The Lancet regional health. Southeast Asia最新文献

{"title":"Immunogenicity and safety of ‘Comvigen’, a bivalent SARS-CoV-2 vaccine, in comparison to Comirnaty bivalent vaccine in Thailand: a phase 2, non-inferiority randomised trial","authors":"Watsamon Jantarabenjakul ,&nbsp;Rapisa Nantanee ,&nbsp;Thanyawee Puthanakit ,&nbsp;Sivaporn Gatechompol ,&nbsp;Anchalee Avihingsanon ,&nbsp;Suda Punrin ,&nbsp;Terapong Tantawichien ,&nbsp;Sorachai Nitayaphan ,&nbsp;Arunee Thitithanyanont ,&nbsp;Supranee Buranapraditkun ,&nbsp;Anan Jongkaewwattana ,&nbsp;Chutitorn Ketloy ,&nbsp;Eakachai Prompetchara ,&nbsp;Saranath Lawpoolsri ,&nbsp;Wassana Wijagkanalan ,&nbsp;Mohamad-Gabriel Alameh ,&nbsp;Lina Hong ,&nbsp;Mijo Samija ,&nbsp;Drew Weissman ,&nbsp;Kiat Ruxrungtham ,&nbsp;Nanthida Wonglertnirant","doi":"10.1016/j.lansea.2025.100650","DOIUrl":"10.1016/j.lansea.2025.100650","url":null,"abstract":"<div><h3>Background</h3><div>Strengthening mRNA vaccine development in LMICs is essential for enhancing global pandemic preparedness. This study evaluated the safety and immunogenicity of Comvigen, a bivalent SARS-CoV-2 vaccine, in comparison to the Comirnaty bivalent vaccine (Comirnaty).</div></div><div><h3>Methods</h3><div>This phase II, randomised, open-label, non-inferiority trial was conducted in Thailand across four centres. Participants (n = 450) were randomly assigned (2:1) to receive either Comvigen (50 μg) or Comirnaty (30 μg), using block randomisation (size = 9). Eligible participants had completed at least 2 doses of any approved COVID-19 vaccine, with the last mRNA-vaccine dose given over 3 months before enrolment. The non-inferiority margin of a geometric mean ratio (GMR) of 0.67. The primary immunogenicity endpoint was pseudovirus neutralisation titres (psVNT-50) against SARS-CoV-2 wild-type and Omicron BA.4/BA.5 at Day 29. Safety outcomes included local and systemic adverse reactions up to six months post-vaccination. Immunogenicity analyses were conducted on the Per-Protocol (PP) population and the modified Intent-to-Treat (mITT) population; safety analyses included all participants. Laboratory personnel were blinded to vaccine assignment (<span><span>ClinicalTrials.gov</span><svg><path></path></svg></span>: <span><span>NCT05930730</span><svg><path></path></svg></span>).</div></div><div><h3>Findings</h3><div>Between October and November 2023, 450 participants were enrolled (median age of 36 years, IQR 30–45). At day 29, the geometric mean titre (GMT) of psVNT-50 against wild-type virus increased from 475.9 to 2062.9 for Comvigen and from 458.8 to 1905.1 for Comirnaty (GMR 1.1, 95% CI: 1.0–1.2), meeting non-inferiority criteria. Against Omicron BA.4/BA.5, GMTs were 3909.8 for Comvigen and 3288.6 for Comirnaty (GMR 1.2, 95% 1.0–1.4). Local and systemic reactions were more frequent with Comvigen (91% vs. 78%, p = 0.0002, 79% vs. 70%, p = 0.028) but were mild or moderate and transient with no difference in fever (6% vs. 5%, p = 0.84).</div></div><div><h3>Interpretation</h3><div>Comvigen demonstrated non-inferiority immunogenicity to Comirnaty and had a comparable safety profile, supporting mRNA vaccine development for global access and pandemic preparedness.</div></div><div><h3>Funding</h3><div>Covid-19 Pandemic Emergency Fund granted by <span>Thailand's National Economic and Social Development Council</span> provided major funding. Supplementary funding was provided by <span>National Vaccine Institute (NVI)</span>, Thailand; Center of Excellence in Vaccine Research and Development (Chula VRC), <span>Faculty of Medicine, Chulalongkorn University</span>; <span>Chulalongkorn University Second Century Fund (C2F)</span>; BioNet-Asia and Public Donation through Covid-19 vaccine development fund of the <span>Faculty of Medicine, Chulalongkorn University</span> and the <span>Thai Red Cross Society</span>, Thailand.</div></div>","PeriodicalId":75136,"journal":{"name":"The Lancet regional health. Southeast Asia","volume":"40 ","pages":"Article 100650"},"PeriodicalIF":6.2,"publicationDate":"2025-08-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144851949","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Epidemiology and determinants of stillbirth disparities in India: a geospatial hotspot clustering study using integrated population-level data.","authors":"U Venkatesh, Om Prakash Bera, Ashoo Grover, Siddhant Shastri, Sayantan Chakraborty","doi":"10.1016/j.lansea.2025.100647","DOIUrl":"10.1016/j.lansea.2025.100647","url":null,"abstract":"<p><strong>Background: </strong>Stillbirth is a significant public health issue worldwide, with India bearing a substantial burden. While male fetuses are biologically more vulnerable, the geographic distribution of sex-specific stillbirth rates remains underexplored. This study investigates district-level stillbirth patterns across India and evaluates their spatial association with maternal, socio-demographic, and delivery care factors.</p><p><strong>Methods: </strong>This ecological study employed data integration using the Civil Registration System (CRS-2020) and the National Family Health Survey (NFHS-5) to compile district-level estimates of stillbirth rates (SBRs) along with maternal, delivery care, and socio-demographic indicators. SBR was calculated as the number of stillbirths per 1000 total births for each sex. Spatial autocorrelation was assessed using Global and Local Moran's I. Additionally, univariate and bivariate Local Indicators of Spatial Association (LISA) were conducted separately for male and female stillbirth rates to examine spatial clustering and associations with selected correlates, identifying hotspot and cold-spot regions across districts.</p><p><strong>Findings: </strong>The nationwide stillbirth rate (SBR) in 2020 was 6.548 per 1000 total births (female: 6.54; male: 6.63). Stillbirth rates were higher among urban mothers compared to rural mothers. Northern India, particularly Chandigarh, Jammu & Kashmir, and Rajasthan, recorded the highest SBR. Spatial analysis identified stillbirth hotspots primarily in Northern and Central India. Univariate Moran's I indicated strong spatial clustering for maternal factors, including below-normal BMI (Moran's I = 0.62) and iron-folic acid supplementation (Moran's I = 0.551). Bivariate Moran's I showed similar spatial trends for both sexes, with stillbirth rates positively correlated with anemia (female: 0.087; male: 0.078) and institutional births in public facilities (female: 0.084; male: 0.086), and negatively correlated with literacy (female: -0.069; male: -0.063) and cesarean deliveries in private facilities (female: -0.055; male: -0.090).</p><p><strong>Interpretation: </strong>This study found no significant geospatial disparity in sex-specific stillbirth rates across Indian districts, with similar clustering patterns for both sexes. Key determinants included literacy, wealth status, anemia, and cesarean deliveries. District-specific strategies, guided by geospatial insights, are essential for focused public health measures. Strengthening stillbirth registration and utilizing advanced spatial methods are crucial for improved monitoring and intervention planning.</p><p><strong>Funding: </strong>No funding was issued for this research.</p>","PeriodicalId":75136,"journal":{"name":"The Lancet regional health. Southeast Asia","volume":"40 ","pages":"100647"},"PeriodicalIF":6.2,"publicationDate":"2025-08-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12355120/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144877135","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Correspondence to editorial “Oral health in southeast Asia: addressing inaccessibility”","authors":"Romain Lan ,&nbsp;Laurie Fraticelli ,&nbsp;Denis Bourgeois ,&nbsp;Florence Carrouel","doi":"10.1016/j.lansea.2025.100550","DOIUrl":"10.1016/j.lansea.2025.100550","url":null,"abstract":"","PeriodicalId":75136,"journal":{"name":"The Lancet regional health. Southeast Asia","volume":"39 ","pages":"Article 100550"},"PeriodicalIF":6.2,"publicationDate":"2025-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144827576","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Melioidosis: a call for recognition as a neglected tropical disease under the Southeast Asia regional neglected tropical disease framework","authors":"Prasanta Raghab Mohapatra ,&nbsp;Bijayini Behera","doi":"10.1016/j.lansea.2025.100625","DOIUrl":"10.1016/j.lansea.2025.100625","url":null,"abstract":"","PeriodicalId":75136,"journal":{"name":"The Lancet regional health. Southeast Asia","volume":"39 ","pages":"Article 100625"},"PeriodicalIF":6.2,"publicationDate":"2025-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144827577","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Sample representativeness and temporal comparability in SEAR study, and achieving equitable health insurance coverage — Authors' reply","authors":"Sudheer Kumar Shukla ,&nbsp;Pratheeba John ,&nbsp;Nishikant Singh ,&nbsp;Navin Singh","doi":"10.1016/j.lansea.2025.100648","DOIUrl":"10.1016/j.lansea.2025.100648","url":null,"abstract":"","PeriodicalId":75136,"journal":{"name":"The Lancet regional health. Southeast Asia","volume":"39 ","pages":"Article 100648"},"PeriodicalIF":6.2,"publicationDate":"2025-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144826875","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Health insurance in southeast Asia: is it enough for UHC?","authors":"The Lancet Regional Health – Southeast Asia","doi":"10.1016/j.lansea.2025.100653","DOIUrl":"10.1016/j.lansea.2025.100653","url":null,"abstract":"","PeriodicalId":75136,"journal":{"name":"The Lancet regional health. Southeast Asia","volume":"39 ","pages":"Article 100653"},"PeriodicalIF":6.2,"publicationDate":"2025-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144827574","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Balancing public health priorities and inclusivity in medical education: a clarification on curriculum revisions","authors":"Mirza Jahanzeb Beg ,&nbsp;B. Sai Chaitanya Reddy ,&nbsp;Manik Inder Singh Sethi","doi":"10.1016/j.lansea.2025.100563","DOIUrl":"10.1016/j.lansea.2025.100563","url":null,"abstract":"","PeriodicalId":75136,"journal":{"name":"The Lancet regional health. Southeast Asia","volume":"39 ","pages":"Article 100563"},"PeriodicalIF":6.2,"publicationDate":"2025-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144827575","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Diagnostic accuracy of convolutional neural networks in classifying hepatic steatosis from B-mode ultrasound images: a systematic review with meta-analysis and novel validation in a community setting in Telangana, India","authors":"Akshay Jagadeesh ,&nbsp;Chanchanok Aramrat ,&nbsp;Santosh Rai ,&nbsp;Fathima Hana Maqsood ,&nbsp;Adarsh Kibballi Madhukeshwar ,&nbsp;Santhi Bhogadi ,&nbsp;Judith Lieber ,&nbsp;Hemant Mahajan ,&nbsp;Santosh Kumar Banjara ,&nbsp;Alexandra Lewin ,&nbsp;Sanjay Kinra ,&nbsp;Poppy Mallinson","doi":"10.1016/j.lansea.2025.100644","DOIUrl":"10.1016/j.lansea.2025.100644","url":null,"abstract":"<div><h3>Background</h3><div>Ultrasound is a widely available, inexpensive, and non-invasive modality for evaluating hepatic steatosis (HS). However, the scarcity of radiological expertise limits its utility. Convolutional Neural Networks (CNNs) have potential for automated classification of HS using B-mode ultrasound images. We aimed to assess their diagnostic accuracy and generalisability across diverse study settings and populations.</div></div><div><h3>Methods</h3><div>We systematically reviewed two biomedical databases up to Dec 12, 2023, to identify studies that applied CNNs in the classification of HS using B-mode ultrasound images as input (PROSPERO: CRD42024501483). We supplemented this review with a novel analysis of the community-based Andhra Pradesh Children and Parents’ Study (APCAPS) in India to address the overrepresentation of hospital samples and lack of data on South Asian populations who exhibit a distinct central adiposity phenotype that could influence CNN performance. We quantitatively synthesised diagnostic accuracy metrics for eligible studies using random-effects meta-analyses.</div></div><div><h3>Findings</h3><div>Our search returned 289 studies, of which 17 were eligible. All but one of the 17 studies were based in hospital or clinical outpatient settings with curated cases and controls. Studies were conducted exclusively in East Asian, European, or North American populations. Studies employed varying gold standards: seven studies (41.18%) used liver biopsy, three (17.64%) used MRI proton density fat fraction, and seven (41.18%) used clinician-evaluated ultrasound-based HS grades. The APCAPS sample included 219 participants with radiologist-assigned HS grades. Across the range of study settings and populations, CNNs demonstrated good diagnostic accuracy. Meta-analysis of studies with low risk of bias reporting on five unique datasets showed a pooled area under the receiver operating characteristic curve of 0.93 (95% CI 0.73–0.98) for detecting any severity and 0.86 (95% CI 0.77–0.92) for detecting moderate-to-severe HS severity grades, respectively.</div></div><div><h3>Interpretation</h3><div>CNNs have good diagnostic accuracy and generalisability for HS classification, suggesting potential for real-world application.</div></div><div><h3>Funding</h3><div><span>Medical Research Council</span>, UK (<span><span>MR/T038292/1</span></span>, <span><span>MR/V001221/1</span></span>).</div></div>","PeriodicalId":75136,"journal":{"name":"The Lancet regional health. Southeast Asia","volume":"40 ","pages":"Article 100644"},"PeriodicalIF":6.2,"publicationDate":"2025-07-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144749801","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Urgent need to integrate gender-sensitive financing in Southeast Asia's health insurance expansion","authors":"Schawanya Kaewpitoon Rattanapitoon ,&nbsp;Natnapa Heebkaew Padchasuwan ,&nbsp;Nav La ,&nbsp;Nathkapach Kaewpitoon Rattanapitoon","doi":"10.1016/j.lansea.2025.100645","DOIUrl":"10.1016/j.lansea.2025.100645","url":null,"abstract":"","PeriodicalId":75136,"journal":{"name":"The Lancet regional health. Southeast Asia","volume":"39 ","pages":"Article 100645"},"PeriodicalIF":6.2,"publicationDate":"2025-07-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144722540","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Sample representativeness and temporal comparability in SEAR study","authors":"Jabed Iqbal","doi":"10.1016/j.lansea.2025.100646","DOIUrl":"10.1016/j.lansea.2025.100646","url":null,"abstract":"","PeriodicalId":75136,"journal":{"name":"The Lancet regional health. Southeast Asia","volume":"39 ","pages":"Article 100646"},"PeriodicalIF":6.2,"publicationDate":"2025-07-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144722541","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}