-immunocompromised female with acute intracerebral haemorrhage.

Background: In Oman, many extended families tend to live in one household. Some families can include 20–30 individuals with the majority of them being children. This study investigates the role of children in spreading SARS-CoV-2 causing COVID-19 within family clusters in Oman. Methods: This retrospective study includes data of 1026 SARS-CoV-2 positive children (≤18 years) collected from the national surveillance database for COVID-19 between 1 February 2020 and 30 May 2020. Results: We included 1026 patients. Most, 842 were Omani (82%), 52% male, and 28.5% asymptomatic. Close to the half of symptomatic 419 (40%), patients presented with fever associated with other respiratory symptoms. Fifty pediatric patients were index cases who transmitted the virus to 107 patients in total (86 adults and 21 children) with a mode of 1. There is no statistical significance of all studied risk factors in the transmission of the SARS-CoV-2 virus including age, gender, and cycle threshold (CT) value. Conclusions: According to this study, children are not to be considered a significant driver of transmission of SARS-CoV-2 in Oman.

ABSTRACT: Objective: To assess the seroprevalence of severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) in Oman and longitudinal changes in antibody levels over time within the first 11 months of the coronavirus disease 2019 (COVID-19) pandemic. Methods: This nationwide cross-sectional study was conducted as a four-cycle serosurvey using a multi-stage stratified sampling method from July to November 2020. A questionnaire was used and included demographics, history of acute respiratory infection and list of symptoms, COVID-19 contact, previous diagnosis or admission, travel history and risk factors. Results: In total, 17,457 participants were surveyed. Thirty percent were female and 66.3% were Omani. There was a significant increase in seroprevalence throughout the study cycles, from 5.5% (4.8–6.2%) in Cycle 1 to 22% (19.6–24.6%) in Cycle 4. There was no difference in seroprevalence between genders, but significant differences were found between age groups. There was a transition of seroprevalence from being higher in non-Omanis than Omanis in Cycle 1 [9.1% (7.6–10.9%) vs 3.2% (2.6–3.9%)] to being higher in Omanis than non-Omanis in Cycle 4 [24.3% (21.0–27.9%) vs 16.8% (14.9–18.9%)]. There was remarkable variation in the seroprevalence of SARS-CoV-2 according to governorate. Close contacts of people with COVID-19 had a 96% higher risk of having the disease [adjusted odds ratio (AOR) 1.96, 95% confidence intervals (CI) 1.64–2.34]. Labourers had 58% higher risk of infection compared with office workers (AOR 1.58, 95% CI 1.04–2.35). Conclusion: This study showed a wide variation in the spread of SARS-CoV-2 across governorates in Oman, with higher estimated seroprevalence in migrants in the first two cycles. Prevalence estimates remain low and are insufficient to provide herd immunity.

Water quality monitoring is essential for managing water resources and ensuring human and environmental health. However, obtaining reliable data can be challenging and costly, especially in complex systems such as estuaries. To address this problem, we propose a novel deep learning-based approach that uses limited available data to accurately estimate and reconstruct critical water quality variables, such as electrical conductivity, dissolved oxygen, and turbidity. Our approach included two tasks, numerical modeling and historical reconstruction, and was applied to the Seine River in the Normandy region of France at four quality stations. In the first task, we evaluated four deep learning approaches (GRU, BiLSTM, BiLSTM-Attention, and CNN-BiLSTM-Attention) to numerically simulate each variable for each station under different input data selection scenarios. We found that incorporating the quality data with the water level data collected at the various stations into the input data improved the accuracy of the water quality data simulation. Combining water levels from multiple stations reliably reproduced electrical conductivity, especially at stations near the sea where tidal fluctuations control saltwater intrusion in the area. While each model had its strengths, the CNN-BiLSTM-Attention model performed best in complex tasks with dissimilar input trends, and the GRU model outperformed other models in simple monitoring tasks with similar input-target trends. The second task involved automatically searching the optimal configurations for completing the missing historical data in sequential order using the modeling task results. The electrical conductivity data were filled before the dissolved oxygen data, which were in turn more reliable than the turbidity simulation. The deep learning models accurately reconstructed 15 years of water quality data using only six and a half years of modeling data. Overall, this research demonstrates the potential of deep learning approaches with their limitations and discusses the best configurations to improve water quality monitoring and reconstruction.

Objective: To determine the seroprevalence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in healthcare workers (HCWs) based on risk of exposure to COVID-19 patients. Method: This was a SARS-CoV-2 seroprevalence cross-sectional study in risk-stratified HCWs randomly selected from three main district hospitals in Oman. Results: 1078 HCWs were included, with an overall SARS-CoV-2 seroprevalence of 21%. The seropositivity rates in low-, variable-, and high-risk groups were 29%, 18%, and 17%, respectively (p-value < 0.001). The study found higher positivity in males (crude odds ratio [COR] 1.71, 95% confidence interval [CI] 1.28–2.3), and workers residing in high-prevalence areas (COR 2.09, 95% CI 1.42–3.07). Compared with doctors, workers from supporting services, administration staff, and nurses were more likely to test positive for SARS-CoV-2 antibodies (COR 9.81, 95% CI 5.26–18.27; 2.37, 95% CI 1.23–4.58; 2.08 95% CI 1.14–3.81). The overall rate of previously undetected infection was 12%, with higher values in low-risk HCWs. High district prevalence was a driving factor for seropositivity in the low-risk group (adjusted odds ratio [AOR] 2.36, 95% CI 1.0–5.59). Conclusion: Low-risk supporting services workers can drive SARS-CoV-2 transmission in hospitals. More attention and innovation within this area will enhance the safety of health care during epidemics/pandemics.

Background The Sultanate of Oman is country a low TB-incidence, with less than seven cases per 105 population detected in 2020. Recent years have witnessed a persistence in TB cases, with sustained incidence rate among expatriates and limited reduction among Omanis. This pattern suggests transmission from the migrant population. The present study examined the genetic profile and drug resistance-conferring mutations in Mycobacterium tuberculosis collected from Omanis and expatriates to recognise possible causes of disease transmission. Methods We examined M. tuberculosis cultured positive samples, collected from Omanis (n = 1,344) and expatriates (n = 1,203) between 2009 and 2018. These isolates had a known in vitro susceptibility profile to first line anti-TB, Streptomycin (SM), Isoniazid (INH), Rifampicin (RIF), Ethambutol (EMB) and Pyrazinamide (PZA). The diversity of the isolates was assessed by spacer oligo-typing (spoligotyping). Drug resistance-conferring mutations resulted from full-length sequence of nine genes (katG, inhA, ahpc, rpoB, rpsL, rrs, embB, embC, pncA) and their phenotypic relationship were analysed. Results In total, 341/2192 (13.4%), M. tuberculosis strains showed resistance to any drug, comprising mono-resistance (MR) (242, 71%), poly-resistance (PR) (40, 11.7%) and multi-drug resistance (MDR) (59, 17.3%). The overall rate of resistance among Omanis and expatriates was similar; however, MDR and PZAR were significantly higher among Omanis, while INHR was greater among expatriates. Mutations rpsL K43R and rpoB S450L were linked to Streptomycin (SMR) and Rifampicin resistance (RIFR) respectively. Whereas, katG S315T and inhA –C15T/G–17T were associated with Isoniazid resistance (INHR). The resistance patterns (mono-resistant, poly-resistant and MDR) and drug resistance-conferring mutations were found in different spoligo-lineages. rpsL K43R, katG S315T and rpoB S450L mutations were significantly higher in Beijing strains. Conclusions Diverse drug resistant M. tuberculosis strains exist in Oman, with drug resistance-conferring mutations widespread in multiple spoligo-lineages, indicative of a large resistance reservoir. Beijing’s M. tuberculosis lineage was associated with MDR, and multiple drug resistance-conferring mutations, favouring the hypothesis of migration as a possible source of resistant lineages in Oman.

Background: Severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) has been proven to be lethal to human health, which affects almost every corner of the world. The objectives of this study were to add context to the global data and international genomic consortiums, and to give insight into the efficiency of the contact tracing system in Oman. Methods: We combined epidemiological data and whole-genome sequence data from 94 samples of SARS-CoV-2 in Oman to understand the origins, genetic variation, and transmissibility. The whole-genome size of sequence data was obtained through a customized SARS-COV-2 research panel. Amplifier methods ranged from 26 Kbp to 30 Kbp and were submitted to GISAID. Findings: The study found that P323L (94.7%) is the most common mutation, followed by D614G (92.6%) Spike protein mutation. A unique mutation, I280V, was first reported in Oman and was associated with a rare lineage, B.1.113 (10.6%). In addition, the study revealed a good agreement between genetic and epidemiological data. Interpretation: Oman’s robust surveillance system was very efficient in guiding the outbreak investigation processes in the country, the study illustrates the future importance of molecular epidemiology in leading the national response to outbreaks and pandemics.

Background: Mortality surveillance provides a crucial method for monitoring disease activity. Coronavirus disease 2019 (COVID-19) can cause excess mortality both directly and indirectly by increasing deaths from other diseases. The aim of this study was to investigate the effects of COVID-19 on mortality in Oman. Methods: A cross-sectional retrospective analysis of mortality data from 1 January 2015 to 16 August 2020 was undertaken. Baseline mortality estimated using the Farrington flexible model and excess mortality were calculated for the pandemic period (16 March–16 August 2020) according to cause of death, place of death and age group. Results: During the pandemic period, there was a 15% [95% confidence interval (CI) 14–17] increase in all-cause mortality from baseline. When classifying by cause, there was a 9% (95% CI 5–12) increase in deaths due to respiratory diseases, a 2% (95% CI 1–4) increase in deaths due to infectious diseases and a 9% (95% CI 8–11) increase in unclassified deaths. In terms of place of death, 12% (95% CI 11–14) of excess mortality occurred in hospitals and 7% (95% CI 5–8) occurred in homes during the pandemic period. Patients aged >60 years recorded a 15% (95% CI 13–16) increase in all-cause mortality during this period. Conclusion: The COVID-19 pandemic has resulted in a 15% increase in all-cause mortality in Oman, mainly as a result of deaths from COVID-19. However, unclassified deaths, deaths due to respiratory diseases and deaths due to infectious diseases have also increased, enforcing the need for a holistic approach and appropriate coordination of health services during such health crises.