This study examined the performance and structures of national immunization program in five middle-income Southeast Asian countries - Malaysia, Thailand, Philippines, Viet Nam, and Myanmar, and analyzed how the different structures relate to the difference in program performance to identify effective strategies in the study countries that facilitated good immunization performance. Data were derived from published literature, and WHO/UNICEF/Gavi databases, with 2010 as the baseline year. UMICs Malaysia and Thailand maintained ≥90 % coverage from 2010 to 2020 and even during the COVID-19 pandemic in 2021. LMICs Viet Nam and donor-supported Myanmar also achieved 80-90 % coverage for most routine vaccines in 2020. The Philippines have not reached ≥90 % coverage since 2010, with the maximum only 72 % (MCV1 and Polio3) in 2020. All study countries prioritize immunization and increased government financing since 2010 by minimum 91 % in Malaysia and 1897 % in Myanmar. However, Myanmar still largely depended on donor support with government financing only 32 % of immunization costs in 2021. The Philippines funds 100 % of immunization costs and ensures sustainable financing for the NIP through earmarked "sin tax" revenues from alcohol and tobacco. Donor support influenced new vaccine introductions among the study countries, with Gavi countries Myanmar and Viet Nam introducing more new vaccines, compared to Gavi-ineligible Malaysia and Thailand. The Philippines reported vaccine stock-outs every year amounting to 28 stock-outs events from 2010 to 2019, compared to only 1-4 stockouts in the other study countries. Donor support, innovative financing, and domestic vaccine manufacturing all play an important role in the efficient delivery of immunization services as demonstrated by the several new vaccine introductions and high immunization rates in Myanmar though Gavi and UNICEF support, additional annual $1.2 billion budget for health and immunization from "sin taxes" in the Philippines, and lack of stockouts for vaccines sourced at affordable prices from domestic manufacturers in Viet Nam.
The multifactorial likelihood analysis method has demonstrated utility for quantitative assessment of variant pathogenicity for multiple cancer syndrome genes. Independent data types currently incorporated in the model for assessing BRCA1 and BRCA2 variants include clinically calibrated prior probability of pathogenicity based on variant location and bioinformatic prediction of variant effect, co-segregation, family cancer history profile, co-occurrence with a pathogenic variant in the same gene, breast tumor pathology, and case-control information. Research and clinical data for multifactorial likelihood analysis were collated for 1,395 BRCA1/2 predominantly intronic and missense variants, enabling classification based on posterior probability of pathogenicity for 734 variants: 447 variants were classified as (likely) benign, and 94 as (likely) pathogenic; and 248 classifications were new or considerably altered relative to ClinVar submissions. Classifications were compared with information not yet included in the likelihood model, and evidence strengths aligned to those recommended for ACMG/AMP classification codes. Altered mRNA splicing or function relative to known nonpathogenic variant controls were moderately to strongly predictive of variant pathogenicity. Variant absence in population datasets provided supporting evidence for variant pathogenicity. These findings have direct relevance for BRCA1 and BRCA2 variant evaluation, and justify the need for gene-specific calibration of evidence types used for variant classification.