Central Warehouse Research Articles

Survival 1.0: A Novel Autonomous Industrial Mobile Warehouse (AIMW) for Industrial Environments

This article presents the design, implementation and start-up of the first AIMW (Autonomous Industrial Mobile Warehouse) in the industry, in particular, in the factory located at Ford España S.L. in Almussafes (Valencia). This first version has been given the name of “Survival”, due to its ability to survive the industrial environment commonly known as “the jungle”. The motivation for the design of the first AIMW was due to the management of spare warehouses for maintenance tasks. In all factories there is a central warehouse where replacement materials with a higher probability of use are placed near the warehouse exit, thus reducing the time to obtain the replacement. However, in large factories, such as automobile manufacturing, the distance between the central warehouse and the place where the breakdown occurs may cause very long delays. For this reason, there are smaller warehouses distributed throughout the plant that replicate the part of the central warehouse where the most used materials are kept. The objective of our research is to make that part of the central warehouse mobile with the AIMW design, thus eliminating the fixed warehouses. In the factory at Ford España S.L. in Almussafes there are 170 of these warehouses distributed in a homogeneous way. In this first proposal of an AIMW, and with the primary objective of reducing costs, Survival 1.0 has been designed based on a commercial AMR. For its choice, commercial AMRs were tested in real situations within the Ford factory (Almussafes). As a result, none of them were able to pass all the tests. In addition, the current regulations for AMRs, the ANSI/ITSDF B56.5:2019 and the EN 1525:1997 standard, only define minimum test standards to describe how manufacturers and users must carry out the safety measurements of AGVs and AMRs. However, from an industry point of view, these regulations are not adequate. Therefore, there are extensions of these regulations generated by the companies themselves that imply additional developments of commercial AMRs. This paper shows the developments made to be able to integrate the first AIMW into the production line, but it also shows the gap between research and standardization of AMRs with respect to the demands and needs of the industry. There are currently three Survival 1.0 AIMWs in operation in the factory at Ford España S.L. in Almussafes.

Utilization of IoT and database system of central warehouse project in the pharmaceutical industry

This study aims to develop an MRPII device that utilizes internet technology for inventory management control processes, using case studies from pharmacutical companies in Indonesia. The research was conducted using field observation methods and system development, then comparing the manual system and MRPII. An internet-based inventory management system was created by integrating the warehouse’s material database into each material code via a QR. code. The study found that implementing the MRP II system design increases work effectiveness and reduces the risk of errors that frequently occur in conventional systems. Moreover, using the MRPII can facilitate the audit process and establish transparency in the inventory management process. Data processed using IoT is generated faster and more accurately as company operations improve quality, reduce unnecessary activities, and make it easier to organize materials and run administrative and technical processes in inventory management; it is measured based on reach, workforce requirements, supply, and handling time. In the industrial world, the MRPII database system has the potential to evolve into several more complex and comprehensive systems. It has broad integration and can assist humans working across all lines, particularly in the data processing system.

Vehicle routing problem for omnichannel retailing including multiple types of time windows and products

This paper addresses the capacitated vehicle routing problem for omnichannel retailing with multiple types of time windows (hard time windows and soft time windows) and multiple types of products simultaneously. The problem aims to transfer multiple products from a central warehouse to stores and satellites, where split delivery is allowed since the demands of stores or satellites are large and the different product types have different volumes. Based on different characteristics of purchasing channels, the time window of a store is a hard constraint while the time window of a satellite is a soft one. This type of vehicle routing problem exists extensively in omnichannel retail distribution systems in the logistics industry of China, which considers multiple purchasing channels for customers. Since this type of vehicle routing problem is an NP-hard problem and more complicated than the conventional vehicle routing problem with time windows, we design an adaptive large neighborhood search (ALNS) method to solve it. Finally, numerical experiments are conducted to evaluate the effectiveness of the proposed algorithm and reveal some managerial insights. The numerical experiments show that the proposed algorithm can obtain a high-quality solution under a shorter computation time compared with the state-of-the-art MIP solver (Gurobi).

A Bi-Objective Model for the Multi-Period Inventory-Based Reverse Logistics Network: A Case Study from an Automobile Component Distribution Network

Supply chain management and distribution network design has attracted the attention of many researchers in recent years. The timely satisfaction of customer demands leads to reducing costs, improving service levels, and increasing customer satisfaction. For this purpose, in this research, the mathematical programming models for a two-level distribution network including central warehouses, regional warehouses, and customers are designed so that several products with definite demands in multiple periods are distributed from central warehouses to customers. In this problem, two objective functions are considered. The first objective function seeks to minimize the costs of establishment, transportation, inventory, and shortage, and the second objective function attempts to maximize the satisfaction level corresponding with the supply rate of different goods for numerous customers. The presented models include the basic model, inventory-based model, multi-period inventory-based model, and multi-period inventory-based reverse logistics model. The validation and applicability of the proposed models were demonstrated by implementation in a real case study of the automobile industry. The LINGO software 20.0 was used to solve the models. The results show that incorporating the inventory management policies into the basic model and converting from a single-period to a multi-period reverse logistics model will significantly increase company profitability and customer satisfaction.

Analysis of Central Warehouse Location and Logistics Distribution Land and Sea Modes

Distribution Center Warehouse has a very important role in logistics process and selecting the most strategic location is a must. Strategic location in Bali Province will give certain advantage to logistics company with travelling time as a point of view. Industrial Revolution 4.0 enable us finding such location with the help of computer simulation software such as AnyLogic. This research use AnyLogic capability to compare travelling time for 2 case of Distribution Center Warehouse: Mangupura and Negara. This comparison takes into account logistic process of delivering goods to Bali Province via sea transport (Gilimanuk Port). Result shows that Distribution Center Warehouse in Negara has an advantage compare to Mangupura in term of travelling time.

Modern approaches to data storage: comparison of relational and cloud data warehouses using etl and elt methods

The paper analyses various aspects of the use of relational and cloud data warehouses as well as methods of integrating ETL and ELT data. A comparative analysis of these approaches, their advantages and disadvantages are provided. A central relational data warehouse is proposed that provides a single version of truth (SVOT), which allows standardising and structuring data, avoiding differences and providing the access to the same information for all users of an organisation. It is analysed the methodological approaches to implementing a data warehouse: top-down, bottom-up, and from middle. It is described cloud data warehouses that use cloud technologies to provide scalability, availability and fault tolerance, which is important for the companies with huge amounts of data. The advantages and disadvantages of ETL and ELT are analysed: ETL transforms data before it is loaded into the warehouse, which makes it easier to maintain data confidentiality. ELT performs transformation after loading, which allows for more flexible data processing directly in the warehouse. In the article, we deal with the approaches to implementing a data warehouse: top-down is suitable for strategic planning, bottom-up allows for faster results, and the middle approach combines both methods to achieve optimal efficiency. We considered cloud data storage: compared to relational storage, cloud storage is more flexible, scalable and efficient, providing speed and reducing infrastructure costs. It is described cloud storage architectures: massive parallel processing, hybrid architectures, lambda architectures, and multi-structured architectures. They provide high performance and flexibility in data processing. It is described data storage technologies: Data Lake, Polyglot Persistence, Apache Iceberg, Apache Parquet, and columnar databases that provide efficient storage and processing of large amounts of data

The prevalence of human papillomavirus in ocular surface squamous neoplasia in HIV positive and negative patients in a South African population.

To assess the prevalence and subtypes of Human Papillomavirus (HPV) in Ocular Surface Squamous Neoplasia (OSSN) in Human Immunodeficiency Virus (HIV) positive and negative patients in South Africa. This study was a single center retrospective cross-sectional study, conducted at Tygerberg Hospital, Western Cape, South Africa. We assessed 63 histopathologically confirmed OSSN formalin-fixed paraffin-embedded (FFPE) tissue blocks from 2015-2023. The presence of HPV was determined using the Hybrispot Direct Flow Chip Kit. Corresponding clinical data was retrieved from the National Health Laboratory Service (NHLS) central data warehouse. Of the confirmed OSSN samples, 66.7% tested positive for HPV (95% confidence interval [CI] 54-77.3%). Of the 42 HPV positive samples, 38 (90.5%) had one or more known genotypes detected and 4 had unknown genotypes. The most prevalent subtypes were HPV 11, 16 and 18 (found in 61.9%, 52.4% and 33.3% of HPV positive samples respectively). 88.9% of the lesions biopsied were from HIV positive patients, of whom 56.4% had a CD4 + count of < 200 cells/µL. A lower median CD4 + count was detected among HIV positive patients with invasive squamous cell carcinoma compared to those with moderate dysplasia (p < 0.0198). There is a high prevalence of HPV in OSSN in South Africa. Certain subtypes namely, 11, 16, 18, 31, 33 and 35 may be more carcinogenic. HIV with HPV co-infection may be linked as a causative factor in the development of OSSN.

Inventory reallocation in a fashion retail network: A matheuristic approach

We consider a fashion retail network consisting of a central warehouse, owned by a fashion firm, and a fairly large number of retail stores. Some stores are owned by the firm itself, whereas others are owned by franchisees. An initial inventory allocation decision is made at the beginning of the selling season and is periodically revised. Inventory reallocation comprises both direct shipments from the warehouse to stores and lateral shipments among the stores. Besides stock availability and shipping costs, a suitable reallocation policy must take into account the probability of selling each item, some operational constraints, as well as other preference factors that define the utility of shipping an item from a node of the network to another one. Since the problem does not lend itself to the application of typical tools from inventory theory, we propose an optimization model that complements such tools. The model, given the number of nodes and SKUs, may involve about one million binary variables, and just solving the LP relaxation may take hours using state-of-the-art software. Since typical metaheuristics for combinatorial optimization do not seem a viable alternative, we propose a matheuristic approach, in which a sequence of maximum-weight matching problems is solved in order to reduce the problem and restrict the set of potential shipping pairs, with a corresponding drop in the number of decision variables. Computational results obtained on a set of real-life problem instances are discussed, showing the viability of the proposed algorithm.

A novel cross-docking EOQ-based model to optimize a multi-item multi-supplier multi-retailer inventory management system

AbstractNowadays, the retail industry accounts for a large share of the world’s economy. Cross-docking is one of the most effective and smart inventory management systems used by retail companies to respond to demands efficiently. In this study, the aim is to develop a novel cross-docking EOQ-based model for a retail company. By considering a two-stage inventory procurement process, a new multi-item, multi-supplier, multi-retailer EOQ model is developed to minimize the total inventory costs. In the first stage, the required items are received from suppliers and are held in a central warehouse. In the second stage, these items are delivered to several retail stores. The total inventory costs include four main parts, i.e., holding costs at the central warehouse, holding costs at the retail stores, fixed ordering costs from the suppliers, and fixed ordering costs from the central warehouse. The optimal inventory policy is obtained by analyzing extrema, and a numerical example is used to confirm the efficiency of the proposed model. Based on the obtained results, it is evident that the proposed model produces the optimal policy for the cross-docking system. Furthermore, the model enables managers to analyze the effects of key factors on the costs of the system. Based on the obtained results, the annual demand of each retailer, the ordering cost by the central warehouse, the ordering cost at each retail store, and the holding cost at each retail store have a direct impact on the optimal cost. Furthermore, it is not possible to describe the effects of the holding cost at the central warehouse on the optimal cost of the system generally.

Are ICD codes reliable for observational studies? Assessing coding consistency for data quality.

International Classification of Diseases (ICD) codes recorded in electronic health records (EHRs) are frequently used to create patient cohorts or define phenotypes. Inconsistent assignment of codes may reduce the utility of such cohorts. We assessed the reliability across time and location of the assignment of ICD codes in a US health system at the time of the transition from ICD-9-CM (ICD, 9th Revision, Clinical Modification) to ICD-10-CM (ICD, 10th Revision, Clinical Modification). Using clusters of equivalent codes derived from the US Centers for Disease Control and Prevention General Equivalence Mapping (GEM) tables, ICD assignments occurring during the ICD-9-CM to ICD-10-CM transition were investigated in EHR data from the US Veterans Administration Central Data Warehouse using deep learning and statistical models. These models were then used to detect abrupt changes across the transition; additionally, changes at each VA station were examined. Many of the 687 most-used code clusters had ICD-10-CM assignments differing greatly from that predicted from the codes used in ICD-9-CM. Manual reviews of a random sample found that 66% of the clusters showed problematic changes, with 37% having no apparent explanations. Notably, the observed pattern of changes varied widely across care locations. The observed coding variability across time and across location suggests that ICD codes in EHRs are insufficient to establish a semantically reliable cohort or phenotype. While some variations might be expected with a changing in coding structure, the inconsistency across locations suggests other difficulties. Researchers should consider carefully how cohorts and phenotypes of interest are selected and defined.

A Multisite Electronic Health Record Integrated Remote Monitoring Intervention for Hypertension Improvement: Protocol for a Randomized Pragmatic Comparative Effectiveness Trial.

Hypertension is a major contributor to various adverse health outcomes. Although previous studies have shown the benefits of home blood pressure (BP) monitoring over office-based measurements, there is limited evidence comparing the effectiveness of whether a BP monitor integrated into the electronic health record is superior to a nonintegrated BP monitor. In this paper, we describe the protocol for a pragmatic multisite implementation of a quality improvement initiative directly comparing integrated to nonintegrated BP monitors for hypertension improvement. We will conduct a randomized, comparative effectiveness trial at 3 large academic health centers across California. The 3 sites will enroll a total of 660 participants (approximately n=220 per site), with 330 in the integrated BP monitor arm and 330 in the nonintegrated BP control arm. The primary outcome of this study will be the absolute difference in systolic BP in mm Hg from enrollment to 6 months. Secondary outcome measures include binary measures of hypertension (controlled vs uncontrolled), hypertension-related health complications, hospitalizations, and death. The list of possible participants will be generated from a central data warehouse. Randomization will occur after enrollment in the study. Participants will use their assigned BP monitor and join site-specific hypertension interventions. Cross-site learning will occur at regular all-site meetings facilitated by the University of California, Los Angeles Value-Based Care Research Consortium. A pre- and poststudy questionnaire will be conducted to further evaluate participants' perspectives regarding their BP monitor. Linear mixed effects models will be used to compare the primary outcome measure between study arms. Mixed effects logistic regression models will be used to compare secondary outcome measures between study arms. The study will start enrolling participants in the second quarter of 2023 and will be completed by the first half of 2024. Results will be published by the end of 2024. This pragmatic trial will contribute to the growing field of chronic care management using remote monitoring by answering whether a hypertension intervention coupled with an electronic health record integrated home BP monitor improves patients' hypertension better than a hypertension intervention with a nonintegrated BP monitor. The outcomes of this study may help health system decision makers determine whether to invest in integrated BP monitors for vulnerable patient populations. ClinicalTrials.gov NCT05390502; clinicaltrials.gov/study/NCT05390502. PRR1-10.2196/45915.

Warehouse Automation Implementation Environment: Case of Central Warehouse Management in Mali, West Africa

The implementation of warehouse automation has proven to be an effective way to increase productivity and inventory accuracy, lower labor costs, and improve safety in the warehouse environment. This research aims to investigate the factors contributing to the success of warehouse automation implementation. This study offers a unique and modern warehouse automation environment model as a solution for complete implementation in warehouse automation operations. The study was conducted in Mali, West Africa. A total of 100 responses were collected among warehouse managers through an online Microsoft Forms survey. Smart PLS version 4.0 software was used to analyze the data.

Pengadaan Barang di Gudang PT. Bumitama Gunajaya Agro Kecamatan Kota Waringin Barat Barat Kalimantan Tengah

This research aims to determine the procedures for procurement of goods in warehouses related to company operations. This research uses a basic qualitative descriptive method, a location determination method using a purposive method and was carried out at PT. Bumitama Gunajaya Agro (BGA). Data obtained from interviews with the Head of Warehouse, Warehouse Mador and KTU. The results obtained from this research are that the procurement of goods in warehouses has been implemented by PT. Bumitama Gunajaya Agro has used procurement procedures from planning to control, but there is still a need for coordination between the estate warehouse and the central warehouse.

Performance evaluation of a two-echelon inventory system with network lost sales

Inventory systems are largely analyzed in the literature under the common assumption of backorders due to the complexity of lost sales. In this paper, we consider a two-echelon inventory system composed of a central warehouse and multiple local warehouses subject to lost sales. The demand faced by each local warehouse is a Poisson process and the stock in the warehouses is controlled according to a continuous review base-stock policy. This system has been analyzed in the literature under deterministic or exponential lead-times at the central warehouse, deterministic lead times at the local warehouses and approximate performance evaluations have been proposed for two cases: (1) the demand is lost if no items are available in the local warehouse, the central warehouse, or in the pipeline in between (i.e., a waiting time threshold for incoming demand equal to the local warehouse lead time), and (2) when there is a waiting time threshold less than the local warehouse lead time. Based on a queuing network representation of the system, we extend the performance analysis of the system in the first case by considering generally distributed lead times both at the central and local warehouses and by providing the exact closed-form expressions for the inventory performance measures. In the second case, we provide new approximate solutions under generally distributed lead times at the central warehouse. We numerically show that our exact and approximate solutions perform equally or better than those presented in the literature under deterministic lead times.

Inventory Control and Learning for One-Warehouse Multistore System with Censored Demand

Efficient Learning Algorithms for Dynamic Inventory Allocation in Multiwarehouse Multistore Systems with Censored Demand Motivated by collaboration with a prominent fast-fashion retailer in Europe, the researchers focus their attention on the one-warehouse multistore (OWMS) inventory control problem, specifically addressing scenarios in which the demand distribution is unknown a priori. The OWMS problem revolves around a central warehouse that receives initial replenishments and subsequently distributes inventory to multiple stores within a finite time horizon. The objective lies in minimizing the total expected cost. To overcome the hurdles posed by the unknown demand distribution, the researchers propose a primal-dual algorithm that continuously learns from demand observations and dynamically adjusts inventory control decisions in real time. Thorough theoretical analysis and empirical evaluations highlight the promising performance of this approach, offering valuable insights for efficient inventory allocation within the ever-evolving retail industry.

Omni-fulfillment network design for supply chain service platform considering cost, service and resilience tradeoffs

Supply chain service platform (SCSP) plays an indispensable role in omni-fulfillment supply chain network services in the digital economy era. In this context, this paper studies the omni-fulfillment supply chain network design considering cost, service, and resilience tradeoffs. The problem is modeled as a multi-objective mixed integer nonlinear programming (MOMINLP) model based on omni-fulfillment services. To improve the solving efficiency, the model is linearized, and a tailored multi-objective optimization algorithm is developed. The significant advantage of this algorithm is that the multi-loop skipping mechanism is embedded in the Epsilon-constraint method to obtain the Pareto front faster. The effectiveness of the proposed decision-making framework is verified by real-case data. Numerical results show that the proposed algorithm outperforms AUGMECON2 algorithm in terms of problem size and computational time. In the case of order segmentation, the shorter the delivery time of goods, the higher the cost of the supply chain network. Furthermore, implementing capacity redundancy in the central warehouse can mitigate the impact of different disrupting scenarios.

Solution Of Capacitated Vehicle Routing Problem For A Food Delivery Company With Heuristic Methods

A food delivery company operates in Balıkesir performs to the distribution for the products of a certain brand from the central warehouse to the customers located in the central districts of Altıeylül and Karesi by using two vehicles with high capacity. The company visits customers on certain routes to meet their daily demands and is able to meet all demands at the end of the day. In this study, the distribution of the company's products was considered as a Vehicle Routing Problem, and it was aimed to reconstruct the distribution routes of the vehicles with the help of various algorithms and to provide cost savings in terms of the distance traveled. In order to solve the problem, first of all, an appropriate capacity assumption was made for the vehicles by considering the daily demand amounts of the customers. Under this assumption, first new customer groups to be visited in daily periods were created, and then new routes were obtained for the relevant customer groups. In this process, the problem was designed as a Capacity Constrained Vehicle Routing Problem, and the results obtained using Fisher and Jaikumar's Algorithm and Clarke and Wright's Savings Algorithm were evaluated. When the results obtained are compared with the current route status of the company, it has been determined that it is possible to achieve a high rate of improvement by using the routes determined by algorithms.

Evaluation of tumour marker utilisation and impact of electronic gatekeeping in the province of KwaZulu-Natal, South Africa.

Inappropriate testing remains a high healthcare cost driver. Tumour marker tests are more expensive than routine chemistry testing. Implementing test demand management systems like electronic gatekeeping (EGK) has reportedly decreased test requests. This study aimed to describe the appropriateness of tumour marker tests, carcinoembryonic antigen, alpha foetal protein, prostate-specific antigen, carbohydrate antigen 19-9, cancer antigen 15-3, cancer antigen 125, and human chorionic gonadotropin, and determine the effectiveness of the EGK used in the public health sector in KwaZulu-Natal, South Africa. Tumour marker test data for the KwaZulu-Natal province were extracted from the National Health Laboratory Service Central Data Warehouse for 01 January 2017 - 30 June 2017 (pre-EGK) and 01 January 2018 - 30 June 2018 (post-EGK implementation). Questionnaires were sent to the clinicians in the regional hospitals ordering the most tumour marker tests to assess ordering practices. In addition, we assessed monthly rejection reports to determine the effect of the EGK. The EGK minimally reduced tumour marker requests or associated costs (1.4% average EGK rejection rate). An overall 18% increase in the tumour marker tests occurred in 2018. The data suggest inappropriate tumour marker test utilisation, particularly for screening. The introduction of EGK as a test demand management had little impact on tumour marker test requests and costs. Continuous education and reiteration of indications for tumour marker test use are required. This study demonstrates the ineffectiveness of EGK in tumour marker orders, and provides some insight as to why these markers are being ordered, which is important in trying to decrease inappropriate ordering of these tests.

From Paper Files to Web-Based Application for Data-Driven Monitoring of HIV Programs: Nigeria's Journey to a National Data Repository for Decision-Making and Patient Care.

Timely and reliable data are crucial for clinical, epidemiologic, and program management decision making. Electronic health information systems provide platforms for managing large longitudinal patient records. Nigeria implemented the National Data Repository (NDR) to create a central data warehouse of all people living with human immunodeficiency virus (PLHIV) while providing useful functionalities to aid decision making at different levels of program implementation. We describe the Nigeria NDR and its development process, including its use for surveillance, research, and national HIV program monitoring toward achieving HIV epidemic control. Stakeholder engagement meetings were held in 2013 to gather information on data elements and vocabulary standards for reporting patient-level information, technical infrastructure, human capacity requirements, and information flow. Findings from these meetings guided the development of the NDR. An implementation guide provided common terminologies and data reporting structures for data exchange between the NDR and the electronic medical record (EMR) systems. Data from the EMR were encoded in extensible markup language and sent to the NDR over secure hypertext transfer protocol after going through a series of validation processes. By June 30, 2021, the NDR had up-to-date records of 1,477,064 (94.4%) patients receiving HIV treatment across 1,985 health facilities, of which 1,266,512 (85.7%) patient records had fingerprint template data to support unique patient identification and record linkage to prevent registration of the same patient under different identities. Data from the NDR was used to support HIV program monitoring, case-based surveillance and production of products like the monthly lists of patients who have treatment interruptions and dashboards for monitoring HIV test and start. The NDR enabled the availability of reliable and timely data for surveillance, research, and HIV program monitoring to guide program improvements to accelerate progress toward epidemic control.

Hepatitis B Virus Immunity Gap: A Six-Year Laboratory Data Review of Hepatitis B Serological Profiles in Gauteng Province, South Africa.

In 1995, the hepatitis B vaccine in South Africa was incorporated into the childhood expanded programme of immunization. We report on immunity gaps of laboratory-based hepatitis B virus (HBV) among patients in public facilities in Gauteng Province from 1st January 2014 to 31st December 2019. Methodology. We analyzed HBV serological data extracted from the National Health Laboratory Services Central Data Warehouse (NHLS CDW). A descriptive analysis was performed for hepatitis B surface antigen (HBsAg), antibodies to HBV core (anti-HBc) total, anti-HBc IgM, and antibodies to HBV surface antigen (anti-HBs) according to annual distribution, age groups, and sex. The HBsAg positivity rate was 7.0% (75,596/1,095,561; p=0.001): 7.4% (96,532/944,077) in the 25 years and over age group and 4.0% (358/9,268 and 325/10,864) in the under 5 and 13-24 year age groups. The positivity rates of the other HBV serological markers were as follows: anti-HBc total was 37.0% (34,377/93,711; p < 0.001), anti-HBc IgM was 2.4% (5,661/239,237; p=0.05), and anti-HBs was 37.0% (76,302/206,138; p ≤ 0.001). Naturally acquired HBV immunity was detected in 25.7% (11,188/43,536) of patients in the 25 years and over age group, and 9.7% and 8.2% (113/1,158 and 541/6,522) among those under 5 years and 13-24 year age group, respectively (p < 0.001). Vaccine-induced immunity was 56.6% (656/1,158) in children under 5 years and 10.2% (4,425/43,536) among those 25 years and above (p < 0.001). Fifty-six percent (29,404/52,581) of patients were HBV seronegative; predominantly among patients in the 13-24 year age group (60.6%; (3,952/6,522)) and 25 years and over (56.3% (24,524/43,536)) (p=<0.001). The HBV infection seroprevalence remains high in South Africa, with Gauteng province having high intermediate endemicity. However, the HBV immunity gap has shifted from younger children to older children and adults.