Polio eradication surveillance in Sri Lanka,2019-2023

Objective:To evaluate the polio laboratory surveillance carried out from January,2019 to May,2023 by the Polio Regional Reference Laboratory,Sri Lanka.Methods:This retrospective study analyzed all stool samples received under the acute flaccid paralysis(AFP)and immunodeficient vaccine-derived poliovirus(VDPV)surveillance at Polio Regional Reference Laboratory,Sri Lanka from January,2019 to May,2023.The results of the testing methodologies were extracted from the laboratory data system,i.e.,poliovirus virus isolation,intra-typic differentiation/VDPV real time reverse transcriptase polymerase chain reaction(ITD/VDPV rRTPCR)and sequencing,along with the data on timing of reporting results,stool adequacy and socio-demographics.Data was analyzed using descriptive statistics.Results:A total of 2141 stool samples from 1644 cases were received for AFP surveillance from Sri Lanka(93.61%),Maldives(1.52%),and immunodeficient VDPV(4.86%)surveillance.Both polioviruses(19/1644,1.15%)and non-polio enteroviruses(73/1644,4.44%)were isolated,while Sabin-like 3 virus was detected in majority(12/19,63.15%)among the poliovirus isolated.Wild polioviruses or circulating VDPVs were not detected among the cases.During all years of the study,the non-polio AFP detection rate was>1/100000 in children aged less than 15 years,whereas stool adequacy rate was>80%.All results were reported within 14 days of receipt,ensuring timely reporting as per global guidelines.Conclusions:The Polio Regional Reference Laboratory,Sri Lanka plays a vital role in maintaining the polio-free status in the country through its robust laboratory surveillance,while adhering to the surveillance indicators.Non-detection of wild polioviruses and circulating VDPV during the study period reinforces the polio-free status in the country.

Epidemiology of Mpox Outbreaks and Implications for Surveillance in Imo State, Nigeria

Mpox disease is caused by a double-stranded DNA virus, genus Orthopoxvirus of the family Poxviridae. The incubation period is usually 6 to 13 days but can range from 5 to 21 days while symptoms and signs may persist for 2 to 5 weeks. Although, the clinical features are usually less severe when compared to the deadly smallpox, the disease can be fatal with case fatality rate between 1% and 10%. In Imo State, Nigeria, there has been a changing epidemiology of the disease in the last 6 years and the frequency and geographic distribution of cases have progressively increased. This study aims to conduct a review of the disease epidemiology between 2017 and 2023 and implications for surveillance in Imo State. Surveillance data from the Surveillance Outbreak Response and Management System (SORMAS) was extracted between January 2017 and December 2023 across the 27 Local Government Areas (LGAs) of Imo State. A line list of 231 suspected cases was downloaded into an excel template and analyzed using SPSS® version 20 software. Analysis was done using descriptive statistics and associations were tested using Fischer’s exact at 0.05 level of significance. Of the 231 suspected cases, 57.1% (132) were males, 42.9% (99) were females and the modal age group was between the ages of 0 - 4 (32.5%). Eight (8) LGAs (districts) accounted for 71% (n = 164) of all the suspected cases. 21.2% (49) were confirmed positive, 27 males (55.1%) and 22 females (44.9%) (p > 0.05). Modal age group was 20 - 24 (22.4%, n = 11), 18% (9) were children under 14 years, p > 0.05. Case fatality rate was 8% (n = 4). There was no significant association between mortality and age group. Five (5) LGAs accounted for about 60% (29) of all confirmed cases. These LGAs contribute only 20% to the total population in the State. Only 5.6% and 4% of suspected and confirmed cases, respectively, had knowledge of contact with an infectious source. The study described the epidemiology of Mpox outbreaks between 2017 and 2023 and the findings have significant implications on detection and outbreak response activities.

PCR-HRM for Genomic Surveillance of SARS-CoV-2: A Variant Detection Tool in Côte d’Ivoire, West Africa

The rise of new viruses, like SARS-CoV-2 causing the COVID-19 outbreak, along with the return of antibiotic resistance in harmful bacteria, demands a swift and efficient reaction to safeguard the health and welfare of the global population. It is crucial to have effective measures for prevention, intervention, and monitoring in place to address these evolving and recurring risks, ensuring public health and international security. In countries with limited resources, utilizing recombinant mutation plasmid technology in conjunction with PCR-HRM could help differentiate the existence of novel variants. cDNA synthesis was carried out on 8 nasopharyngeal samples following viral RNA extraction. The P1 segment of the SARS-CoV-2 Spike S protein was amplified via conventional PCR. Subsequently, PCR products were ligated with the pGEM-T Easy vector to generate eight recombinant SARS-CoV-2 plasmids. Clones containing mutations were sequenced using Sanger sequencing and analyzed through PCR-HRM. The P1 segment of the S gene from SARS-CoV-2 was successfully amplified, resulting in 8 recombinant plasmids generated from the 231 bp fragment. PCR-HRM analysis of these recombinant plasmids differentiated three variations within the SARS-CoV-2 plasmid population, each displaying distinct melting temperatures. Sanger sequencing identified mutations A112C, G113T, A114G, G214T, and G216C on the P1 segment, validating the PCR-HRM findings of the variations. These mutations led to the detection of L452R or L452M and F486V protein mutations within the protein sequence of the Omicron variant of SARS-CoV-2. In summary, PCR-HRM is a vital and affordable tool for distinguishing SARS-CoV-2 variants utilizing recombinant plasmids as controls.

Summary Analysis of National Surveillance on Kashin-Beck Disease from 1990 to 2023

Objective To analyze the epidemiological characteristics and epidemic situation of children with Kashin-Beck disease(KBD)in China,and provide the basis for formulating prevention and control measures.Methods Fixed-point monitoring,moving-point monitoring,and full coverage of monitoring were promoted successively from 1990 to 2023.Some children(7-12 years old)underwent clinical and right-hand X-ray examinations every year.According to the KBD diagnosis criteria,clinical and X-ray assessments were used to confirm the diagnosis.Results In 1990,the national KBD detectable rate was 21.01%.X-ray detection decreased to below 10%in 2003 and below 5%in 2007.Between 2010 and 2018,the prevalence of KBD in children was less than 0.4%,which fluctuated at a low level,and has decreased to 0%since 2019.Spatial epidemiological analysis indicated a spatial clustering of adult patients prevalence rate in the KBD areas.Conclusion The evaluation results of the elimination of KBD in China over the last 5 years showed that all villages in the monitored areas have reached the elimination standard.While the adult KBD patients still need for policy consideration and care.

Imperative for long-term management and surveillance in Kawasaki disease

Kawasaki disease(KD)is a significant pediatric vasculitis known for its potential to cause severe coronary artery complications.Despite the effectiveness of initial treatments,such as intravenous immunoglobulin,KD patients can experience long-term cardiovascular issues,as evidenced by a recent case report of an adult who suffered a ST-segment elevation myocardial infarction due to previous KD in the World Journal of Clinical Cases.This editorial emphasizes the critical need for long-term management and regular surveillance to prevent such complications.By drawing on recent research and case studies,we advocate for a structured approach to follow-up care that includes routine cardiac evaluations and preventive measures.

Establishment of a surveillance program for anal cancer in Crohn's disease

This letter discusses the incidence of anal cancer among Crohn's disease(CD)-related malignancies.Patients with CD have been demonstrated to be at a higher risk of developing small bowel and colorectal cancers than healthy individuals.Although CD-associated anal cancer is relatively rare,patients with CD accom-panied by anal or perianal lesions are at increased risk of anal cancer.Addi-tionally,compared to ulcerative colitis,which is also an inflammatory disease,CD-related anal cancer is often detected at an advanced stage owing to the complexity of CD and is associated with a poor prognosis with frequent local recurrences.Therefore,the detection of early-stage cancer is crucial for improving the prognosis.However,the surveillance methods recommended for CD-related malignancies in the United States and Europe are similar to those for ulcerative colitis.They are not appropriate for detecting CD-related malignancies in the recto-anal region.Therefore,there is an urgent need for surveillance programs aimed at the early detection of malignant anorectal lesions in patients with CD.

How to use the Surveillance,Epidemiology,and End Results(SEER)data:research design and methodology

In the United States(US),the Surveillance,Epidemiology,and End Results(SEER)program is the only comprehensive source of population-based information that includes stage of cancer at the time of diagnosis and patient survival data.This program aims to provide a database about cancer incidence and survival for studies of surveillance and the development of analytical and methodological tools in the cancer field.Currently,the SEER program covers approximately half of the total cancer patients in the US.A growing number of clinical studies have applied the SEER database in various aspects.However,the intrinsic features of the SEER database,such as the huge data volume and complexity of data types,have hindered its application.In this review,we provided a systematic overview of the commonly used methodologies and study designs for retrospective epidemiological research in order to illustrate the application of the SEER database.Therefore,the goal of this review is to assist researchers in the selection of appropriate methods and study designs for enhancing the robustness and reliability of clinical studies by mining the SEER database.

Liver cell cancer surveillance practice in Nigeria:Pitfalls and future prospects

Hepatocellular carcinoma(HCC)is a disease of public health concern in Nigeria,with chronic hepatitis B and C infections contributing most to the disease burden.Despite the increasing incidence of HCC,surveillance practices for early diagnosis and possible cure are not deeply rooted in the country.This article aims to review the current status of HCC surveillance in Nigeria,stressing the encounters,breaches,and potential prospects.Several factors,such as limited tools for screening and diagnostics,insufficient infrastructure,and low cognizance among the doctors,and the general public affect the surveillance practices for HCC in Nigeria.Moreover,the lack of standardized guidelines and protocols for HCC surveillance further intensifies the suboptimal diagnosis and treatment.Nevertheless,there are opportunities for refining surveillance practices in the country.This would be achieved through boosted public health sensitization campaigns,integrating HCC screening into routine clinical services,and leveraging technological developments for early detection and monitoring.Furthermore,collaboration between government agencies,healthcare providers,and international organizations can facilitate the development of comprehensive HCC surveillance programs person-alized to the Nigerian setting.Thus,HCC surveillance practice faces substantial challenges.By addressing the drawbacks and leveraging prospects,Nigeria can improve HCC surveillance,with subsequent improved outcomes for individuals at risk of developing the disease.

The crucial role of surveillance in disease outbreak control:a comprehensive review

Surveillance systems are vital for detecting,managing,and mitigating infectious disease outbreaks.This review highlights the importance of modern technologies like AI and big data in enhancing surveillancecapabilities.It underscores the need for global collaboration and examines the role of surveillance in diseases likeinfluenza,Ebola,and COVID-19.Technological innovations such as geospatial mapping and wearable healthdevices are transforming disease control,though they raise ethical concerns about privacy.Continuousadvancements and ethical safeguards are crucial for effective surveillance and global health protection.

Surveillance strategies following curative resection and nonoperative approach of rectal cancer:How and how long?Review of current recommendations

Different follow-up strategies are available for patients with rectal cancer following curative treatment.A combination of biochemical testing and imaging investigation,associated with physical examination are commonly used.However,there is currently no consensus about the types of tests to perform,the timing of the testing,and even the need for follow-up at all has been questioned.The aim of this study was to review the evidence of the impact of different followup tests and programs in patients with non-metastatic disease after definitive treatment of the primary.A literature review was performed of studies published on MEDLINE,EMBASE,the Cochrane Library and Web of Science up to November 2022.Current published guidelines from the most authoritative specialty societies were also reviewed.According to the follow-up strategies available,the office visit is not efficient but represents the only way to maintain direct contact with the patient and is recommended by all authoritative specialty societies.In colorectal cancer surveillance,carcinoembryonic antigen represents the only established tumor marker.Abdominal and chest computed tomography scan is recommended considering that the liver and lungs are the most common sites of recurrence.Since local relapse in rectal cancer is higher than in colon cancer,endoscopic surveillance is mandatory.Different follow-up regimens have been published but randomized comparisons and meta-analyses do not allow to determine whether intensive or less intensive follow-up had any significant influence on survival and recurrence detection rate.The available data do not allow the drawing of final conclusions on the ideal surveillance methods and the frequency with which they should be applied.It is very useful and urgent for clinicians to identify a cost-effective strategy that allows early identification of recurrence with a special focus for highrisk patients and patients undergoing a“watch and wait”approach.

Treatment and surveillance for non-muscle-invasive bladder cancer:a clinical practice guideline(2021 edition)

Non-muscle invasive bladder cancer(NMIBC)is a major type of bladder cancer with a high incidence worldwide,resulting in a great disease burden.Treatment and surveillance are the most important part of NIMBC management.In 2018,we issued“Treatment and surveillance for non-muscle-invasive bladder cancer in China:an evidencebased clinical practice guideline”.Since then,various studies on the treatment and surveillance of NMIBC have been published.There is a need to incorporate these materials and also to take into account the relatively limited medical resources in primary medical institutions in China.Developing a version of guideline which takes these two issues into account to promote the management of NMIBC is therefore indicated.We formed a working group of clinical experts and methodologists.Through questionnaire investigation of clinicians including primary medical institutions,24 clinically concerned issues,involving transurethral resection of bladder tumor(TURBT),intravesical chemotherapy and intravesical immunotherapy of NMIBC,and follow-up and surveillance of the NMIBC patients,were determined for this guideline.Researches and recommendations on the management of NMIBC in databases,guideline development professional societies and monographs were referred to,and the European Association of Urology was used to assess the certainty of generated recommendations.Finally,we issued 29 statements,among which 22 were strong recommendations,and 7 were weak recommendations.These recommendations cover the topics of TURBT,postoperative chemotherapy after TURBT,Bacillus Calmette–Guérin(BCG)immunotherapy after TURBT,combination treatment of BCG and chemotherapy after TURBT,treatment of carcinoma in situ,radical cystectomy,treatment of NMIBC recurrence,and follow-up and surveillance.We hope these recommendations can help promote the treatment and surveillance of NMIBC in China,especially for the primary medical institutions.

Safety and effectiveness of lurasidone in the treatment of Chinese schizophrenia patients:An interim analysis of post-marketing surveillance

BACKGROUND Schizophrenia is a psychiatric disorder characterized by chronic or recurrent symptoms.Lurasidone was licensed in China in 2019 for the treatment of adult schizophrenia in adults with a maximum dose of 80 mg/d.However,post-market surveillance(PMS)with an adequate sample size is required for further validation of the drug’s safety profile and effectiveness.AIM To conduct PMS in real-world clinical settings and evaluate the safety and effectiveness of lurasidone in the Chinese population.METHODS A prospective,multicenter,open-label,12-wk surveillance was conducted in China's Mainland.All patients with schizophrenia from 10 sites who had begun medication with lurasidone between September 2019 and August 2022 were eligible for enrollment.Safety assessments included adverse events(AEs),adverse drug reactions(ADRs),extrapyramidal symptoms(EPS),akathisia,use of EPS drugs,weight gain,and laboratory values as metabolic parameters and the QTc interval.The effectiveness was assessed using the brief psychiatric rating scale(BPRS)from baseline to the end of treatment.RESULTS A total of 965 patients were enrolled in the full analysis set and 894 in the safety set in this interim analysis.The average daily dose was 61.7±19.08 mg(mean±SD)during the treatment.AEs and ADRs were experienced by 101 patients(11.3%)and 78 patients(8.7%),respectively,which were mostly mild.EPS occurred in 25 individuals with a 2.8%incidence,including akathisia in 20 individuals(2.2%).Moreover,59 patients received drugs for treating EPS during the treatment,with an incidence of 6.6%which dropped to 5.4%at the end of the treatment.The average weight change was 0.20±2.36 kg(P=0.01687)with 0.8%of patients showing a weight gain of≥7%at week 12 compared with that at the baseline.The mean values of metabolic parameters and the QTc interval at baseline and week 12 were within normal ranges.The mean changes in total BPRS scores were-8.9±9.76(n=959),-13.5±12.29(n=959),and-16.8±13.97(n=959)after 2/4,6/8,and 12 wk,respectively(P<0.001 for each visit compared with the baseline)using the last-observation-carried-forward method.CONCLUSION The interim analysis of the PMS of adult patients with schizophrenia demonstrate the safety and effectiveness of lurasidone in the Chinese population.No new safety or efficacy concerns were identified.

Intelligent Traffic Surveillance through Multi-Label Semantic Segmentation and Filter-Based Tracking

Road congestion,air pollution,and accident rates have all increased as a result of rising traffic density andworldwide population growth.Over the past ten years,the total number of automobiles has increased significantly over the world.In this paper,a novel method for intelligent traffic surveillance is presented.The proposed model is based on multilabel semantic segmentation using a random forest classifier which classifies the images into five classes.To improve the results,mean-shift clustering was applied to the segmented images.Afterward,the pixels given the label for the vehicle were extracted and blob detection was applied to mark each vehicle.For the validation of each detection,a vehicle verification method based on the structural similarity index is proposed.The tracking of vehicles across the image frames is done using the Identifier(ID)assignment technique and particle filter.Also,vehicle counting in each frame along with trajectory estimation was done for each object.Our proposed system demonstrated a remarkable vehicle detection rate of 0.83 over Vehicle Aerial Imaging from Drone(VAID),0.86 over AU-AIR,and 0.75 over the Unmanned Aerial Vehicle Benchmark Object Detection and Tracking(UAVDT)dataset during the experimental evaluation.The proposed system can be used for several purposes,such as vehicle identification in traffic,traffic density estimation at intersections,and traffic congestion sensing on a road.

ISHD:Intelligent Standing Human Detection of Video Surveillance for the Smart Examination Environment

In the environment of smart examination rooms, it is important to quickly and accurately detect abnormal behavior(human standing) for the construction of a smart campus. Based on deep learning, we propose an intelligentstanding human detection (ISHD) method based on an improved single shot multibox detector to detect thetarget of standing human posture in the scene frame of exam room video surveillance at a specific examinationstage. ISHD combines the MobileNet network in a single shot multibox detector network, improves the posturefeature extractor of a standing person, merges prior knowledge, and introduces transfer learning in the trainingstrategy, which greatly reduces the computation amount, improves the detection accuracy, and reduces the trainingdifficulty. The experiment proves that the model proposed in this paper has a better detection ability for the smalland medium-sized standing human body posture in video test scenes on the EMV-2 dataset.

Treatment trends of muscle invasive bladder cancer: Evidence from the Surveillance, Epidemiology, and End Results database, 1988 to 2013

Objective:Guidelines for muscle-invasive bladder cancer(MIBC)recommend that patients receive neoadjuvant chemotherapy with radical cystectomy as treatment over radical cystectomy alone.Though trends and practice patterns of MIBC have been defined using the National Cancer Database,data using the Surveillance,Epidemiology,and End Results(SEER)program have been poorly described.Methods:Using the SEER database,we collected data of MIBC according to the American Joint Commission on Cancer.We considered differences in patient demographics and tumor charac-teristics based on three treatment groups:chemotherapy(both adjuvant and neoadjuvant)with radical cystectomy,radical cystectomy,and chemoradiotherapy.Multinomial logistic regression was performed to compare likelihood ratios.Temporal trends were included for each treatment group.Kaplan-Meier curves were performed to compare cause-specific sur-vival.A Cox proportional-hazards model was utilized to describe predictors of survival.Results:Of 16728 patients,10468 patients received radical cystectomy alone,3236 received chemotherapy with radical cystectomy,and 3024 received chemoradiotherapy.Patients who received chemoradiotherapy over radical cystectomy were older and more likely to be African American;stage III patients tended to be divorced.Patients who received chemotherapy with radical cystectomy tended to be males;stage II patients were less likely to be Asian than Caucasian.Stage III patients were less likely to receive chemoradiotherapy as a treatment op-tion than stage II.Chemotherapy with radical cystectomy and chemoradiotherapy are both un-derutilized treatment options,though increasingly utilized.Kaplan-Meier survival curves showed significant differences between stage II and III tumors at each interval.A Cox proportional-hazards model showed differences in gender,tumor stage,treatment modality,age,andmarital status.Conclusion:Radical cystectomy alone is still the most commonly used treatment for muscle-invasive bladder cancer based on temporal trends.Significant disparities exist in those who receive radical cystectomy over chemoradiotherapy for treatment.

Surveillance of emerging SARS-CoV-2 variants by nanopore technology-based genome sequencing

Objective:To surveill emerging variants by nanopore technology-based genome sequencing in different COVID-19 waves in Sri Lanka and to examine the association with the sample characteristics,and vaccination status.Methods:The study analyzed 207 RNA positive swab samples received to sequence laboratory during different waves.The N gene cut-off threshold of less than 30 was considered as the major inclusion criteria.Viral RNA was extracted,and elutes were subjected to nanopore sequencing.All the sequencing data were uploaded in the publicly accessible database,GISAID.Results:The Omicron,Delta and Alpha variants accounted for 58%,22%and 4%of the variants throughout the period.Less than 1%were Kappa variant and 16%of the study samples remained unassigned.Omicron variant was circulated among all age groups and in all the provinces.Ct value and variants assigned percentage was 100%in Ct values of 10-15 while only 45%assigned Ct value over 25.Conclusions:The present study examined the emergence,prevalence,and distribution of SARS-CoV-2 variants locally and has shown that nanopore technology-based genome sequencing enables whole genome sequencing in a low resource setting country.

The Contribution of the Xpert® MTB/RIF Assay to the Surveillance of Drug-Resistant Tuberculosis in the Central African Republic

Introduction: The Central African Republic is one of the 30 high Tuberculosis burden countries in the world, with an incidence of 540 cases per 100,000 population and a mortality of 91 deaths per 100,000 population. Since 2020, following WHO recommendations, the National Reference Laboratory for Tuberculosis has been using the Xpert® MTB/RIF assay as a first-line diagnostic test for the early detection of Drug Resistance Tuberculosis. The goal of this study was to evaluate the contribution of the Xpert® MTB/RIF assay to the surveillance of rifampicin resistance in new and previously treated tuberculosis cases. Materials and Methods: The data relative to the Xpert® MTB/RIF assay carried out on various categories of tuberculosis patients registered at the National Reference Laboratory for Tuberculosis in 2020 were analyzed retrospectively. The categories of tuberculosis patients were new cases, failed treatment cases, relapse cases, lost-to-follow-up cases and multidrug-resistant tuberculosis contact cases. Results: A total of 1404 tuberculosis patients were registered at the NRL-TB in 2020;the mean age was 39.2 years (2 - 90 years) and the male-to-female sex ratio was 1.16:1. Overall, 32.7% (454/1404) proved infected with tuberculosis, of which 22.5% (102/454) cases showed resistance to rifampicin. The primary resistance rate was 9.1% (27/298) and the secondary resistance rate was 46.6% (75/161). Treatment failures and relapsed cases were significantly associated with rifampicin resistance (p 0.005). Conclusion: Large-scale use of Xpert® MTB/RIF, especially in the provinces of the Central African Republic, will help the Ministry of Health to better control Drug Resistance Tuberculosis in the country.

An Efficient Attention-Based Strategy for Anomaly Detection in Surveillance Video

In the present technological world,surveillance cameras generate an immense amount of video data from various sources,making its scrutiny tough for computer vision specialists.It is difficult to search for anomalous events manually in thesemassive video records since they happen infrequently and with a low probability in real-world monitoring systems.Therefore,intelligent surveillance is a requirement of the modern day,as it enables the automatic identification of normal and aberrant behavior using artificial intelligence and computer vision technologies.In this article,we introduce an efficient Attention-based deep-learning approach for anomaly detection in surveillance video(ADSV).At the input of the ADSV,a shots boundary detection technique is used to segment prominent frames.Next,The Lightweight ConvolutionNeuralNetwork(LWCNN)model receives the segmented frames to extract spatial and temporal information from the intermediate layer.Following that,spatial and temporal features are learned using Long Short-Term Memory(LSTM)cells and Attention Network from a series of frames for each anomalous activity in a sample.To detect motion and action,the LWCNN received chronologically sorted frames.Finally,the anomaly activity in the video is identified using the proposed trained ADSV model.Extensive experiments are conducted on complex and challenging benchmark datasets.In addition,the experimental results have been compared to state-ofthe-artmethodologies,and a significant improvement is attained,demonstrating the efficiency of our ADSV method.

Knowledge,perceptions,and practice towards adverse events following immunization surveillance among vaccination workers in Zhejiang province,China

Objective:To access the level of knowledge,perceptions,and practice towards adverse events following immunization(AEFI)surveillance among vaccination workers in Zhejiang province,China.Methods:This was a cross-sectional survey involving 768 vaccination workers.Data were collected using self-administered questionnaires and analyzed by using SAS 9.3 software.Knowledge,perceptions,and practice on AEFI surveillance were summarized using frequency tables.The mean±SD value was used as the cut-off for defining good(values≥mean)and poor(values<mean)knowledge,perceptions or practice.Binary logistic regression analysis was used to determine sociodemographic variables associated with knowledge,perceptions,and practice towards AEFI.Results:The proportions of good knowledge,perceptions and practice on AEFI surveillance were 78.13%,57.81%and 66.15%,respectively.Having a higher education background,longer years of experience,previous training on AEFI and≥30 years of age were factors associated with good knowledge,perceptions and practice on AEFI surveillance among vaccination workers.Conclusions:Over half of the respondents had good knowledge,perceptions and practice on AEFI surveillance work.Interventions on improving the vaccination workers’knowledge,perceptions and practice on AEFI surveillance should be considered in order to develop a more effective surveillance system.

Quantum Computing Based Neural Networks for Anomaly Classification in Real-Time Surveillance Videos

For intelligent surveillance videos,anomaly detection is extremely important.Deep learning algorithms have been popular for evaluating realtime surveillance recordings,like traffic accidents,and criminal or unlawful incidents such as suicide attempts.Nevertheless,Deep learning methods for classification,like convolutional neural networks,necessitate a lot of computing power.Quantum computing is a branch of technology that solves abnormal and complex problems using quantum mechanics.As a result,the focus of this research is on developing a hybrid quantum computing model which is based on deep learning.This research develops a Quantum Computing-based Convolutional Neural Network(QC-CNN)to extract features and classify anomalies from surveillance footage.A Quantum-based Circuit,such as the real amplitude circuit,is utilized to improve the performance of the model.As far as my research,this is the first work to employ quantum deep learning techniques to classify anomalous events in video surveillance applications.There are 13 anomalies classified from the UCF-crime dataset.Based on experimental results,the proposed model is capable of efficiently classifying data concerning confusion matrix,Receiver Operating Characteristic(ROC),accuracy,Area Under Curve(AUC),precision,recall as well as F1-score.The proposed QC-CNN has attained the best accuracy of 95.65 percent which is 5.37%greater when compared to other existing models.To measure the efficiency of the proposed work,QC-CNN is also evaluated with classical and quantum models.