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The aim of this study was to assess the pooled seroprevalence of hepatitis E across countries within the Southeast Asian region by the UN division.<\/jats:p>\n                  <jats:p>The study analyzed 66 papers across PubMed, Web of Science, and Scopus databases, encompassing data from of 44,850 individuals focusing on anti-HEV seroprevalence. The investigation spanned nine countries, excluding Brunei and East Timor due to lack of data. The pooled prevalence of anti-HEV IgG was determined to be 21.03%, with the highest prevalence observed in Myanmar (33.46%) and the lowest in Malaysia (5.93%). IgM prevalence was highest in Indonesia (12.43%) and lowest in Malaysia (0.91%). The study stratified populations into high-risk (farm workers, chronic patients) and low-risk groups (general population, blood donors, pregnant women, hospital patients).\u00a0It revealed a higher IgG\u201428.9%, IgM\u20144.42% prevalence in the former group, while the latter group exhibited figures of 17.86% and 3.15%, respectively, indicating occupational and health-related vulnerabilities to HEV.<\/jats:p>\n                  <jats:p>A temporal analysis (1987\u20132023), indicated an upward trend in both IgG and IgM prevalence, suggesting an escalating HEV burden.<\/jats:p>\n                  <jats:p>These findings contribute to a better understanding of HEV seroprevalence in Southeast Asia, shedding light on important public health implications and suggesting directions for further research and intervention strategies.<\/jats:p>\n                  <jats:p>\n                    <jats:bold>Key points<\/jats:bold>\n                  <\/jats:p>\n                  <jats:p>\n                    <jats:bold>Research Question<\/jats:bold>\n                  <\/jats:p>\n                  <jats:p>Investigate the seroprevalence of hepatitis E virus (HEV) in Southeast Asian countries focusing on different patterns, timelines, and population cohorts.<\/jats:p>\n                  <jats:p>\n                    <jats:bold>Findings<\/jats:bold>\n                  <\/jats:p>\n                  <jats:p>Sporadic Transmission of IgG and IgM Prevalence:<\/jats:p>\n                  <jats:p>\u2022 Pooled anti-HEV IgG prevalence: 21.03%<\/jats:p>\n                  <jats:p>\u2022 Pooled anti-HEV IgM prevalence: 3.49%<\/jats:p>\n                  <jats:p>Seroprevalence among specific groups:<\/jats:p>\n                  <jats:p>High-risk group (farm workers and chronic patients):<\/jats:p>\n                  <jats:p>\u2022 anti-HEV IgG: 28.9%<\/jats:p>\n                  <jats:p>\u2022 anti-HEV IgM: 4.42%<\/jats:p>\n                  <jats:p>Low-risk group (general population, blood donors, pregnant women, hospital patients):<\/jats:p>\n                  <jats:p>\u2022 anti-HEV IgG: 17.86%<\/jats:p>\n                  <jats:p>\u2022 anti-HEV IgM: 3.15%<\/jats:p>\n                  <jats:p>Temporal Seroprevalence of HEV:<\/jats:p>\n                  <jats:p>Anti-HEV IgG prevalence increased over decades (1987\u20131999; 2000\u20132010; 2011\u20132023): 12.47%, 18.43%, 29.17% as an anti-HEV IgM prevalence: 1.92%, 2.44%, 5.27%<\/jats:p>\n                  <jats:p>\n                    <jats:bold>Importance<\/jats:bold>\n                  <\/jats:p>\n                  <jats:p>Provides a comprehensive overview of HEV seroprevalence in Southeast Asia.<\/jats:p>\n                  <jats:p>Highlights variation in seroprevalence among different population groups.<\/jats:p>\n                  <jats:p>Reveals increasing trend in HEV seroprevalence over the years.<\/jats:p>\n                  <jats:p>Distinguishes between sporadic and epidemic cases for a better understanding of transmission dynamics.<\/jats:p>","DOI":"10.1186\/s12879-024-09349-2","type":"journal-article","created":{"date-parts":[[2024,5,24]],"date-time":"2024-05-24T15:01:29Z","timestamp":1716562889000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":19,"title":["Systematic review and meta-analysis of hepatitis E seroprevalence in Southeast Asia: a comprehensive assessment of epidemiological patterns"],"prefix":"10.1186","volume":"24","author":[{"given":"Ulugbek Khudayberdievich","family":"Mirzaev","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Serge","family":"Ouoba","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ko","family":"Ko","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Zayar","family":"Phyo","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Chanroth","family":"Chhoung","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Akuffo Golda","family":"Ataa","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Aya","family":"Sugiyama","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Tomoyuki","family":"Akita","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Junko","family":"Tanaka","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2024,5,24]]},"reference":[{"issue":"7","key":"9349_CR1","doi-asserted-by":"publisher","first-page":"692","DOI":"10.1099\/jgv.0.001435","volume":"101","author":"DB Smith","year":"2020","unstructured":"Smith DB, Izopet J, Nicot F, Simmonds P, Jameel S, Meng XJ, et al. 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