Machine Learning Enables Accurate Prediction of Quinone Formation during Drug Metabolism.

Metabolism helps in the elimination of drugs from the human body by making them more hydrophilic. Sometimes, drugs can be bioactivated to highly reactive metabolites or intermediates during metabolism. These reactive metabolites are often responsible for the toxicities associated with the drugs. Identification of reactive metabolites of drug candidates can be very helpful in the initial stages of drug discovery. Quinones are soft electrophiles that are generated as reactive intermediates during metabolism. Quinones make up more than 40% of the reactive metabolites. In this work, a reliable data set of 510 molecules was used to develop machine learning and deep learning-based predictive models to predict the formation of quinone-type metabolites. For representing molecules, two-dimensional (2D) descriptors, PubChem fingerprints, electro-topological state (E-state) fingerprints, and metabolic reactivity-based descriptors were used. Developed models were compared to the existing Xenosite web server using the untouched test set of 102 molecules. The best model achieved an accuracy of 86.27%, while the Xenosite server could achieve an accuracy of only 52.94% on the test set. Descriptor analysis revealed that the presence of greater numbers of polar moieties in a molecule can prevent the formation of quinone-type metabolites. In addition, the presence of a nitrogen atom in an aromatic ring and the presence of metabolophores V51, V52, and V53 (SMARTCyp descriptors) decrease the probability of quinone formation. Finally, a tool based on the best machine learning models was developed, which is accessible at http://14.139.57.41/quinonepred/.

TNFipred: a classification model to predict TNF-α inhibitors.

Rheumatoid arthritis (RA), characterized by severe inflammation in the joint lining, is a progressive, chronic, autoimmune disorder with high morbidity and mortality rates. There are several mechanisms responsible for joint damage, but overproduction of TNF-α is a significant mechanism that results in excess swelling and pain. Drugs acting on TNF-α are known to significantly reduce the disease progression and improve the quality of life in many RA patients. Hence, inhibiting TNF-α is considered one of the most effective treatments for RA. Currently, there are only a few FDA-approved TNF-α inhibitors, which are mainly monoclonal antibodies, fusion proteins, or biosimilars with disadvantages such as poor stability, difficulty in route of administration (often given as injection or infusion), cost-prohibitive large-scale production, and increased side effects. There are just a handful of small compounds known to have TNF- inhibitory capabilities. Thus, there is a dire need for new drugs, especially small molecules in the market, such as TNF-α inhibitors. The conventional method of identifying TNF-α inhibitors is expensive, labor, and time intensive. Machine learning (ML) can be used to solve existing drug discovery and development problems. In this study, four classification algorithms-naïve Bayes (NB), random forest (RF), k-nearest neighbor (kNN), and support vector machine (SVM)-were used to train ML models for classifying TNF-α inhibitors based on three sets of features. The performance of the RF model was found to be best when using 1D, 2D, and fingerprints as features, with an accuracy of 87.96 and a sensitivity of 86.17. To our knowledge, this is the first ML model for TNF-α inhibitor prediction. The model is available at http://14.139.57.41/tnfipred/.

FGFR1Pred: an artificial intelligence-based model for predicting fibroblast growth factor receptor 1 inhibitor.

Fibroblast growth factor receptors (FGFRs) are a family of cell surface receptors that bind to fibroblast growth factor (FGF) and mediate various cellular functions (translocating proteins, tissue repair, cell proliferation, development, and differentiation) through complex signaling pathways. The FGFR1 growth receptor is essential in the pathogenesis of numerous malignancies, including but not limited to breast cancer, bladder cancer, hepatocellular carcinoma (HCC), and cholangiocarcinoma. The higher levels of FGFR1 expression on the surface of cancer cells cause overly active signaling, which leads to rapid cell proliferation, resulting in a high spread of cancer cells. The kinases that FGFR1 activates migrate across the cell nucleus, activating genes and kinase proteins necessary for the growth and survival of cancerous cells. Therefore, FGFR1 targeting shows therapeutic promise in some diseases, including cancer. Inhibitors of FGFR1s are being developed and studied for their potential to block aberrant FGFR1 signaling and inhibit cancer growth. Since the discovery of new FGFR1 inhibitors in the laboratory is difficult, expensive, time-consuming, and labor-intensive, only a small number of FGFR1 inhibitors have been approved by the FDA for use in the treatment of cancer. To accelerate drug discovery by efficiently exploring the vast chemical space, and identifying potential candidates with higher accuracy and reduced cost, we developed artificial intelligence (AI)-based prediction models for FGFR1 inhibitors using a dataset of 2356 chemical compounds. Four machine learning (ML) algorithms (SVM, RF, k-NN, and ANN) were used to train different prediction models based on molecular descriptors (1D and 2D, with and without molecular fingerprints). Among all trained models, the random forest (RF)-based prediction model achieved the highest accuracy on the training (98.9%), test (89.8%), and external test (90.3%) datasets. The developed inhibitor prediction model (FGFR1Pred) provides a valuable tool for identifying potential FGFR1 inhibitors, expediting the drug discovery process and ultimately facilitating the development of new therapeutics. The model is made available at https://github.com/PGlab-NIPER/FGFR1Pred.git.

Machine learning-based modeling to predict inhibitors of acetylcholinesterase.

Acetylcholinesterase enzyme is responsible for the degradation of acetylcholine and is an important drug target for the treatment of Alzheimer's disease. When this enzyme is inhibited, more acetylcholine is available in the synaptic cleft for the use, which leads to enhanced memory and cognitive ability. The aim of the present work is to create machine learning models for distinguishing between AChE inhibitors and non-inhibitors using algorithms like support vector machine (SVM), k-nearest neighbor (k-NN) and random forest (RF). The developed models were evaluated by 10-fold cross-validation and external dataset. Descriptor analysis was performed to identify most important features for the activity of molecules. Descriptors which were identified as important include maxssCH2, minHssNH, SaasC, minssCH2, bit 128 MACCS key, bit 104 MACCS key, bit 24 estate fingerprint and bit 18 estate fingerprints. The model developed using fingerprints based on random forest algorithm produced better results compared to other models. The overall accuracy of best model on test set was 85.38 percent. The developed model is available at http://14.139.57.41/achepredictor/ .

Improving community coverage of Japanese encephalitis vaccination: lessons learned from a mass campaign in Battambang Province, Cambodia.

A mass Japanese encephalitis (JE) immunization campaign for children aged 9 months through 12 years was conducted in 2013 in Battambang province, western Cambodia. Vaccinators working at almost 2,000 immunization posts in approximately 800 villages provided vaccinations to almost 310,000 children using one dose of Chengdu Institute of Biological Products' live, attenuated SA14-14-2 JE vaccine (CD-JEV), achieving a coverage rate of greater than 90%. Lessons learned, in general for mass vaccination campaigns and specifically for vaccination with CD-JEV, are described. These observations will be of benefit for public health officials and to help inform planning for future campaigns for JE or other vaccine-preventable diseases in Cambodia and elsewhere.

Mechanistic studies on the drug metabolism and toxicity originating from cytochromes P450.

Cytochromes P450 are oxidizing enzymes; a few families of cytochromes P450 are implicated in drug metabolism. These enzymatic reactions involve many processes including (i) prodrug to drug conversion, (ii) easy excretion of drug, (iii) generation of reactive metabolites, many of which cause toxicity. In this review, the fundamental biochemical mechanisms associated with the conversion of drugs into the useful or toxic metabolites have been discussed. The mechanisms can be established with the help of many experimental methods like mass spectral analysis, NMR and in vitro analysis etc. Computational methods provide detailed atomic level information, which is generally not available from experimental studies. Thus, the in silico efforts in elucidating the molecular mechanisms are complementary to the known experimental methods and are often clearer (especially in providing 3D information about the metabolites and their reactions). Quantum chemical methods and molecular docking become especially very useful. This review includes five case studies, which explain how the atomic level details were obtained to explore the reaction mechanisms of drug metabolism by cytochromes P450.

Progress Toward Hepatitis B Control - South-East Asia Region, 2016-2019.

In 2015, the World Health Organization (WHO) South-East Asia Region (SEAR)* reported an estimated 40 million persons living with chronic hepatitis B virus (HBV) infection and 285,000 deaths from complications of chronic infection, cirrhosis, and hepatocellular carcinoma (1). Most chronic HBV infections, indicated by the presence of hepatitis B surface antigen (HBsAg) on serologic testing, are acquired in infancy through perinatal or early childhood transmission (2). To prevent perinatal and childhood infections, WHO recommends that all infants receive at least 3 doses of hepatitis B vaccine (HepB), including a timely birth dose (HepB-BD)† (1). In 2016, the SEAR Immunization Technical Advisory Group endorsed a regional hepatitis B control goal with a target of achieving hepatitis B surface antigen (HBsAg) seroprevalence of ≤1% among children aged ≥5 years by 2020, which is in line with the WHO Global Health Sector Strategy on Viral Hepatitis 2016-2021 (2,3). The South-East Asia Regional Vaccine Action Plan 2016-2020 (SEARVAP) (4) identified the acceleration of hepatitis B control as one of the eight regional goals for immunization. The plan outlined four main strategies for achieving hepatitis B control: 1) achieving ≥90% coverage with 3 doses of HepB (HepB3), 2) providing timely vaccination with a HepB birth dose (HepB-BD), 3) providing catch-up vaccination of older children, and 4) vaccinating adult populations at high risk and health care workers (1,4). In 2019, SEAR established a regional expert panel on hepatitis B to assess countries' HBV control status. This report describes the progress made toward hepatitis B control in SEAR during 2016-2019. By 2016, all 11 countries in the region had introduced HepB in their national immunization programs, and eight countries had introduced HepB-BD. During 2016-2019, regional HepB3 coverage increased from 89% to 91%, and HepB-BD coverage increased from 34% to 54%. In 2019, nine countries in the region achieved ≥90% HepB3 coverage, and three of the eight countries that provide HepB-BD achieved ≥90% HepB-BD coverage. By December 2019, four countries had been verified to have achieved the hepatitis B control goal. Countries in the region can make further progress toward hepatitis B control by using proven strategies to improve HepB-BD and HepB3 coverage rates. Conducting nationally representative hepatitis B serosurveys among children will be key to tracking and verifying the regional control targets.

Structure-Based Virtual Screening to Discover Potential Lead Molecules for the SARS-CoV-2 Main Protease.

The COVID-19 disease is caused by a new strain of the coronavirus family (SARS-CoV-2), and it has affected at present millions of people all over the world. The indispensable role of the main protease (Mpro) in viral replication and gene expression makes this enzyme an attractive drug target. Therefore, inhibition of SARS-CoV-2 Mpro as a proposition to halt virus ingression is being pursued by scientists globally. Here we carried out a study with two objectives: the first being to perform comparative protein sequence and 3D structural analysis to understand the effect of 12 point mutations on the active site. Among these, two mutations, viz., Ser46 and Phe134, were found to cause a significant change at the active sites of SARS-CoV-2. The Ser46 mutation present at the entrance of the S5 subpocket of SARS-CoV-2 increases the contribution of other two hydrophilic residues, while the Phe134 mutation, present in the catalytic cysteine loop, can cause an increase in catalytic efficiency of Mpro by facilitating fast proton transfer from the Cys145 to His41 residue. It was observed that active site remained conserved among Mpro of both SARS-CoVs, except at the entrance of the S5 subpocket, suggesting sustenance of substrate specificity. The second objective was to screen the inhibitory effects of three different data sets (natural products, coronaviruses main protease inhibitors, and FDA-approved drugs) using a structure-based virtual screening approach. A total of 73 hits had a combo score >2.0. Eight different structural scaffold classes were identified, such as one/two tetrahydropyran ring(s), dipeptide/tripeptide/oligopeptide, large (approximately 20 atoms) cyclic peptide, and miscellaneous. The screened hits showed key interactions with subpockets of the active site. Further, molecular dynamics studies of selected screened compounds confirmed their perfect fitting into the subpockets of the active site. This study suggests promising structures that can fit into the SARS-CoV-2 Mpro active site and also offers direction for further lead optimization and rational drug design.

Using the Stop Transmission of Polio (STOP) Program to Develop a South Sudan Expanded Program on Immunization Workforce.

In 2009, the international Stop Transmission of Polio (STOP) program began supporting the Global Polio Eradication Initiative in the Republic of South Sudan to address shortages of human resources and strengthen acute flaccid paralysis surveillance. Workforce capacity support is provided to the South Sudan Expanded Program on Immunization by STOP volunteers, implementing partners, and non-governmental organizations. In 2013, the Polio Technical Advisory Group recommended that South Sudan transition key technical support from external partners to national staff as part of the Polio Eradication and Endgame Strategic Plan, 2013-2018. To assist in this transition, the South Sudan Expanded Program on Immunization human resources development project was launched in 2015. This 3-year project aims to build national workforce capacity as a legacy of the STOP program by training 56 South Sudanese at national and state levels with the intent that participants would become Ministry of Health staff on their successful completion of the project.

Experiences and Lessons From Polio Eradication Applied to Immunization in 10 Focus Countries of the Polio Endgame Strategic Plan.

Nine polio areas of expertise were applied to broader immunization and mother, newborn and child health goals in ten focus countries of the Polio Eradication Endgame Strategic Plan: policy & strategy development, planning, management and oversight (accountability framework), implementation & service delivery, monitoring, communications & community engagement, disease surveillance & data analysis, technical quality & capacity building, and partnerships. Although coverage improvements depend on multiple factors and increased coverage cannot be attributed to the use of polio assets alone, 6 out of the 10 focus countries improved coverage in three doses of diphtheria tetanus pertussis containing vaccine between 2013 and 2015. Government leadership, evidence-based programming, country-driven comprehensive operational annual plans, community partnership and strong accountability systems are critical for all programs and polio eradication has illustrated these can be leveraged to increase immunization coverage and equity and enhance global health security in the focus countries.

Strengthening the partnership between routine immunization and the global polio eradication initiative to achieve eradication and assure sustainability.

Since the launch of the Global Polio Eradication Initiative (GPEI) in 1988, the number of polio endemic countries has declined from 125 to 3 in 2013. Despite this remarkable achievement, ongoing circulation of wild poliovirus in polio-endemic countries and the increase in the number of circulating vaccine-derived poliovirus cases, especially those caused by type 2, is a cause for concern. The Polio Eradication and Endgame Strategic Plan 2013-2018 (PEESP) was developed and includes 4 objectives: detection and interruption of poliovirus transmission, containment and certification, legacy planning, and a renewed emphasis on strengthening routine immunization (RI) programs. This is critical for the phased withdrawal of oral poliovirus vaccine, beginning with the type 2 component, and the introduction of a single dose of inactivated polio vaccine into RI programs. This objective has inspired renewed consideration of how the GPEI and RI programs can mutually benefit one another, how the infrastructure from the GPEI can be used to strengthen RI, and how a strengthened RI can facilitate polio eradication. The PEESP is the first GPEI strategic plan that places strong and clear emphasis on the necessity of improving RI to achieve and sustain global polio eradication.

Limitations of using administratively reported immunization data for monitoring routine immunization system performance in Nigeria.

BACKGROUND: Efforts are underway to strengthen Nigeria's routine immunization system, yet measuring impact poses a challenge. We document limitations in using administrative data from 12 states in Nigeria and explore alternative approaches. METHODS: We compared state-reported coverage with the third dose of diphtheria-tetanus-pertussis vaccine (DTP3) to district-reported coverage and data from coverage surveys conducted during 2006-2013. We used district-reported data during 2010-2013 to calculate the annual change in immunization coverage, the percentage of the target population that was unimmunized, and the number of vaccine doses administered. Data quality indicators were also assessed. RESULTS: State-reported DTP3 coverage was 66%-102% in 2010, 49%-98% in 2011, 38%-84% in 2012, and 75%-123% in 2013 and was a median 46%-114% greater than survey coverage during 2006-2013. The mean local government area (LGA)-reported coverage varied substantially (standard deviation range, 10%-33% across years). For 2010-2013, the mean annual percentage change in LGA-reported DTP3 coverage was -15% from 2010 to 2011, -9% from 2011 to 2012, and 74% from 2012 to 2013; the mean annual percentage change in the percentage of the target population unimmunized was -62%, 426%, and -62%, respectively; and the mean annual percentage change in the number of doses administered was -13%, -7%, and 90%, respectively. Annually, a mean 14% of LGAs reported DTP3 coverage of >100%. DISCUSSION: Assessing immunization system performance by using administrative data has notable limitations. In addition to long-term improvements in administrative data management, alternatives for measuring routine immunization performance should be considered.

Maternal, fetal, and neonatal outcomes associated with measles during pregnancy: Namibia, 2009-2010.

BACKGROUND: Previous studies of maternal, fetal, and neonatal complications of measles during pregnancy suggest the possibility of increased risk for morbidity and mortality. In 2009-2011, a nationwide laboratory-confirmed measles outbreak occurred in Namibia, with 38% of reported cases among adults. This outbreak provided an opportunity to describe clinical features of measles in pregnant women and assess the relative risk for adverse maternal, fetal, and neonatal outcomes. METHODS: A cohort of pregnant women with clinical measles was identified retrospectively from 6 district hospitals and clinics over a 12-month period. Each pregnant woman with measles was matched with 3 pregnant women without measles, randomly selected from antenatal clinic registers at the same hospital during the same time interval. We reviewed hospital and clinic records and conducted in-person interviews to collect demographic and clinical information on the pregnant women and their infants. RESULTS: Of 55 pregnant women with measles, 53 (96%) were hospitalized; measles-related complications included diarrhea (60%), pneumonia (40%), and encephalitis (5%). Among pregnant women with known human immunodeficiency virus (HIV) status, 15% of those without measles and 19% of those with measles were HIV positive. Of 42 measles-related pregnancies with known outcomes, 25 (60%) had ≥1 adverse maternal, fetal, or neonatal outcome and 5 women (12%) died. Compared with 172 pregnancies without measles, after adjusting for age, pregnancies with measles carried significantly increased risks for neonatal low birth weight (adjusted relative risk [aRR] = 3.5; 95% confidence interval [CI], 1.5-8.2), spontaneous abortion (aRR = 5.9; 95% CI, 1.8-19.7), intrauterine fetal death (aRR = 9.0; 95% CI, 1.2-65.5), and maternal death (aRR = 9.6; 95% CI, 1.3-70.0). CONCLUSIONS: Our findings suggest that measles virus infection during pregnancy confers a high risk of adverse maternal, fetal, and neonatal outcomes, including maternal death. Maximizing measles immunity among women of childbearing age would decrease the incidence of gestational measles and the attendant maternal, fetal, and neonatal morbidity and mortality.

Population-based surveillance for bacterial meningitis in China, September 2006-December 2009.

During September 2006-December 2009, we conducted active population and sentinel laboratory-based surveillance for bacterial meningitis pathogens, including Streptococcus pneumoniae, Neisseria meningitidis, and Haemophilus influenzae type b, in 4 China prefectures. We identified 7,876 acute meningitis and encephalitis syndrome cases, including 6,388 among prefecture residents. A total of 833 resident cases from sentinel hospitals met the World Health Organization case definition for probable bacterial meningitis; 339 of these cases were among children <5 years of age. Laboratory testing confirmed bacterial meningitis in 74 of 3,391 tested cases. The estimated annual incidence (per 100,000 population) of probable bacterial meningitis ranged from 1.84 to 2.93 for the entire population and from 6.95 to 22.30 for children <5 years old. Active surveillance with laboratory confirmation has provided a population-based estimate of the number of probable bacterial meningitis cases in China, but more complete laboratory testing is needed to better define the epidemiology of the disease in this country.

CRAFT: a web-integrated cavity prediction tool based on flow transfer algorithm.

Numerous computational methods, including evolutionary-based, energy-based, and geometrical-based methods, are utilized to identify cavities inside proteins. Cavity information aids protein function annotation, drug design, poly-pharmacology, and allosteric site investigation. This article introduces "flow transfer algorithm" for rapid and effective identification of diverse protein cavities through multidimensional cavity scan. Initially, it identifies delimiter and susceptible tetrahedra to establish boundary regions and provide seed tetrahedra. Seed tetrahedron faces are precisely scanned using the maximum circle radius to transfer seed flow to neighboring tetrahedra. Seed flow continues until terminated by boundaries or forbidden faces, where a face is forbidden if the estimated maximum circle radius is less or equal to the user-defined maximum circle radius. After a seed scanning, tetrahedra involved in the flow are clustered to locate the cavity. The CRAFT web interface integrates this algorithm for protein cavity identification with enhanced user control. It supports proteins with cofactors, hydrogens, and ligands and provides comprehensive features such as 3D visualization, cavity physicochemical properties, percentage contribution graphs, and highlighted residues for each cavity. CRAFT can be accessed through its web interface at http://pitools.niper.ac.in/CRAFT , complemented by the command version available at https://github.com/PGlab-NIPER/CRAFT/ .Scientific contribution: Flow transfer algorithm is a novel geometric approach for accurate and reliable prediction of diverse protein cavities. This algorithm employs a distinct concept involving maximum circle radius within the 3D Delaunay triangulation to address diverse van der Waals radii while existing methods overlook atom specific van der Waals radii or rely on complex weighted geometric techniques.

Barriers and facilitators to hepatitis B birth dose vaccination: Perspectives from healthcare providers and pregnant women accessing antenatal care in Nigeria.

Nigeria is estimated to have the largest number of children worldwide, living with chronic hepatitis B virus (HBV) infection, the leading cause of liver cancer. Up to 90% of children infected at birth develop chronic HBV infection. A birth dose of the hepatitis B vaccine (HepB-BD) followed by at least two additional vaccine doses is recommended for prevention. This study assessed barriers and facilitators of HepB-BD administration and uptake, using structured interviews with healthcare providers and pregnant women in Adamawa and Enugu States, Nigeria. The Consolidated Framework for Implementation Sciences Research (CFIR) guided data collection and analysis. We interviewed 87 key informants (40 healthcare providers and 47 pregnant women) and created a codebook for data analysis. Codes were developed by reviewing the literature and reading a subsample of queries line-by-line. The overarching themes identified as barriers among healthcare providers were: the lack of hepatitis B knowledge, limited availability of HepB-BD to vaccination days only, misconceptions about HepB-BD vaccination, challenges in health facility staffing capacity, costs associated with vaccine transportation, and concerns related to vaccine wastage. Facilitators of timely HepB-BD vaccination included: vaccine availability, storage, and hospital births occurring during immunization days. Overarching themes identified as barriers among pregnant women were lack of hepatitis B knowledge, limited understanding of HepB-BD importance, and limited access to vaccines for births occurring outside of a health facility. Facilitators were high vaccine acceptance and willingness for their infants to receive HepB-BD if recommended by providers. Findings indicate the need for enhanced HepB-BD vaccination training for HCWs, educating pregnant women on HBV and the importance of timely HepB-BD, updating policies to enable HepB-BD administration within 24 hours of birth, expanding HepB-BD availability in public and private hospital maternity wards for all facility births, and outreach activities to reach home births.

Poliomyelitis-related case-fatality ratio in India, 2002-2006.

BACKGROUND: On the basis of studies from developed countries, the case-fatality ratio (CFR) of poliomyelitis generally ranges from 2%-5% among children <5 years of age to 10%-30% among adults. However, little information is available for poliomyelitis-related CFR in developing countries. We conducted a study to determine the CFR in India, 1 of the 4 remaining countries with endemic wild poliovirus (WPV) circulation, during outbreaks of WPV infection during 2002 and 2006 and during the inter-epidemic years of 2003-2005. METHODS: We conducted a descriptive analysis with use of data from the acute flaccid paralysis surveillance system in India. Variables analyzed included age, caregiver-reported vaccination status, date of paralysis onset, laboratory results, final case classification, and survival outcome. Our analysis also accounted for surveillance changes that occurred in 2005, impacting case definitions and final classification. RESULTS: In 2006, 45 deaths occurred among 676 WPV cases in India, yielding a CFR of 6.7%. By comparison, in 2002, there were 66 deaths among 1600 reported WPV cases (CFR, 4.2%) and during 2002-2005, CFR was 1.5%-5.2%. All 45 deaths were among 644 (95%) WPV cases in children aged <5 years (CFR, 7.0%). Among those who died, 33 (73%) were children aged <2 years (CFR, 7.1%). CONCLUSIONS: The CFR among children aged <2 years in India is high compared with previously published CFRs for young children, in part because of improved case finding through enhanced surveillance techniques. Fatal cases emphasize the lethal nature of the disease and the importance of achieving polio eradication in India.

Applying Adult Learning Best Practices to Design Immunization Training for Health Care Workers in Ghana.

INTRODUCTION: A 2016 assessment of frontline health care workers (HCWs) in Ghana identified knowledge, skill, and attitude gaps related to immunization during the second year of life (2YL). The U.S. Centers for Disease Control and Prevention subsequently supported the Ghana Health Service Immunization Program to apply best practices of adult learning and training of trainers (TOT) for a cascade training program for 2YL. METHODS: Five districts from each of the 3 regions (Greater Accra, Northern, and Volta) were selected for the TOT based on key measles and rubella vaccination coverage indicators. The design incorporated best practices of adult learning and TOT. The curriculum integrated 3 major topical themes: technical (immunization topics), operational, and training adults. The technical and operational content was based on HCW tasks most directly affecting 2YL objectives. A cross-functional team developed all classroom, field activity, and training evaluation materials. RESULTS: Seventy-four participants attended TOT workshops in 2017. Based on a rubric defined by the course designers, 99% of the participants reported an acceptable level of confidence to apply and teach the course content. After the TOTs, participants conducted 65 workshops, 43 field visits, and 4 review meetings, reaching 1,378 HCWs within 7 months. Fifty-four percent of HCWs who received training from TOT participants reported an acceptable level of confidence in using the skills, and 92% reported they would prioritize applying the skills acquired during the training. DISCUSSION: The success factors for effective adult learning and TOT can be applied to design and implement high-quality TOT even in resource-limited settings. The factors include using a variety of approaches, spending enough class time to prepare TOT participants for their training role, setting specific expectations for cascading the training, and following up through mentorship and reporting. Strong collaboration across the administrative levels of the Ghana Health Service enabled cascade training.

Evaluation of the Impact of Immunization Second Year of Life Training Interventions on Health Care Workers in Ghana.

INTRODUCTION: As part of a suite of training interventions to improve the knowledge and practice of immunization in the second year of life (2YL), training of trainers workshops were conducted with regional and district health management teams (DHMTs) in 15 districts in 3 regions of Ghana. Using adult learning principles, DHMTs implemented several capacity-building activities at the subdistrict and health facility levels, including health facility visits, on-the-job training, and review meetings. The current evaluation investigated whether frontline health care workers (HCWs) reported or demonstrated improvements in knowledge, attitudes, and practices after training interventions. METHODS: Quantitative and qualitative methods with a utilization-focused approach guided the framework for this evaluation. A systematic random sample of 115 HCWs in 3 regions of Ghana was selected to complete a competency survey before and after training, which focused on 3 core competency areas-Expanded Programme on Immunization (EPI) policy; communication with caregivers; and immunization data management, recording, and use. Interviews and direct observations by data collectors were done to assess HCWs' knowledge, self-reported attitude, and behavior changes in practices. RESULTS: Of 115 HCWs, 102 were surveyed before and 4 months after receiving capacity-building interventions. Modest but not statistically significant improvements were found in knowledge on EPI policy, immunization data management, and communication skills with caregivers. HCWs reported that they had improved several attitudes and practices after the 2YL training. The most improved practice reported by HCWs and observed in all 3 regions was the creation of a defaulter list. DISCUSSION: Findings of this evaluation provide encouraging evidence in taking the first step toward improving HCW knowledge, attitudes, and practices for 3 core immunization competency areas. The use of learner-focused teaching methods combined with adult learning principles is helpful in solving specific performance problems (such as lack of knowledge of EPI policy).

Use of a district health information system 2 routine immunization dashboard for immunization program monitoring and decision making, Kano State, Nigeria.

Introduction: a district health information system 2 tool with a customized routine immunization (RI) module and indicator dashboard was introduced in Kano State, Nigeria, in November 2014 to improve data management and analysis of RI services. We assessed the use of the module for program monitoring and decision-making, as well as the enabling factors and barriers to data collection and use. Methods: a mixed-methods approach was used to assess user experience with the RI data module and dashboard, including 1) a semi-structured survey questionnaire administered at 60 health facilities administering vaccinations and 2) focus group discussions and 16 in-depth interviews conducted with immunization program staff members at the local government area (LGA) and state levels. Results: in health facilities, a RI monitoring chart was used to review progress toward meeting vaccination coverage targets. At the LGA, staff members used RI dashboard data to prioritize health facilities for additional support. At the State level, immunization program staff members use RI data to make policy decisions. They viewed the provision of real-time data through the RI dashboard as a "game changer". Use of immunization data is facilitated through review meetings and supportive supervision visits. Barriers to data use among LGA staff members included inadequate understanding of the data collection tools and computer illiteracy. Conclusion: the routine immunization data dashboard facilitated access to and use of data for decision-making at the LGA, State and national levels, however, use at the health facility level remains limited. Ongoing data review meetings and training on computer skills and data collection tools are recommended.